sedawgyi water resources/irrigation system simulations

HAARLEM HYDRAULICS & TECHNICAL UNIVERSITY OF DELFT

Sedawgyi Water Resources/Irrigation system simulations

A study into the water resources and flood risk of Mandalay basin with RIBASIM

Sebastiaan Quirijns

1387272

11/14/2014

Supervisors

TU First: Nick van der Giesen

TU Second: Martine Rutten

Company: Peter Kerssens

Haarlem Hydraulics

A study performed by Sebastiaan Quirijns in order to accomplish his internship at Haarlem Hydraulics for the Technical University of Delft.

Internship Report by Sebastiaan Quirijns Sedawgyi Water Resources/Irrigation system simulations

Haarlem Hydraulics & Technical University of Delft | Summary 1

Thank you all

For helping me by sharing your knowledge,

guidance and resources.

For giving me this amazing experience

Peter J.M. Kerssens

Gary Moys

Wil van der Krogt

Uu Tin Oo

Htet Wint Naing

PM- Group

Safege

MMiC

Mandalay City Development Committee

Irrigation Department, Mandalay (and Main Office)

Asian Development Bank

Agence Française de Développement

Technical University of Delft

Deltares

E.A.

Summary During three months a study has been done by Sebastiaan Quirijns into the modelling of

the water resources of the Sedawgyi Irrigation Network. In this study the feasibility of multiple

scenarios have been modelled regarding the water resources system efficiency. The modelling of

this basin has been executed with RIBASIM (River Basin Simulation Model). A modelling

program made by ‘Deltares’. The setup of the study is done by the ASSECR-method, in

chronological order this is analyses, synthesis, simulation, evaluation and last is conclusions and

recommendations.

The current situation in the Sedawgyi basin is the low efficiency of the water usage in the

water resources system. During the rainy season lots of water gets released to avoid spillage.

Not all this released water can be used in the agricultural areas, so the water flows towards

Mandalay and causes serious floods in the city. On the other hand the during the drought periods

the water is accumulated in the basin and there is not enough water for all the demand. Another

issue in the area is the flood risk caused by the Shan Hills to the east of Mandalay. Precipitation

in the catchment area flows towards Mandalay city and causes floods eastern parts of Mandalay.

Scenarios are based upon actual ideas or designs by ‘ADB PPTA’ and ‘M.C.D.C.’. Although

the ‘ADB PPTA’ is already in a further stage, the modelling results are needed to give support to

the decisions made by ‘ADB PPTA’.

The scenarios are the:

1. ‘Base Case’; In this case the current situation is shown.

2. ‘Do Nothing Case’; This case is similar to the ‘Base Case’, but it is now including long term

effects and visualizes the issues if nothing is done in 2040.

3. ‘ADB Reference Case’; Here all future plans of ‘ADB PPTA’ are included in the model for

2040.

4. ‘SUDS scenario’; Increasing the return flow to the surface water and reduce flood risk in

the city in 2040, in order to increase quality of life in Mandalay.

5. ‘Capacity Training Agriculture scenario’; By increasing the irrigation efficiency a higher

production yield can be achieved with less supply.

6. ‘Secondary Open Channel’; The purpose of this secondary channel is to reduce flood risk

by rainfall in the Shan Hills. The water is than redirected as a new inflow into the

Sedawgyi water resources system.

7. ‘Separation of water resources system’; By dividing the water resources for public water

supply for Mandalay and irrigational purposes more water is available for irrigation

coming from Sedawgyi dam.

After the simulations it was clear that in the ‘Do Nothing Case’ in 2040 some sincere

issues were raised in water availability for both PWS and irrigation. The climate change effects

and other long term autonomous effects which were included in the 2040 models, seriously

reduce the total water availability by the Sedawgyi Reservoir. For all the other scenarios the

results were evident that it is not possible with the current operational settings to combine PWS

and irrigation. This is in line with the expectations of ‘ADP PPTA’. In order to raise total water

usage efficiency the water resources system has to be separated and combined with increased

irrigation efficiency.

