central mekong delta region connectivity project

MEKONG D E LTA C EN T RA LCONNEC T I V I T Y P RO J E C T

R A P I D C L I M AT E C H A N G E T H R E AT & V U L N E R A B I L I T Y A S S E S S M E N T

S o c i a l i s t R e p u b l i c o f V i e t n a m

September, 2012ICEM – International Centre for Environmental Management

for ADB – Asian Development Bank

TA Number – 6420 (REG) Promoting Climate Change Adaptation in Asia and the Pacific using CQS January, 2012

Final Report Mekong Delta Central Connectivity Project: Rapid Climate Change Threat and Vulnerability Assessment

Produced by: ICEM ‐ International Centre for Environmental Management

Produced for: Asian Development Bank Copyright: © 2010 ICEM Citation: ICEM. 2012. Rapid Climate Change Threat and Vulnerability Assessment for the Mekong

Delta Central Connectivity Project. Consultant report prepared for the Asian Development Bank, Hanoi, Viet Nam.

More information: www.icem.com.au | [email protected]

ICEM International Center for Environmental Management 6A To Ngoc Van Street, Tay Ho, HANOI, Socialist Republic of Viet Nam

Cover images: Mekong Delta and Cambodian Floodplain satellite image (To Quang Toan, 2012) Project Team: Mr Jorma Koponen (Team Leader), Mr Tarek Ketelsen, Dr Jeremy Carew‐Reid, Dr To Quang

Toan, Mr John Sawdon, Mr Pertti Kaista, Mr Tran Thanh Cong, Dr Tranh Thi Thanh

Acknowledgements: The team wish to thank the following for their support and provision of information: MR Duong Tuan Minh, Dr Au Phu Thang, Mr tran Van Thi, Mr Tranh Anh Duong, Mr Nguyen Van Cong, Mr Cam Vu Tu, Truong Hong Hai, Mr Charles Rodgers, Mr Rustam Ishenaliev, Mr Benoit Laplante, Mr John Cooney, Mr Brian Barwick, Mr Anthony Green, Mr Nihal Alagoda, Mr Ha Quoc Dong, Mr Nguyen Huu Thien, Ms Nguyen Bich Ngoc

ADB | Mekong Delta Bridges CC Vulnerability Assessment| Final Report | ICEM

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ABBREVIATIONS

AASHTO American Association of State Highway and Transportation Officials ADB Asian Development Bank AR4 Assessment Report 4 CBA Cost Benefit Analysis CCAM Climate Change Adaptation & Mitigation methodology CEA Cost Effectiveness Analysis CO2 Carbon Dioxide DARD Department of Agriculture and Rural Development DOIT Department of Industry and Trade DONRE Department of Natural Resource and Environment DOT Department of Transport EIA Environmental Impact Assessment ENSO El Nino Southern Oscillation EPC Engineering, procurement, construction GHG Greenhouse Gas GOV Government of Viet Nam ha hectares ICEM International Centre for Environmental Management IPCC Intergovernmental Panel on Climate Change NDF Nordic Development Fund NPV Net Present Value NR National Road/Highway JV WSA Joint Venture Wilbur Smith Associates masl metres above sea level mcm million cubic metres MONRE Ministry of Natural Resources and Environment MOIT Ministry of Industry and Trade NTPCC National Target Program for Climate Change PPC Provincial People’s Committee PR Provincial Road RIAM Rapid Impact Assessment Matrix RSDD Regional and Sustainable Development Department SEA Strategic Environmental Assessment SIWRP Southern Institute of Water Resource Planning SCCP Southern Coastal Corridor Project SRES Special Report on Emissions Scenarios TEDI Transport Engineering Design Incorporated ToR Terms of Reference UNIDO United Nations Industrial Development Organisation USA United States of America VEA Vietnam Environment Agency

ADB | Mekong Delta Bridges CC Vulnerability Assessment| Mid‐term Report | ICEM

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TABLE OF CONTENTS

ABBREVIATIONS ............................................................................................................................ III

TABLE OF CONTENTS ..................................................................................................................... IV

1 INTRODUCTION ................................................................................................................. 2 1.1 Project outcomes ............................................................................................................ 4 1.2 Project outputs ............................................................................................................... 4 1.3 Scope ............................................................................................................................... 4

2 BACKGROUND ................................................................................................................... 7 2.1 Origins and geomorphology of the Mekong Delta ......................................................... 7 2.2 Hydrological zoning of the Delta ..................................................................................... 8 2.3 Land use and infrastructure of the Delta ........................................................................ 8 2.4 Project site .................................................................................................................... 10 2.5 Central Mekong Delta Connectivity project (CMDCP) .................................................. 12

3 EXISTING ISSUES FOR TRANSPORT DEVELOPMENT IN THE MEKONG DELTA ...................... 16 3.1 Seasonal flooding and water levels ............................................................................... 16 3.2 Geotechnical stability of Delta soils and river banks .................................................... 23

4 METHODOLOGY ............................................................................................................... 29 4.1 Overview ....................................................................................................................... 29 4.2 Modelling overview ...................................................................................................... 33 4.3 Threat and exposure analysis ....................................................................................... 42 4.4 Sensitivity analysis ........................................................................................................ 44 4.5 CC Impact assessment................................................................................................... 44 4.6 Vulnerability assessment .............................................................................................. 45 4.7 Adaptation priority setting ............................................................................................ 45

5 CLIMATE CHANGE THREATS FOR THE MEKONG DELTA ...................................................... 46 5.1 Air temperature ............................................................................................................ 46 5.2 Rainfall .......................................................................................................................... 51 5.3 Mekong River flow – typical events .............................................................................. 55 5.4 Mekong River flow – extreme events ........................................................................... 59 5.5 Sea Level Rise ................................................................................................................ 63 5.6 Storms, Storms surge and extreme events ................................................................... 69 5.7 Non‐climate change threats .......................................................................................... 71 5.8 Flooding ......................................................................................................................... 75

6 VULNERABILITY ASSESSMENT ........................................................................................... 89 6.1 Bridge substructure ....................................................................................................... 91 6.2 Bridge superstructure ................................................................................................... 95 6.3 Connecting and approach roads ................................................................................. 100

7 CONCLUSIONS AND RECOMMENDATIONS ...................................................................... 104 7.1 Summary of Key findings on climate change threats.................................................. 104 7.2 Summary of Key findings on climate change vulnerability ......................................... 107

8 REFERENCES ................................................................................................................... 111


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1 INTRODUCTION Climate change is a maturing science. Efforts over the last two decades have built understanding and confidence of how climate is changing and more importantly the science behind it. We now have evidence that temperatures are becoming hotter and more variable, rainfall in tropical regions will also increase in both intensity and variability with wetter wet seasons and drier dry seasons, arctic sea ice extent is shrinking faster than projected while sea levels are rising more rapidly than anticipated and return periods for extreme events such as major floods and droughts are reducing. The science of climate change has progressed to the point where projections are successful in predicting long‐term trends in hydroclimate and the majority of remaining uncertainty in the implications of feed‐back loops for the global climate system is skewed towards a stronger not weaker climate response (Roe et al, 2007). Understanding of the global climate system has progressed sufficiently for scientists to understand that in the next fifty years fundamental changes to the global hydroclimate are inevitable – regardless of any efforts by the international community to reduce greenhouse gas (GHG emissions). Adaptation is therefore an urgent priority for the vulnerable social, economic, built and natural systems around the world. And Vietnam; as a populous rapidly growing Southeast Asian nation, whose citizens, cities and economic activity are concentrated in low lying coastal deltas of some of East Asia’s major river basins is one of the most vulnerable nations in the world (Gupta et al, 2007).

The application of climate science to inform adaptation response remains an emerging field. For built systems, adaptation means making tangible adjustments to the design and maintenance of infrastructure assets and represents a balance between engineering risk, regulatory requirements and economic costs. To do so with confidence requires detailed quantification of future hydroclimate conditions with climate change as well as an understanding of the variability, assumptions and uncertainty behind these projections.

In the Asia‐Pacific, growth in the transport sector outpaces gross domestic product (GDP) and will continue to do so for the foreseeable future (ADB, 2011). Growth in this sector has helped to drive economies, connect countries and forms the backbone of cities throughout the region. Governments in the Asia‐Pacific are now spending close to 1% of GDP on transport expenditure (Dulac, 2012), while multi‐lateral development banks are spending billions of dollars per annum ‐ $3.4 billion per year by the ADB alone (ADB, 2011). These investments are vulnerable to climate change.

The development of transport infrastructure represents a substantial investment for developing countries, both as an upfront capital cost and in on‐going maintenance. These investments are made on the understanding that structures and its individual components will have long design lives of 30, 60 and up to 100 years allowing benefits to accrue over tens of decades of use (Figure 1‐1). Engineers are asked to design for and manage risk over the project lifespan, requiring a balance between a desired level of safety, optimisation of performance and a minimisation of costs. Many of the design parameters and safety margins incorporated during the design phase will change in response to global climate change. Engineers need to make a decision on how best to integrate this changing hydroclimate context into their transport projects. From a risk perspective, cautious approaches that take full account of all risks will inflate upfront investment costs, while conservative approaches will increase ongoing maintenance and repair costs as well as compounding additional risk to structural integrity and safety issues.

Figure 1‐1: Design life of key road and bridge infrastructure (adapted from ICEM, 2011; Cochran, 2009; DEFRA, 2010)

Vietnam maintains an investment in transport infrastructure equivalent to 2.5% of GDP – more than double the average for the Asia Pacific. This has led to significant advancements in the development of the national

Expansion joints Free slide bearings

Bridge Deck Stay Cables Pylons & bridge foundations

Approach bridge support piles

Road drainage & culverts

River & road Embankments

Road foundations Pavements


transport network. In particular road infrastructure has improved with nearly 30,000km being added to the network and five‐fold increase in paved roads during the last seven years. This has contributed significantly to Vietnam’s economic growth, with per‐capita gross domestic product (GDP) increasing from USD 406 in 2000 to USD 765 in 2007. Growth of the national road network has also included the establishment of some 33 border crossings with China, Lao PDR and Cambodia, contributing to a three‐fold increase in exports from USD 14.5 billion to USD 48.6 billion (JICA, VITRANSS 2, 2009). Vietnam’s road network now comprises over 256,000km, of which 17,385km are national highways, 22,783km are provincial roads, and the remaining are local roads (district roads, commune roads, urban roads and exclusive roads). The network is relatively dense and is considered to be well distributed for demand and terrain; however roads are generally narrow with 60% of roads having less than two lanes, severely limiting their capacity. In addition major government and international assessments have identified that connectivity of the network remains one of the most pressing and critical issues for the sector (JICA, VITRANSS, 2009).

The ADB Central Mekong Delta Connectivity project represents a USD 750 million investment by the Government of Vietnam for the development of strategic transport infrastructure to enhance connectivity between the central agricultural and agro‐processing provinces of the Mekong Delta with major regional hubs such as Ho Chi Minh City and further afield Phnom Penh and Bangkok. Design and construction of the project has been phased into 6 components, of which components 1‐3 are the focus of this Climate Change Vulnerability and Adaptation study (VA Study) (Table 1; Figure 1‐2).

Table 1: Main infrastructure components of the Central Mekong Delta Connectivity Project

Figure 1‐2: Layout of Central Mekong Delta Connectivity Project

•6 lane Cao Lanh Bridge 3km over the Tien River (7.8km with approach roads)Component 1

• 4 lane Cao Lanh – Vam Cong connecting road (15.65km)Component 2

•6 lane Vam Cong Bridge 3km over the Hau River (5.75km with approach roads)Component 3

•Long Xuyen bypass to to Long Xuyen City (17.45km + 6.11km)Component 4 + 5

•4 lane My An – Cao Lanh connecting road to link up with NH30 (26.2km)Component 6


The bridge design has completed the feasibility stage. In October 2011 the detailed design team was fielded, with the detailed design phase scheduled for completion by October 2012. Construction is scheduled to start six months later in April/May 2013, and completed by 2016.

The project – Delta Bridges: Rapid Climate Change Vulnerability and Adaptation Assessment (VA Study) – falls under ADB TA‐6420(REG) Promoting Climate Change Adaptation in Asia and the Pacific using CQS and has been commissioned by ADB to quantify the risk posed by climate change to the current design of components 1‐3 and to suggest adaptation options which may be included into the detailed design phase. The VA Study has been designed to run in parallel to the detailed design phase and engage in the project development cycle prior to construction or finalisation of decisions on design and investments to: (i) integrate adaptation options into the project from the outset (figure 1‐3), and (ii) ensure the overall sustainability and longevity of the development in the context of climate change.

Figure 1‐3: Timing of the CC assessment – the V7A Study will present adaptation options during the detailed design phase to ensure integration with EPC at the outset of the project

ADB will use the outputs of this rapid assessment to apply to the Nordic Climate Facility under the Nordic Development Fund (NDF) for a grant to finance adaptation options. ICEM has been contracted by ADB Regional and Sustainable Development Department (RSDD) to implement the VA Study over 6 months from September 2011 to February 2012. The study will provide the technical and economic justification for climate change adaptation response for the broader Central Mekong Delta Connectivity Project.

1.1 Project outcomes The outcome of the project will be two‐fold: (i) the integration of climate change risk management into the detailed design of components 1‐3 of the Central Mekong Delta Connectivity Project, and (ii) pilot‐testing of a rapid climate change Vulnerability and Adaptation methodology for transport infrastructure projects. The latter outcome extends further than the Central Mekong Delta Connectivity project to other transport development projects being considered by the ADB and the Government of Vietnam.

1.2 Project outputs The project aims to achieve the outcomes through:

(i) quantifying climate change impacts on the infrastructure, performance, maintenance and legal compliance of the Bridges and connecting road;

(ii) prioritising specific adaptation options that are technically sound, realistic and economically viable;

(iii) improving understanding of climate change risks of key stakeholders, including the detailed design team and the Cuu Long CIPM;

(iv) testing a climate change V&A methodology for use in transport infrastructure projects

1.3 Scope Setting the scope of the VA Study includes both a spatial and a temporal component and has been determined based on the design life of the infrastructure components and technical considerations associated with the climate change modelling methodology.


1.3.1 Geographical focus The project will consider four primary geographical scales of focus (figure 1‐4). The purpose of tailoring the assessment to different scales is to progressively downscale changes in the hydro meteorological regime to a resolution suitable for analysis of climate change (CC) vulnerability. Resolution at the global level (used in GCMs – Global Circulation Models) is in the order of 250km x 250km. At the Mekong basin level modelling resolution is increased to 5km x 5km, and <1km x <1km at the Mekong Delta Level. At the project level resolution is in tens of metres.

Figure 1‐4: Geographic focus of the VA Study

The two primary scales of focus for assessment findings include the project site and Mekong delta level:

1) PROJECT SITE LEVEL: Assessment at the project site level involves detailed three‐dimensional simulation to quantify clear and justifiable causal links between changes in hydro‐geo‐physical processes (e.g. rainfall intensity, range in daily temperature, flow velocities and water levels) with impact on specific bridge components (e.g. pylons, stay cables, road embankments).

2) MEKONG DELTA LEVEL: the Delta‐wide threat assessment will give a broader understanding of how the river channel and surrounding floodplain will respond to climate change. Assessment at this scale will integrate the project into its surrounding context producing a more realistic assessment of vulnerability and consideration of issues and impacts which extend beyond the local conditions of the project site. The Delta scale also introduces more options for adaptation response. In some cases it may be possible to reduce climate change threats by altering management in a broader area. For example, some of the impacts on Components 1‐3 associated with changes in flood dynamics could be offset by better management of the wider delta floodplain and the introduction of flood relief zones designed to store overland flow during flood peaks and release during flood recession.

1.3.2 Spatial scope The time scales for the assessment are defined for baseline and future climate conditions.

Baseline: 1980 – 2005 One of the major difficulties in predicting future climate is reconciling the complex inter‐decadal trends in climate and rainfall. The Mekong rainfall regime undergoes decadal patterns of wet and dry spells influenced by the strength of the monsoon, occurrence of cyclone activity and ENSO variations (Figure 1‐5). Therefore, the selection of the baseline period affects the magnitude of relative climate change because it provides the historic levels against which future climate change is assessed and determines what kind of climate conditions (average, wet, dry) are incorporated as part of that baseline. Short baselines could result in a drier or wetter average baseline rainfall which would alter the size of change predicted by climate change modelling. Previous studies have found that mean annual rainfall between historical decades can vary by as much as +/‐ 30% (Johnston et al, 2009; MRC, 2012; Figure 1‐5). For this study a 25 year baseline was selected to ensure that


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average (early 1980s), wet (1996 – 2005) and dry phases (1985 – 1995) were captured in baseline trends (Figure 1‐5).

Figure 1‐5: Decadal variability in Mekong rainfall: Percentage variance of the mean annual rainfall compared to the long‐term historical mean. (Source: MRC, 2012)

Source: (MRC, 2010) Under the chosen 25year baseline, all available monitoring stations provided an average one station per 7,418km2 of basin area (Table 1‐2). Coverage is worse in Lao PDR and Cambodia where long time series data is not available in remote areas. Improved station density could be provided by including more monitoring stations but at a cost to the length of available time series.

Table 1‐2: Spatial distribution of Meteorological monitoring stations used in CC downscaling

LMB Country* No. Precipitation stations

No. Temperature Stations

Total Station Density (km2/station)

Cambodia 6 6 12 13,090

Lao PDR 16 4 29 10,388

Thailand 98 12 110 1,714

Vietnam 7 8 15 4,481

Total 127 30 166 7,418

* Note, this table only shows stations within the Lower Mekong Basin, a number of stations in the Upper Mekong Basin and the surrounding catchments were also used in the modelling but have not been included in calculating densities.

A shorter baseline would have increased the number of available monitoring stations as many of the stations in the Mekong Basin do not extend back to 1980 (for example in Lao PDR), however, this would have reduced the historical variability of the Mekong hydroclimate encapsulated in the baseline. At the same time, longer baselines reduce the coverage of monitoring stations which have the required time‐series observational data, resulting in a poorer distribution of input data and less confidence in the modellings ability to undertake spatial interpolation to “fill the gaps” between monitoring stations.

Future time slice: 2050 and 2100 Future time slices were selected to be centred on 2050 and 2100. The 2050 time slice aggregates daily data for hydroclimate variables over the period 2045 – 2069, while the 2100 time slice aggregates over the period 2074 – 2099.1 These 25year time slices have been selected to match the spatial range available in the baseline data.

From an asset point of view, these two time periods represent the projected total design life (i.e. 90‐100 years) and approximate half‐life (40‐50years) when major upgrades and replacements are often scheduled (for example, stay cables, free slide bearings and road foundations).

1 Not all GCM data could be statistically downscaled to 2100. For some downscaled time series data extended only to 2088.


2 BACKGROUND

2.1 Origins and geomorphology of the Mekong Delta The origins and fate of the Mekong Delta are fundamentally linked to sea surface levels and changes in hydrology of the Mekong River. Some 8,000 years ago, at the start of the Holocene, sea levels were in the order of 4.5m above present levels and the coastline of the South China Sea reached close to Phnom Penh, some 4,000 years ago, the coastline was in the vicinity of Can Tho City (Figure, 2‐1; MRC, 2011). Southeastward aggradation of the delta was due to alluvial deposition from the Mekong River which built up the land mass in combination with a slowing rate of sea level rise in the past 7,000 years (Church, 2008). Rates of aggradation peaked at 17‐18 m per year (MRC, 2011) with some present sites of aggradation remaining on the tip and western shoreline of the Ca Mau Peninsula. Formation of the delta has resulted in flat low lying terrain with an average elevation less than 1.0 m above sea level, with the exception of some small mountains in Kien Giang and An Giang provinces. More than 61.5% of the delta lies below 1masl, while only 2.1% is greater than 3.0masl (Figure 2‐2).

Figure 2‐1: Aggradation of the Mekong Delta during the Holocene: dotted lines and numbers in white circles indicate the location of the coastline and the timing in thousands of years (Source: MRC, 2012)

Source: (MRC, 2011)

Figure 2‐2: Distribution of delta land area by elevation

Source: Southern Institute of Water Resources Research (SIWRR), 2010


From a geomorphological point of view the Delta can be classified into three broad categories based on the fluvial nature of its formation:

1) Ancient alluvial terrace: Fluvial deposition of Mekong sediments has built up the border area between Cambodia and Vietnam to create an alluvial terrace approximately 2.0‐5.0masl;

2) Riverine levies: Fluvial deposition of Mekong sediments has also resulted in the creation of natural levies along Tien and Hau rivers channels, typically with an elevation of 1.0 – 3.0m;

3) Freshwater and coastal floodplains: Adjacent to the Tien and Hau Rivers are two important floodplain depressions (Plain of Reeds and Long Xuyen Quadrangle respectively). These areas together with the coastal tidal areas typically have an elevation of 0.3 – 1.5m.

The project site is located within the transition zone of the alluvial terraces to low lying floodplain.

2.2 Hydrological zoning of the Delta

The Mekong Delta can be divided into three broad zones based on the balance between coastal and upstream hydrological influences:

1) Deep inundation zone (Plain of Reeds, Long Xuyen Quadrangle): Northern region of the Vietnamese Mekong Delta dominated by overbank flooding of the Tien and Hau river channels due to upstream hydrology. Flood levels in this zone typically exceed 2.0m.

2) Moderate inundation Zone (Can Tho, Vinh Long, My Tho): Central region of the Mekong Delta constituting mixed influences of upstream hydrology and coastal influences

3) Coastal zone (Mekong River mouth and Ca Mau peninsula): Eastern and southern regions of the Delta, where marine processes dominate local hydrology.

Figure 2‐3: Zones of the Mekong Delta: (LEFT) Broad zones based on coastal and fluvial hydrological drivers; (RIGHT) Hydrodynamic zones of the deep inundation zone/ The Central Mekong Delta Connectivity project connects Zone C to Zone A with Component 2 crossing Zone B

Source: (LEFT) ICEM, 2012; (RIGHT) Douven et al, 2008

The Central Mekong Delta connectivity project lies in the transition area between zone 1 and 2, where local hydrology is influenced by both upstream flooding and marine processes. The MRC Flood Management and Mitigation Program (FMMP) has further subdivided this zone (Douven et al, 2008). The FMMP zoning is based on hydrodynamic characterisation of the different areas, though the floodplain is basically divided by roads and rivers. For Viet Nam three different zones can be distinguished, named A, B and C (see Figure 2‐3),with the project site traversing Zone B and connecting Zone A to C.

2.3 Land use and infrastructure of the Delta The Mekong Delta of Vietnam has a total area of about 4 million hectares, of which 2.4 million ha is agriculture land, contributing some 48% of national food production, more than 85% of annual rice exports, 57% of

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2

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national aquaculture production and 41% of Vietnam’s capture fishery (GSO, 2010). In 2010, the total population of the delta was more than 17.3 million people (19.9% population of Vietnam).

Figure 2‐4: Mekong Delta Water Resources development plan to adapt with climate change and SLR: BLUE areas will be under partial flood protection; MAUVE and YELLLOW – under full flood protection; and PURPLE ‐ brackish zone. The Central Mekong Delta Connectivity project lies within the zone of full flood protection.

Source: SIWRP, 2011‐SCN‐II

Three kinds of infrastructure are wide‐spread throughout the Delta: canals, sluice gates and embankments. The canal systems, sluices and embankment have played an important role to extend the agriculture area and increase the agriculture production from 6.3 million tons of rice in 1985 to 21 million tons in present time. Road development plays an important role for socio‐economic development.

Canal network: The Mekong delta of Vietnam has about 28,600 km long of the rivers and canal. In which 13,000 km consist of the rivers and canals with water depth greater than 1 m and hence suitable for navigation; 6000 km of which are suitable for large ships with transportation capacity of 50 to 100 tons.


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Sluice gates: The Mekong delta has about 80 sluice gates with a width of above 5m; hundreds of sluice gates with a width of 2m to 4m and more tens of thousands of small sluices (SIWRR, 2010). The sluice gates play an important role in the prevention of saline intrusion, acid sulphate soil control, irrigation and drainage as well as for flood and fire control.

Transport and agricultural embankments: The development of flood control infrastructure in the delta has been rapid, with little existing prior to 1996. To date the delta has about 7,000 km of low embankment to protect the area at the early stage of floods. While an additional 450 km of sea dike, 1,290 km of river dike and more than 7,000 km of canal embankment are being planned and investigated (figure 2‐4). In addition roads in the Mekong Delta are typically built on embankments which also alter flood flow dynamics. The delta has about 22,800 km of roads, 2,471 km of which are national road; 3,400 km of provincial roads and 17,000 km of rural roads.

The 1999 Water Resources Master plan (including flood protection) was recently updated to include climate change with the key objective of taking advantage of the benefits of regular flooding while protecting from the damages associated with extreme flooding (figure 2‐4). In general, the spatial distribution of flood protection level in the water resources development plan to adapt with climate change and sea level rise are similar to that in the water resources development plan to 2010 with the following areas of the delta are under full and partial flood protection;

Full flood protection (mauve and yellow in figure 2‐4): a high ring dike will be introduced for urban areas and high development areas (3 rice crop areas or fruit tree areas) for full flood protection even under extreme flooding. Northern part of the Mekong delta, the Plain of Reeds, the South Nguyen Van Tiep canal will be full protection by ring dikes, and the areas between the Tien and Hau River channels.

Partial Flood protection (blue figure 2‐4): Areas protected from flooding until the arrival of the flood peak at the end of August, after which time the dyke is overtopped and the area is flooded. The purpose of this is to protect agricultural land during the early part of the flood season for harvesting and then to allow peak flood waters to replenish agricultural land with fluvial sediments. The areas of Nguyen Van Tiep and Tan Thanh ‐Lo Gach will be partial protection.

2.4 Project site Based on the geomorphological and hydrological zones identified above, the project site is located on the riverine levies of Flood Zone B spanning the area between the Bassac (Hau) and the Mekong (Tien) Rivers. The Delta Bridges project area is located in the middle part of zone B in between Long Xuyen and Cao Lanh cities (see Figure 1‐1; 2‐4). A broad overview of the land use, infrastructure and socio‐economic characteristics of this zone is presented below based on Douven (2008).

1) Ecology: Zone B does not contain any remaining natural areas. Regarding agriculture, the zone consists of fertile alluvial soils. Fish migration routes are mostly confined to the rivers, though in the wet season fish can move over the floodplains. Movements are, however, restricted by the numerous levees.