For achieving this modelling results in real life ,’ M.C.D.C’ is advised to construct a separate

system for PWS, such as water treatment plans and retention ponds. Also increase the capacity


Haarlem Hydraulics & Technical University of Delft | Summary 3

of the farmers to achieve higher production yields. This can be done by investing in new

methods and material for the farmers, who now still apply old fashioned methods for irrigation.

List of abbreviations Abbreviation Description ADB Asian Development Bank AFD Agence Francaise Developpement DNC Do Nothing Case ID Irrigation Department DY Distributaries ETo Relative Evapotranspiration MCDC Mandalay City Development Committee MMc Mandalay Main canal MUSIP Mandalay Urban Services Improvement

Project NRW Non Revenue Water PPTA Project Preparation Technical Assistance PWS Public Water Supply SIN Sedawgyi Irrigation Network SUDS Sustainable Urban Drainage System SUI Secondary Uncontrolled Inflow SWRS Splitting the Water Resources System SRWRS Sedawgyi Reservoir Water Resources System ts Time step WRS Water Resources System Table 1 List of abbreviations


Haarlem Hydraulics & Technical University of Delft | List of conversions 5

List of conversions 1 inch [in] 0.0254 [m 1 foot [ft] 0.3048 m 1 meter [m] 39.37 inch [m] 1 meter [m] 3.28 feet [ft] 1 square foot [ft2] 0.0929 [m2] 1 acre 4046.86 [m2] 1 acre 0.404686 [ha] 1 square meter [m2] 10.76 square feet [ft2] 1 square meter [m2] 0.00024 acres 1 hectare [ha] 2.47 acre 1 square miles [sq-miles] 259 hectare [ha] 1 hectare [ha] 0.003861 square miles [sq-mil] Volume 1 cubic foot [ft3] 0.0283 m3 1 cubic meter [m3] 35.315 cubic feet [ft3] 1 acre feet 0.0012335 Mm3 1 acre feet 1233500 m3 1 m3 0.000811 Acre feet [Ac-ft] Flow 1 cubic feet per second (Cusec) 0.02832 cubic meter per second (m3/s)

Contents Summary................................................................................................................................................................................ 2

List of abbreviations ......................................................................................................................................................... 4

List of conversions ............................................................................................................................................................. 5

1 Introduction ................................................................................................................................................................ 9

1.1 Project description ......................................................................................................................................... 9

1.2 My objective ................................................................................................................................................... 10

1.3 Scope of the project .................................................................................................................................... 10

1.4 Set up of the study ....................................................................................................................................... 12

1.5 Notes for reading the report ................................................................................................................... 12

1.5.1 Personal Notes .................................................................................................................................... 12

1.5.2 Files on Appendix CD ........................................................................................................................ 13

2 Initial Analysis of the project area .................................................................................................................. 14

2.1 Project Area: Mandalay region ............................................................................................................... 14

2.1.1 Mandalay and Sedawgyi Irrigation Network area ................................................................ 14

2.2 Water Resources .......................................................................................................................................... 24

2.2.1 Supply ..................................................................................................................................................... 24

2.2.2 Demand .................................................................................................................................................. 26

2.2.3 Sedawgyi Irrigation area ................................................................................................................. 29

2.3 Civil objects and canals ............................................................................................................................. 30

2.3.1 Sedawgyi Dam ..................................................................................................................................... 30

2.3.2 Canals ...................................................................................................................................................... 30

2.4 Data Analysis ................................................................................................................................................. 31

2.4.1 Data gaps ............................................................................................................................................... 31

2.4.2 Flawed Data .......................................................................................................................................... 31

2.4.3 Summary of causes of the errors ................................................................................................. 32

2.4.4 Small conclusion about data errors ............................................................................................ 32

2.5 Green Cities .................................................................................................................................................... 32

2.5.1 Relation to Mandalay/Sedawgyi Irrigation Network modelling .................................... 32

3 Introduction to RIBASIM .................................................................................................................................... 33

3.1 Basics of RIBASIM ........................................................................................................................................ 33

3.2 Applied model of the Sedawgyi Irrigation Network Model........................................................ 34

3.3 Definitive model ........................................................................................................................................... 34


Haarlem Hydraulics & Technical University of Delft | List of conversions 7

4 Scenarios ................................................................................................................................................................... 35

4.1 Long term effects ......................................................................................................................................... 35

4.2 ADB PPTA Plans ........................................................................................................................................... 36

4.3 Design criteria ............................................................................................................................................... 36

4.4 Constructing the scenarios ...................................................................................................................... 37

5 Simulations with RIBASIM ................................................................................................................................ 39

5.1 Base Case ......................................................................................................................................................... 39

5.1.1 Measured data ..................................................................................................................................... 39

5.1.2 Calibration............................................................................................................................................. 39

5.2 Do Nothing Case ........................................................................................................................................... 41

5.3 ADB Reference Case .................................................................................................................................... 41

5.4 SUDS .................................................................................................................................................................. 41

5.5 CTA..................................................................................................................................................................... 41

5.6 SOC ..................................................................................................................................................................... 42

5.7 SWRS ................................................................................................................................................................. 42

6 RIBASIM results ..................................................................................................................................................... 43

6.1 Sedawgyi reservoir volume ..................................................................................................................... 43

6.2 Reservoir spillage ........................................................................................................................................ 44

6.3 Net flow in water resources system ..................................................................................................... 45

6.4 Generation of hydropower ...................................................................................................................... 46

6.5 Actual cultivation areas ............................................................................................................................. 47

6.6 Supply/demand ratios for cultivations .............................................................................................. 48

6.7 Irrigation efficiency .................................................................................................................................... 49

6.8 Resources for PWS ...................................................................................................................................... 50

6.9 Continuous flow in the moat canal ....................................................................................................... 51

7 Conclusion and Recommendations ................................................................................................................ 53

7.1 Conclusions .................................................................................................................................................... 53

7.1.1 Overall ..................................................................................................................................................... 53

7.1.2 Scenarios ................................................................................................................................................ 53

7.1.3 Miscellaneous Conclusions ............................................................................................................ 55

7.1.4 Final Conclusion ................................................................................................................................. 55

7.2 Recommendations ....................................................................................................................................... 56

7.2.1 Final recommendation ..................................................................................................................... 56

8 Evaluation of applied methods ........................................................................................................................ 57

9 Assumptions ............................................................................................................................................................ 58

10 Recommended topics for further investigation ........................................................................................ 58

11 Bibliography ............................................................................................................................................................ 59

12 List of figures ........................................................................................................................................................... 61


Haarlem Hydraulics & Technical University of Delft | Introduction 9

1 Introduction On request of the Burmese government (Mandalay City Development Committee) a

project is performed in Mandalay in the context of the “Mandalay Urban Services Improvement

Project” (MUSIP). For this project a joint venture has been formed between two consultants PM-

group and Safege. The financing of the project is provided by the Asian Development Bank and

Agence Française de Développement. MMiC is a local sub-contractor who mostly assists by

providing local knowledge and connections in Myanmar as well as domestic experts. The PM-

group is an international consultancy firm who hires engineers, such as Peter J.M. Kerssens, the

owner of Haarlem Hydraulics, who works on the project as an “Urban Drainage and Flood

Management”-specialist, and also is the supervisor of Sebastiaan Quirijns. As a component of

MUSIP a study was performed regarding water supply from Sedawgyi dam/reservoir to

Mandalay city and Sedawgyi irrigation area. This study was executed from the end of July until

the end of October by Sebastiaan Quirijns at the ADB PPTA office in Mandalay. The modeling of

the water resources in the selected project area was done with the program “RIBASIM” provided

by “Deltares”. An extensive training-course for the RIBASIM program was given by Wil van der

Krogt, a RIBASIM specialist at Deltares.

This study and report is done by Sebastiaan Quirijns to finalize his internship at Haarlem

Hydraulics and the Technical University of Delft. An internship of at least two months has to be

performed during the master phase of Civil Engineering at the Technical University of Delft. The

faculty of Civil Engineering values an internship with 10 ECT’s, which is equivalent to ca. 280

working hours.

1.1 Project description

The study performed for MCDC is done in the context of the Project Preparation and

Technical Assistance (PPTA) for Mandalay. As mentioned before the project is to improve the

urban services in Mandalay, such as drainage and flood protection, solid waste handling, waste

water treatment and water resources for public water supply and irrigation, but also social

surveys and capacity building.