2) Land use: Many areas are islands that are only accessible by ferry or boat. Nearly all of the available land in this zone is used for agriculture, as the most fertile lands in the Mekong Delta are found here.

3) Settlements: There are no major towns, except for some smaller settlements, though the levees are inhabited by local farmers and hence population density is relatively high. These areas have a higher elevation, which also allows growing of perennial crops, such as fruit trees.

4) Roads: The south‐eastern border of zone B is formed by highway 1. Even at times of large floods this road section is hardly affected. National Road 80 crosses zone B. Other main roads can be found along the Hau and Mekong Rivers. The road network in zone B is further formed by paved and unpaved roads on natural and manmade levees.

5) Socio‐economic characteristics: The western part of Zone B is relatively remote while the eastern part is located closer the major transportation routes. Zone B has easy access to water transportation, being surrounded by rivers. The higher lands on the levees make some diversification of agricultural production possible; hence zone B produces more fruits.

Taking into account these zonal characteristics, the modelling under this VA Study has included a local floodplain description characterised by full flood protection (figure 2‐5).


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Figure 2‐5: Floodplain elevations and infrastructure at the project site: Full flood protection structures are shown in pink

2.4.1 Road impact on flooding The road embankment of Component 2 shall be constructed higher than the existing ground elevation and cross natural drainage lines of the floodplain. As such, the road embankment will have the potential to impede the flow of surface run‐off particularly during flooding events exacerbating water impoundment and localized flooding. The possible areas to be affected along the Project corridor are shown in Figure 2‐6.

Figure 2‐6: Potential impacts of CMDCP on flooding: Shaded areas are potentially flood prone due to the project

Source: SMEC, 2011

The TEDI EIA (2009) assessed increased flooding risk to be low given the transverse culverts and bridges along the alignment and the very high drainage density and flat topography of the Delta. Drainage density in the


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project area is estimated at 2.5 km/km2 to 3.8 km/km2, a factor which according to TEDI allows flood water to drain freely provided these channels are not obstructed. Components 4 and 5 will have 25 bridges while Component 6 will have 23 bridges and 36 cross culverts. The aperture and elevation of the culverts are based on hydrologic and hydraulic calculations. The total water drainage aperture of culverts is designed to be bigger than the total water opening of existing culverts on NH91, NH80 and NH54. The designed apertures have been issued written approval by the People’s Committee of Can Tho City and Dong Thap Province.

2.5 Central Mekong Delta Connectivity project (CMDCP)

2.5.1 National context Over the last decade, Vietnam has made significant advancements in the development of its transport infrastructure. In particular road infrastructure has improved with nearly 30,000km being added to the network and the amount of paved roads has increased five times in the last seven years. This has contributed significantly to Vietnam’s economic growth, with per‐capita gross domestic product (GDP) increasing from USD 406 in 2000 to USD 765 in 2007. Exports also grew more than three times – from USD 14.5 billion to USD 48.6 billion (JICA, VITRANSS 2, 2009).

Despite ongoing advancements, the gap between available infrastructure capacity and increasing demand has widened. Investment in transportation has stayed at approximately 2.5% of Vietnam’s GDP. Many transportation issues have also emerged including traffic congestion in urban areas, low mobility in rural areas, inadequate road maintenance, a lack of funding, poor infrastructure quality, and weak transportation services (JICA, VITRANSS 2 – Chapter 3, 2009). In addition to these fundamental issues, Vietnam is also affected by natural disasters that are likely to change the frequency, duration and severity with climate change and threaten infrastructure. It is likely this will not only affect transport infrastructure, but also its operation and the demand for transport services (UoC and CIEM, 2011).

Between 2001 and 2005, extreme weather events caused VND 2,571 billion of damage to the transport sector. If mean sea level rises by one metre, MONRE estimates that 11,000 km of roads could be submerged. The total length of national highways threatened would be 695 km (MONRE, 2010). An estimated 4.3% of existing national and local roads would be permanently underwater, including 574km of dykes. In addition recent studies of climate change impacts for the national transport sector have found that opportunity costs associated with potential climate change impacts on transport, among other sectors, have the potential to further delay infrastructure development plans through diverting funding to the maintenance and adaptation of existing infrastructure (CIEM, 2011).

Transport networks of the Mekong Delta are the most vulnerable in the nation to climate change. More than 70% of national highway predicted to be permanently inundated by Sea Level Rise (SLR) (MONRE, 2011) and almost 90% of affected road infrastructure lies within the Mekong Delta region (Carew‐Reid 2007).

Motorisation is rapidly increasing in Vietnam due to rapid urbanization, population growth and economic development, causing increased air pollution, especially in cities such as Hanoi, Danang and HCMC. Studies have shown that air quality in Vietnam’s major cities is becoming significantly deteriorated (ALMEC, 2010). The number of registered vehicles in Vietnam has rapidly increased over the last two decades, reaching approximately 28 million in 2009, from 6.68 million in 2000 and 1.45 million in 1990. Vehicles registered in Hanoi and HCMC account for 70% of Vietnam’s total automobiles and 30% of motorcycles. Motorcycles account for almost 96% of Vietnam’s registered vehicles.

At the same time there is a critical and increasing demand for enlargement and improvement of the national road network. Overall, transport demand has grown rapidly in the last decade and at a rate slightly faster than economic growth. In the Transport Development Strategy 2020, the MOT projects an average growth rate of 7.3% per year between 1990 and 2030 for goods transport demand. The demand for passenger transport is growing even faster at 12% per year for the same period. Other estimates have projected a growth in transport demand to be between 5.2% and 6.2% annually (VITRANSS, 2009).

2.5.2 Need for the CMDCP The Central Mekong Delta Connectivity Project consists of two bridges and an interconnecting road, which will form part of a strategic transportation link, connecting the provinces of Dong Thap, An Giang and Can Tho to the Second Southern Highway. This will enhance the access of the highly competitive agro‐industries in these


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areas to important regional and international export markets. The total financial cost of the project was estimated to be about USD 706 million in 2011 (Table 3).

Currently the route crosses the Tien and Hau rivers by ferry, which represents a significant bottleneck, extending journey times considerably. In the future, projected increases in traffic flows would necessitate expansion of ferry capacity. Relative to the current road‐ferry connection the project is expected to shorten journey times by about 24 minutes, through reduced waiting time for the ferry, increased road speeds over the new much widened and improved road sections, and slightly reduced distance. Overall the project is expected to generate considerable benefits.

Table 3: Financial costs (2010 USD)

Component Item USD (million)

Cao Lanh and approach roads

Construction 208.2

Physical contingency 24.4

Land and resettlement 22.9

subtotal 255.5

Interconnecting road

Construction 141.9



subtotal 174.5

Vam Cong Bridge and approach roads

Construction 241.8



subtotal 275.9

Total 705.9 Source: SMEC, 2011

2.5.3 Main components of the CMDCP Based on a review of the documentation, the sensitivity analysis grouped the design components of the bridge and road. The sensitivity of these component groups is a function of the infrastructure they comprise, the processes they support, and the maintenance they require:

1) Bridge superstructure: Components of the bridge above the foundations including the deck, stay cables, cross beams and edge beams. For the purposes of this study, expansion joints, free‐sliding bearings, railings have been considered components of the superstructure.

2) Bridge substructure: Foundations and support components of the bridge, including pylons, foundations and metal reinforcements.

3) Roads, approach roads and foundations: Connections between Component 2 and components 1/3 and road surfaces

4) Embankments and road foundations: foundations, underlying geotechnical properties of the ground conditions, embankment and revetment design

5) flood protection control and drainage infrastructure: casing and protective works for road and embankment surfaces, culverts, flow‐through and drainage outlet structure and rip‐rapping

Understanding of the design of the bridge and road components is based on: (i) the feasibility study report, (ii) discussions held with Cuu Long CIPM and the detailed design team (September 2011; and March, 2012). Components 1, 2and 3 comprise: (a) a cable‐stayed bridge over the Tien River; (b) 26 smaller bridges to facilitate road crossings over the delta floodplain; and (c) 24.1km of connecting road extending towards the Vam Cong bridge – a cable stayed bridge over he Hau River.

Main bridges The project includes two major bridges, Cao Lanh and Van Cong crossing the Mekong River. Cao Lanh bridge is a cable‐stayed bridge with spans 150+350+150m and approach bridges with a total length of 682m on both sides. Vam Cong bridge is a cable‐stayed bridge with spans 190+450+190m and approach bridges with a total length of 1139m and 960m. All approach bridges are made using precast concrete elements. The road section on bridges is 24.5m wide. Substructures are made with cast‐in‐situ concrete. Both bridges are founded on bored piles.


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The bridges shall be designed using Vietnamese bridge design code 22TCN272‐05. The code bases on AASHTO LRFD (Load and Resistance Factor Design) design method. The LRFD bridge design philosophy is based on the premise that four Limit States are stipulated to achieve the basic design objectives of constructability, safety and serviceability. All limit states are given equal importance. LRFD method is a probability‐based Limit State design where structural components and systems are classified according to redundancy, ductility and operational importance. The four limit states are Service Limit State (SLS), Fatigue and Fracture Limit State, Strength Limit State (ULS) and Extreme Event Limit State. The SLS gives limitations for usability and durability of structure. Fatigue and Fracture Limit state handles the repeated traffic loading on structure. The ULS is the main limit state for structural safety. The Extreme Event Limit State handles unique occurrences like a major earthquake, flood, collision by a vessel or vehicle, etc.

In terms of water levels, there is a design constraint for bridge elevation based on providing a minimum navigation clearance of 37.5m for the P5% flood (Annex 2). The VA study understanding is that the P5% is defined as 2.6masl and approximate to the year 2000 flood event.2

This clearance has been set in consultation with the Mekong River Commission (MRC) to allow future passage of 10,000DWT vessels upriver to Phnom Penh port.

Approach and connecting roads The approach and connecting roads include 26 bridges which cross canals and smaller rivers. The bridges are designed as precast concrete bridges with lengths between 34m and 603m. The openings of the bridges are designed to be adequate for design floods. The bridges are founded on bored or driven piles. Bridge approach roads will have embankments set for the P1% event and supported by driven piles.

To avoid sharp differences in settlements the bridge approach embankments are designed to be constructed using transition piling. In road structures sand drains, PVD’s, soil‐cement columns and concrete piling are used to reduce settlements. The bridge foundations and embankments shall be protected against scour.

Roads associated with Components 1, 2 and 3 are designed to accommodate 6 lanes of traffic in the future with a total cross‐sectional width of 30.6m. Embankment side slopes are1V:2H. The minimum elevation of the road profile is based on:

(i) P1% flood event; (ii) 0.5m freeboard to accommodate overflow and wave action from upstream flood plain; and (iii) 0.3m freeboard nominally set to account for SLR.

In addition there is a 0.3m crossfall from the road centre line to the outer shoulder of the embankment. Discussion with the detailed design team in March 2012 indicated that road elevations can reach up to 4.75m.

Road drainage Road structures will include two main design solutions for drainage:

(i) Surface drainage: Concrete curbs will be provided for embankments with elevations greater than 4m. Discharge points will be every 25m with rock rip rap at the outlet to protect embankments.

(ii) Flood conveyance: 28 culverts are proposed along the alignment of the connecting road ranging in size from 2mX2m box culverts to 3mX3m multi‐cell culverts. The number and sizing of culverts has been set to provide sufficient openings for conveyance of the P1% event and is currently being assessed by the detailed design hydraulic study.

Bridge crossings Given the complexity of the delta canal and river network, there is a total of 26 and some 4.1km of bridge crossings. Vertical clearance for the bridge crossings is based on the following:

(i) Navigable channels and rivers: Navigation clearance for the P5% event. Discussion with the detailed design team in March 2012 indicated that this clearance is in the order of 1.2 –

2 Calculation of the P5% flood for Cao Lanh station is shown in Annex 1 and equal 2.54m at Cao Lanh Station, accounting for water slope this equals 2.57m or approximately 2.6m at the bridge site.


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3.5m, except for the Lap Vo River Bridge (KM18.7+) where the navigation clearance is set at 7m.

(ii) Non‐navigable canals: for small non‐navigable waterways the bridge clearance level is set as P1% + 0.5m freeboard.

2.5.4 Policy context The national and regional policy and planning context is summarised in the table below.

Table 4: National and Regional policy milestones for climate change response in the transport and water resource sectors

National

Delta Region

In 2008 the Government of Vietnam instructed MONRE to prepare a National Target Plan for Response to Climate Change (NTP).

Sea dike implementation, under the decision 667/QD‐TTg on 27

th May 2009 for improving the

sea dike from Quang Ngai to Kien Giang;

In December 2008, the GoV approved the NTP (Decision 158/2008/QD‐TTg dated 2nd Dec 2008). Under the NTP each ministry and People’s Committee are required to produce an Action Plan for Climate Change Adaptation.

Provincial action plan to adapt with climate change, number of provinces in the Mekong delta have approved their action plan, like Can Tho and Ben Tre

Ministry of Transport, with support from ADB (TA 7779), is currently preparing their ministerial Action Plan with a focus on reviewing and updating design standards and identifying priority assets of national interest at risk.

Flood protection and inundation protection for Can Tho, Vinh Long and Ca Mau provinces done by MARD;

National water resources development strategy to 2020 with a view to 2050 was approved by decision 1590/QD‐TTg dated 10th Sep 2009.

Water resources development plan in the Mekong delta to adapt with climate change and sea water level rise.

The official national projection of climate change including sea level rise was approved in 2009.

In December 2011, the national strategy for Climate change response was also approved (2139/QD‐TTg on 5th Dec 2011).

In 2012, MONRE will release the revised official national projections for climate change including sea level rise. The document took into account recent improvements in climate science and climate modelling.

The GoV intends to update the official climate change projections every five years. The main reason behind this is that most of historical climate and hydrological information collected under the French colonial regime and during the war with US was lost or damaged, consequently, the majority of hydrological and climate observational data starts from 1978, therefore a five yearly update allows for a continued improvement and of the climate change baseline to build confidence in long term predictions of climate change.

At the time of the VA Study, the national projection for climate change released in 2009 was not yet officially superseded and has been used as a reference throughout this report. Sea Level Rise (SLR) predictions are derived directly from the official projections. Updates expected in the revised version are not expected to have significant impacts on the findings of this study.


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3 EXISTING ISSUES FOR TRANSPORT DEVELOPMENT IN THE MEKONG DELTA

3.1 Seasonal flooding and water levels

3.1.1 Typical flood events Flooding is recognized as part of the natural geomorphologic process that maintains high primary and fisheries productivity and drives the dynamic evolution of the Mekong Delta. The annual flooding event is responsible for replenishing the fertile alluvium that is vital to the agricultural productivity of the Delta region. The floods also play a vital role in the natural treatment of the acidic water produced by the leaching of the acid sulfate soil that permeates much of the lower reaches of the Mekong Delta.

Flooding in the Mekong Delta is moderate in comparison to flooding in the upstream region. Flood amplitudes of 3.5 – 4.0 m occur near the boundary areas of Chau Doc and Tan Chau with water level change rates of 20 ‐ 30 cm per day and channel flow speeds between 0.4 and 0.6 m/s. There are generally two peaks of flooding during the year, one in September / October and the other in August. It is estimated that during occurrence of high flood, 40,000 to 45,000m3/s of flood water crosses the border from Cambodia into the Delta, where 80% of this flow is coursed through the main river and 20% occurs as overland flow.

Six of the 13 Delta provinces regularly experience flooding, including: Dong Thap, Long An, An Giang, Kien Giang, Can Tho, Tien Giang, Hau Giang and Vinh Long. In a large flood, inundated areas may encompass 1.6 million hectares, while elevated flood water levels can last between 3 to 6 months. Conversely, seven provinces are prone to drought and salinity intrusion, including: Kien Giang, Tra Vinh, Ben Tre, Soc Trang, Ca Mau, Bac Lieu and Long An, with more than 1 million hectares affected by salinity intrusion with a concentration of above 4 g/l.

Zone B receives floodwater from both fluvial overbank and overland flow from Cambodia (Figure 3‐1). An elevation gradient between the Tien and Hau rivers drives flow from the Tien River, over the floodplain and into the Hau River – crossing the project site north to south. Drainage of the floodplain is primarily south‐eastward through the main channels and distributaries of the Mekong, though some of the flood waters are drained from the Long Xuyen Quadrangle through the extensive canal network and into the West Sea.

3.1.2 Extreme flooding events Serious flooding has occurred in the Delta during the years 1961, 1966, 1978, 1991, 1994, 1996, 2000, 2001, 2002 and 2011. Severe flooding usually occur when events of very strong rain coincides with spring tide, high‐high tide. Based on records, the historical flood of year 2000 is the worst flood within the last 75 years with:

• 600 people were killed • Total damages amounted to more than VND4,000 billion; • more than 2.3 million ha of land area affected; • 1,273km of the National inter‐provincial road and 9,737km of inter‐commune, inter‐town road

submerged; • 1,470km of dike and revetment damaged; and • 168'814 ha of paddies and about 93'265 ha of fruit and industrial tree plantations affected.


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Figure 3‐1: Flooding of the Mekong Delta freshwater floodplain under year 2000 conditions: Flood water reached up to 2.6m near the right‐bank of the Tien River but remained below 1.5m in the vicinity of the Hau River channel.

Simulation of flood water levels during extreme conditions is shown in Figure 3‐1 based on the MIKE 11 model. At the project site, floodplain water levels are greatest at the right and left bank of the Tien River and lower near the banks of the Hau River. This reflects the dominance of the Tien River in the conveyance of Mekong flow at this point – with two‐thirds of river discharge travelling down the Tien River. In addition the location of the project site at the transition from deep to medium inundation zone can clearly be seen with the majority of upstream areas experiencing flooding of up to 2.6m, while the area immediately downstream is restricted to flood depths of less than 1.5m.

Based on observation of previous historic floods and model simulations, the SIWRR has developed a simple, empirical water balance of flood movement through the delta (figure 3‐2). There is an average of 80% of the flood water pass through the main Tien and Hau rivers and about 20% of the flood flow arriving as overland flow from Cambodia into the two major flood depressions of the Plain of Reeds and the Long Xuyen quadrangle. However, during a large flood like the 2000 flood, the maximum of overland flood discharge was accounted for more than 30% of the maximum flood discharge to the Mekong delta.


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Figure 3‐2: Distribution of Mekong Flood flows through the Mekong Delta system: The contribution of overland flow from Cambodia increases during extreme flood situations.

Source: SWIRR, 2010

3.1.3 Tidal influences and saline intrusion Streams and canals in the Mekong Delta are influenced by the tides of both the South China Sea (East Sea) and the Gulf of Thailand (West SEA). In the South China Sea, the tide is semidiurnal but irregular and has a large tidal amplitude of 3 to 3.5 m. The regime has a 15 day cycle with a annual maxima in December and a minima July. The tidal effects from the South China Sea propagate over much of the Delta through the primary, secondary and tertiary canal systems. Farmers use these tidal fluctuations to drain and flood their lands.

Due to the high tidal amplitude at the river mouth, the tide’s range of influence on Hau River during the dry season extends deep into the delta. Its influence goes beyond Long Xuyen City, up to Chau Doc. At Long Xuyen, the elevation of the tide peak is 0.9 m lower than the river estuary and with lag time of five hours. During the flood season, the immense volume of fresh water from the Mekong River pushes the salt water interface seawards allowing for planting for about six months. Prolonged flooding may occur if drainage floods coincide with the spring tide (White, 2000). During this season the water surface gradient from Chau Doc to Long Xuyen is from two to four times higher than that from Long Xuyen to Can Tho due to the tide.

The combination of terrain and tides has resulted in strong propagation of sea influence throughout the delta.

In the coastal and mid‐delta zones, tidal fluctuations drive saline intrusion more than 80km upstream from the coast, affecting an average of 40% of the delta (SIWRR 2010; ICEM, 2010).

In the floodplain regions of the delta bordering Cambodia, tidal influences will affect water levels in the Mekong river channels by reducing the fluvial head of flow through the elevation of the mean sea water surface elevation. The reduced head will increase backwater effects within the channel prolonging the drainage of the channel and floodplains at the end of the flood season and consequently elevating the channel and floodplain water levels. The effect is most pronounced during high tide events or in combination with extreme events such as storm surge and king tides.


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3.1.4 Issues for transport infrastructure Figure 3‐3 identifies the key hydroclimate parameters which affect the functioning and integrity of road infrastructure. The different hydraulic components act differently on different damage mechanisms which can deteriorate a road (embankment and or surface). Six of the ten parameters are predicted to vary in response to climate change.

Figure 3‐3: Hydrodynamic/hydraulic and geotechnical failure mechanisms for road infrastructure in large floodplains

Source: Douven et al, 2008

Roads and road embankments are subjected to hydraulic loads in terms of water height, flow velocities, waves and rain. The action of floodwaters in combination with wind‐induced waves can compromise embankment protection works (even concrete), cause under‐scouring of embankment foundations and eventually destabilization or collapse of road surfaces (Figures 3‐10; 3‐11; 3‐12). A number of protection measures have been used by Delta provinces with limited long‐term success due to intensive maintenance requirements. For example, concrete casing (and rock/concrete rip rap) is highly susceptible to scour at the foot of the casing and the joins between concrete panels. Over time wave energy is able to erode the supporting geotextile behind the casing causing collapse (figure 3‐12). Lower cost options include the planting of Melaleuca trees form wind breaks immediately in front of the embankment, and the use of tarpaulin screen supported by polders can be back‐filled with branches & organic matter to dissipate wave energies (figure 3‐12). Though cheap, this option is easily damaged and needs continuous maintenance.

The dimensions of flooding mean that through‐flow structures are subjected to intense flow velocities and downstream scouring. Rip‐rapping of the culvert outlet can greatly reduce downstream erosion issues – though costly. In addition human use of the floodplain environment can see a quick build up of woody debris and sediments which can reduce the efficiency of flow through structures.

Where flow through structures have become partially or fully blocked, or in the event of a major flood events, upstream water levels can build up behind the embankment causing overtopping of the road surface. Though rare for national highways in the delta, this is a common phenomena for provincial and sub‐provincial roads leading to downtime during which the road is impassable and deterioration of the road surface.

Lastly, where the integrity of the embankment protection works have been breached floodwaters can increase the pore water content of embankment soils. The seasonal wetting and drying of embankment foundations will also lead to localized movement within the foundations, destabilization of the road surface and the development of pot‐holes (figure 3‐7).

Many of these issues are driven by wave energy acting on the embankment wetted surface. Changes in road alignment and embankment slope can, to a certain extent, minimize direct contact between the structure and the wave front and hence deflect some of the wave energy.


Figure 3‐4: Wet season conditions at the bridge sites ‐ Rice processing plant adjacent to the Vam Cong Bridge site. Water levels in September 2011 were 0.8m below the year 2000 flood max water

level (indicated in red)

Figure 3‐5: Wet season conditions at connecting road

sites ‐ site of Component 2 connection with PR849. Agricultural land and

provincial roads at the site are subject to shallow inundation during the wet season. In the

Future the Government of Vietnam plans to convert all of

the area surrounding Component 2 to “full‐flood

projection3”

Figure 3‐6: Floodplain inundation without flood

protection – inundation of up to 4.0m is common for Dong

Thap natural floodplains in the wet season. Wind and waves

acting on the open water surface can cause severe

erosion problems for road and irrigation infrastructure

downstream of the floodplain

3 Full‐flood protection uses dykes to prevent year round flooding during average conditions. Partial flood protection uses lower dykes to delay flooding until August under average conditions – allowing for the harvesting of the second crop before wet season inundation.


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Figure 3‐7: Hydro‐physical vulnerability of existing

provincial transport infrastructure – high water

tables, heavy inundation and weak soil structures reduce the

life of provincial roads in the Delta, resulting: in (top)

subsidence of road foundations (potholes); (bottom‐left)

erosion of road embankments and (bottom‐right) river

embankments

Figure 3‐8: Financial vulnerability of existing

provincial transport infrastructure – the

development and maintenance of transport infrastructure is

hampered by budgetary constraints. Dozens of bridges

and culverts on provincial roads connecting to the Cao

Lanh bridge remain unfinished or in a state of disrepair

Figure 3‐9: River bank erosion and protection options – River

banks of the Tien and Hau Rivers are predominantly clay

with interspersed lenses of sand‐size material. Annual

over bank flooding causes the erosion of the more mobile

sand layers and bank collapse: (top) houses on the in‐channel island of Hong Ngu district are highly vulnerable to river bank

erosion with three homes collapsing into the Tien River in

the 2011 flood season; (bottom ‐ left) concrete bank protection works in Hong Ngu

town; and (bottom – right) simpler wooden polder bank protection on the Tien River

south of Cao Lanh City


Figure 3‐10: Road embankment erosion and

protection options – Roads in Delta floodplain are elevated above the flood level by earth embankments which hinder

the conveyance of flood flows, protecting some areas of the

delta, prolonging inundation in others, and heightening

erosional issues from wind and wave action against transport

infrastructure

Figure 3‐11: Options for road embankment protection – wind and wave energies are sufficient that maintaining embankment integrity for

infrastructure in the floodplain is a major challenge

Figure 3‐12: Embankment protection measures – A

number of protection measures have been used with limited long‐term success due

to intensive maintenance requirements (bottom‐left)

concrete casing – by scouring the foot and joins of concrete panels, wave energy is able to

erode the supporting geotextile causing collapse;

(bottom‐middle) rock /concrete rip rap begins to

scour at the foot of the revetment; (bottom‐right) Melaleuca trees form wind

breaks. Tarpaulin supported by polders are erected along the

embankment & back‐filled with branches & organic matter to dissipate wave

energy


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The different failure mechanisms are:

flood overflowing ‐ flood waters cause increased water levels and flow over road

water surface tilting, water level oscillations, storm surges ‐ wind, tides or sudden surrounding flow and water level changes increase water levels at the road and cause overflowing

wave overtopping ‐ waves reach top of the road structure

wave run‐up ‐ wave energy pushes water above stable water level (SWL); the simplest estimate is R = 3*H, where R is maximum vertical run‐up compared to SWL and H is wave height

rainfall intensity ‐ energy of the raindrops erodes road surfacing

water level difference ‐ the water pressure gradient through the road structure can induce water flow through the structure and wash finer material and cause collapse of the structure

eroding flow ‐ sufficiently high flow velocity can cause erosion of the embankment

In this study the changes in these failure mechanisms have been assessed by the 3D hydrodynamic modeling in baseline and climate change conditions with the exception of the rainfall intensity. Modeling tools would allow estimation of for instance rainfall erosion energy, but current climate change information is lacking in estimating changes in rainfall intensity and storm activity.