The purpose of this component is to simulate the water demand and supply of the

Sedawgyi irrigation area and Mandalay City. In order to aid the ADB PPTA, this report

contributes by visualizing the problems that occur and testing multiple scenarios for

improvement of the water usage efficiency.

Mandalay has a monsoon climate, with a clear dry season and rain only during the rainy

season. Most of the water supply is controlled by the Sedawgyi Multipurpose Dam. The water is

accumulated in the Sedawgyi Lake for irrigational use and hydropower. Problems have risen

that there is too much spillage of water during the rainy season, while during the dry season

there is a shortage. The secondary function of the dam is generation of electricity by producing

hydropower. There is currently no clear operational combination of both functions regarding

the downstream water and power demand. This results in a very low efficiency of water usage

efficiency. So logically the goal of this research is:

“Modeling the water resources in the Mandalay region in order to raise the water usage

efficiency”

In this respect there is a secondary risk which needs to be analyzed. Due to the heavy

rainfall, in the mountains in the east of Mandalay, a lot of water will flow towards the city. A

potential solution which needs to be studied, in order to lower the flood risk, is a side channel

around Mandalay, i.e. a collector drain at the foot of the Shan mountain range, or a second

reservoir. However, in RIBASIM it is not possible to calculate flood waves or water level based

on the elevation of the area. Consequently, the only way to look into this option is by considering

the potential discharge capacity for flood waters.

1.2 My objective

As mentioned before, during this internship I have studied the water resources of the

Mandalay region and processed the data in RIBASIM. The data were provided by the Mandalay

City Development Committee (MCDC), and the local Irrigation Department (ID). When the data

were not available a field research was executed.

The water supply to the area of interest is regulated by the Sedawgyi dam. The primary

function of this dam is for irrigation use, and secondary is the hydropower production. At the

moment too much water is lost, because it is not used by irrigation or the city. The demand and

supply were modeled in the RIBASIM program. In this way a more efficient use can be simulated

and may serve to get better insight into the project area and the water utilization. As a result the

consultants can give better advice to MCDC. A second part of the research was to investigate the

possibilities to lower the flood risk by constructing a side channel. Multiple scenarios were made

in RIBASIM to analyze the response of the system.

1.3 Scope of the project

In this research some boundaries have to be set. The outer limits of the project area are

the Ayeyarwaddy River to the west, Sedawgyi Lake to the north, the Shan Hills on the east, and

the Dokhthawaddy River in the south. See figure 1 on the next page for a clear figure of the

boundary limits.

RIBASIM is a model that simulates the demand and supply in a surface water system. This

is built up of nodes that are either supply or demand, and links connecting the nodes. When a

demand node sends a request to the supply node a water allocation is made, based on priorities

and the total amount of water available.

Regarding the scope of research in the water resources system, all the water supply is

controlled by Sedawgyi Dam. Two catchment areas are located in the Shan Hills and are

simulated as a time series due to precipitation. Next is that Mandalay city is modelled as three

nodes, considering Public Water Supply (PWS), Moat flow around the Royal Palace, and the Non

Revenue Water (NRW). NRW is water losses in the distribution system of Mandalay. The

irrigation canals modelled are the primary and secondary canals of the Sedawgyi irrigation

system. Looking at the agricultural area, multiple farms are clustered into one area. This is no

loss of accuracy since it is possible to assign multiple crop sorts to one area. Finally, the ground

water flow is excluded as an inflow, but taken into account as an outflow (drainage) in the

irrigation area.

As mentioned before, it is not possible in RIBASIM to calculate flood waves or putting an

elevation (water levels) and/or slopes into the system. Another difference with RIBASIM is that

the flow in the links is determined by the demand nodes and allocation settings.



Figure 1 Boundary limits © September 2014, ADB PPTA, Mandalay

1.4 Set up of the study

The objective of the research is to visualize the water demand and supply of the Mandalay

area in Myanmar. This will be done for the current situation called ‘Base Case’ and for the future

situation in 2040 in which a variety of scenarios was simulated, such as climate change or a

secondary controlled inlet. All these scenarios were compared with the reference case, the “ABD

Reference case’ in 2040. The latter case is characterized by the urban development of Mandalay,

i.e. autonomous developments regarding population growth, urbanization, and the construction

of industrial and residential compounds.

All required information was provided by MCDC, the Irrigation Department or by the ADB

PPTA- group. When the information is not available, the information was collected in the field.

All the data for modelling were defined by RIBASIM and were implemented in the model.

After the introductions of this report multiple analyses follow those were necessary for

retrieving some insight of the study area. When this is done we will zoom in to Mandalay, the

Sedawgyi Network Irrigation System and some key values for the Sedawgyi dam. The last

analysis is to give some background information into the applications of RIBASIM. When the

analyses are performed, the modelling with RIBASIM starts. Hereafter the ‘Base Case’ will be

compared with the measurements done for calibration of the model.

After the model is sufficiently accurate, a variety of scenarios are tested. These scenarios

include long term autonomous effects which influence the future designs. The results of the

scenarios are compared with respect to pre-determined design criteria. In the end a final advice

will be presented to the ‘ADB’- group to support their advice to ‘M.C.D.C.’. This advice includes

visualizations of the water efficiency, optimum scenario and a quick and dirty research into

flood risk reduction of the canals.

1.5 Notes for reading the report

The reports consists of four segments, first the main report, second and third are

respectively Appendix I & II and fourth is a CD-storage disc.

Regarding the whole report is that all major aspects are in the main report. In Appendix I

the background information of the main report is presented. Also a brief summary of executed

fieldtrips and interviews is included in Appendix I. All supporting files, such as figures, graphs,

tables and PowerPoint presentation for the main report are included in Appendix II. Large data

files such as large Excel files and photos made during fieldtrips are included in Appendix CD.

1.5.1 Personal Notes

These notes are intended to give the reader some information about the setup of the report.

1. Some significant pictures or tables are referred several times in the report. Therefore

these pictures and tables are included in Appendix II.

2. All of the RIBASIM-files are included in Appendix CD. The files in FIXED and HYDROLOGY

are the most referred to in the reports. The RIBASIM-files within both directories should

be opened with <Notebook.exe>. The Excel-files of these RIBASIM-directories are

included in the report if the size allows it.



1.5.2 Files on Appendix CD

ACTRAIN.xlsx

ADBRAIN.xlsx

Calibration base case V2 and V3.xlsx

Half-monthly Waterbalance V1.xlsx

Mandalaypresentation 25-10-2014 (V02).pptx

Photos made during fieldtrips and workshops

o All: Scenarios, Fixed values, Hydrological time series

Results per Scenario.xlsx

RIBASIM-files-Mandalay

Sedawgyi dam Project Data.pdf

Sedawgyi dam Summary.xlsx

Sedawgyi Irrigation Scheme-Final 2012-13.xlsx

Statement of year in,sup, eva & Balance.xlsx

Summary Water balance 1999-2040.xlsx

Waterdemand Mandalaycity.xlsx

2 Initial analysis of the project area Various initial analyses were performed in order to collect information about the project

area, water resources, dimensions of civil objects and canals. Since the gathered data was flawed

or missing a little analyses about these errors is discussed in this chapter. Although both are not

really an analyses, a small summary of the ‘Green Cities’ and background information about

RIBASIM are included in this chapter.

2.1 Project area: Mandalay region

First some background information is acquired about Myanmar. Hereafter, the Sedawgyi

Irrigation Network and Mandalay are analyzed. In the main report the information is specified

about Mandalay and the Sedawgyi Irrigation Network. Some exploratory background

information of Myanmar is treated in Appendix I-B.

2.1.1 Mandalay and Sedawgyi Irrigation Network area

Mandalay is located to the north of the capital Nay Pyi Taw and has a central location in

Myanmar. Mandalay and the irrigation area are downstream of the Sedawgyi reservoir. The

downstream flow is through the Mandalay Main Canal (MMC) and controlled by the Sedawgyi

dam. Sedawgyi Multipurpose Dam has two main functions, supplying irrigation demand and the

generation of hydropower. An enlarged version of figure 2 is shown in Appendix II-A2. This map

will be referred to throughout the whole report.