3.2 Geotechnical stability of Delta soils and river banks

3.2.1 Delta Soils Due to the origin and formation of the delta, the soil structure is dominated by young deposits emerging since the Holocene (QIV). These deposits typically extend 30m below the surface and can be divided into four broad layers:

1) The surface land layer: 0.5 – 1.5m thick, including bright grey, yellow‐grey dust clay and sandy clay, dark grey organic silty clay. In this layer, some areas are over groundwater level and some areas are under groundwater level

2) The organic clay layer: under the surface layer is the organic clay layer with thickness increasing towards the coast and ranging from: 3 ‐ 4m (in Long An); 9 ‐ 10m (Thach An region, Can Tho), and 18 ‐ 20m (Long Phu region, Can Tho). The organic clay is often dark grey, bright grey or bright yellow. Generally, this layer is often soft plastic, plastic flow to flow. The soil is not compacted, contains a high void ratio, small density, and low shear strength.

3) The layer of sandy clay mixed with grains, laterite fragments and shells, or sand: This layer is 3 ‐ 5m thick, often lies between organic and inorganic clay layers (e.g. along Phung Hiep‐Quan Lo channel). However, some places such as My Tu and Can Tho have the sandy layers between the clay layers. This layer is not continuous in the whole region of Mekong Delta.

4) The clay unmixed with organic layer: the deepest of the Holocene layers with thickness increasing towards the coast and ranging from: 3‐4m from (Long An); 9 ‐ 10m (Thach An, Can Tho), 15 ‐16m (Vinh Quy, Tan Long, Can Tho), and 25 ‐ 26m (My Thanh, Can Tho). The clay layer is yellow‐grey or bright‐yellow and has a better load capacity is better than the organic clay layer.


3.2.2 Riverbank stability Riverbank collapse is wide spread in the Mekong Delta with an increasing frequency of occurrence as population pressures coupled with clearing of bank vegetation lead to more intensive use of river bank areas for housing, aquaculture and navigation activities. Changes in sediment loads of the Mekong due to upstream hydropower will lead to further escalation of this issue (ICEM, 2010). Each year houses, commercial infrastructure, roads and farmland are damaged or lost entirely through erosion and collapse of river banks.

The process of river bank collapse is summarized in Figure 3‐13. One of the critical mechanisms of relevance to this study is the mobilization of the less cohesive layers of the river bank through the rise and fall of the annual flood. These layers typically sit below the surficial layer and their erosion undermines the overlaying top layer eventually leading to collapse of the bank into the channel. Vulnerable sections of riverbank can be tens to hundreds of meters long and have been known to extend tens of meters inland destabilizing the foundations of road infrastructure located 20‐30m from the river bank itself (see examples below).

Figure 3‐13: Common mechanism for riverbank collapse in the Mekong Delta: Banks of the Tien and Hau Rivers are comprised of interspersed clay, and sandy‐clay layers often with some laterite fragments. The rise of flood waters, overtopping of the bank and subsequent return flow draining the floodplain back into the river lead to the mobilization of less cohesive sandy layers which undermine the stability of the overlaying riverbank (A). Over time failure occurs with unsupported overlaying layers collapsing into the water column.

Source: SIWRR, 2012

3.2.3 Lateral migration of river channel From Pnnom Penh the Mekong River divides into two tributaries: Tien River to the north and Hau River to the south. As the two rivers approach Vinh Long and Can Tho respectively, there is a sharp fourfold drop in river gradient and the rivers begin to fan out into a network of some seven distributaries. The drop in gradient also results in a slowing of flow velocities and a widening of the river channel cross‐section reaching several kilometers across at the river mouth. The changing hydrodynamics lead to further branching of the river channel – in particular for the Tien River which first divides into the My Tho and Co Chien rivers and then into a network of six distributaries including: Cua Tieu, Cua Dai,Cua Ba Lai,Cua Ham Luong, Cua Co Chien, cua Cung Hau (Figure 3‐14). Throughout their lengths, the Tien and Hau Rivers comprise numerous in‐channel islands of varying size with surface elevations set by high flood events. The islands concentrate river flow at the river banks contributing to riverbank erosion and scouring of the river bed (Dong, 2010). For the Tien River, the hydrodynamics of these meandering sections also leads to the formation of deep pools and can be up to 20m deep with an average depth of 10m upstream of Vinh Long (Dong, 2010).


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Dong ThapThuong Phuoc Village, Hong Ngu district

August 2011: Left bank of the Tien River collapses over night destroying three households as well as a number of

pig‐sty and cattle‐feed houses. 40 other households remain vulnerable to river bank collapse in this area of 80m X 25m. The main drivers of bank collapse are likely to be: (i) weak soil matrix in the top 5‐15m soil layer is

seasonally eroded by overbank flooding and return flow, and (ii) river planform results in turbulent, erosive flows.

Dong Thap

Tan Binh village, Thanh Binh June 2012: nearly 100m of riverbank collapses into the Tien River through a series of three movements over consecutive days. Areas affected extended up to 7m

away from the river bank destroying a road and cutting of traffic in other.

Surrounding villages of An Phong and Binh Thanh also suffered severe erosion of homes and roads, include collapse of the Binh Thanh Market and partial loss of

market land area.

Dong Thap Long Thuan, Hong Ngu district

June‐July 2012: 300m crack develops on Highway 30 extending more than 20m inland from the river bank. The crack is likely an initial indication of erosion of weak soils

under the road surface

Binh Thoi 1, Long Xuyen city (An Giang) May 2012: 120m of shoreline along extending more than

30m inland collapsed into the Hau River, destroying 6 households and an ice‐factory.

Meander and the formation of in‐channel geomorphologic features is limited in the Hau River by a deep underground fault line (Dong, 2010). In this channel, islands are typically elongated lozenge‐shaped and located within the middle of the channel. Flow in the Hau River increases significantly after the confluence with the Vam Nao River which transfers flow from the Tien to the Hau – evening out the distribution between the two channels.. 75km from the sea, the Hau River divides into two estuaries: Dinh An and Tranh De, and Bat Xac as the main estuary (Figure 3‐14).

During the flood season, discharge in the two channels increases by an order of magnitude and the complex interaction of flood flows and tidal excursion up the river channel result in turbulent flow and erosion of river banks. Cai Be and Can Tho are considered hotspots for wet season erosion as they represent the interface between these two hydraulic drivers (Dong, 2010). During the dry season the penetration of tidal influence reaches further upstream and the erosion interface can reach as far upstream as Chau Doc (Dong, 2010). An Giang and Dong Thap provinces in general are a hotspot for erosion because of the interaction of fluvial and marine flow drivers (FoG, 1996).


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Figure 3‐14: River Network of the Mekong Delta

From the actual surveys and reports written by the Institute of Marine Engineering, changes in the channel planform are shown for the Tien River within immediate vicinity of the project site (Figure 3‐14; 3‐15). more than 40 years of observational data indicate that the Tan Thuan Dong island immediately upstream of the Cao Lanh bridge site has grown on its downstream shoreline while eroding at the Island head. Due to the orientation of river curvature, the right‐bank of the Tien River has shown greater rates of erosion and lateral movement immediately up of the bridge site, with greater rates of aggradation downstream. Compared to the immediate surrounds and also the broader conditions for Dong Thap province, the river channel is relatively stable at the bridge site. In the future without climate change, the current trends of erosion of Tan Thuan Dong island head and outer banks of the river channel will continue (Figure 3‐15).

3.2.4 Issues for transport infrastructure The geological characteristics of Mekong Delta soils is typically of a weak surficial soil layer with organic content underlain by sandy soils and then a layer of mixed sand‐clay. The surficial layer can be 16‐30m deep, and up the sandy layer 9‐20m. These stratigraphical characteristics coupled with the delta’s hydrological regime make the region poorly suited for geological works and construction leading to issues of subsidence and destabilising of foundation works.


27

Figure 3‐15: Historical river bank erosion for the Tien river‐ Dong Thap province in 1966 – 2009

Source: MARD, 2002


28

Figure 3‐16 Predicted sites of future river bank erosion for the Tien River (2020)

Source: MARD, 2002


29

4 METHODOLOGY

4.1 Overview The VA Study will utilise ICEMs CAM assessment methodology4, which has been tailored to fit the geographical and sector focus of the study. The assessment methodology has been designed to use the latest in climate science to quantify the threat of climate change in terms of variables directly relevant to road and bridge infrastructure, combined with a technical review of feasibility study design and surrounding environmental conditions to clear articulate the impact of climate change. At the core of this approach are three key principles:

1. Confidence in impact: the study will focus on those threats which can be directly linked to Central Mekong Delta Connectivity design. Direct threats are those which affect a key design parameter of the built system and for which change in trends for that parameter can be quantified with confidence. The concept of directness is an important element of the methodology to reduce the level of uncertainty which the climate change analysis introduces into the design.

2. Identify levels of uncertainty: acknowledging the uncertainty in climate science can better characterise exposure and build confidence in assessment findings. In this study the methodology will assess the outputs from 6 different GCMs to explore a range of impact based on the range of threats predicted by international scientific consensus.5 Where necessary, reporting has followed these ranges to better characterise threat.

In addition results will be compared to the recently revised Official Climate Change scenarios for Vietnam as published by the Ministry of Natural Resources and Environment (MONRE)

3. Comparable methodology: where possible similar methodologies are employed in the study as those used by design engineers to set the design parameters. This allows results to be compared with calculations undertaken under conventional design phases.

The CAM methodology allows for the rapid quantification of the range in climate change vulnerability expected for a natural, social, economic, built or institutional system and for the planning and development of adaptation responses which; build adaptive capacity, reduce system sensitivity and minimise exposure to climate change threats.6

The CAM methodology involves six key assessment steps (figure 4‐1). First climate change threats are quantified and exposure is defined, then the sensitivity of the built system is characterised for specific components of infrastructure. The next step is to quantify the impact of climate change as a function of the threat and sensitivity. Impact Assessment matrices adapted from conventional environmental assessments will be used to score and rank the cumulative impact of climate change on the built system. The VA study will then assess the capacity of the project’s scheduling, technologies, finances and institutions to adapt to the change. Lastly, the VA study will then scope and set priorities for adaption response in those areas defined as being most vulnerable and finance options will be explored through the NDF. Follow‐up to the VA study would involve the detailed design, implementation and monitoring of specific adaptation response measures.

Figure 4‐2 summarises the vulnerability assessment approach. Threats are identified for the atmospheric and hydrological system at four scales (c.f. Section 1.3). Sensitivity is assessed for specific components of the bridge and road design (c.f. Section 3.3). Impact is a function of the threat and sensitivity and considered as changes to: (i) the integrity of project assets (i.e. damage), (ii) performance or use of the bridge and road, (iii) maintenance requirements over the project life, and (iv) the project’s legal compliance (e.g. design standards or regulations) (c.f. Section 3.4). The vulnerability of the bridge and road components is the combination of the impact and the adaptive capacity of the project both in term of technical aspects of design and project phasing and in term of financial and management capacity to define and respond to change (c.f. Section 3.5). Vulnerability is considered in terms of safety, longevity, and utility of the project.

4 ICEMs CAM – Climate Change Adaptation and Mitigation Assessment Methodology has been designed for implementation in developing country contexts and has been applied to nine countries in the Asia‐Pacific, including Vietnam. 5 IPCC. 2000. Special Report on Emissions Scenarios (SRES). Cambridge University Press, Cambridge

6 For large integrated CC projects for cities, catchments and nations, the CAM methodology also integrates CC mitigation activities into the assessment cycle, incorporating long‐term mitigation efforts as a way to avoid escalation of threats


Figure 4‐1: Overview of the Climate Change Vulnerability and Adaptation approach

The response to climate change impacts varies depending on the type of impact. Some impacts, such as compliance with Vietnamese national law or ADB safeguard standards must be avoided regardless of cost. Some impacts could potentially be absorbed with little change; others will require adaptation at different phases throughout the design and maintenance life. Figure 4‐3 identifies the key steps in the vulnerability assessment methodology.


3

Figure 4‐2: ICEMs CAM Approach for built systems: Scoping and categorising climate change vulnerability for bridge and road infrastructure

ADB | Mekong Delta Bridges CC Vulnerability Assessment| Inception Report | ICEM

32

Figure 4‐3: ICEM CAM methodology: Key steps in the Vulnerability assessment to quantify threats, sensitivity and impact of climate change on built systems

CLIMATE CHANGE THREAT IDENTIFICATION

Review of past climate change assessments, identification of potential threats, identification of data sources

CHARACTERISATION OF DIRECT THREATS

TO BRIDGES & ROADS

REVIEW OF DESIGNS &

DEVELOPMENT OF ASSET

INVENTORY

ASSESSMENT OF BUILT SYSTEM VULNERABILITY

(i) Safety (ii) Design life (iii) Performance

QUANTIFICATION OF DIRECT THREAT

Selection of IPCC scenarios, downscaling of 6 GCMs

BASELINE ASSESSMENT Review of historic trends in hydro‐metrological data

HYDROLOGICAL & HYDRO‐DYNAMIC MODELLING(i) Basin‐wide hydrological modelling – integration of climate change & upstream development (ii) Mekong Delta hydrological modelling – discharge in Hau River & regional flooding (iii) Hydro‐dynamic modelling – detailed flooding, flow velocity & water temp. profiling

Adaptation planning

Threat Vulnerability

Impact

IMPACT OF CLIMATE CHANGE ON CENTRAL MEKONG DELTA CONNECTIVTY PROJECT

COST OF CLIMATE CHANGE

Valuation of impact

ASSESSMENT OF ADAPTIVE CAPACITY

ASSESSMENT & VALUATION OF PRIORITY AREAS OF ADAPTATION

ASSESSMENT OF BUILT SYSTEM SENSITIVITY

(i) Process/operations (ii) Infrastructure (iii) Maintenance


4.2 Modelling overview The hydro‐meteorological threat of climate change is modelled using a statistical downscaling technique and a combination of hydrological and hydro‐dynamic modelling at three different scales.

1) Selection of appropriate IPCC SRES scenario(s) 2) Selection and processing of GCM data 3) Downscaling of GCM data to the Mekong Region 4) Hydrological and Hydrodynamic modelling

These critical steps and decision points in developing the modelling methodology and results are described in detail below.

4.2.1 Selecting IPCC SRES scenarios and observational data The threat modelling component started with a selection of IPCC scenarios and appropriate GCMs which have performed well in the Mekong Basin. Given the design life of the Central Mekong Delta Connectivity project, analysis of trends in threats will draw from a 120 year time period (1980 – 2100) of simulated data. The baseline period, 1980‐2005 will be compared to observed monitoring data from more than 100 weather stations to assess the suitability of the simulated data (figure 4 ‐ 4). The requirement of a long‐term baseline (25years) has limited the number of climate monitoring stations which can be utilised in the downscaling process, resulting in a concentration of data in Northeast Thailand and sparse coverage in Lao PDR.7

Figure 4‐4: Model set up: (left) Comparison of IPCC SRES scenarios8; (right) location of temperature (red) and precipitation (blue) monitoring stations in the Mekong River Basin

IPCC SRES A1B was selected for use in the study because it falls within the range predicted by the official climate change scenarios of the Vietnamese government (A2 and B2), but is closer to the upper limit (figure 4‐4). Recent studies have found that the original range of change expressed in the IPCC SRES scenarios, first developed in 2000, underestimates the likely impact and that changes in atmospheric CO2 concentrations experienced in the last 12 years is comparable or exceeds the upper limit of the SRES projections, limiting the applicability of the B1/B2 family of scenarios.

4.2.2 Selecting GCMs

The IPCC utilize 24 different GCMs in the AR4 – Assessment 4 report.9 GCMs include a full description of atmospheric and ocean physics which drive global circulation patterns, because of this complexity they operate at relatively coarse resolutions (200‐400km grid cells). In addition the description of physical processes

7 The paucity of long‐term data in Lao PDR, may affect the model’s ability to replicate the rainfall‐runoff response for specific sub‐catchments in Lao PDR, however, at the basin‐scale the model verification has proven calibration and a high level of correlation between observed and simulated baseline data (c.f. 4.3.3.4) 8 IPCC. 2007. Climate Change 2007: synthesis report. Contribution of working groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [ Core Writing Team, Pachauri, R.K. and Reisinger A. (eds).] IPCC, Geneva, Switzerland 9 ibid.


and parameters can vary depending on the GCM used resulting in varying accuracy for any given GCM over the earth’s surface. Some GCMs are therefore better at predicting the future climate of the Mekong River Basin than others.

Studies at the global level have identified that GCMs have varying levels of accuracy for different regions in the world.10 12 GCMs have been considered in past studies for the Mekong Basin (Table 5), of which six are known to have performed well in simulating the Mekong Climate.11 Outputs from the six selected GCMs will provide daily future climate data for average, maximum and minimum temperature and precipitation at the 100 monitoring stations. The six GCMs were selected by assessing the 12 GCMs which have been used in the basin for their ability to replicate historic precipitation records and are highlighted in table 6. The use of six GCMs allows the study team to explore the suitability of different GCMs to the Mekong region and the impact of model architecture on climate change results.

Table 5 GCMs applied to the Mekong Basin: GCMs to be used in the VA study have been shaded blue and their resolution is presented in the figure below

GCM name Institute of origin GCM name Institute of origin

ncar_ccsm3_0 NCAR USA csiro_mk3_0 CSIRO Australia

miub_echo_g MIUB Germany cnrm_cm3 CNRM France

micro3_2_medres CCSR Japan cccma_cgcm3_1_t63 CCCMA Canada

micro3_2_hires CCSRJapan cccma_cgcm3_1 CCCMA Canada

inv_echam4 MPI Germany bccr_bcm2_0 BCCR Norway

giss_aom GISS USA gfdl_cm2.1 GFDL USA

4.2.3 Downscaling global climate predictions Global climate circulation models (GCMs) operate at coarse resolution because of limits to computer processing power (200‐400km grid cells) (table 6). This resolution is inappropriate for detailed spatial assessment at the national, basin or provincial level. The next step in the methodology was to downscale predicted climate change to grid sizes suitable for spatial assessment. There are three accepted methods for downscaling GCM climate information.

1. Spatial redistribution/pattern downscaling: in regions where climate data is both spatially distributed and extensive, a relatively simple downscaling technique can use this fine‐resolution observation data to spatially differentiate the GCM results for a given grid cell into more detailed future climate outputs. This method cannot correct for statistical bias and so can only be used to assess relative changes or explore relative trends – it is not successful in predicting future absolute climate values.

10 Cai,X., Wang,D., Zhu,T. & Ringler,C. (2009). Assessing the regional variability of GCM simulations. Geophysical Research Letters, 36: L02706, doi:10.1029/2008GL036443 11Ibid.


In the Mekong Basin a variation of this approach has been applied by CSIRO which divided the Mekong Basin into 18 lumped sub‐catchments and assumed linearity in future climate trends. This assumption was then used to scale the results from 11 GCMs to each sub‐catchment using global interpolated data.12

2. Statistical/empirical downscaling: relies on the premise that local climate is conditioned by large‐scale (global) climate and by local physiographical features such as topography, distance from the ocean, and vegetation, such that at any specific location there is a link between large‐scale and local climatic conditions. Often determining the nature of these links in terms of physical processes can be difficult but by fitting long time‐series data with a statistical distribution, empirical links can be identified between the large‐scale patterns of climate elements (predictors) and local climate conditions (predicted). To do this, GCM output is compared to observed information for a reference period to calculate period factors, which are then used on the rest of the GCM time series in order to adjust biases. These factors can be annual means (resulting in a single correction factor) or monthly means (resulting in 12 correction factors). In addition, it is possible to correct data in such a way that not only the mean, but also the variance is corrected on the basis of the variance observed in the reference time series (Bouwer et al., 2004). Statistical downscaling can be done for points (i.e. individual stations), but can also be spatially explicit (i.e. maps). Because of the use of correction factors, statistical techniques have been shown to be less accurate in arid climates where future climate trends can be masked by the correction factor, though results have been better for tropical zones. Standard interpolation techniques are then used to provide area‐based climate information between stations and covering the entire basin.

3. Regional climate model (RCM)/dynamical downscaling: The most sophisticated way to downscale GCM data is to use a physically based regional climate model. Such models are forced at the boundaries by GCMs and calculate the flows of energy, gasses, etc. at a higher resolution for a specific area. These can also be ‘nested’ in a GCM itself. Creating such a RCM requires a lot of expertise and labour to set it up and calibrate it properly and is also computationally very expensive. To date in the Mekong Basin, there has been one attempt at dynamical downscaling using PRECIS. The PRECIS dynamic downscaling model was developed by the Met Office Hadley Centre for Climate Prediction and Research in UK and was used by consortium partner SEA START for IPCC SRES A2 and B2.

Several studies have compared results from statistical and regional modelling; showing that the two downscaling techniques are usually quite similar for present‐day climate, while differences in future climate projections are more frequent. These differences can, to a large degree, be explained by the unwise choice of predictors in the statistical downscaling ‐ although the superiority of either technology is not well established.

The biggest factor affecting accuracy of downscaling is the availability of existing climate information for the target region. This weather data is used for the calibration of the model and must be sufficiently long to ensure that inter‐annual variability in climate patterns is picked up. ICEM has long time‐series historical data for more than 100 weather stations in the Mekong Basin covering the period 1980‐2005. The number of weather stations was limited by the need for long time‐series, consequently, some countries in the Mekong Basin like Lao PDR, have poorer coverage of weather records with most monitoring stations extending back 15years or less. These data records have been collected from national government sources, regional bodies (e.g. the Mekong River Commission) and global sources including: (i) TRMM – Tropical Rainfall measuring mission, (ii) NCEP‐DOE – US National Oceanic and Atmospheric Administration National Centres for Environmental Predictions, and (iii) NCDC – US National Climatic Data Centre.

This study will draw on downscaled data from the six GCMs utilising both the statistical and RCM techniques, providing an opportunity to compare downscaling results from two different techniques. This represents a first for the Mekong region and an opportunity to consolidate and assess some of the variability found in previous modelling efforts.

12 Eastham, J., Mpelasoka,F., Mainuddin,M., Ticehurst,C., Dyce,P., Hodgson,G., Ali,R. & Kirby,M. (2008). Mekong river basin water

resources assessment: impacts of climate change. CSIRO.


4.2.4 Hydrological and hydrodynamic modelling The modelling strategy and approach is schematically represented in the figure below:

1) Basin‐wide hydrological/hydrodynamic model providing boundary values for the Delta model. Model includes erosion, sediment transport and sediment trapping by reservoirs. Modelled future changes in sediment input to the Delta will be used directly in the local model.

2) Regional Cambodian and Vietnamese Delta hydrodynamic model providing boundary values for the local models.

3) 3D floodplain and river model for detailed study on the bridges and roads in the project area.

Figure 4‐5: Schematic representation of the Delta Bridges modelling approach showing the three model levels: downscaled temperature and precipitation data will be inputted into a basin‐wide 1D hydrological model which will

compute discharge inputs at Kratie and establish the boundary conditions for a Mekong Delta model, which will in turn establish the boundary conditions for a high‐resolution hydrodynamic model at the project site


Basin‐wide modeling The basin‐wide model is ICEM EIA IWRM‐model that has been developed together with the Mekong River Commission over a decade. It is a gridded, “raster based”, watershed model, allowing for strong correspondence to GIS based data representation. The IWRM model integrates different types of models that are usually run separately. These include hydrology, water resources allocation and management and hydrodynamics.13 The steps for the basin‐wide modelling are:

1. Select period for the baseline that includes dry, average and wet years (e.g. 1995 ‐ 2005 or 1991 ‐ 2001)

2. Select comparable periods in the future scenarios, e.g. 2041 ‐ 2051 and 2091 ‐ 2101

3. Compute the scenarios (baseline + future climate change) with the basin‐wide model for baseline, 2041 ‐ 2051 and 2091 ‐ 2101 using data from 6 different downscaled Global Circulation Models

4. Develop daily time‐series for discharge at Kratie

In addition sediment will be modelled and results used for the local modelling and assessment. The major issues for sediment are changes in watershed erosion and sediment trapping by hydropower dams. The changes in sediment input can have major impact on sedimentation and erosion balance and in the Delta and this way on bridge and road structures. Sediment data is derived from the suspended sediment concentration data base of the Mekong River Commission.

Model calibration Assessment of model calibration indicates a strong statistical correlation at the basin scale between the observed and simulated data for the baseline period 1980‐2005, with and R2 value of 0.91 (figure 4‐6).

Figure 4‐6: Observed (red line) and computed (black line) daily flows at Kratie station

Delta modeling The Delta model utilises the MIKE 11 platform developed by DHI. The model’s hydraulic schematization starts from Kratie, it covers the floodplain in Cambodia, including the Tonle Sap system and the whole Mekong Delta of Vietnam (Figure 4‐7). Discharges from outside simulated areas in the Mekong River (upstream of Kratie) and

13 The elements of the IWRM‐model are: (i) gridded hydrology and kinematic routing (VMOD); (ii) 1D hydrodynamics (RNet); (iii) watershed

erosion, sediment transport and sediment trapping; (iv) water quality (VMOD) including nutrients and salinity; (v) flooding; (vi) groundwater; (vi) crops and irrigation; (vii) water diversions from rivers, lakes, reservoirs and groundwater; (viii) hydropower operations and reservoirs database


Saigon – Dongnai river basins (upstream of Tri An hydropower station) together with tidal data for the South China Sea and the Gulf of Thailand were selected as boundary conditions for the model.

The model set up includes more than 3,900 river and canals and more than 5,000 hydraulic works representing irrigation and drainage sluices as well as overland flood flow to the flood plain via low lying parts of roads. The model divides the delta into 120 zones and utilises more than 25,900 water level and 18,500 flow points to calculate small‐area water balances.

Figure 4‐7: The hydraulic schematization for Mekong delta

The input data for model consists of:

Cross sections of rivers and canal system, distance between cross‐sections

DEM – digital elevation map of the modelled area, DEM of flood plain area, Z~W curve

Present hydraulic constructions: location, dimensions, operation schedule

Data on embankment status and overland flood flows

Hydro‐meteorological and water quality data: (i) Tidal boundaries, (ii) Water flow boundaries, (iii) Irrigation boundaries, (iv) Rainfall and evaporation boundaries (NAM), (v) Salinity concentration boundaries

Other input data (direct or indirect input data to model): (i) Present land use map, (ii) Land use planning, (iii) Upstream development including hydropower, (iv) Land use change, (v) Water management scenarios, (vi) Climate change input data.


The steps for the Delta modelling are:

1. Define model boundary conditions using the daily discharge data at Kratie and rainfall and temperature data for Mekong monitoring stations within the delta

2. Compute the 3 scenarios using the 6 GCM datasets combined with predicted sea level rise of 0.5m (2041‐2051) and 1m (for 2091 ‐ 2101)

3. Analyse the spectrum of changes focusing on average changes and extremes (extreme dry and wet episodes)

4. Simulate highest flood period with maximum storm surge added

5. Simulate impact of highest estimated sea level rise for the period 2091 ‐ 2101 (2 ‐ 3 m).14

Project site modeling 3D modeling is required for simulation of the river flow, sediment transport and erosion. 3D modeling takes into account both horizontal and vertical flow and suspended sediment distribution. As flow dynamics and sediment concentration varies greatly both in horizontal and vertical directions 1D averaged approach is not sufficient for a detailed study. Also flooding is in principal a 2D process that is sometimes difficult to describe with 1D models.

The ICEM EIA 3D model is used in the study. The model has been used in more than 300 projects since 1982. During 2001 ‐ 2010 the model has been used in South East Asia for 8 areas. In Vietnam applications have included whole Delta and high resolution applications in Plain of Reeds, Tan Chau and Tan Tieu River mouth including coastal areas (reference Mekong River Commission and National Mekong Committees). In 2010 the model was used in the Omon power plant climate change vulnerability assessment study.

The ICEM EIA 3D model characteristics are:

1. spatial description in 3‐dimensions (requirement to obtain horizontal and vertical distributions; also proper description of stratification, turbulence and other parameters requires 3D model)

2. calculation of density (temperature, salinity) 3. calculation of sediment related processes, that is transport, sedimentation, resuspension, erosion,

bed load etc. 4. advanced turbulence calculation for vertical mixing and flow properties (in EIA model several options

including most universal k‐e model) 5. ability to combine high‐resolution near‐field calculation with far‐field simulation for large sea impact

through sea currents and wind, wave and tide induced circulation (in EIA model nesting with varying resolution is used, for instance 1 ‐ 200 m resolution)

6. accurate description of small‐scale features important for flow such as bottom channels and jetties 7. description of momentum advection 8. wave modelling 9. inclusion of tides in the calculation 10. accurate flooding description.

The objectives of the 3D hydrodynamic modeling of the climate change impacts are:

integrate floodplain, infrastructure and river channel impacts on flow and water levels

integrate complex interaction of river, floodplain and wind induced flows

provide quantitative information on how climate change impacts road failure factors (see previous chapter) as well as bridge design parameters

through integrated and holistic analysis, provide basis for assessing mitigation measures.

Due to the available resources and study focus the 3D modeling scope is limited to:

14 Estimates for the upper limit of sea level rise are derived from latest predictions from IPCC Working Group 1. See for example, Stocker

et al. (eds), 2010. IPCC Workshop on Sea Level Rise and Ice Sheet Instabilities workshop report for IPCC Working Group 1 – The Physical Science Basis, Kuala Lumpur, Malaysia 21‐24 June 2010


local area; surrounding area impacts are not considered including overland flow, changes in flood protection and infrastructure development and larger scale hydrodynamic changes (except what the 1D regional model provides)

road embankment without detailed description of bridges and culverts; but sensitivity analysis has been conducted in relation road openings

flow and flooding; actual erosion and sediment transport are not included

hydrodynamics; environmental, fisheries, agricultural and socio‐economic impacts are not included

the major 2000 flood event; focus on the main flood episode has enabled much more thorough computation and analysis than would have been possible with multiple events.

More detailed studies and analysis should be part of the road and bridge design work. This study purpose is to provide basic information on climate change impacts from where detailed planning can proceed.

Three different local models have been constructed for the study site in order to allow hydraulic analysis at a resolution suitable for river channel flow (Model A and B) and floodplain dynamics (Model C) (Figure 4‐8, Table 7). Two models focus on river channels at the bridge sites and the third one covers the broader project site to allow for an assessment of floodplain flow and flood issues (figure 4‐9, 4‐10).

Table 6: Project site models: summary of setup

Parameter Model A Model B Model C

Geographical coverage Component 1 Component 3 Component 1‐3

Resolution 10m X 10m 20m X 20m 100m X 100m

No. Grid cells 36,000 28,000 80,000

The steps for the local modelling are:

1. use the discharges and water levels obtained from the Delta model + sediment results from the basin‐wide model on the local model boundaries

2. calculate flow, water levels, waves, sedimentation and erosion in the river channels on the bridge sites

3. calculate flow, water levels, waves, sedimentation and erosion during flood situations on the floodplains surrounding the planned roads

4. provide detailed and quantified data on CC threats related to sediments, water quality, flooding and flow dynamics as an input into the impact assessment process.


Figure 4‐8: Geographical scope of project site models

Figure 4‐9: Component 1 river channel model grid.

Colours show water depths

Model C

Model A

Model B


Figure 4‐10: Component 3 river channel model grid.

Colours show water depths. Grid is rotated in relation to north‐south

direction

Figure 4‐11: Whole study

site model for the river channels,

floodplain and road

embankment. Colours show

elevations. Grid is rotated in relation to

north‐south direction

4.3 Threat and exposure analysis

The main objective of the threat analysis is to define and quantify the spatio‐temporal changes in hydro‐meteorological variables and the exposure of different components and features of the bridge and road design to these threats. This includes changes in incidence, magnitude, range and of key hydro‐metrological phenomena. Based on a review of project documentation and existing literature, the following threats have been identified as being of direct relevance to the Mekong Delta Central Connectivity Project:

1. Ambient temperature: mean daily temperature, daily range in temperature and daily/seasonal extreme temperatures

2. Rainfall: intensity, daily and seasonal volumes

3. Flooding: frequency, intensity and duration of flood typical and extreme events

4. Water Level: sea level rise, river level rise (due to changes in upstream hydrology), flow velocities

5. Sediment: changes in sediment load, transport and composition of suspended and bed load sediments

The threat analysis relies on observed and simulated time‐series data for the above parameters and employs statistical techniques to explore the relative change in parameters with climate change above the normal variability expected in historic data for daily, monthly, seasonal and annual time‐steps. The analysis considered change in terms of mean values, extreme values, periodic ranges and timing.

4.3.1 Temperature and rainfall Quantification of the threats posed by temperature and rainfall changes will rely on the statistically downscaled data from six GCMs. The 1D hydrological model will be used to interpolate the spatial distribution of these parameters between monitoring stations. In order to ensure the climate change modelling accommodates quasiperiodic and inter‐annual climate patterns (e.g. ENSO, consecutive years of drought or wet), the study will employ a 25 year baseline period of daily data as the basis for the climate change


downscaling. At the basin‐scale there are some 100 stations with suitable time‐series data for inclusion in the model, however at the project site level there are relatively few stations in the Mekong Delta with sufficiently long time series for inclusion in the model and none in direct proximity of the Central Mekong Delta Bridges project site.

Consequently, spatial interpolation will then be used to estimate the 25 year daily temperature and rainfall time series for each grid cell between monitoring stations, using the built‐in module of the IWRM 1D hydrological model at a resolution of 5km X 5km. This data will be used to define the long term relative trends in climate change for precipitation and temperature.

Relative trends of change in rainfall and temperature parameters within these grid cells will be super‐imposed on top of monitoring data provided by provincial authorities of Dong Thap, Can Tho and An Giang provinces to couple long term climate change trends with short‐term observation data.15

Statistical analysis will then be used on this time‐series data to identify changes in the frequency, magnitude and duration of rainfall events, hot days, daily minimums and maximums, and droughts.

4.3.2 Flooding, water levels, sediment and water quality Assessment of the threat of climate change utilised daily temperature and rainfall data from six Global Circulation Models (GCMs)

16 under IPCC SRES A1b and B2 to develop a continuous daily time‐series for 1980 –

2100. These GCM time series were downscaled using a statistical technique for 151 precipitation and 61 temperature stations in the Mekong Basin (Annex 3). Downscaled data for each GCM was then compared to the historical baseline at the monitoring station and the Vmod distributed hydrological model – custom built for the Mekong Basin ‐ was then used to spatially interpolate for temperature and rainfall throughout the catchment at a resolution of 5kmx5km. Model simulations were then undertaken for approximately 25years of centred on two future time periods (2050 and 2100) to determine the changes in Mekong River hydrology and floodplain dynamics.

Simulations also included scenarios for hydropower development in the Mekong Basin, including 126 hydropower projects in the Mekong Basin with a combined active storage of 107.8MCM, which represents the full exploitation of all hydropower currently being considered by the five Mekong countries of China, Lao PDR, Cambodia, Thailand and Vietnam within the Mekong Basin. Based on the IPCC SRES scenarios, GCMs, and hydropower development a total of 24 future scenarios were simulated for each time slice (Annex 4). Results presented in this technical note reflect the full range of these scenarios.

Findings for flooding and flood water levels draw from the following assessments:

(i) Climate change downscaling and interpolation of changes in daily rainfall and temperature for the Mekong Basin;

(ii) Basin‐wide modelling of catchment rainfall response and changes in surface hydrology with a focus on daily discharge at Kratie.17

(iii) Flood frequency analysis and changes in the expected return period of Mekong flood events in the context of climate change

(iv) Hydrodynamic assessment of changes in river channel water levels due to sea level rise, hydropower and climate change.

(v) Exceedance analysis for the P1% and P5% flood in the Tien river using hourly simulation data for existing and climate change conditions.

15 In this section long‐term refers to 25years of data considered suitable for accommodating decadal patterns of warming and cooling in

the Mekong meso‐climate regime. Short‐term projects refers to 10 years of observational data 16 GCMs utilized were developed by: NCAR (USA); CCSR (Japan); GISS (USA); CNRM (France); BCCR (Norway); GFDL (USA)

17 Kratie represents the most downstream station before the Mekong River enters the Cambodian floodplain and surface hydrology

becomes dominated by floodplain hydrodynamics rather than in‐channel flow.


4.4 Sensitivity analysis The purpose of the sensitivity analysis is twofold. First to understand how the structure, functioning and linkages between different infrastructure components of the Central Mekong Delta Connectivity project and their design, integrity and functioning is related to the surrounding hydro‐meteorological and geo‐physical environment. Second, to understand the existing pressures, drivers and health of the surrounding delta system. Existing pressures, such as river bank erosion or land subsidence, can affect the integrity, safety and useability of Components 1‐3 and could be greatly exacerbated when compounded with climate change pressures.

Central to the sensitivity analysis are two critical documents:

1) Components 1‐3 Feasibility study: Feasibility level design for Components 1‐3 has been completed by TEDI. The documentation details the general layout and design of the components which has been used to determine the dimensions and location of Components 1‐3 as used in the modelling.

2) Vietnamese Design standards for Bridges and roads: The Ministry of Construction (MOC) has developed a set of standards based on the AASHTO standards from the USA. These standards establish legal compliance thresholds for specific design components as well as the safety margins and acceptable ranges for specific parameters.

Based on a review of the documentation, the sensitivity analysis grouped the design components of the bridge and road. The sensitivity of these component groups is a function of the infrastructure they comprise, the processes they support, and the maintenance they require:

1) Bridge superstructure: Components of the bridge above the foundations including the deck, stay cables, cross beams and edge beams. For the purposes of this study, expansion joints, free‐sliding bearings, railings have been considered components of the superstructure.

2) Bridge substructure: Foundations and support components of the bridge, including pylons, foundations and metal reinforcements.

3) Roads, approach roads and foundations: Connections between Component 2 and components 1/3 and road surfaces

4) Embankments and road foundations: foundations, underlying geotechnical properties of the ground conditions, embankment and revetment design

5) flood protection control and drainage infrastructure: casing and protective works for road and embankment surfaces, culverts, flow‐through and drainage outlet structure and rip‐rapping

All specific components of the bridge and road infrastructure have been designed based on the surrounding environmental conditions at the project site. The sensitivity analysis will develop an inventory of components and then assess how sensitive individual components of infrastructure are change in surrounding environmental parameter and what implications changes will have on safety margins built into the design. Together with the threat analysis (c.f. Section 4.2), the sensitivity analysis will set the priority areas of focus for the impact assessment and detailed quantification.

4.5 CC Impact assessment The impact analysis overlayed each climate change threat predicted by the modelling on the vulnerability of specific built system components, using identified functional links. Functional links are proven empirical or theoretical relationships between an environmental parameter and the performance or integrity of a built system component. Based on these relationships, an assessment will then be made on the magnitude of the climate change impact over the design life, quantifying the scale of the risk posed by climate change to the design and the time frame over which it is expected to occur. Both the threat and sensitivity analysis will apply detailed quantification assessment techniques so that impacts contain a high level of confidence and sufficient detail for design response.

Table 5 presents a summary of the threat‐sensitivity couplings (functional links) which are likely to be important for the Central Mekong Delta Connectivity project and scopes the potential impact which needs to be assessed for each of these couplings. In some cases it is clear that individual components of the design will be exposed to more than one threat (e.g. the Bridge deck will be exposed to changes in temperature, rainfall


and wind speeds), similarly each climate change threat will affect more than one component. The study will utilise an impact assessment matrix adapted from RIAM – Rapid Impact Assessment Matrix18 to score the impact for each threat‐sensitivity coupling according to table 8. Scores for individual couplings range from ‐3 (major dis‐benefit) to +3 (major benefit). These are then tallied to give cumulative totals for: (i) each threat, and (ii) for each sensitive built system component, based on multiple threats for each component. This methodology allows for a weighted indicator of priority for each threat and for each plant component and will help in identifying priority areas for adaptation response.19 Once the impact of climate change is defined from a technical point of view, the VA study will then undertake economic analysis to quantify the cumulative impact from an economic point of view. Section 4.4.1 outlines the approach for the economic assessment.20

Table 7: Ranking impact and cumulative impact of climate change on built components of the Central Mekong Delta Connectivity project

MAGNITUGE OF THREAT MAGNITUDE OF CUMULATIVE THREAT +3 = major positive benefit

> +6 = major positive impact +2 = significant improvement in status quo

> + 4 = significant positive impact +1 = improvement in status quo

> + 2 = improvement in the status quo 0 = no change/status quo

‐ 1 to + 1 = no change/status quo ‐1 = negative change to status quo

< ‐ 2 = negative change to the status quo ‐2 = significant negative dis‐benefit or change

< ‐ 4 = significant negative dis‐benefit ‐3 = major dis‐benefit or change

< ‐ 6 =major negative dis‐benefit

4.6 Vulnerability assessment The vulnerability assessment combined aspects of conventional engineering feasibility assessments with life‐cycle analysis. It relied on two assessment phases –the combination of the quantified direct threat and built system’s sensitivity to climate variability to determine the impact over the design life, and the capacity which is available to avoid, mitigate or accommodate climate change.

The VA Study will rely on findings from stakeholder consultations to both contextualise the impact assessment findings and to assess the capacity for adaptation response. Adaptive capacity will be assessed in terms of:

1) Project scheduling: the projects design, procurement, construction, operations and maintenance schedules will be assessed to identify entry points for adaptation response during the project’s 100 year design life.

2) Technical: potential for adaptation using existing technologies and proven alternatives will be assessed based on the need and economic implications.

3) Financial: The VA study will work with ADB to secure additional funding for climate change adaptation.

4) Institutional: Adaptation options will priorities those consistent with the existing institutional capacity of the project management unit, ADB and the Government of Vietnam for building and monitoring the Central Mekong Delta Connectivity Project.

4.7 Adaptation priority setting Using the Cumulative Impact assessment matrix as the framework, the VA Study will develop a long‐list of adaptation options to respond to each impact. The scoping of adaptation options will also include a review of the performance and likelihood of success for potential the adaptation options, including an economic assessment of costing, resulting in a short‐list. The study will then set priorities for adaptation response based on the need, likelihood of success and cost of adaptation.

18 Pastakia, C.M.R 1995a. The Rapid Impact Assessment Matrix: A new tool for EIA, VKI, Agern Alle 11, DK‐2970 Hoersholm, Denmark

19 The adapted RIAM matrix has been applied to a Climate Change Vulnerability and adaptation assessment for the O Mon IV Combined

Cycle power station in the Mekong Delta. See ICEM. 2010. O Mon IV: Climate Change Threat and Vulnerability assessment. final report prepared for the ADB 20 The approach to the economic analysis presented in Section 4.4.1 extends further than the economic assessment of climate change

impact and also incorporates the economic assessment of adaptation response, which will feed into the study when setting adaptation response priorities (c.f. Section 4.6)

ADB | Mekong Delta Bridges CC Vulnerability Assessment| Inception Report | ICEM

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5 CLIMATE CHANGE THREATS FOR THE MEKONG DELTA

As defined in Section 4, the objective of the threat analysis is to develop robust causal linkages between changes in global, meso and local hydro‐meteorology to specific parameters and attributes of the bridge and road design. This is done through review of design parameters and calculations to identify critical hydroclimate variables which have shaped the current design process (figure 5‐1). The threat assessment then quantifies changes in these parameters using the suite of modelling tools identified in section 4.

Figure 5‐1: Linking hydroclimate parameters to transport infrastructure: Review of bridge design parameters and understanding of key geophysical processes of the Mekong Delta environment allowed the VA study team to draw clear causal links between components of the bridge and road infrastructure and the changing hydroclimate.

The following threats have been identified as being of direct relevance to the Mekong Delta Central Connectivity Project and are assessed in the ensuing sections:

1. Ambient temperature: mean daily temperature, daily range in temperature and daily/seasonal extreme temperatures

2. Rainfall: intensity, daily and seasonal volumes

3. Upstream discharge: seasonal and daily variability in average and extreme flows

4. Water Level: sea level rise, river level rise (due to changes in upstream hydrology), flow velocities

5. Flooding: frequency, intensity and duration of flood typical and extreme events

The variables above are not independent and closely inter‐linked with one another – primarily through the basin’s water and energy cycles. Flooding and water levels in particular represent a culmination of the other variables. The threat of climate change posed by each variable is assessed separately in this section and then the cumulative exposure of all relevant variables is presented for each asset in Section 6.

5.1 Air temperature Temperature variability in Lower Mekong Basin is driven by two key factors: (i) latitude, and (ii) elevation (MRC, 2011; ICEM, 2012). Latitudinal gradients function at global and meso scales affecting broad variation in continental climate, while elevation gradients function at smaller scales. Historic maximum daily temperatures in the LMB range on average between 17 – 35 Deg C (Figure 5‐2). Hottest temperatures are experienced in the low elevation regions of the Cambodian floodplain, Khorat Plateau and Mekong Delta with decreasing temperatures in mid‐elevation and high‐elevation regions – in particular the higher elevation areas of the Annamite mountain ranges and Northeastern Lao PDR along the eastern catchment divide.

Climate and hydrological

system

mean daily temperature and

temperature range

daily/seasonal extreme

temperatures

Wind speeds

Extreme gusts, cyclones

wind‐induced wave energy

rainfall intensity

rainfall volume

flood frequency and intensity

sea level rise

floodplain and in‐channel flow

velocities

sediment load and composition

Bridge & road structures

Expansion joints

free‐sliding bearings

bridge deck

stay cables

pylons and bridge foundations

approach bridge support piles

drainage system & road culverts

Road/river embankments &

river bank stability

Road foundation

road surface


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Figure 5‐2: Annual average maximum daily temperature (1980 ‐ 2004)

At the project site between the Cambodian and Vietnamese border, average maximum daily temperatures vary between 29.8 – 34.7 Deg Celscius with an average of 31.8 Deg C (Figure 5‐3). Temperatures peak at the end of the dry season (March – June), dropping to a minimuma at the end of the calendar year. Interannual variability of baseline temperatures is greatest during the dry season and smallest during the transistion to flood when temperatures peak.


Figure 5‐3: Statistical variability in baseline max daily temperatures in Dong Thap province (1980‐2004)

5.1.1 Changes in Mekong Basin temperature There is considerable variability between changes in temperature throughout the LMB. Climate threat modeling predicted that across the basin the annual average maximum temperature by 2050 will increase by between two to three Deg C. Greater increases are projected for the southern and eastern regions of the basin (Figure 5‐4). The largest change in temperature will occur in the Sesan, Srepok, Sekong catchments including a small area of the Srepok catchment with an increase of almost five Deg C. The expected increase in temperature gradually decreases toward the north along the Annamite ranges, and south east, toward the Mekong Delta (Figure 5‐4Error! Reference source not found.). These areas are predicted to have an increase in average annual temperature of around 2.75 Deg C. Within the Mekong Delta the Northwestern region near the Cambodian border is projected to have a higher increase in maximum daily temperatures, while the eastern and southern regions will have an increase of up to 2.5 Deg C.

Figure 5‐5 presents the projections for future daily maximum temperature near the project site and averaged between six GCM results and a 25year time slice. More than 80% of all simulated data indicates a clear increase in the maximumdaily temperatures.Year round maximum daily temperature is projected to increase by an average of 2.3 Deg C (1.5‐3.0 Deg C). The largest increases are projected for the months of May – August exacerbating hot weather at the start of the wet season. Greatest agreement between model results occurred for end of dry season and transistion season – with consistent trends from all GCMs except for the MP model during the start of the dry season.


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Figure 5‐4Change in mean annual temperature averaged over 6 GCMs for IPCC SRES A1b for 2050


Figure 5‐5: Statistical variability in projected future max daily temperatures in Dong Thap province with climate change (2045‐2069)

Figure 5‐6 presents the projections for variation in percentage exceedance curves for daily maximum temperatures, which quantifies the proportion of a typical year which is exceeded by a given temperature. The shaded blue area represents the variability in results across all climate models. Under typical baseline conditions max daily temperatures do not exceed 35Deg C. With climate change between 15‐45% of the year will see temperatures exceed 35Deg C, reflecting a 1 – 4.5 Deg C increase in the highest temperature expected to be experienced in a typical year. The highest projections were derived from the MI GCM and while MP predicted the lowest increase.

Figure 5‐6: Daily maximum temperature percentage exceedance curves


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5.2 Rainfall The Mekong Basin is one of the few regions in the world under the influence of two monsoon systems, the East‐Asian monsoon and the Indian monsoon. The result is a marked contrast between wet and dry season rainfall which divides the hydrologic year (MRC, 2011). The Southwest monsoon is the result of a strong seasonal temperature gradient between the Indian Ocean and the Asian landmass, which forces moisture‐laden air over the Mekong catchment and is the dominant driver for wet season rainfall (June – July), while the Mekong Basin is largely in the rain shadow of the Northeast monsoon – except for the Vietnamese areas of the basin, including the delta.

Figure 5‐7: Historical mean annual precipitation in the Lower Mekong Basin (1980‐2004)


Distribution of rainfall is highly variable throughout the basin. Highest rainfall occurs on the western slopes of the Annamites of Lao PDR and Vietnam, where mean annual rainfall can exceed 2,500mm/year, while the majority of Northeast Thailand and the Northeastern coastal region of the Delta experience less than 1,200mm/yr (Figure 5‐7). Rainfall at the project site displays two peaks: a leading peak in May corresponding to the start of the SW monsoon and the main peak in October corresponding to the start of the NW monsoon (figure 5‐10). Average peak rainfall is 273mm/month.

5.2.1 Changes in Mekong Basin rainfall Warmer atmospheric temperatures will affect the strength of the hydrologic cycle and so rainfall patterns. The capacity for the atmosphere to hold water is exponentially proportional to the air temperature. As temperatures continue to rise in the 21st century, the mass of water vapour held in the atmosphere will also increase, which will in turn increase the magnitude of rainfall events. In addition, one of the key drivers of storms is the release of latent energy from water vapour as it condenses to form clouds. In a wetter atmosphere the energy available to power storms will increase proportionate to the increase in atmospheric water vapour content, resulting in more intense storms (c.f. Section 5.5).

Climate change analysis by the VA study indicates that total annual precipitation is predicted to increase in the LMB by an average of 162mm by 2050, except for small segments in the Cardamom Ranges (Figure 5‐8), while maximum annual precipitation is expected to increased by 933mm. The vast majority of the increase in rainfall will occur during the wet season affecting the hydrology of the Mekong River and ultimately the water levels in the Mekong floodplain during the flood season.

Spatially the highest increases are predicted for areas with historically high rainfall, including: (i) in the central and northern Annamites (more than 500mm increase per annum), and (ii) to the east of the basin (increase of more than 300mm per annum). In the mid‐elevation areas of northern Thailand and Lao PDR near the borders with China and Myanmar, precipitation will experience a moderate increase (200‐300mm increase per annum). Lower increases in precipitation will occur in: the Khorat Plateau of Thailand; the Cambodia floodplain, and the delta of Vietnam (less than 200mm increase per annum).

Figure 5‐8: Basin‐wide average changes in mean and maximum precipitation: (left axis + blue line = max annual precipitation; right axis + grey line = mean annual precipitation)

Source: ICEM, 2012


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Figure 5‐9: Change in mean annual precipitation averaged over 6 GCMs for IPCC SRES A1b


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The impact of changes in precipitation manifest as two issues: (i) changes in rainfall‐runoff regime and hence changes in upstream discharge arriving at the delta (c.f. Section 5.3 and 5.4 below), and (ii) changes in direct precipitation at the project site. The Mekong Delta is projected to experience smaller increases in precipitation compared to the rest of the basin. At the project site, the largest increases in rainfall are expected for the wet season, including an average 8% increase in peak rainfall during October. Variability in peak October rainfall is large ranging between ‐8% to + 50% across the six GCMs (figure 5‐10).

Figure 5‐10: Changes in average monthly rainfall in Dong Thap province

Figure 5‐11: Changes in cumulative rainfall totals for the Project Site


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Cumulative rainfall is expected to increase from an average of 1,300mm/yr to 1,400mm/yr with all GCM simulations predicting an annual increase (Figure 5‐12). During the wet season, average historic wet season rainfall varied between 600 – 1,400mm. With climate change wet season rainfall will become 50% more variable, ranging between 600 – 1,800mm (figure 5‐12). In addition, there is not likely to be a significant increase in the number of rainy days during the wet season, so that individual rainfall events are becoming more intense. This is confirmed by ranking peak rainfall days and plotting the resultant series (Figure 5‐12 right).