Figure 2 Sedawgyi dam irrigation network map, March © 2014 Irrigation Department


Haarlem Hydraulics & Technical University of Delft | Initial analysis of the project area 15

2.1.1.1 Mandalay

Mandalay is the second largest city of Myanmar and was the last royal capital of Burma.

Mandalay’s location in the central/northern part of Myanmar makes it an important hub for

transport of people and goods. Also in the religious context it is important, as it is seen as the

pilgrimage for the Buddhist.

The city is divided in seven townships:

Chanayethazan (city center)

Amarapura

Aungmyethazan

Chanmyathazi

Mahaaungmye

Patheingyi

Pyigyidagun

A research by (Mann Htun, 2014) has been performed to acquire accurate data of the total

population of Mandalay. The results are presented in Table X. However, since even the last

census in 2014 did not provide sufficient reliable data, due to religious or socio-economic

constraints, population projections had to be estimated.

Mandalay District Population in 2014 SR Township Urban Rural Total Population

Nr.Houses Nr.Households Population Nr.House Nr.Household Population Nr.House Nr.Household Population

1 Aungmyethazan 29.929 36.389 177.653 29.929 36.389 177.653

2 Chanayethazan 22.001 28.796 146.125 22.001

28.796 146.125

3 Mahaaungmye 29.162 35.840 171.655 29.162 35.840 171.655

4 Chanmyathazi 35.402 38.797 204.929 35.402 38.797 204.929

5 Pyigyidagun 25.212 30.654 154.741 25.212 30.654 154.741

6 Amarapura 10.631 13.503 59.374 24.100 28.758 122.272 34.731 42.261 181.646

7 Patheingyi 2.240 2.590 11.417 35.487 36.490 175.125 37.727 39.081 186.542

Total 154.577 186.569 925.894 59.587 65.248 297.397 214.164 251.818 1.223.291

Table 2 Inhabitants of Mandalay in 2014 per township © 2014, Mann Htun, Mandalay

Note: Significance is too accurate for such estimation, yet this seems to be common in Myanmar

A quick and dirty estimation has been done by the ‘ADB PPTA’ Urban Planning section

for a population projection in 2040. The estimation is based upon two former censuses and the

estimation of the Ministry of Population. These censuses were done in 1984 and 2014, so thirty

years apart. For estimating the total amount of inhabitants an educated guess has been made

with multiple scenarios including population growth, urbanization and two developing areas in

Amarapura and Patheingyi. The results are given in table 3. It is estimated that in 2040 the

development plan for Amarapura is finished for 90% and in Patheingyi for 60%. This difference

is a result of the existing trend of extending the city in southward direction, and in addition the

roads are in better condition compared to Patheingyi. However, as mentioned, these

expectations are quite uncertain.

90% in DA1 and 60% in DA2 by 2040 Township/area Total Population Phased % AAGR 2014-20 2021-30 2031-40 2014-2040 Aungmyethazan 190423 215746 241070 0,51

Chanayethazan 153574 168445 183316 0,38

Mahaaungmye 181351 198372 215393 0,37 Chanmyathazi 222459 257152 291845 0,59 Pyigyidagun 163494 198623 233752 0,79 Amarapura Existing Urban

62857 69597 74651 0,38

Amarapura Existing Villages

54822 110543 152333 2,89

Development Area 1 (Amurapura)

141481 391358 578765 5,94

Total Amurapura 259160 571497 805750 3,44

Development Area 2 (Patheingyi)

107841 284005 370087 4,9

Total 1278302 1893840 2341213 1,47 Table 3 Estimation of population in Mandalay in 2040 ©2014, ADB PPTA, Mandalay

An extra 245000 people live in other rural areas of Amarapura and Patheingyi outside

proposed development areas. The total estimated Mandalay population will be about 1.2 million.

Figure 3 Population growth rate © 2014, ADB PPTA, Mandalay

2.1.1.2 Religion

For religion in Mandalay a reference is made Appendix I-B.1.2: “Background information

Myanmar”. The data will mostly be the same. However, Mandalay is a religious hub for the

Buddhist, thus a higher percentage of Buddhists is expected. Since it is common for Buddhists to

go here on their pilgrimage, the amount of total inhabitants being Buddhist is possibly even

higher. No data are present about the amount of monks living in Mandalay, even though

estimations are based on the latest census in 2014. The number of Muslims living in

Mandalay/Myanmar is also increasing due to refugees from India or Bangladesh. However, this

will never be acknowledged by the census.