Figure 5‐12: Changes to the variability of wet season rainfall at the project site: (LEFT) variation in total seasonal rainfall and number of rain days; (RIGHT) daily rainfall maxima rank for baseline and climate change conditions. The data shows that the wet season is getting wetter through more intense rainfall events

5.3 Mekong River flow – typical events The Mekong River is 4,880km long with a total fall of 4,583m, area of 795,000km² and average annual flow of 505km³ (MRC, 2005; Kummu et al, in publication). Originating in the Tibetan plateau the river spans a wide range of geologic, climate, drainage and ecological zones. The unifying hydrological feature of the system is the river’s flood pulse, which sees the individual rainfall‐runoff events throughout the catchment coalesce into a stable and

predictable hydrograph with distinct hydrological seasons (Error! Reference source not found.).

The annual hydrograph for the Mekong River has three important features which are critical for the functioning of the current hydrological regime:

(i) the response of the hydrograph to the monsoon exhibits a single amplitude peak complemented by a highly predictable phase (MRC, 2006);

(ii) the onset of the flood season occurs within a consistent and small time window with a standard deviation of approximately two weeks (MRC, 2006);

(iii) there is a long period of low flows which facilitate the seasonal transition from aquatic to terrestrial environments.

This predictability of the river hydrology has resulted in a good understanding of the dynamic natural equilibrium that is manifest throughout the 90years of sampling data (ICEM, 2010).


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Figure 5‐13: Average daily flow hydrographs for the Mekong River (1986 ‐ 2000)

Source: ICEM, 2010

Hydrology of the Mekong basin was simulated using the 1D ICEM EIA IWRM model which has been custom built for the Mekong Basin with a grid resolution of 5km X 5km. The model was calibrated for discharge at two monitoring stations on the Mekong mainstream: Chiang Saen and Kratie. Output data was generated for Kratie station and then compared to observational data data from the station with a correlation coefficient (R2) exceeding 0.9 (c.f. section 4). Kratie Station was selected because it represents the most downstream station on the Mekong River before the river enters the Cambodian floodplain. The model showed good capability to model the timing and duration of the Mekong flood pulse, and the magnitude of the flood event. Under one baseline year the model significantly overestimated the peak flood magnitude.

5.3.1 Changes in discharge Changes in catchment rainfall will increase seasonal discharge in the Mekong River. At the same time, storage hydropower in the Mekong basin will, under average conditions, store wet season flows for release during the dry season – moderating the CC‐induced increases in discharge. Using the VMod model, the VA study inputted daily climate data from six GCMs for two 25 year time periods centred on 2050 and 2100 respectively. This analysis produced some 500 future hydrological years for analysis.

Analysis of daily data for historic and future climate data at six mainstream stations indicates that the nature of change is consistent along the course of the Mekong River and can be summarized by four key changes:

(i) Increase in flood magnitude and volume: The dominant feature of the Mekong flood pulse is a single flood peak during August/September. Across all stations, Climate change will increase the flow during the flood season and the size of the flood peak (Figure 5‐14). In terms of the average annual total flow volume the increase in flow will be more pronounced in the lower reaches, reaching up to an increase of 51,000MCM at Kratie (Figure 5‐14). In terms of the percentage change in volume, the increase will be greatest for the upper reaches including an over 25% increase in flow at Chiang Saen, approximately 20% for the middle reaches of the Mekong (Vientiane – Pakse), and 15% in the lower riverine reaches (Pakse – Kratie).

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

1‐Jan 1‐Feb 1‐Mar 1‐Apr 1‐May 1‐Jun 1‐Jul 1‐Aug 1‐Sep 1‐Oct 1‐Nov 1‐Dec

PAKSE

VIENTIANE

CHIANG SAEN

KRATIE

TAN CHAU

CHAU DOC


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Figure 5‐14: Changes in annual and seasonal flow volumes for the Mekong River

(ii) Increase flood duration: Historically the flood season of the Mekong River is defined as the period of the

year in which the flow exceeds the mean annual flow and typically starts in June and ends in November (depending on the station). Across all stations, Climate change will increase the duration of the flood season.

(iii) Shortening of transition seasons and onset of flooding: Situated between the wet season and dry season are two important transition seasons: transition to flood (May/June) and transition to dry (Nov/Dec). These transition seasons are typically short in duration but are important in triggering a number of biological processes and in controlling the rate of transition of floodplain environments from terrestrial to aquatic and vice‐versa. Climate change will shorten the transition seasons at all stations and increase the rate of increase of discharge. This will accelerate the rate of transition from dry to flood and vice‐versa.

(iv) Increase in dry season water levels: Climate change will increase dry season flows in response to increases in dry season rainfall for most areas of the Mekong catchment. The middle reaches of the Mekong (Vientiane to Pakse) will experience the largest proportional increases in dry season water levels (20‐30%) due to changes in dry season rainfall in the highly productive left‐bank tributaries draining the Annamite mountain ranges. These tributaries account for some 30% of the total flow in the Mekong River (MRC, 2012). Stations further upstream (Chiang Saen and Luang Prabang) will experience smaller proportionate increases in dry season water levels of 10‐20% due to the dominance of the Upper Mekong Basin to dry season hydrology, where snow‐melt is the dominant driver not changes in rainfall. Stations in the lower reaches (Pakse – Kratie) will also experience proportionately smaller increases in dry season water levels (5‐20%), predominately due to significant widening and braiding of the channel increasing cross‐sectional flow areas.

Figure 5‐15 compares the 2000 flood event (blue) to some 150 hydrological years with climate change (grey) and illustrates that there is a considerable range in the response of the river hydrograph to changes in climate and hydropower exploitation. Under baseline conditions, the year 2000 flood is considered an extreme event, however comparison to the full set of climate change projections shows that the likelihood of more extreme discharges at Kratie are increasing. The greatest variability in prediction occurs during the flood peak in September, where future flood peaks ranged between 20,000cumecs and 140,000cumecs (figure 5‐15).


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This range in peak flows lies outside the historic range observed over 86years of data, indicating that peak flows are increasing in both variability and magnitude.

Table 8: Variability in Kratie peak discharge with climate change

Monitoring Station Time period Min peak daily flow (m3/s) Max peak flow (m3/s)

Kratie Baseline (1924 – 2009) 33,850 77,069

Climate Change (up to 2100) 27,221 141,166

Year 2000 ‐ 56,273

Figure 5‐15: Daily discharge at Kratie under baseline and future climate scenarios or change in Kratie water levels

Source: ICEM, 2012

Due to CC‐induced increases in rainfall, flow in the Mekong River will on average increase in both the dry and wet season. While the increase is observed in mean flow conditions, the peak flow events of the flood season are expected to be significantly impacted resulting in greater variability of the flood event and higher flood peaks. Figure 5‐16 presents a statistical summary of the min, average and max hydrograph at Kratie under: (i) baseline, (ii) 2050 and (iii) 2100 conditions. A summary table of statistical changes is presented in Annex 4, with the main conclusions being:

(i) The largest impact of climate change will be on the peak flood events. 60% of all simulated peak daily flows increased by a factor of 1.08 – 1.93 (average of 1.21), compared to simulated baseline flows;

(ii) The most extreme peak events (greater than the 80th percentile) saw peak simulated floods 1.25 – 1.5 times the baseline simulated floods. While the smallest flood events saw simulated peak floods increase 2.25‐2.5 times simulated baseline flows;

(iii) Peak flows are greater for the period centred on 2050 (i.e. 2045‐2069) than 2100, because of the nature of the SRES emissions scenario A1b, which sees a stabilisation in global population and shift to a global economy with more renewable technology and greater efficiency in the last quarter of the century;


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(iv) changes in mean annual flow experienced similar changes at 2050 and 2100, with increases in flow during the dry season, flood season and decrease during the transition to flood.

Figure 5‐16: Climate change influence on the Kratie hydrograph

Source: ICEM, 2012

5.4 Mekong River flow – extreme events Previous sections assessed how discharge and water levels in the Mekong River change in response to climate change. This was undertaken by simulating key hydro‐meteorological processes using a suite of modelling techniques. This section assesses how the likelihood of extreme events will change in response to climate change.

Frequency analysis uses probabilities to express the likelihood of an event based on fitting statistical distributions to time series data. Return periods express the likelihood that a certain value will be exceeded – for example the P1% or 1 in 100year flood, indicates that there is annually a 1% chance of a flood exceeding or equal to that flood. The selection of the appropriate return period is then determined by the significance of exceedence. For example, the P5% is selected for navigation clearance because the implications of exceeding this limit, though inconvenient for navigation and economic activity does not represent a risk to the structural integrity of the infrastructure, while the P1% is selected for embankment design, because overtopping during flood events can wash out the structure causing damage and safety risks. If extreme events are predicted to become more frequent (i.e. the return period diminishes) then the risk associated with the design will increase.

Central to statistical methods used in frequency analysis is the assumption that the time series can be approximated as stationary – that is, key statistical parameters (mean, variance) are approximately constant over very long periods (Chow et al, 1988). In the context of climate change, it is clear that time series for hydro‐meteorological phenomena are non‐stationary – that is the values for the mean, variance and mode are dynamic


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over time. This presents a challenge for the use of extreme event analysis. Climate change assessments have one of two options:

(i) Assume stationarity of the long term time series and combine historic and future time series into one record and conduct frequency analysis over the entire data set.

(ii) Acknowledge non‐stationarity by disaggregating future time series data from past time series data and undertake frequency analysis on each data set separately. This means that the future hydro‐meteorological regime is seen to have undergone a fundamental shift from the historic regime to a new regime. Frequency analysis is then applied on the future CC time series independent on the past time series.

In choosing how to approach frequency analysis with climate change, neither option is technically wrong, but each comes with a set of assumptions and implications for the structures risk profile. From a risk management point of view, Option 2 is more cautious as the changes in magnitude and frequency of extreme events will be greater when decoupled from historic data, while option 1 is more conservative. The VA study team undertook the frequency analysis assuming stationarity (Option 1) which produces a lower level of risk. For completeness, the VA study team also undertook a rapid sensitivity analysis to the findings by comparing with the range of risk estimated with this method to the range of risk estimated using Option 2.

Analysis was undertaken to determine the return periods for Kratie station under baseline conditions. A historic annual maxima series for daily peak flows was developed for 86years of gauging station data available for the MRC (1924 – 2009). The data was then fitted to an extreme value distribution (EV1) and return periods calculated using the methodology outlined by Chow et al (1988) for peak flows at Kratie. The calculated extreme event frequency distribution was then compared to that calculated by the Mekong River Commission for the same Station (Kratie) and parameter (peak discharge) and using a baseline period of 1924 to 2006 (Figure 5‐17; Table 9; MRC, 2011).

Table 9: Calculation of return periods for extreme flows at Kratie Station

Return Period (T) Annual Exceedance Probability (%)

Mekong River Commission (1924‐2006)

This Study (1924‐2009)

% variability from MRC estimate

2 year 50% 52,000 52,745 +1.4%

5 year 20% 58,000 58,309 +0.5%

10 year 10% 63,000 61,992 ‐1.6%

20 year 5% 68,000 65,526 ‐3.6%

100 year 1% 78,500 73,527 ‐6.3%

Estimates produced by the VA Study produced marginally higher estimates for high frequency events (return periods of less than 5years, and lower estimates for infrequent events with return periods greater than 5 years, compared to the MRC estimates.

The future daily flow was calculated for Kratie over the period 2045 – 2069 using six GCMs, providing a total of 168 hydrological years of daily data. For each GCM, the 25year future data set was then coupled with the 86year historic baseline and then fitted with the EV1 distribution to calculate magnitudes and return periods.

Results are presented in Figure 5‐18 and tabulated in Annex xxx. Based on this analysis, peak flow flows are likely to increase in magnitude. For example, the P1% flood at Kratie will increase in magnitude from 77,597m3/s to between 82,862 and 102,586m3/s (table 8).


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Figure 5‐17: Comparison of Baseline return periods for Kratie peak discharge: The return period for extreme events at Kratie was calculated (BLUE LINE) and then compared with calculations published by the MRC (BEIGE LINE). Calculations showed good agreement given that the

extreme value distributions used were different and that the length of the time series data varied by 3%.

With climate change flood events of a given size which historically occurred with a certain return period are likely to be more frequent. For example, a peak flow of 77,597m3/s (historic P1%) is likely to occur with a return period of once every 15 – 40years, where as an historic 1 in 20year event will occur with a return period of 1 in 5 to 1 in 10 (Figure 15). If the historic 1 in 100year event become a 1 in 40year event (as predicted by all of the GCMs), the risk of experiencing this event at least once over the design life rises from 63.4% to 92%.

Table 10: Variation in the P15 and P5% peak flows for Kratie

Return period Historic flow at Kratie (m3/s)

Range of predicted flow at Kratie with CC (m3/s)

Predicted flow at Kratie with CC (m3/s)

P5% 66,928 70,262 – 83,581 74,889

P1% 77,597 82,862 – 102,586 89,290


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Figure 5‐18: Changes in extreme events at Kratie Station (EV1 distribution)

5.4.1 Uncertainty and assumptions in sensitivity analysis There is a significant amount of uncertainty in extreme event frequency analysis, especially in the case of climate change where current limitations in our understanding of the fundamental hydro‐meteorological processes means we cannot have confidence in selecting one GCM as indicative of the future. The large variability between the changes in return periods predicted above by the six GCMs reinforces this uncertainty. What is clear from the analysis is that the magnitude of extreme events will increase and that design water levels should be adjusted accordingly.


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Figure 5‐19: Comparison of stationary and non‐stationary calculation of CC‐induced return periods: blue shaded area represents the range in frequency analysis experienced by the 6 GCMs over the full data set 1924‐2100; the grey shaded area represents the range in frequency analysis experienced by the 6 CGMs for future CC data only.

Source: ICEM, 2012

Figure 5‐19 illustrates the range in predicted future return periods comparing the two methods with and without stationarity. The numbers used in the VA study reflect the stationarity assumption and are encapsulated by the blue shaded area in Figure 5‐19. The range in return periods assuming non‐stationarity are shown by the grey shaded area. The graph shows that specific design return period for any given event can vary markedly, for example the 1 in100year event with climate change could range between a conservative estimate of 80,000 and an upper estimate of 140,000m3/s. While we have confidence that the actual return period lies somewhere between these two extremes, design engineers need to assess the acceptable risk tolerance level for the structure and make a decision of much f this incremental future risk can be accommodated in the design.

5.5 Sea Level Rise Sea level rise (SLR) due to climate change will exacerbate flooding issues at the project site by reducing the delta’s drainage efficiency, prolonging both the depth and duration of flooding.

5.5.1 Long term historic trends in sea level The rate of global sea level rise (SLR) has tripled in the past 100 years, with long term rates for the twentieth century ranging between 1.9 – 3.4mm/yr (Rahmstorf, 2007; Cazenave, 2010; IPCC, 2007; Church, 2008). Analysis of historic rates of sea level rise indicate that they are non‐linear as they are an expression of a complex interaction of processes, including glacial, sheet ice and polar melt as well as thermal expansion of the oceans due to increasing temperatures. Over the 21st Century, the increase in sea levels has accelerated in recent decades


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reaching 3.1mm/yr (1993‐2006), more than double the average rate of rise for the 20th century (Figure 5‐20), while the rate of rise in the 20th century was an order of magnitude larger than the two millennia preceding (Church, 2008).

Figure 5‐20: Global mean seal level from 1870 to 200 (one standard deviation estimates): the blue trend line exhibits the non‐linearity of sea level rise over the past 140 years. (Source: Church, 2008)

Source: (Church et al, 2008)

Actual rates of sea level rise along the coastlines of the earth’s continents are highly dependent on meso and regional scale dynamics of the ocean system with large variability within and between oceans (Figure 5‐21). In the western coastlines of the Pacific Ocean, Vietnam is considered to be highly exposed. Analysis of the hourly fluctuation of sea levels at Vung Tau gauging station in Southern Vietnam indicates that sea levels have risen on average 3.0mm/yr between 1979 and 2006 (Figure5‐22), compared to averaged annual SLR of 1.8 and 2.0mm/yr in Shanghai and Hong Kong respectively (Yu, 2002; Ding, 2001).21

Figure 5‐21: Spatial distribution of sea level rise (1993 – 2006).

Source: (Church et al, 2008)

21 Analysis of SLR at Shanghai and Hong Kong used tidal data for the period: 1945 – 2001. The longer time period compared to the Vung Tau

measurements will have an impact on the calculated annual SLR increment because sea level rise is a non‐linear phenomena which has been accelerating in recent decades (c.f. Rahmstorf, 2007).

Global M

ean Sea

Level (mm)


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Figure 5‐22: Historic sea level rise at Vung Tau station (1978‐2007)

Source: Southern Institute of Water Resources Research (SIWRR), 2010

5.5.2 Projections of future sea level rise Figure 5‐23 presents the range in sea level rise expected for the 21st century in comparison to the averaged 1980‐1999 reference level. The estimates were produced by IMHEN – Institute of Meteorology Hydrology and Environment using three IPCC SRES B1, B2 and A1F1, representing a range of future emissions scenarios from low (B1 and B2) to high (A1F1) and represent the official scenarios for SLR from the Government of Vietnam. Under these official projections, sea levels in 2050 will be 0.28 – 0.33m higher than 1980‐1999 levels, while by the end of the century levels will be 0.65 – 1.0m above baseline levels (Figure 5‐23). The design life of the Cao Lanh and Vam Cong bridges is 100years, and the design should take into account a realistic projection of SLR during this time horizon. The VA study assesses SLR using the highest official estimate at the 2100 time slice.

Figure 5‐23: Revised Vietnam National Scenarios for Climate Change induced Sea Level Rise

Source: Institute of Meteorology Hydrology and Environment (IMHEN), 2011


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As the Central Mekong Delta Connectivity project is located more than 120km from the coast‐line specific changes in channel water levels are dependent on hydraulics of the river channel including bed slope, channel width, height, upstream flow inputs, tidal influence and distance from the coastline. Using the MIKE 11 model, the VA study assessed the sensitivity of in‐channel water levels for five monitoring stations on the Tien River and three on the Hau River over a distance of approximately 100km (Tan Chau/Chau Doc to Can Tho/My Thuan) (Figure 5‐24).22 The assessment inputted 0.5m, 0.75m and 1.0m SLR forcings onto hourly flow simulations for the year 2000 flood year and then assessed how peak water levels at the monitoring stations responded to this forcing (figure 5‐24). Stations closest to the coast responded with the greatest increase in water levels, with increases of water levels at My Thuan and Can Tho ranging between 78 ‐ 93% of the SLR increment, while upstream stations like Tan Chau, Chau Doc, experienced increases in water levels equivalent to 10 ‐ 15% of the SLR increment.

At the project sites (Cao Lanh and Long Xuyen), water level increases corresponded to approximately 55% of the SLR increment, for example, an increase in SLR of 0.5m resulted in an increase of water level at Cao Lanh of 0.24m. Figure 5‐24 indicates that the there is a strong linear correlation between river water levels and SLR. For Cao Lanh this change in water level can be approximated using the equation (R2 = 0.995):

Based on SLR alone, Cao Lanh will experience the following increases in maximum water levels during peak flood events:

Table 11: Relationship between SLR and increase in river water levels at Cao Lanh Station

Monitoring Station SLR (m) Estimated year Rise in Tien River water level (m)

Cao Lanh 0.3 2050 0.15

1.0 2100 0.55

The linear relationship presented above should be taken as an indicative approximation of the relative change in Cao Lanh water levels compared to the change in SLR. Actual changes in water level induced by SLR are dependent on prevailing hydraulic conditions and should be assessed using detailed hydraulic conditions at an hourly time step (see next section). The table above reflects changes in water levels due to SLR a particular peak flood event (year 2000). During the dry season, when upstream flows are an order of magnitude lower, the influence of SLR will be different. However, from the perspective of the design of the bridges and embankments, this will not be an issue because design levels are set against flood conditions.

In addition, the SLR impacts may be aggravated by increased storm, cyclone and typhoon intensity. To date conclusive modelling of future extreme events has not been undertaken, however, understanding of atmospheric processes indicates that storms and cyclones will not become more frequent but will become more intense and for Vietnam track further southwards (c.f. Section 5.6). Historic observations at Vung Tau station indicate that spring tides can increase sea levels by as much as 0.03m between consecutive years (SIWRR, 2010).

22 Locations for the monitoring stations are presented in Annex 1 for reference


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Figure 5‐24: Correlation between rate of change in river channel water levels and increasing sea level rise for peak flood events of Tien and Hau rivers

Source: Southern Institute for Water Resources Research (SIWRR), 2011

5.5.3 Limitations, uncertainty and improvements to SLR projections Projections of sea level rise made by the Government of Vietnam have been based on global projections for sea level rise by the IPCC. The IPCC Third Assessment Report (TAR) projected that by the end of this century global sea levels would rise by 0.2 – 0.7m increasing to 0.88m if preliminary estimations for changes in land‐ice where included (Church et al, 2008). Comparison of SLR projections in TAR and AR4 by Church (2008) indicates that there is agreement on the median and upper limits of sea level rise between the two reports and AR4 estimates were within 10% of TAR estimates (figure5‐25; Copenhagen Diagnosis, 2009). AR4 was considered to have included a comprehensive assessment of the key processes influencing sea level, with the greatest uncertainty associated with the response of the large polar ice‐sheets of Greenland and Antarctica23 (IPCC, 2010).

23 AR4 had assumed that the dynamics of the Antarctic ice‐sheet was likely to increase in mass, acting as a stablising force on the rate of sea

level rise, however recent analysis of the ice‐sheet indicates that it is losing mass not gaining (c.f. Copenhagen Diagnosis, 2009).

~85km

~135km

~195km


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Figure 5‐25: Comparison of IPCC projections for SLR under TAR and AR4: Dark green shading indicates the average results from all models and all SRES scenarios under TAR; light green shading indicates the envelope for all results from models and SRES scenarios under TAR; dark green lines indicate uncertainty associated with land‐ice dynamics; Pink bar indicates the range of model projections under AR4 and ranges from 0.18‐0.59m; the red bar includes estimation of additional contributions from Greenland and Antarctic ice‐sheets.

Source: Church, 2008

Projections under TAR and AR4 between 1990 and the present have been compared with observed sea level data using both tidal gauges and satellite altimeters (Figure 5‐26). Analysis indicates that without the inclusion of ice‐sheet estimates, TAR was underestimating rates of global sea level rise and that actual rates of SLR are 80% faster than predicted in that report (Figure 5‐26; Copenhagen Diagnosis, 2009). Comparison with all IPCC projections from both reports and satellite data up to 2010 confirms that actual rates of SLR are equal to or exceeding the upper boundary of the projection envelope from all IPCC results (5‐26).

Figure 5‐26: Comparison of IPCC SLR projections for 1990‐present with observed data: (LEFT)1990‐2006 vs TAR; (RIGHT) 1990‐2009 all projections

Source: (LEFT) Church, 2008; (RIGHT) Copenhagen Diagnosis, 2009


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Recent projections of SLR have suggested that updated projections for SLR are double the projections made under AR4 (i.e. 0.36 – 1.18m) (Richardson et al, 2009), while Rahmstorf (2007) projected SLR to reach 1.4m by the end of this century (Figure 5‐27). Given the rates of SLR in recent observational data and the higher projections from post‐AR4 assessments, the study assumption to use the upper bound of the Official Vietnamese Government projections for the 21st Century (i.e. 1.0m SLR) is considered appropriate and conservative. Lower projections are highly likely to underestimate the problem, while there is still considerable debate and uncertainty surrounding the higher estimates (c.f. Holgate et al, 2007).

Figure 5‐27: Post‐AR4 Projections of SLR

Source: Church, 2008

5.6 Storms, Storms surge and extreme events Warmer atmospheric temperatures will also affect the dynamics of extreme events such as tropical cyclones and storms. In East Asia cyclones form over the Pacific Ocean and typically track, either: (a) eastward reaching the Asian mainland in Northern/Central Vietnam and Southern China; or (b) northeast reaching the Asian mainland in Central/Northern China, Korea and Vietnam (c.f. Annex XXX). Analysis of cyclone data from 1956 to 2009 (Annex XXX) indicate a number of key characteristics for cyclones making landfall in Vietnam:

(i) Though cyclones have been known to hit Vietnam from May onwards, the majority of cyclone activity is concentrated in the months July – November.

(ii) During the season, cyclones first affect northern Vietnam and move southward (iii) Cyclones do not frequently make land fall in the Mekong Delta, when they do it is most likely to occur

during November of December. (iv) The biggest cyclones to have reached the delta include Cyclone Linda (1997), and Cyclone Durian (2006).

As these events are infrequent, the communities and sectors of the Mekong Delta are ill‐prepared to deal with cyclone impacts. Cyclone Linda resulted in the death of thousands of people as well as the loss of thousands of homes, boats and severe erosion of exposed coastlines in Bac Lieu and Ca Mau Provinces.

5.6.1 Historical trends in cyclone activity Tropical cyclones are low pressure systems which form over tropical and subtropical oceans. They are among the most complex of climatalogical systems resulting in extreme conditions (e.g. intense winds) which has made it difficult to take direct measurements – scientists typically rely on satellite imagery analysis (Veldern et al, 2006);


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and make predictions of their origin, track and intensity (WMO, 2006). However, the climatalogical conditions required for their formation are well understood to primarily include: warm sea surface temperatures (SST); low vertical wind shear; and high relative vorticity – a measure of spin and rotation of fluid in the atmosphere (WMO, 2006). In addition, the ENSO phenomenon is a strong interannual driver altering the region of genesis (“cyclogenesis”) and subsequent track of cyclones in the Pacific (Chan, 2000; Ho, 2006).

Over the past three decades, there has been a substantial increase in the strength of cyclones, and a near 100% increase in the proportion of cyclones which are classified severe, compared to those classified as weak (Emmanuel, 2005; Webster et al, 2005). In the future, climate change will continue to impact on the intensity, frequency and genesis of cyclones.

5.6.2 Cyclone intensity One measure of cyclone intensity is the maximum potential intensity (MPI), which identifies the maximum possible cyclone intensity for a given atmospheric and oceanic thermodynamic environment (Emmanuel 1987; 1999). Idealised models and theoretical predictions have concluded that climate change will bring a significant increase in the MPI for cyclonic events with estimates that MPI would increase by 3‐5% for each degree increase in mean annual temperature (Emmanuel, 1987; Tonkin, 1997; Knutsen et al, 2004).

Results from global circulation models (GCMs) have not yet been successful in reproducing accurately previous cyclones (in particular through the underestimation of cyclone intensity), consequently there remains a high level of uncertainty in their projections for the future (WMO, 2006). However, the GCMs with higher resolution generally confirm the trends developed through theoretical and idealised models that the intensity of cyclones will increase (WMO, 2006).

5.6.3 Cyclone frequency To date it is not possible to predict the change in cyclone frequency expected with climate change. The trend observed over the past three decades of strong cyclones becoming more frequent and weaker cyclones becoming less frequent is likely to continue (WMO, 2006).

5.6.4 Cyclogenesis and track Broadly speaking the regions of the Pacific Ocean where cyclones form is not expected to change significantly with climate change (WMO, 2006). Consequently the land areas affected by cyclones are also not expected to change (WMO, 2006). For Vietnam in particular, some studies have indicated that cyclones may track further south, increasing the frequency with which cyclones make landfall in the Mekong Delta.

5.6.5 Threats from cyclones to the Mekong Delta Cyclones have the potential to affect transport infrastructure through a combination of intense wind speeds, intense precipitation and storm surge.

The expected increasing in MPI of cyclone events will likely increase the intensity of cyclone‐induced rainfall as well as winds. Storm surge is the offshore elevation of sea surface levels arising as tropical cyclones approach land. Wind intensity is the main factor affecting storm surge though coastal bathymetry can also be important. Given the speeds of cyclonic winds, storm surges can manifest in short periods of time, making storm surge and the associated flooding one of the primary causes of deaths during cyclone events (WMO, 2006).

As the East Sea undergoes a large variability in tidal fluctuations, the scale of impact from storm surge in the Mekong Delta is also highly dependent on the timing of landfall. The combination of high tide and storm surge could greatly exacerbate the impacts felt coastal and inland areas of the delta.

In the context of climate change, the magnitude of storm surge will also increase due to increasing cyclonic MPI. In addition SLR will in the future increase the impact of storm surge as it raises the mean sea surface level.


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5.7 Non‐climate change threats Aside from climate change, human activities can have a profound influence on the hydrology of river systems by altering:

(i) Water availability: changes in land use and land cover can affect the rainfall‐runoff response of catchments as deforestation can accelerate the response time of the catchment to rainfall events and expansion of agriculture within the floodplain can reduce dispersion of flood flows by confining the natural floodplain. Both of these will increase the depth and duration of flood events and both are prevalent within the Mekong Basin.

To date this has not been a significant issue for the Mekong River – at the basin scale – due to the size of the catchment (ICEM, 2010). There is also insufficient understanding at present to accurately project forward future implications, though the 2011 flood season was an indication that the problem is worsening.24

(ii) Water Consumption: Upstream water consumption for irrigation and domestic supply can affect the seasonal hydrology of the river by reducing flow volumes. Under the most aggressive irrigation expansion strategy (total basin irrigated area of 6million ha), the abstraction volumes will be minor and, for example, an order of magnitude below forest evapotranspiration (MRC, 2010). Due to the size of the Mekong flow regime, and the focus of design criteria on the flood season, the expected changes in water consumption are not likely to affect design water levels of the Tien and Hau rivers.

(iii) Water Storage: Natural water storage is an important feature of the Mekong hydrological regime which slows the movement of water through the basin effectively storing water from the wet season and making it available during the dry season. For the Mekong Basin the majority of the natural storage results from infiltration of rainfall into the soil horizon and groundwater aquifers.

Another important natural storage feature is the Tonle Sap Lake. Each flood season the Tonle Sap lake increases in size from 2,500km2 to approximately 15,000km2 as an average of 73km3 of floodwaters overflow from the Mekong into the Tonle Sap (Kummu et al, 2008). These floodwaters are retained during the flood season, then as the water levels in the Mekong drop with the onset of the dry season, the Tonle Sap lake drains back into the Mekong system providing an important contribution to dry season water availability.

In addition to natural storage, human construction of reservoirs can also store Mekong surface water between seasons and years. The rapid expansion of hydropower in the Mekong Basin will increase the storage capacity of the basin. Under average conditions hydropower reservoirs will store wet season flows to increase the electricity generating capacity during the dry season (Figure 5‐28). Plans for hydropower exploitation in the Mekong Basin are ambitious, with a total of 84 large‐scale hydropower projects under consideration in the next 20 years and a total potential for more than 120 projects (Table 11). If all hydropower potential was installed, the reservoirs would have the capacity to store in the order of 20% of the mean annual flow (MAF).

Table 12: Hydropower potential of the Mekong Basin

Country Number of Reservoirs Active Storage (mcm)

China 6 21.39

Lao PDR 89 58.48

Cambodia 13 21.21

Thailand 7 3.57

Vietnam 11 3.15

Total 126 107.8 Source: MRC, 2009

24 The 2011 flood saw water levels in the Tien and Hau Rivers comparable to the 2000 flood event, though the volume of the flood event was

significantly smaller, suggesting that in‐channel water levels were kept high because of reduced access to the Cambodian floodplain.


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Figure 5‐28: Typical response of hydrograph to hydropower regulation under average flow conditions

Source: MRC, 2009

5.7.1 Impact of hydropower on Mekong Delta flooding Of the three human activities discussed above only hydropower has the capacity to affect the peak flood flow in the Mekong River and subsequently the design water levels for the Central Mekong Delta Connectivity project.

Hydropower development is accelerating in the upstream Mekong countries. China and Laos are developing large water storage capacity in form of regulated reservoirs. The basin‐wide VMod model includes developed hydropower potential in the future scenarios. Altogether 126 reservoirs are included in the simulation, using the MRC database to characterise the salient features of each project (location, dam height, design discharge, reservoir volume etc.).

The impact of hydropower development was analysed using the VMod hydrological model. The simulation period was 1990 ‐ 2000 and actual weather measurements from this period were used as the model inputs. The simulation was run with and without hydropower development.

Simulations for average flood conditions did conform to the theoretical expectation outlined in figure 5‐29, with hydropower regulation reducing the flood peak, shortening the duration of the transition seasons and increase dry season flows. However, there is increasing observational and simulated evidence that current reservoir management practices limit the capacity of reservoirs to induce similar changes in extreme flood hydrographs (ICEM, under publication). This is primarily because of the rapid onset of extreme conditions in the Mekong and the desire of hydro‐electric stations to maximise electricity production which keeps reservoir levels high, such that there is limited or no storage capacity to receive extreme flood waters.

Results for the large flood year 2000 are shown in Figure 5‐29. The reservoirs have largest relative impact during dry season when stored water is released. During the onset of the flood season reservoirs are filled. Under average hydrological years, wet season flows are stored in the reservoir and then released during the dry season. The effect of this is to lower the wet season flow and increase dry season flows (figure 5‐29).

The precise nature of the impact on seasonal flows depends greatly on the management of reservoirs and their coordination in cascade. For the Mekong region it is typical that reservoir operators will try to maintain reservoir water levels as high as possible to maximise hydro‐electric potential. This means that during large flood years the reservoirs are typically full during the flood peak and spillway gates are opened to pass as much of the receiving flow as possible, such that the Mekong downstream flow is similar to the natural one or in some cases larger. Figure 5‐29 illustrates this for the year 2000 flood, where changes in flow were significant during the dry and transition to flood season, but the peak flows were not appreciably affected.


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Table 13 shows simulated discharges without and with Mekong hydropower development for dry, early flood and peak flood periods for years 1990 ‐ 2000. The highest relative hydropower impact is during the dry season when on the average Mekong downstream discharge increases 90%. During early and peak flood discharge decreases 18% and 14% respectively. The discharge amount changes approximately 2500 m3/s in both dry and early flood seasons. During peak flood the change is double, that is approximately 5000 m3/s. Table 13indicates that the hydropower impact to the components 1‐3 of the Central Mekong Delta Connectivity Project during the critical peak flood period is minor compared to the climate change and sea level rise.

Figure 5‐29: Simulated Mekong flow at the downstream Kratie station for the large flood year 2000.

Table 13: Simulated average discharges without (BL) and with (BL+hydro) Mekong hydropower development for dry, early flood and peak flood periods for years 1990 ‐ 2000. 126 hydropower reservoirs are included in the hydropower development

Dry Period Early Flood Peak Flood

Jan ‐ June June ‐ August August ‐ October

year BL BL+hydro BL BL+hydro BL BL+hydro

1990 2218 4931 19433 15613 32248 29527

1991 2365 4998 8588 7426 33623 27975

1992 2411 4803 6077 6935 32589 24934

1993 2572 4910 10935 9145 23677 19884

1994 2965 4866 20495 15145 39309 35432

1995 2437 4794 9088 8221 39316 32623

1996 2595 4843 10031 8690 41405 33376

1997 2850 5147 13341 11634 40035 35297

1998 2100 4694 8176 7493 23896 19711

1999 2894 4453 19332 14741 37397 32432

2000 3036 5294 26779 20287 40606 39295

average 2586 4885 13843 11394 34918 30044

change +89% ‐18% ‐14%


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Figure 5‐30: Existing and planned hydropower in the Lower Mekong Basin by sub‐catchment


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5.8 Flooding Figure 5‐31 outlines the causal relationships through which climate change will change the water levels of the Tien and Hau Rivers and the inter‐channel floodplain and hence impact the design of the bridge and embankment structures. Each of the key threats identified above are brought together and assessed for their cumulative impact on water levels and flow velocities for both floodplain and channel environments.

Figure 5‐31: Causal relationship between climate change threats and water levels at the project site

Summarising from previous sections, the key assumptions in developing projections of future flood dynamics at the project site include:

1) Increase in Sea Level rise has been set at 1.0m as this represents the upper limit of the official GoV scenarios

2) Increase in catchment rainfall is based on a future timeslice of 2045‐209, based on an assessment that increases are among the largest within this bracket.

3) Increase in hydropower storage takes into account all hydropower under some form of consideration, however its impact affects average flows not extreme flows.

5.8.1 Typical flood years Figure 5‐32 compares average flooding at the project site under baseline and climate change conditions. Average flooding conditions are summarised in Table 13 and calculated using 25 years of observation data (baseline) and 150 years of simulated data compiled from 6 GCMs. There is an approximate 15% increase in both mean annual and peak flows due to climate change, while the timing and duration of the flood season, together with the proportion of annual flow arriving during the flood season remains at approximately 80%.

Table 14: Overview of average Kratie flood characteristics under baseline and CC scenario

Parameter Baseline Climate Change

mean annual flow (m3/s) 11,983 13,585 peak flow (m3/s) 39,810 46,007

flood season volume (MCM) 297,680 340,577

flood duration (days) 134 137

flood start 1‐Jul 28‐Jun

flood end 12‐Nov 12‐Nov

Annual flow volume (MCM) 377,908 428,418

DRIVER OF CHANGE

EXPOSURE

THREAT

Increase in tidal excursion and back‐

water effects

Sea level rise (SLR)

Increase in water levels at Cao Lanh

Climate Change

Upstream hydropower

Increase in seasonal storage

Increase in catchment rainfall Net increase in Tien

river discharge & overbank flow


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Figure 5‐32: Comparison of average flood conditions in project vicinity under baseline and climate change conditions


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Under baseline conditions, flooding at the project site remains uniformly below 1.5masl. Location of the connecting road is marginally higher than the surrounding floodplain and there is a natural southward gradient which orients drainage from the Tien River and surrounding floodplains to the Hau River channel. With climate change floodplain dynamics are not expected to change significantly but there will be an increase in the flood water levels. Most of the connecting road will be exposed to water levels between 1.5 – 2.6masl.

The two bridges are located at sites where water levels remain relatively stable under interannual fluctuations in flooding. Analysis of historic water levels indicate that even between low flood and above average floods water levels at Cao Lanh and Vam Cong vary by less than one metre (SIWRR, 2010).

5.8.2 Extreme flood years In pulsing tropical rivers like the Mekong, flooding is an annual occurrence. Extreme flood events are those which differ substantially from typical conditions expected on a year‐in‐year‐out basis – though definitions of ‘substantial’ can vary. One option for defining ‘substantial difference’ is assess the long term historic distribution of annual flood volume and fit this data to a statistical distribution. This has been undertaken for Kratie station by the MRC (2011) with results presented in figure 5‐33.

Figure 5‐33: Statistical definition of extreme floods for the Mekong based on flow volume at Kratie (1924‐2006)

Source: MRC, 2011

Based on this definition significant events are those with a return period greater than 1 in 10 years (P10%), and extreme floods are those with a return period greater than 1 in 20 (P5%). Section 5.xx presented results for the return periods of flood events at Kratie under baseline and climate change conditions.

In order to link these events to flood dynamics at the project site, the VA study team assessed peak water levels at the two gauging stations closest to the bridge sites: Cao Lanh and Long Xuyen (Figure 5‐34).


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Figure 5‐34: Minimum and maximum water levels at Cao Lanh and Vam Cong site

Based on this analysis the P1% and P5% water levels at Cao Lanh and Long Xuyen were identified (table 14).

Table 15: Historic extreme water levels at Cao Lanh and Long Xuyen

Station Annual Exceedance probability

Max. water level (m)

Long Xuyen P1% 2.76

P5% 2.59

Cao Lanh P1% 2.84

P5% 2.53

The methodology for calculating the return period used an annual maxima series derived from the peak daily discharge event in each flood season. It should be noted that this works well for discharge frequency analysis where flow is predominately confined to channel systems. However, linking these return periods to levels in a floodplain environment can show poor correlation. For the Mekong, where downstream of Kratie flows spill in and out of the river channel into the surrounding floodplain including the reversal and natural storage of flows in the Tonle Sap, other assessments have used the 1 month flow volume during the peak flood month (Faulkner et al, 2012).

For example, comparison of recent large floods has shown that the 1961 flood was smaller than the 2000 flood both in terms of flood volume and flood peak, however the maximum water levels in the Delta were higher than the 2000 flood. This reflects the dynamic nature of the floodplain environment especially in relation to the distribution of floodwaters between the channels and floodplain. It is likely that in 1961 floodwaters were more confined to the Mekong channels than in 2000, when overland flow account for 20‐30% of total volume.


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A ‐ Changes in floodplain levels under the P1% event Under the baseline P1% scenario, the areas surrounding the left‐bank of the Hau River are subject to flooding of less than 1.5masl, while the right‐bank of the Tien River will experience deeper flooding of up to 2.6masl (figure 5‐35). With climate change P1% floodplain water levels along component 2 will reach up to 2.6masl. Increases in flooding become more pronounced further upstream in the vicinity of Cho Moi and the Cambodian border.

Comparison of floodplain water levels immediately upstream of component 2 indicates that the design embankment height of 2.86masl is sufficient to accommodate for the historic P1% flood (2.74masl) and some 0.22m above the year 2000 flood level. With climate change water levels at the site will increase resulting in a peak water level of 3.47masl. This is 0.61m above the current design embankment height and 0.03m above the river water level.

Under future P1% conditions in the floodplain with climate change, the water levels will exceed the embankment height for one month spread out between late August and mid‐November.

Results above are from the MIKE 11 model and show good agreement with the 3D model results. Figure 5‐36 identifies that the maximum water levels are highest at the middle part of the road and that the eastern part of the road has higher levels than the western. This is primarily a result of land elevation and the alignment of the road alignment in relation to floodplain drainage lines. The maximum water levels are about 3.1 masl near Hau River, 3.6masl in the middle and 3.2masl near the Tien River. In addition wind speeds of up to 15m/s will raise water surface elevations by approximately 0.1m (Figure 5‐38).

Compared to baseline conditions, the 3D model results show good agreement with the 1D delta‐wide model that P1% flows with climate change will be 0.6m above baseline conditions.

Table 16: Variation in P1% floodplain water levels with climate change: range in water levels presented for 3D model results shows variability along the road length

Baseline CC (1D model) CC (3D model) Increase in WL(m)

P1% Water Level (masl)

2.74 3.47 3.1 – 3.6 +0.6


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Figure 5‐35: Change in P1% flooding of the Mekong Delta with climate change: (TOP) baseline conditions, (BOTTOM) with climate change


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Figure 5‐36: P1% Hourly Water Levels in the surrounding floodplain: Design embankment elevation is shown at 2.86masl (RED LINE), z_P1% = historic P1% flood level; z_P1%CC = future P1% flood levels with climate change; z_2100max = largest annual flood event produced by 500 years of simulated data form 6 GCMs; and z_2000 = water level during the year 2000 flood

Figure 5‐37: Maximum water levels for the P1% event with climate change: this figure shows the connecting road, the Tien and Hau River banks lie just outside the figure


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Figure 5‐38: Sensitivity of floodplain water levels to wind

Figure 5‐39: Comparison of P1% floodplain levels with and without climate change (3D model): 3D model results for increment in floodplain water levels due to climate change show good agreement with results obtained from the 1D delta‐wide model

B ‐ Changes in River water levels under the P1% event Figure 5‐40 compares Cao Lanh water levels under baseline and climate change conditions. Comparison of river water levels at the Cao Lanh bridge site indicates that the design embankment height of 2.86masl is sufficient to accommodate for the historic P1% flood (2.7masl) and some 0.22m above the year 2000 flood level. With climate change water levels at the site will increase resulting in a peak water level of 3.44masl. This is 0.58m above the current design embankment height.

Under future P1% conditions in the Tien River channel with climate change, water levels will exceed the embankment height for one month, spread out between late August and mid‐November.

Comparison of the results shows good agreement between the 1D and 3D models at Cao Lanh site. Figure 5‐41 shows that during the peak flood period, water levels at Cao Lanh will reach 3.4masl. This is 0.54m above the current design embankment height.


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Figure 5‐40: P1% Hourly Water Levels at Cao Lanh: Design embankment elevation is shown at 2.86masl (RED LINE), z_P1% = historic P1% flood level; z_P1%CC = future P1% flood levels with climate change; z_2100max = largest annual flood event produced by 500 years of simulated data form 6 GCMs; and z_2000 = water level during the year 2000 flood

Figure 5‐41: Simulated water levels – Cao Lanh bridge site under baseline and climate CC: (RED) climate change; (BLACK) baseline

A summary of the changes in water levels at the bridge site is presented in table 16 below.

Table 17: Variation in P1% Cao Lanh water levels with climate change: range in water levels presented for 3D model results shows variability along the road length

Baseline CC (1D model) CC (3D model)


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Cao Lanh P1% Water Level (masl)

2.7 3.44 3.4

C ‐ Changes in River water levels under the P5% event Under the baseline scenario, the areas surrounding the left‐bank of the Hau River are subject to flooding of less than 1.5masl, while the right‐bank of the Tien River will experience deeper flooding of up to 2.6masl (figure 5‐43). With climate change P5% floodplain water levels along component 2 will reach up to 2.6masl. Increases in flooding become more pronounced further upstream in the vicinity of Cho Moi and the Cambodian border.

Comparison of river water levels at the Cao Lanh bridge site indicates that the design navigation clearance of 2.6masl is sufficient to accommodate for the historic P5% flood (2.58masl) and approximately equivalent to the year 2000 flood level (5‐43). With climate change water levels at the site will increase resulting in a peak water level of 3.33masl. This is 0.73m above the current design level. The P5% water level with climate change will exceed the design clearance for more than two months spread out between mid‐August and late‐November.

Figure 5‐42: P5% Hourly Water Levels at Cao Lanh: Design navigation clearance is shown as 2.6masl (RED LINE), z_P1% = historic P1% flood level; z_P1%CC = future P1% flood levels with climate change; z_2100max = largest annual flood event produced by 500 years of simulated data form 6 GCMs; and z_2000 = water level during the year 2000 flood


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Figure 5‐43: Change in P1% flooding of the Mekong Delta with climate change: (TOP) baseline conditions, (BOTTOM) with climate change


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D – Changes in flow velocities An assessment was made of changes in flow speed at the bridge and road sites using the 3D hydrodynamic model. Results were outputted for mid‐stream, surface and bed velocities at the two bridge sites and for surface velocities along the road alignment.

Surface velocities peak near 5m/s in the Tien River channel and nearly 6m/s in the Vam Cong in the last half of September, while mid‐stream velocities reach 4.8m/s a Cao Lanh and 5.9m/s at Vam Cong (figure 5‐44). With climate change the mid‐stream flow velocities have increased by +0.2m/s and +0.5m/s at Cao Lanh and Vam Cong respectively. The high velocities especially near channel banks require attention for bank protection.

Figure 5‐44: Changes in mid‐stream flow velocities with climate change: (TOP) Cao Lanh; (BOTTOM) Vam Cong. RED = Climate change scenario, BLACK = baseline

In the floodplain environment, the highest average flow speeds are over 0.7 m/s on the Western and Eastern ends of the connecting road. Speeds of 0.7 m/s can be critical velocity for onset of erosion. Assessments were also made to assess the sensitivity of floodplain flow speeds to wind conditions. It is evident that wind plays a minor role compared to the flood flow.

With climate change flow speeds through road embankment openings are likely to increase by 0.5 – 0.8m/s during the 1 in 100year event.

Waves are a serious threat to floodplain roads; they increase water overtopping over the road and can cause major embankments erosion. Wave height depends mostly on fetch (length of open space for wave formation) and water depth. The highest waves are generated by Northerly winds. Wave heights for 15 m/s North wind, can reach a height of is 33 ‐ 42 cm on the Northern side of the road embankment.

A rapid, simple model was also developed to assess flow through hydraulics for drainage culverts in the context of future P1% event with climate change. Flow speeds through the structures were capable of reaching speeds of 1.5‐4.0m/s


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Figure 5‐45: Simulated velocity profile at Cao Lanh with P1% climate change scenario: (LEFT) Surface velocities peak at almost 5m/s in the centre of the channel; (RIGHT) near bed velocities are greatest near the left‐bank of the Tien channel reaching 0.9m/s

Figure 5‐46 Simulated velocity profile at Vam Cong with P1% climate change scenario: (LEFT) Surface velocities peak at almost 6m/s in the centre of the channel; (RIGHT) near bed velocities reach peaks of up to 1m/s

E – Estimating future return periods for design options In response to the implications of climate change on water levels at the project site, the Government of Vietnam and ADB have started to explore options for raising the design height for embankments. One option suggested is to raise the height to 3.16masl, which amounts to a +0.3m increase in the current design height. While 0.3m is below the increment required to respond to climate change (this study recommends +0.6m), there are other economic and political considerations which need to be factored into the decision. The VA Study team was asked to define what the corresponding return period is for a flood which would produce water levels of 3.16masl.

In order to do so, the VA Study team developed annual maxima series for water level data from Vam Cong and daily discharge data from Kratie for the period 1978‐2002. These were plotted to assess correlation (Figure 5‐48).


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Trend lines were developed using linear and logarithmic assumptions, with corresponding equations presented below.

Figure 5‐47: Correlation between Kratie peak discharge and Cao Lanh peak levels (1978‐2002)

These trends were then used to extrapolate indicative peak discharges at Kratie Station, which were then together with figure 5‐18 to estimate the approximate size of the corresponding return period. Results are tabulated in Table 17. Based on this methodology adding +0.3m to the current design height would ensure that the embankments are built in response to the 1 in 30year future flood.

Table 18: Summary of hydrological parameters for the Embankment Design height + 0.3m

Parameter Linear relationship Log. relationship Cao Lanh Water Level (m) 2.86 + 0.3 = 3.16 2.86 + 0.3 = 3.16

Estimated Kratie Qmax (m3/s) 76,967 72,729

Estimated Baseline Return Period (T) 190 ‐ 210 80 ‐ 100

Estimated CC Return Period (T) 25 ‐ 30 15 ‐ 20

As described earlier in this section (p79) and in Faulkner (2012), there are some important limitations in linking water levels in the delta floodplain to peak events at Kratie –especially as the extrapolation extends beyond the range available within the sample data. A proper assessment would require actual simulation of flood dynamics for different conditions at Kratie to explore how water levels respond. The findings summarised in table 17 represent only a preliminary assessment and should be used as indicative.


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6 VULNERABILITY ASSESSMENT

In the infrastructure design process, engineers utilise an understanding of the hydro‐meteorological processes to quantify the occurrence and magnitude of forces experienced by infrastructure as a result of their surrounding environment (floods, storms, wind speeds, temperatures). This understanding is then used to establish design criteria which set the level of risk considered acceptable on an annual basis or over the design life. It is neither economical nor technically possible to design infrastructure that is immune to the surrounding environment, so the engineering design process is fundamentally one of managing physical and economic impacts to minimise risk to an acceptable level.

In the context of climate change, it is also not economical or technically possible to climate‐proof infrastructure beyond all doubt. Engineers, together with climate scientists, need to establish a clear evidence base of how climate change is impacting the surrounding environment and then assess what level of additional risk is acceptable. This determination of acceptable risk is as much a function of economic and political considerations as it is a technical one – especially given the novelty of climate change assessments and that to date there are no formal standards for infrastructure design with climate change within Vietnam’s legislative framework.

Engineering risk is the cumulative probability of occurrence for a particular extreme event over the structure’s design life. For example, figure 6‐1 illustrates the probability that an extreme event will occur during the 100 year design life of the project. Under baseline conditions, the P5% has a 99.4% chance of occurring at least once during the design life, whereas the P1% flood has a 63.4% chance of occurring at least once during the design life.

Figure 6‐1: Extreme event risk for P1% flood over 100year design life: climate change will reduce the return period of peak events and increase the likelihood of occurrence over the design life.

Source: adapted from Chow et al, 1988

Section 5 has presented an overview of the key changes to the hydroclimate of the Mekong Delta. Where possible, the VA Study team utilised methods to quantify absolute and relative changes in these parameters, expressing results in terms of ranges and adopting a cautionary approach. In section 6, this is used to define the exposure of specific components to climate change. For bridge sub‐ and super‐structures, the approach and connecting roads; road surfaces, embankments, drainage systems and foundations of the CMDCP, the VA study team has linked exposure to changes in the Mekong hydro‐meteorological system with potential sensitivities of specific infrastructure components. Impact has then been defined as the product of exposure and sensitivity.