2.1.1.3 Madaya

Nowadays Madaya is a small town with only a few inhabitants (ca.30000). It is located

near the Chaungmagyi River in the north of the project area. While they are currently not

connected Sedawgyi Water Resources Network, but they published a Water Management Master

Plan for Madaya in 2035 in which they state their intention is to connect Madaya to the

Sedawgyi Network. Currently their water supply is by groundwater and distributed in bottles,

but in the future this will not suffice1. It is expected that in 2040 the population of Madaya will

be increased to 100,000 people.

2.1.1.4 Elevation of the research area

Mandalay was formerly called Yadanarpon. A terrain map of the project area is presented

in figure X. The hills in the west are the Shan Hills.

Figure 4 Topographic map of the project area ©2014, Google Maps & 2013 Maphill.com

2.1.1.5 Main Rivers

Looking at Appendix II-A2 the ‘Sedawgyi Network Irrigation Network Map’, there are

three distinct rivers, namely:

Ayeyarwaddy River (West)

Dokhthawaddy River (South)

Chaungmagyi River (North)

The flow of the Chaungmagyi River in the north is controlled by the Sedawgyi dam and at

Sedaw weir the river is divided into three separate rivers or canals. These are Yenatha Canal,

1 Appendix I-I: Interview with Madaya City Council

Mandalay Main canal and the resulting Chaungmagyi River, which continues to flow towards the

Ayeyarwaddy River.

2.1.1.6 Primary and secondary canals

The primary canals are the diversion canals taking water from the Chaungmagyi River at

the Sedaw weir. Secondary canals are the distributaries (DY) connecting the irrigation areas to

the Mandalay Main Canal. This has all been visualized in Appendix II-A2 & figure 2 of the main

report. The second and third figures are the ‘Mandalay Canal Irrigation System’ in Appendix II-

A3 & the ‘Connections to Mandalay Main Canal’ in Appendix II-A4.

Mandalay channel is formed in the north by the Sedaw weir. At this weir the Chaungmagyi

is separated in three sections:

Chaungmagyi river

Yenatha Canal

Mandalay Main canal

The Chaungmagyi river flows further west into the Ayeyarwaddy. Second is the Yenatha

Canal, a man-made canal that flows into the northern irrigation network distributaries 1 to 9.

Third is the Mandalay Main canal, which flows southward to Mandalay. The Mandalay Main

Canal (MMC) is a man-made canal with a constant cross-section over the whole length. Along the

MMC are many distributaries (DY) or secondary canals. All the connections of the MMC are

visualized by the department Roads and Bridges in Appendix II-A4. The water distribution

between these sections is unknown, but not necessary for the demand by the model. However,

the irrigation department did make a statement about this matter, their response being that

75% goes in the MMC and 25% in Yenatha canal2. Obviously, this is an illogical response, since

with the current ratio no water will flow in the Chaungmagyi.

2 See appendix I-I Fieldtrips and Interview: Request to DoIA



Index Canal Length [m] Depth [m]

Q[m3/s] Summer paddy [ha]

1 Shwetha-Chaung

3810 1.0 56,6 5608,4

2 Thamok-So 10363,2 1,4 54,1 1827,6

3 Nandar 5852,2 1,1 34.0 1633,2

4 Alebon 6370,3 0,9 29,2 1594,4

5 Htanpingon 6446,5 0,9 22,4 1276,8 Table 4Top 5 largest DY’s in the Irrigation Network fed by the MMC ©2014, Irrigation Department, Mandalay

In table 4 a list is given of the five largest irrigation areas fed by the MMC. For the whole table see Appendix II-B2: ‘Salient features of the Mandalay Main Canal’

2.1.1.7 Water level and major threats

In Mandalay there are some major issues with regard to the water resources. An increase

of water level can be caused by multiple reasons. The issues that are analyzed and included in

the research for the RIBASIM Model are enlisted below:

Causes for increase of flooding risks in Mandalay

o By rainfall

o By internal failure of the water (drainage) system

o By overflowing of the river flood protection infrastructure (dykes)

An investigation into the causes of flooding of Mandalay has been performed by the

TEAM Consultants, together with CH Karnchang Public Company ltd and the Warninn Group of

companies. They established a presentation of the potential causes for failure of the flood

protection system in Mandalay given in Figure X. However, the overflow of the Ayeyarwaddy

River into the city does not seem to be realistic, since the height of the dike is sufficient.