Reduced return period

Corresponding increase in risk


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Central to the characterisation of sensitivity has been an assessment of the specific design requirements of individual components as outlined in the Vietnamese design standards. Environmental loads are defined in the standards according to the Load Resistance Factor Design (LRFD) philosophy, which combines different limit states to establish the design specification for each component against published limiting force/moment capacities. Each limit state is given equal importantance to achieve the basic design objectives of constructability, safety and serviceability.

1. Service limit state: controls long term issues of usability and durability. Typically based on established empirical relationships

2. Fatigue and Fracture Limit State: Exceeding fatigue limits can cause structural damage or lead to limitations for heavy traffic loadings

3. Strength limit state: This is the main limit state for structural safety. Extensive distress and structural damage may occur under strength limit state, but overall structural integrity is expected to be maintained. Ductile behaviour is favoured because large displacements warn users

4. Extreme event limit states: sets loading to resist collapse. Extreme event limit states are considered to be unique occurrences whose return period may be significantly greater than the design life of the bridge.

LRFD provides a framework for understanding sensitivity of individual components. Loadings presented in the standards represent extreme values to be expected in the design life of the structure. The extreme values are defined using existing data available with safety margins depending on the liability and coverage of the data. Design loads are also factored with safety factors. The overall safety margin varies depending on the accuracy of loads and the importance and sensitivity of the structural component under assessment. Larger safety margins are usually used in geotechnical design because of uncertainties in geotechnical parameters and soil conditions. When the Extreme event limit state is applicable, the safety margins are lower and the structures may be subject to remarkable damage although the collapse of the bridge is not accepted.

The design life and maintenance schedule are important considerations for setting the level of vulnerability and also prioritising the phasing of adaptation response. Table 19 presents an overview of these characteristics for the main components of the CMDCP. Maintenance scheduling has been divided by yearly, general (5‐10years) and special inspections (before major repair operations).

Table 19: Overview of design life and maintenance requirements for main components of the CMDCP

Design life Maintenance

The design life for bridges is 100 years

Essential structural parts and parts which are difficult to replace => 100 years

o Stay cables o Substructure o Superstructure

Secondary parts or parts which can be easily replaced => 20 to 50 years

Water‐proofing 20 to 25 years

Railings 25 to 50 years

Roadway surfacing 10 to 25 years

Expansion joints 20 to 25 years

Bearings >50 years

Drainage systems >20 years

Monitoring

Clean‐up, small repairs => yearly

Painting of steel parts: 15 to 20 years

Renewal of water‐proofing 20 to 25 years

Repair/renewal of railings: when needed (10 to 20 years)

Renewal of roadway surfacing: when needed

Renewal/repair of expansion joints: when needed (10 to 20 years)

Maintenance of bearings: 20‐25 years

Renewal of drainage systems: >20 years

Renewal of cable stays: when needed (>25 years)

Repair of structural concrete o Structures exposed by running water:

20‐30 years o Structures subjected to mechanical

wear, collision etc: when needed

Other structures: 30 ‐ 50 years


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6.1 Bridge substructure Bridge infrastructure can be divided into two components, the substructure and superstructure. The substructure consists of the foundational elements including the piling, foundation slabs, abutments, columns, pylons and bearings. Those elements located above the bearings comprise the superstructure (c.f. Section 6.2). The design life of bridge substructures is generally 100 years.

6.1.1 Foundation slabs, pylons and abutments Small and medium size bridges are founded on bored or driven concrete piles (D=2.5m). In the foundations for main bridges large diameter bored concrete piles are used. The foundation slabs are made of reinforced concrete cast in‐situ with dimensions 90x60x6m. The bottom level of foundation slabs for pylons is located below the low water level and the top level above the highest tide level. The abutments are of traditional shape and, like the two columns at each support, are made of reinforced concrete cast in‐situ. The pylons are also made of reinforced concrete cast in‐situ, with their height above the deck level is set as ¼ of main span length. For structural concrete the need of repair is usually after 30 to 50 years, however in surfaces subjected to running water only after 20 to 30 years.

Sensitivity As the massive substructures (foundation slabs and abutments) are made of cast‐in‐situ concrete, they are usually not very sensitive to environmental changes. The threats caused by climate change include:

1) The change in division of support reactions due to changes in stay cable forces. 2) The rise of high water level increases the uplift which reduces stability and changes pile forces 3) Increased water pressure against structures increases overturning moment and changes pile forces 4) Increase in extreme wind speeds increases overturning moment and changes pile forces 5) Increased risk of ship collision 6) Changes in sedimentation and water flows may lead to increased scouring 7) Changes in salinity and pH reduce the service life of structures exposed to river flow.

Exposure and impact Changes in frequency & intensity of flood events & Sea Level Rise: With climate change, the frequency and magnitude of extreme events will increase. Figure 5‐15 defines an increase in the range of peak discharge under future climate change scenarios, demonstrating a significant increase at Kratie. Under typical flood events the increase is by a factor of 1.08‐1.93 times the baseline. Extreme flood events are also likely to become more frequent, for example the historic 1 in 100 year event, is likely to become a 1 in 20‐30year event under future climate. These changes will increase water pressure on foundational structures with the potential to cause uplift.

Changes in flow velocities, sediment load and sediment composition: The threat assessment indicates that the bridge site is located in a geomorphologically stable section of the Tien River, which has undergone minimal lateral migration since 1966. The site is immediately downstream of a channel constriction and future projections without climate change suggest limited erosion in the future. For the bridge substructure, flow speed is used to calculate the water pressure acting on foundations and to estimate the scour depth With climate change in‐channel mid‐stream flow velocities in the Tien River will increase by +0.5m/s, with surface velocities reaching close to 5m/s during the P1% flood, and near bed velocities reaching 0.9m/s. Bed velocities are greatest near the left bank of the Tien. Increases in velocity will increase the stream power and hence energy available for geomorphological work.


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Figure 6‐2: In‐channel scour processes for bridge substructure

Source: CFLHD, 2012

Potential impacts include:

1) Scour to foundation of the bridge: Scouring is one of the most common causes of bridge failure (CFLHD, 2012). Changes in river hydraulics can enhance scouring efficiency at pylons, foundation slabs and other components within waterways, reducing support which can in turn compromise the superstructure and lead to possible failure (figure 6‐2). The VA study has not modeled scour directly, however increases in velocity suggest that the near left‐bank region of the channel cross‐section will be most susceptible to scour.

2) Damage to support piles: there is the potential for increased erosion efficiency at the Tien left‐bank. Erosion can in the medium term lead to exposure of support piles which are currently not designed to be in the river channel.

3) Increased risk of ship collision with pylon/foundation due to change in location of the clearance relative to the structure.

Rainfall intensity: Projections for future rainfall with climate change indicate that the seasonal volume of rainfall is increasing by as much as 50%, while there is no statistically significant variation in the number of rain‐days. While this cannot be quantitatively linked to changes in hourly rainfall intensity it is a clear indication that rainfall intensities are likely to increase. Comparison of peak daily rainfall also confirms that intensities are increasing – whereas under average baseline conditions less than 10 days experienced rainfall totals greater than 100mm/d, with climate change more than 20 days exceeded 100mm/d. For the bridge substructure high intensity, short duration rainfall events can increase water pressure, uplift, and scour at foundations.

Mean wind speed (10min winds): Wind speeds and alignment determine the horizontal and static wind loads. With climate change cyclones are likely to become more intense and there is a possibility that cyclone events will track further south, tracking more frequently over the Mekong Delta, which could lead to increased vibrational forcing from wind loading. At present, evidence is not available to confirm conclusively whether or not this will occur.

Changes in pH, salinity, sulphates, chlorine: increases in river and floodplain salinity and pH can lead to: (1) accelerated concrete erosion of pylons and bridge foundations, (2) accelerated corrosion of metal reinforcements, (3) reduced life of substructure components, (4) increased maintenance effort. The issue was not explored directly in this study, however reductions in dry season flow levels as well as reduction and increasingly erratic direct rainfall during the dry season point to a drier, hotter dry season in contrast to a wetter wet season. Greater


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variability between seasons will enhance the production of acidic waters in the floodplains of Dong Thap and An Giang through the seasonal exposure of acid sulphate soils. This will not affect the large bridge structures nor the small bridges associated with Component 2 (soils are predominately alluvial in that region), but should be assessed for other future components of the CMDCP closer to the Plain of Reeds and Long Xuyen Quadrangle areas.

The pylons are sensitive to following changes in climate:

The increased static and dynamic wind effects cause larger stresses to pylons

The 80m long large diameter piles are not very sensitive to changes caused by short term loading. They also provide a good counterweight against uplift.

The increased scouring is a serious risk which should be considered in detailed design

The changes in pH and salinity should be considered in detailed design by choosing adequate concrete covers, suitable concrete mix and/or non‐corrosive reinforcement.

The movement range of the bearings can be adjusted as a maintenance operation. In case of overloading the bearings have to be replaced by stronger bearings.

The increase in static wind load increases the moments in pylon and it should be considered in final design. The dynamic wind effects are verified using wind tunnel tests. They occur usually on low to moderate wind speeds the environmental change should have negligible effect on them. The changes in stay cable forces due to temperature change are almost symmetrical to the pylon so the resulting moment to the pylon will stay in the safety margins

6.1.2 Free‐sliding bearings Bridge bearings are devices for transferring loads and movements from the deck to the supporting foundations of the substructure. They are designed to allow for controlled relative movement between the bridge substructure and superstructure accounting for thermal expansion, and wind and traffic vibration. The bearings are critical components which are relatively difficult to replace and are typically designed with a design life greater than 50 years, with maintenance required every 20‐25 years.

In the CMDCP the bearings are pot bearings or elastomeric bearings. Pot bearings are used with higher loads and/or to resist horizontal loads or movements. In addition dampers can be used to improve the behavior of bridge deck under dynamic load effects.

Sensitivity The bearings are sensitive to the following changes:

1) The change in division of support reactions due to changes in stay cable forces can lead to overloading and damage of bearings

2) Increase in extreme wind speeds increases horizontal forces for fixed bearings 3) Changes in temperature range and mean temperature cause asymmetric movement which leads to

extended wear and reduces the service life of bearings.

Exposure and impact Change in mean daily temperature: With climate change mean daily temperature will increase by an average of 2.3 Deg C. There will also be a significant shift in maximum daily temperatures. Average maximum daily temperatures did not exceed 35Deg C under baseline conditions, with climate change 35Deg C will be exceeded 15‐45% of the year. Bearings are sensitive to increases in temperature because they are designed to help bridge structures dissipate any potentially harmful loading associated with movement of the superstructure. One of the key factors in this is the difference in response time between steel and concrete components (thermal conductivity of steel l= 25 x l concrete). So changes in temperature need to be considered in the dimensioning of the free‐slide bearings. Inreases in the average and range of temperatures could lead to: (1) asymmetric movement with reduced range for expansion but increased range for compression, (2) expands friction coefficient. The likely


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impact of this will be reduced design life and increased future replacement costs. These impacts could also lead to damage or failure.

Table 20: thermal properties for bearings and expansion joints

6.1.3 Navigation clearance

Sensitivity Design water levels for the river channel and floodplain are set to provide vertical navigational clearance of 37.5m to ensure operation of 10,000DWT vessels for the P5% flood. This clearance has been determined in consultation with the Mekong River Commission (MRC) to allow future passage of 10,000DWT vessels upriver to Phnom Penh port. Bridge approach roads will have embankments set for the P1% event and supported by driven piles.

In addition to the two main bridges spanning the Tien and Hau Rivers, there is a total of 26 smaller bridge crossings which are required to traverse the dense network of channels and canals which cover the delta. Vertical clearance for the smaller bridge crossings is based on the following:

(i) Navigable channels and rivers: Navigation clearance for the P5% event. Discussion with the detailed design team in March 2012 indicated that this clearance is in the order of 1.2 – 3.5m, except for the Lap Vo River Bridge (KM18.7+) where the navigation clearance is set at 7m.

(ii) Non‐navigable canals: for small non‐navigable waterways the bridge clearance level is set as P1% + 0.5m freeboard.

Exposure and impact Rainfall intensity, Rainfall volume, Changes in frequency & intensity of flood events, Sea and river level rise: Increases in frequency and duration of rainfall, sea level rise and increasing river flow will result in elevation of river water levels. The impact of climate change on navigation clearance will be reduced usability through loss of clearance. For the main bridge design 2.6 m river water level is taken as the design criteria for ship clearance. Vertical clearance is then set at 37.5m above this water level allowing passage of 10,000DWT vehicles. Climate change will increase periods of the year when the full navigation clearance of 37.5m is not available.

With climate change water levels at the site will increase resulting in a peak water level of 3.33masl for the P5% event. This is 0.73m above the current design level. The P5% water level with climate change will exceed the design clearance for more than two months (63days) between mid‐August and late‐November. Because the clearance is large the expected future water level rise will not cause major problems for small and medium‐sized vessels, but will impact the largest vessels predicted to use the river channel between the coast and Phnom Penh.

For the smaller bridges, water levels associated with the future P5% will see the majority of component 2 experience water levels of up to 2.6masl; under historic conditions only the road section adjacent to the Tien right‐bank experienced these levels. Current design –based on 2.6masl‐ should not be significantly affected by this.


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Mean wind speed (10min winds): With climate change there is a possibility that cyclone events will track further south, tracking more frequently over the Mekong Delta, which could lead to increased vibrational forcing from wind loading. However, little information is available on baseline wind speeds under non‐cyclone conditions so no projection has been made on how this threat will change. Increases in wind speed will increase the difficulty in navigating ship passage under stronger wind conditions, with the potential to result in collision with pylon/foundation.

6.2 Bridge superstructure The superstructure of the bridges consists of the deck, stay cables, expansion joints, as well as the deck drainage and water proofing systems.

6.2.1 Bridge deck Preliminary design indicates that Cao Lanh bridge will have a pre‐stressed concrete slab, while Vam Cong will have a composite steel‐concrete deck (figure 6‐3). In small and medium size bridges of span lengths up to 24m pre‐stressed concrete slab elements are used in deck structure. For larger spans pre‐stressed Super T‐girder elements are used. The approach bridges are build using precast concrete elements with elastomeric bearings and expansion joints at supports.

The design life of bridge deck is typically 10‐25 years for the road surfacing. The need of maintenance depends on structure. For steel deck new painting is needed in 15 to 20 years. For concrete parts the repair is needed after 30 to 50 years.

Figure 6‐3: Bridge Deck structures: (TOP) Cao Lanh Bridge pre‐stressed concrete slab, (BOTTOM) Vam Cong Bridge Composite steel‐concrete deck


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Sensitivity The bridge deck has the following sensitivities:

Changes in temperature variation and mean temperature can cause changes in stay cable forces and deck stresses leading to reduced safety margins and design life. Increased deflection of the deck reduces clear navigation height and affects vertical road alignment.

Changes in wind and storm conditions can increase dynamic effects on stay cables and the deck.

The dynamic wind effects are verified using wind tunnel tests. They occur usually on low to moderate wind speeds the environmental change should have negligible effect on them.

changes in deck form reduces the usability of the bridge and increases maintenance needed.

Exposure and impact Change in mean daily temperature: With climate change mean daily temperature will increase by an average of 2.3 Deg C. There will also be a significant shift in maximum daily temperatures. Average maximum daily temperatures did not exceed 35Deg C under baseline conditions, with climate change 35Deg C will be exceeded 15‐45% of the year. Significant rises in mean temperature will induce different rates of elongation between stay cables and deck, causing changes in the cable loading and deflection of the bridge deck.

In addition ambient thermal conditions drive a temperature gradient within the deck structure. Temperatures at the surface can be significantly warmer than internal regions causing internal stresses in the structure. Warming temperatures, in particular daily maximum temperatures will increase the thermal forcing at the surface strengthening the gradient.

Impacts from variation in ambient temperatures include: (1) damage due to deflection of the bridge deck, (2) cracking of deck surface, (3) partial loss of navigation clearance.

Figure 6‐4: Schematic description of temperature gradient within deck structures: exposed surface is at the top, with empirical table of design gradients shown to the right. The middle column refers to positive gradient, while right column refers to negative gradient.

Rainfall intensity: Projections for future rainfall with climate change indicate that the seasonal volume of rainfall is increasing by as much as 50%, while there is no statistically significant variation in the number of rain‐days. While this cannot be quantitatively linked to changes in hourly rainfall intensity it is a clear indication that rainfall intensities are likely to increase. Comparison of peak daily rainfall also confirms that intensities are increasing – whereas under average baseline conditions less than 10 days experienced rainfall totals greater than 100mm/d,


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with climate change more than 20 days exceeded 100mm/d. Increase in high intensity, short duration rainfall events will exacerbate short term flooding and uncontrolled floodwater conveyance issues as well as lead to damage to deck & road surface and increased maintenance effort

Extreme gusts, thunderstorm, and cyclones: With climate change cyclones are likely to become more intense and there is a possibility that cyclone events will track further south, tracking more frequently over the Mekong Delta, which could lead to increased vibrational forcing from wind loading. At present, evidence is not available to confirm conclusively whether or not this will occur. Increase in frequency and magnitude of major gusts and storm events resulting in sustained loading at high wind speeds can cause vibration, oscillation, vortex effects and galloping. In addition wind‐ and rain‐induced vibration of stay cables can combine with these other factors to induce dynamic effects such as galloping. The potential impact includes: (1) resonance‐induced structural damage, (2) fatigue of key supports in superstructure.

6.2.2 Stay cables Stay cables are made using either the prefabricated parallel wire cable or parallel strand cable system. Individual strands are encased in a corrosion inhibitor, galvanized and then given an HDPE coating to form cables (Figure 6‐4). There are approximately 30‐100 strands (D=15.7mm) in each cable, requiring the stays to be assembled in two planes.

Although the design life of stay cables is 100 years it is likely that a need for renewal may arise earlier, in 25 to 50 years. The structural system is usually designed to enable the replacement of stay cables one at a time.

Figure 6‐5: Components of Stay Cable

Sensitivity Key sensitivities of stay cables to environmental loadings include:

Changes in temperature variation and mean temperature can cause changes in stay cable forces and deck stresses leading to reduced safety margins and design life.

Increased deflection of the deck reduces clear navigation height and affects vertical road alignment.

Changes in wind and storm conditions can increase dynamic effects on stay cables and the deck.

Changes in stay cable forces will be in the limits of safety margins but the design life of cables reduces.

Exposure and impact Extreme gusts, thunderstorm, and cyclones: With climate change cyclones are likely to become more intense and there is a possibility that cyclone events will track further south, tracking more frequently over the Mekong Delta,


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which could lead to increased vibrational forcing from wind loading. At present, evidence is not available to confirm conclusively whether or not this will occur. Increase in frequency and magnitude of major gusts and storm events resulting in sustained loading at high wind speeds can cause vibration, oscillation, vortex effects and galloping. Potential implications include: (1) resonance‐induced structural damage, (2) fatigue of key supports in superstructure.

Change in mean daily temperature: With climate change mean daily temperature will increase by an average of 2.3 Deg C. There will also be a significant shift in maximum daily temperatures. Average maximum daily temperatures did not exceed 35Deg C under baseline conditions, with climate change 35Deg C will be exceeded 15‐45% of the year. As mentioned in Section 6.2.1, significant rises in mean temperature will induce different rates of elongation between stay cables and deck, causing changes in the cable loading and deflection of the bridge deck. Potential impacts include: (1) damage due to deflection of the bridge deck, (2) cracking of deck surface, (3) partial loss of navigation clearance

Rainfall intensity: Projections for future rainfall with climate change indicate that the seasonal volume of rainfall is increasing by as much as 50%, while there is no statistically significant variation in the number of rain‐days. While this cannot be quantitatively linked to changes in hourly rainfall intensity it is a clear indication that rainfall intensities are likely to increase. Comparison of peak daily rainfall also confirms that intensities are increasing – whereas under average baseline conditions less than 10 days experienced rainfall totals greater than 100mm/d, with climate change more than 20 days exceeded 100mm/d. Increases in high intensity, short duration rainfall events will exacerbate vibration of stay cable, resulting in increased fatigue to stay cables and reduced design life.

6.2.3 Deck drainage The bridge deck drainage system includes the bridge deck itself, bridge gutters, inlets, pipes, downspouts, and bridge end collectors. Bridge deck waterproofing is made using membranes, mastic or liquid materials like polyurethane. The system is designed for major maintenance every 20+ years with regular monitoring and maintenance to ensure proper operations.

Sensitivity The key sensitivity of the deck drainage system is to direct precipitation. An increase in rain intensity can exceed the capacity of drainage system resulting to flooding.

Exposure and impact Rainfall intensity: Projections for future rainfall with climate change indicate that the seasonal volume of rainfall is increasing by as much as 50%, while there is no statistically significant variation in the number of rain‐days. Comparison of peak daily rainfall also confirms that intensities are increasing – whereas under average baseline conditions less than 10 days experienced rainfall totals greater than 100mm/d, with climate change more than 20 days exceeded 100mm/d. While this cannot be quantitatively linked to changes in hourly rainfall intensity it is a clear indication that rainfall intensities are likely to increase. High intensity, short duration rainfall events can exacerbate short term flooding and reduce of drainage structures. The resulting impacts include: (1) accident to drivers using road, (2) down‐time and reduced road usability, and (3) increased maintenance effort.

6.2.4 Expansion joints Expansion joints are built into the end of side spans to to accommodate expansion and contraction of bridge infrastructure in response to the daily and seasonal range in temperature. In small and medium size bridges and approach bridges of main bridges sheet or strip seals or poured seals can be used. Modular Bridge Joint System is used in main bridge joints. All expansion joints should be watertight or waterproofed to avoid deterioration and to ensure they reach their design life of 20‐25years. Maintenance is also required every 10years.


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Figure 6‐6: Expansion joints (modular joint system)

Sensitivity Expansion joints are sensitive to:

Changes in temperature variation and mean temperature cause asymmetric movement which leads to extended wear and reduces the service life of expansion joints.

The need to adjust expansion joint movement range means usually the renewal of joints.

Exposure and impact Change in mean daily temperature: With climate change mean daily temperature will increase by an average of 2.3 Deg C. There will also be a significant shift in maximum daily temperatures. A shift in mean temperature could: (1) accelerate ageing through hardening, UV/solar deterioration, and (2) cause asymmetric movement with reduced range for expansion but increased range for compression, increasing potential for damage, failure, or reduced design life and increased replacement cost

Changes in daily, range in temp and daily seasonal temperature extremes: With climate change there will be a major shift in the size and centre point of the daily temperature range. Average maximum daily temperatures did not exceed 35Deg C under baseline conditions, with climate change 35Deg C will be exceeded 15‐45% of the year. Heatwaves (4‐5days of extreme temperatures) could exacerbate the problem. If upper temperature limit is exceeded (i.e. hotter temperatures than in current design range) could cause collision between bridge and approach roads. If lower temperature limit is breached, could over‐stretch expansion joint. With climate change the likelihood of collision between the bridge and approach roads is increased, and that of over‐stretch reduced as the daily temperature range shift to a hotter zone.

Rainfall intensity and volumes: Projections for future rainfall with climate change indicate that the seasonal volume of rainfall is increasing by as much as 50%, while there is no statistically significant variation in the number of rain‐days. Comparison of peak daily rainfall also confirms that intensities are increasing – whereas under average baseline conditions less than 10 days experienced rainfall totals greater than 100mm/d, with climate change more than 20 days exceeded 100mm/d. While this cannot be quantitatively linked to changes in hourly rainfall intensity it is a clear indication that rainfall intensities are likely to increase. In addition rainfall volumes are also expected to increase from 1,300 to 1,400mm/yr. These changes in rainfall can lead to a number of impacts: (1) damage to expansion join & knock‐on weathering of bearing through increased exposure to rain and sand, (2) structural damage to bridge and approach road; (3) reduced design life of components


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6.3 Connecting and approach roads Aside from the bridge structures, Components 1‐3 of the CMDCP also include a number of key pieces of road infrastructure. Primarily: (a) approach road for Cao Lanh bridge with a total length of 4.8km, (b) approach road for Vam Cong bridge with a total length of 2.75km, and (c) connecting roads between the two major bridges with a total length of 15.65km.

6.3.1 Sensitivity The main risks for road structures are increased rainfall intensity and flooding. Insufficient drainage

system combined with poor maintenance will reduce the usability of the road and also lead to increased scour in slopes.

The road embankment creates a significant dike against flooding. Although the bridge openings are designed wide to minimize this effect, the rise of flood level can cause increased scour and damage to road structures.

6.3.2 Road embankments & road foundations Roads associated with Components 1 and 2 are designed to accommodate 6 lanes of traffic in the future with a total cross‐sectional width of 30.6m and a design speed of 80km/hr. Embankment side slopes are1V:2H. Discussion with the detailed design team in March 2012 indicated that road elevations can reach up to 4.75m for some areas. Design life for the road embankments is 20‐30years, while the road foundations have a longer design life of 50years.

Sensitivity The critical sensitive of road embankments is the design minimum elevation of the road profile, which is established on:

(i) P1% flood event; (ii) 0.5m freeboard to accommodate overflow and wave action from upstream flood plain; and (iii) 0.3m freeboard nominally set to account for SLR.

In addition there is a 0.3m crossfall from the road centre line to the outer shoulder of the embankment. Changes in sea level rise and upstream rainfall and hydrology will lead to variation in water levels in the delta floodplain at the design 1 in 100 year event.

Exposure and impact The design water level for CMDCP embankments corresponds to water surface levels of 2.74masl in the floodplain areas and 2.7masl at the Cao Lanh site.

Floodplains: With climate change water levels at the site will increase resulting in a peak water level of 3.47masl. This is 0.61m above the current design embankment height. Under this event water levels in the floodplain vary along the road alignment, dropping to 3.1masl near the Hau River right‐bank and increasing to 3.6masl in the centre of the floodplain near the Lap Vo crossing (north of NR80). The inclusion of wind effects and wave propagation will see water levels rise a further 0.1m.

With climate change, there will be substantial periods of the year during the P1% when water levels will exceed design expectations:

Late August to Late November: 3 month period were water levels with climate change will exceed the historic P1% water levels (2.74masl)

Late August – Mid November: 35 days during which water levels exceed the design embankment elevation of 2.86masl

Cao Lanh site: With climate change water levels at the site will increase resulting in a peak water level of 3.44masl. This is 0.58m above the current design embankment height.


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With climate change, there will be substantial periods of the year during the P1% when water levels will exceed design expectations:

Under future P1% conditions in the Tien River channel with climate change, water levels will exceed the embankment height for one month, spread out between late August and mid‐November.

Mid August to Late November: 3.5 month period were water levels with climate change will exceed the historic P1% water levels (2.7masl)

Late August – Mid November: 33 days during which water levels exceed the design embankment elevation of 2.86masl

The impact of climate change on road embankments is significant. Apart from compliance issues in relation to design standards, there are a number of key technical impacts:

1) erosion of road embankments, 2) increased maintenance effort, 3) scour of road foundations, 4) pore pressure induced collapse and road subsidence, 5) water logging of road foundations, and 6) reduced macro‐stability of infrastructure

6.3.3 Drainage system & road culverts Road structures will include two main design solutions for drainage:

1) Surface drainage: Concrete curbs will be provided for embankments with elevations greater than 4m. Discharge points will be every 25m with rock rip rap at the outlet to protect embankments.

2) Flood conveyance: 28 culverts are proposed along the alignment of the connecting road ranging in size from 2mX2m box culverts to 3mX3m multi‐cell culverts. The number and sizing of culverts has been set to provide sufficient openings for conveyance of the P1% event and is currently being assessed by the detailed design hydraulic study.

Typically drainage system components will have a design life of 20‐25years.

Sensitivity The approach and connecting roads of the CMDCP bisect the freshwater floodplain of the Mekong Delta. Road embankments are therefore subjected to major forces from floodplain flow. The drainage system plays an important role in maintaining the functioning and integrity of the road system by reducing build up of flood water on the upstream side, preventing overtopping of the road surface and minimizing downstream erosion through the control of outlet flow rates. The drainage systems described above are therefore sensitive to increases in floodwater levels reducing the drainage efficiency and increase velocities through culverts.

In addition surface drainage systems for the road itself are also sensitive to changes in rainfall intensities which can effect the use of the road.

Exposure and impact Rainfall intensity: Projections for future rainfall with climate change indicate that the seasonal volume of rainfall is increasing by as much as 50%, while there is no statistically significant variation in the number of rain‐days. Comparison of peak daily rainfall also confirms that intensities are increasing – whereas under average baseline conditions less than 10 days experienced rainfall totals greater than 100mm/d, with climate change more than 20 days exceeded 100mm/d. While this cannot be quantitatively linked to changes in hourly rainfall intensity it is a clear indication that rainfall intensities are likely to increase. Increase in high intensity, short duration rainfall events can exacerbate short term flooding and reduce efficiency of drainage structures. Design rainfall intensity is


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140mm/h. The implications would be: (1) a greater risk of accident to drivers using road, (2) down‐time and reduced road usability, (3) increased erosion, and (4) increased maintenance effort

Flood levels and volumes: increase in wet season flooding due to increases in overbank flows and increased seasonal rainfall will put greater pressure on flood conveyance infrastructure. Current design is set to allow conveyance of the historic P1% event. With climate change the P1% event will increase in magnitude, with peak water levels in the floodplain rising from 2.74masl to 3.1‐3.6masl. Highest water levels will be experienced north of the intersection between the connecting road and NR80, while lowest levels will be contained to the vicinity of the Hau River left‐bank.

With climate change, water levels will remain above the design flood event for nearly three months from the end of August until the end of September, resulting in approximately one quarter of the design year spent with sub‐optimal drainage capacity.

In addition preliminary simulations for flow velocities through culverts indicate that flow speeds can reach 1.5‐4.0m/s with climate change.

The impact of reduced drainage efficiency includes: (1) damage to road structures through wind and wave action against the upstream face, (2) associated increased maintenance costs, (3) reduced design life, (4) potential for downstream scour/damage to dyke and irrigation structures and less sediment

6.3.4 River embankments & river bank In order to protect the approach road structure, embankments are proposed within the immediate vicinity of the crossing. Driven piles are used to support the bridge approach embankment. The exact design for surficial finishing of the embankment is not known to the VA study team, the Feasibility study due diligence report prepared by SMEC suggests three options for consideration during detailed design (SMEC, 2010). Typically river embankments have a design life in the order of 10‐25years.

Sensitivity The critical sensitivity of river embankments is to scour and erosional processes. If surface protection is poor then erosion can lead to bank collapse, exposure of the support piles and eventually destabilization of the approach road itself. If surface protection has been considered (e.g. geotextile reinforced rock mattresses or rip rap) scour impacts will concentrate at the footing of the embankment and weak points such as the grout between concrete slabs. Over time, the embankment material behind the casing will be slowly mobilized and eroded until the surface casing cracks, thereby exposing the supporting piles. The threat assessment indicates that the bridge site is located in a geomorphologically stable section of the Tien River, which has undergone minimal lateral migration since 1966. The site is immediately downstream of a channel constriction and future projections without climate change suggest limited erosion in the future.

Exposure and impact Wind induced wave energy: increased wave action caused by; (i) wider flood extent and river cross‐sections contributing to increased wind fetch and larger waves, (ii) deeper water with less wave energy dissipation and (iii) longer exposure due to prolonged flooding. Assessment of the influence of wind on wave energy was undertaken for the Tien River channel and was found to be small compared to flow related effect.

Changes in frequency & intensity of flood events, changes in sediment load and composition: Increased erodibility of river banks and embankments and instability of channel form due to:

1) Increases in river and flood return period: With climate change projected return periods for given events will decrease. This will affect typical flood flows like the 1 in 2 year event (often used to define the threshold of geomorphic effective flows c.f. Leopold et al, 1968) as well as extreme flows such as the historic 1 in 100year event, which will become a 1 in 20‐30year event with climate change


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2) Increases in flood flow velocities: For river embankment stability flow velocities can be used to give an indication of the erosion potential for channel flow. With climate change in‐channel mid‐stream flow velocities in the Tien River will increase by +0.5m/s, with surface velocities reaching close to 5m/s during the P1% flood, and near bed velocities reaching 0.9m/s. Bed velocities are greatest near the left bank of the Tien. Increases in velocity will increase the stream power and hence energy available for geomorphological work. Velocities in the Hau River are much greater than the Tien with near bed velocities reaching near 1.0m/s across the channel cross‐section

3) Greater seasonal variability in river water levels exacerbating erosion of sand lens in the riverbank. Assessment of the hydrograph for Kratie under typical conditions demonstrates both an increase in wet season flows and a reduction in dry season flows. This will compound existing problems of bank instability where banks have been degraded or poorly protected.

4) Reduced sediment load inputs combined with increased sediment transport capacity, and reduction in sediment grain size composition and resulting increase in channel material mobility: The VA study did not look at changes to sediment dynamics directly. However, previous studies indicate that upstream hydropower development will have a dominating influence on sediment dynamics with between 50‐75% of the current Mekong sediment load being trapped by the reservoirs proposed in Yunnan Province, the Lower Mekong mainstream and the tributary projects of Vietnam, Cambodia and Lao PDR.

The implications of these changes are: (1) increase erosion of river banks and scour at the foot of river embankments, (2) river bank collapse, and (3) exposure of pylons.


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7 CONCLUSIONS AND RECOMMENDATIONS

The bridge and road structures of the Central Mekong Delta Connectivity project are located in the floodplain of one of Southeast Asia’s largest rivers – the Mekong – and under the dual influence of fluvial and coastal processes. Two cable stayed bridges with spans of 150‐350‐150and 190‐450‐190 are planned to cross the two major distributaries of the Mekong connected by 15.65km of road and some 26 smaller bridge crossings. Soil structures are weak, river banks are mobile and flooding is an annual phenomena. In addition, the Mekong Basin and Vietnam have been identified amongst the most vulnerable in the world to climate change. Sea level rise, increases in catchment precipitation and stronger cyclones, coupled with the shifts and interaction of two monsoon regimes are changing the hydroclimate conditions that have been used to design the bridge and road infrastructure.

The implications of climate change for the CMDCP infrastructure are complex, however the nature and trends in climate change threats are clear. The assessment process has used a multi‐model ensemble of six GCMs, two IPCC scenarios, statistical downscaling techniques and a suite of modelling tools custom built for the Mekong over the past 15years to build an evidence base of climate change vulnerability. Results between GCMs and scenarios vary and study findings have been developed to reflect these ranges and select conservative estimates of future change. A summary of the key threats from climate change are presented in Section 7.1 below.

These threats have been linked to key components off the bridge sub‐ and super‐structures as well as the connecting and approach roads. Assessments were made to understand the sensitivities of these components to variation in hydroclimate parameters. These vulnerabilities are summarised in Section 7.2 below. Findings from the assessment have been streamlined to focus on the potential issues that may require adaptation response during the design, maintenance or refurbishment phases. However, the assessment in the above report also provides confidence on which components of the design are not significantly vulnerable to climate change.

It is neither economical nor technically possible to design infrastructure today that will remain 100% proofed against all future climate conditions for the next 100years – but the risk can be reduced. Adaptation is a continuous process of assessment, implementation and re‐evaluation which should continue throughout the project’s life. Adaptation response to climate change vulnerability can be initiated at any stage during the project life‐cyle, however, it is easier and cheaper to plan for adaptation from the outset. It is important that actions and decisions made now keep open the opportunity for future response so that the long term benefits of the infrastructure continue to accrue to the road users and Government of Vietnam.

7.1 Summary of Key findings on climate change threats

7.1.1 Temperature By 2050, Annual average maximum temperature in the Lower Mekong Basin will increase by between two

to three Deg C, with considerable variability throughout the basin.

At the project site, year round maximum daily temperature is projected to increase by an average of 2.3

Deg C (1.5‐3.0 Deg C). The largest increases are projected for the months of May – August exacerbating

hot weather at the start of the wet season.

Under typical baseline conditions max daily temperatures do not exceed 35Deg C. With climate change

between 15‐45% of the year will see temperatures exceed 35Deg C.

7.1.2 Rainfall

The impact of changes on precipitation manifest as two issues: (i) changes in rainfall‐runoff regime and

hence changes in upstream discharge arriving at the delta, and (ii) changes in direct precipitation at the

project site.


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Total annual precipitation is predicted to increase in the LMB by an average of 162mm by 2050, while

maximum annual precipitation is expected to increase by 933mm/yr. The implication is that variability is

increasing with wet years are becoming wetter.

The vast majority of the increase in rainfall will occur during the wet season affecting the flood hydrology

of the Mekong River and ultimately the water levels in the Mekong floodplain during the flood season

including an average 8% increase in peak rainfall during October.

7.1.3 Mekong hydrology – typical events

Changes in catchment rainfall will increase seasonal discharge in the Mekong River. Leading to four key

changes in the hydrological regime:

(i) Increase in flood magnitude and volume: Climate change will increase the flow during the flood

season and the size of the flood peak.

(ii) Increase flood duration: Across all stations, Climate change will increase the duration of the flood season.

(iii) Shortening of transition seasons and onset of flooding: Climate change will shorten the transition seasons at all stations and increase the rate of increase of discharge. This will accelerate the rate of onset of flood conditions.

(iv) Increased variability of the hydrological regime: Flood regime is becoming more variable with a greater range experienced for peak annual discharge.

7.1.4 Mekong Hydrology – extreme events Peak flow flows at Kratie are likely to increase in magnitude (see table below).

A +0.3m increase in design elevation corresponds to a max design level of 3.16masl. Under future climate

change conditions this is likely to correspond to a return period in the order of 1 in 30 years.

Return period Historic flow at Kratie (m3/s)

Range of predicted flow at Kratie with CC (m3/s)

Predicted flow at Kratie with CC (m3/s)

P5% 66,928 70,262 – 83,581 74,889

P1% 77,597 82,862 – 102,586 89,290

7.1.5 Sea Level Rise Actual rates of sea level rise are 80% faster than the mean predictions of the IPPC and are equal to or

exceeding the upper boundary of the projection envelope from all IPCC results:

Rates of sea level rise along the coastlines of the earth’s continents are highly dependent on meso and

regional scale dynamics of the ocean system with large variability within and between oceans and

Vietnam is considered to be highly exposed.

The VA study assesses SLR using the highest official estimate at the 2100 time slice – consistent with the

official scenarios released by MONRE: SLR = 1.0m.

There is an approximate linear correlation between SLR rise and the rise in water levels at Cao Lanh

during flood conditions, where the increase in Cao Lanh WL ~ 0.54*SLR.

7.1.6 Storms, cyclones and storm surge

Over the past three decades, there has been a substantial increase in the strength of cyclones, and a near

100% increase in the proportion of cyclones which are classified severe, compared to those classified as

weak.


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Climate change will bring a significant increase in the MPI (measure of intensity) for cyclonic events with

estimates that MPI would increase by 3‐5% for each degree increase in mean annual temperature.

Broadly speaking the regions of the Pacific Ocean where cyclones form is not expected to change

significantly with climate change and it remains unclear whether cyclones will change track in response to

CC.

7.1.7 Hydropower and non‐climate drivers Hydropower development in the Mekong Basin is increasingly rapidly with some 126 projects either

identified or under some form of development.

Hydropower will affect the hydrological regime during typical years as projects store wet season flows for

release in the dry season.

However, recent experience and simulations in the basin indicates that hydropower is not likely to have a

major influence on extreme flood events as projects optimized for electricity production will need to pass

peak flows as a matter of safety.

7.1.8 Typical flood events Under baseline conditions, flooding at the project site remains uniformly below 1.5masl.

With climate change floodplain dynamics are not expected to change significantly but there will be an

increase in the flood water levels. Most of the connecting road will be exposed to water levels between

1.5 – 2.6masl.

The two bridges are located at sites where water levels remain relatively stable under interannual

fluctuations in flooding, such that for average floods water levels at Cao Lanh and Vam Cong vary by less

than one metre

7.1.9 Extreme flood events

Floodplain With climate change water levels at the site will increase resulting in a peak water level of 3.47masl. This

is 0.61m above the current design embankment height.

Flood water surface elevations are not uniform along the road alignment and are lowest in the vicinity of the Hau River (~3.1masl) and highest near the intersection of the road with Lap Vo (3.6masl)

Under future P1% conditions in the floodplain with climate change, the water levels will exceed the

embankment height for one month between late August and mid‐November.

Cao Lanh river water levels Design embankment height of 2.86masl is sufficient to accommodate the historic P1% flood (2.7masl) and

some 0.22m above the year 2000 flood level.

With climate change water levels at the site will increase resulting in a peak water level of up to 3.1 to

3.6masl. This is 0.6m above the current design embankment height.

Under future P1% conditions in the Tien River channel, water levels will exceed the embankment height

for one month, between late August and mid‐November.

Under the baseline P5% event:

(i) Design navigation clearance of 2.6masl is sufficient to accommodate for the historic P5% flood

(2.58masl) and approximately equivalent to the year 2000 flood level


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(ii) With climate change water levels at the site will increase resulting in a peak water level of

3.33masl. This is 0.73m above the current design level.

(iii) The P5% water level with climate change will exceed the design clearance for more than two

months spread out between mid‐August and late‐November

A summary of changes to water levels is presented below:

Baseline CC (1D model) CC (3D model) Increase in WL(m)

Floodplain P1% Water Level (masl)

2.74 3.47 3.1 – 3.6* +0.6

Cao Lanh 2.7 3.44 3.4 + 0.7

* Range reflects the variability in WL along the length of connecting road (highest in the centre and lowest near the Hau River)

Flow velocities With climate change, surface velocities peak near 5m/s in the Tien River channel and nearly 6m/s in the

Vam Cong in the last half of September, corresponding to increased of +0.2m/s and +0.5m/s at Cao Lanh

and Vam Cong respectively.

Flow speeds along the road alignment will increase by 0.5 to 0.8m/s with climate change

With climate change, bed velocities at the Cao Lanh site are greatest near the left‐bank of the channel and

approach 0.9m/s

With climate change, bed velocities at the Vam Cong site uniformly approach 1m/s along the channel

cross‐section.

Wind is not a major factor in determining flow velocities at the project site. However winds of 15m/s

could induce waves of 0.33‐0.42m to act against the road embankment structure

7.2 Summary of Key findings on climate change vulnerability

7.2.1 Road embankments The impact of climate change on road embankments is significant and represents the critical issue requiring adaptation response. Without revision of the design height the future P1% event will raise water levels some 0.1m above the embankment freeboard presenting a situation of risk. Impacts from P1% water levels detailed in this report are listed below:

1) erosion of road embankments and scour of road foundations, 2) water logging of road foundations, pore pressure induced collapse and road subsidence 3) reduced macro‐stability of infrastructure, and 4) associated increase in maintenance effort,

7.2.2 Drainage system and road culverts Linked to the impact of climate change on embankments is the issue of drainage efficiency for floodplain through‐flow and surface drainage:

1) The impact of reduced drainage efficiency includes: (a) damage to road structures through wind and wave action against the upstream face, (b) associated increase in maintenance costs, (c) reduced design life, (d) potential for downstream scour/damage to dyke and irrigation structures and less sediment

2) The Impact of reduced surface drainage: Increase in high intensity, short duration rainfall events can exacerbate short term flooding and reduce efficiency of drainage structures. The implications include: (a)


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a greater risk of accident to road users (b) down‐time and reduced road usability, (c) increased erosion, and (d) increased maintenance effort

7.2.3 Foundation slabs, pylons and abutments: 1) Scour to foundation of the bridge: Changes in river hydraulics will enhance scouring efficiency at pylons,

foundation slabs and other components within waterways, reducing support which can in turn compromise the superstructure. The near left‐bank region of the channel cross‐section will be most susceptible to scour.

2) Damage to support piles: There is the potential for increased erosion efficiency at the Tien left‐bank. Erosion can in the medium term lead to exposure of support piles which are currently not designed to be in the river channel. The increased scouring is a serious risk which should be considered in detailed design

3) Increased risk of ship collision with pylon/foundation due to change in location of the clearance relative to the structure.

7.2.4 Free slide bearings and expansion joints 1) Bearings: Increases in the average and range of temperatures will lead to: (a) asymmetric movement with

reduced range for expansion but increased range for compression, (b) expanded friction coefficient, leading to reduced design life and increased future replacement costs.

2) Expansion joints: With climate change the likelihood of collision between the bridge and approach roads is increased, and that of over‐stretch reduced as the daily temperature range shift to a hotter zone.

3) Expansion Joints: A shift in mean temperature could: (a) accelerate ageing through hardening, UV/solar deterioration, and (b) cause asymmetric movement with reduced range for expansion but increased range for compression, increasing potential for damage, failure, or reduced design life and increased replacement cost

4) Expansion joints: changes in rainfall can lead to a number of impacts: (a) damage to expansion join & knock‐on weathering of bearing through increased exposure to rain and sand, (b) structural damage to bridge and approach road; (3) reduced design life of components

7.2.5 Navigation clearance 1) The P5% water level with climate change will exceed the design clearance for more than two months

(63days) between mid‐August and late‐November. Because the clearance is large (37.5m) the expected future water level rise will not cause major problems for small and medium‐sized vessels, but will impact the largest vessels predicted to use the river channel between the coast and Phnom Penh.

2) For the smaller bridges, water levels associated with the future P5% will see the majority of component 2 experience water levels of up to 2.6masl; The navigation clearance in these small channels should not be significantly affected by this.

7.2.6 Bridge deck and stay cables 1) Potential impacts from variation in ambient temperatures could lead to: (a) damage due to deflection of

the bridge deck, (b) cracking of deck surface, (c) partial loss of navigation clearance. 2) Increase in high intensity, short duration rainfall events will exacerbate short term flooding and

uncontrolled floodwater conveyance issues as well as lead to damage to deck & road surface and increased maintenance effort.

3) Increase in frequency and magnitude of major gusts and storm events resulting in sustained loading at high wind speeds can cause vibration, oscillation, vortex effects and galloping. In addition wind‐ and rain‐induced vibration of stay cables can combine with these other factors to induce dynamic effects such as


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galloping. The potential impact includes: (a) resonance‐induced structural damage, (b) fatigue of key supports in superstructure.

4) Significant rises in mean temperature will induce different rates of elongation between stay cables and deck, causing changes in the cable loading and deflection of the bridge deck. Potential impacts include: (a) damage due to deflection of the bridge deck, (b) cracking of deck surface, (c) partial loss of navigation clearance.

5) Increases in high intensity, short duration rainfall events will exacerbate vibration of stay cable, resulting in increased fatigue to stay cables and reduced design life

6) Bridge deck: High intensity, short duration rainfall events can exacerbate short term flooding and reduce of drainage structures. The resulting impacts include: (a) accident to drivers using road, (b) down‐time and reduced road usability, and (c) increased maintenance effort.

7.2.7 River embankments and river banks 1) Increases in river and flood return period: With climate change projected return periods for given events

will decrease. This will affect typical flood flows like the 1 in 2 year event (often used to define the threshold of geomorphic effective flows c.f. Leopold et al, 1968) as well as extreme flows such as the historic 1 in 100year event, which will become a 1 in 20‐30year event with climate change.

2) Increases in flood flow velocities: Increases in velocity will increase the stream power and hence energy available for geomorphological work. Increases in erosion issues are likely to be more important for the Hau River channel than the Tien River Channel.

3) Greater seasonal variability in river water levels exacerbating erosion riverbanks. Increasing variability in flows will compound existing problems of bank instability where banks have been degraded or poorly protected.

4) Reduced sediment load inputs combined with increased sediment transport capacity, and reduction in sediment grain size composition and resulting increase in channel material mobility: The VA study did not look at changes to sediment dynamics directly. However, previous studies indicate that upstream hydropower development will have a dominating influence on sediment dynamics with between 50‐75% of the current Mekong sediment load being trapped by the reservoirs proposed in Yunnan Province, the Lower Mekong mainstream and the tributary projects of Vietnam, Cambodia and Lao PDR.

The above analysis is drawn assuming flood protection in the surrounding areas but not locally at the connecting road site. However, the actual flood protection plans and implementation can change affecting dramatically the road design.

7.2.8 Recommendations The key recommendations of the VA study are:

1) The design height for embankments should be raised by 0.6m to 3.46masl in order to account for changes in the size of the P1% event. Post‐construction elevation of the embankment in the future will be more costly than action now.

2) Funding for the incremental cost of raising the embankments should be sought from global climate funds. There is a robust and credible evidence base to justify the incremental risk climate change poses to the embankments of the Central Mekong Delta Connectivity Project and sufficient to apply for grants.

3) Navigation clearance, though impinged by larger magnitude P5% events should be sufficient for most vessel passage.


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4) Climate change should be incorporated into detailed design technical investigations. A number of detailed studies required by the detailed design team should take into account climate change, including:

(i) Modelling of culvert sizing and alignment (ii) determination of expansion joint, stay cable and bearing design (vis‐a‐vis temperature ranges) (iii) Riverbank erosion studies at the bridge sites

5) Additional study is required to improve understanding of extreme events: A key limitation of this study is the correlation between peak discharges at Kratie and water levels at the project site. In this study extreme event frequency analysis has been calculated based on the conventional approach of instantaneous peak discharge at Kratie station. Analysis by the detailed design team (Faulkner, 2012) has shown that the water levels at Cao Lanh show better correlation with the flow volume in the peak flow month than with the instantaneous peak discharge, however, even this correlation with 1‐month flood volumes can be improved. The purpose of this additional work is to better understand the response of water levels to changing flows.

6) Additional study is required to improve understanding of overland flood flow dynamics. Rapid expansion of agricultural and transport infrastructure in the delta is suspected to have changed the floodplain dynamics of the delta‐system. Current models do not have up‐to‐date representations of delta infrastructure, which is affecting their ability to simulate the flow dynamics. The purpose of this additional work is also to better understand the response of water levels to changing flows.

7) The climate change assessment of the Central Mekong Delta Connectivity Project should be expanded and integrated into the provincial context. During the Inception Mission the provincial government authorities requested that findings and lessons learnt from the study be shared with provincial department staff to improve provincial response to climate change. It is recommended that workshops be conducted with Mekong Delta provinces to share findings and discuss implications for existing and planned provincial roads.

8) There is a need for the Government of Vietnam and the ADB to assess climate change implications for other key transport infrastructure in the Delta. This process should be implemented as part of the Ministry of Transport’s National Target Plan for Climate Change Response.


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8 REFERENCES

ADB. 2011. Guidelines for climate proofing investment in the transport sector: Road infrastructure projects. Mandaluyong City, Philippines: Asian Development Bank, August 2011

Cochran, I. 2009. Climate Change vulnerabilities and adaptation possibilities for transport infrastructure in France. Climate Report 18: Research on the economics of climate change. Mines Paris Tech and Mission Climat of Caisse des Dépôts, Paris, September 2009

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Table 21: Variability of annual hydrographs at Kratie under baseline, CC‐2050 and CC‐2100 events

max (obs) ave (obs) min(obs) max (BL) ave (BL) min(BL) max (2050)

ave (2050) min(2050) max (2100)

ave (2100)

min(2100)

ave 21,037

13,362

7,494

20,805

12,618

7,505

25,219

15,007

9,600

23,574

14,467

8,867

max 59,035

39,870

29,260

94,151

41,299

27,205

144,676

49,473

29,396

117,725

43,524

28,369

min 2,360

2,031

1,559

2,023

1,624

1,092

4,958

4,630

3,934

4,567

4,332

3,934

20th percentile

3,532

2,561

1,994

3,161

2,239

1,425

6,110

5,126

4,377

5,416

4,774

4,277

80th percentile

45,063

28,240

13,598

39,595

25,767

14,223

43,036

27,300

15,915

42,774

27,420

15,368

Table 22: Assessment of changes to return flow magnitude for Kratie

Return period

KRATIE (baseline (1924‐2009)

KRATIE ‐ CC (GIA)

KRATIE ‐ CC (MPA)

KRATIE ‐ CC (CMA)

KRATIE ‐ CC (CNA)

KRATIE ‐ CC (MIA)

KRATIE ‐ CC (NCA)

KRATIE – CC (Combined)

2yr 49,885

50,016

53,223

51,944

50,950

50,134

53,232 59,786

5 yr 57,304

58,876

66,439

62,474

59,610

58,896

64,551 75,202

10 yr 62,216

64,742

75,188

69,445

65,344

64,697

72,045 85,408

20 yr 66,928

70,369

83,581

76,133

70,844

70,262

79,233 95,198

100 yr 77,597

83,110

102,586

91,276

83,297

82,862

95,511 117,367

1000 yr 92,698

101,144

129,486

112,710

100,924

100,696

118,551 148,745


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