Figure 5 Locations and causes of flooding in Mandalay city ©2012, TEAM Consultants, Japan

The external risk is caused by rainfall in multiple areas, as the local rainfall in the city itself is not

the biggest risk for flooding. This is on a small scale and only temporary. More hazardous is the

rainfall in the upstream area of Mandalay, in the Sedawgyi Irrigation network and spillage at the

dam. Also the mountainous areas cause a reasonable flooding risk to Mandalay. This flood flow is

coming from the Shan Hills (Tin Oo, 02-09-2014). High flood peaks will flow into the canals and

increase the flooding risk within the city and surrounding areas.

Internal flooding is caused by failing drainages or pumps. Many drains have been

constructed without a slope or pump, so there is very little to no flow in the drains. This problem

is also not included in the RIBASIM model. However, it is good to know where these issues arise.

Logically the result is that the flooded areas are hard to drain.

Last is the risk of the Ayeyarwaddy River overflowing his outer banks, but Peter Kerssens

concluded this was not the largest probability. More probable is a connection by water flowing

through/underneath the dikes (seepage) causing some flooding problems in this area. Although

this is a realistic problem, it is not handled in this report because of the applied scope of the

research3.

2.1.1.8 Climate and Climate change

Mandalay is located in the so-called “Central Dry Zone”, meaning that there is very little

precipitation even during the rainy season and especially in the summer and winter periods.

Due to the location in the middle in the country there is not much rain or wind. So the

temperatures are rather high. A visualization of this weather is presented in figure 6.

Figure 6 Average minimum and maximum temperatures in Mandalay©2013, Weather and Climate Information

All of the daily rainfall data supplied by the Irrigation Department are converted to half

monthly inputs and are included in Appendix CD. The data collected cover the range from 1990

to 2013 and were measured at four different locations, being Mandalay, Amarapura, Patheingyi

and Madaya. This file is not in any Appendix, since the file is simply too large and it is not

environmentally responsible to print it out on paper.

3 Maxime Riou, a liason engineer at Safege, is researching the effects of groundwater on Mandalay city.



In figure 7 is a visualization of the annual precipitation in Mandalay in 2013.

Figure 7 Average precipitation in Mandalay ©2013, www.weatherandclimateinformation,com

2.1.1.8.1 Climate change

When an analysis is made of the rainfall data collected from the Mandalay Old Airport

station (from Dept. of Meteorology & Hydrology), one could recognize a distinct trend in annual

rainfall rising from 800mm in 1950 to over 900 mm today. This has been validated with other

measurement stations. In figure X it is visible that four of the ten largest annual rainfalls

occurred since 2000. The Depth Duration Frequency curves analysis also shows a more or less

similar increase in daily rainfall.

Figure 8 : Time Series Analysis of annual Rainfall at Mandalay and DDF Curves, © 2014, ADB PPTA, Mandalay

Forecasted changes at Mandalay (Dry Zone) are:

Slight increase of Annual Rainfall

More drought in the pre- and post-monsoon periods (May, June & October)

Decrease in monsoon duration

Increase in intensity of rainfall during the monsoon period

Consequently, of these forecasted changes, the drought period is during the summer and

winter. For the drought period, a decreasing trend of 35% in 26 years in precipitation is the

applied design value for extrapolating the data sets. For the rainy season which now consists of

three months (August, September and October), the applied change in 26 years is a 10%

increase in precipitation. For peak flow (maximum daily rainfall) an increasing trend of 25% in

30 years is the assumed design value in the PPTA project. However, the latter is not included in

the RIBASIM-model, only the increase or decrease of participation in the corresponding season.

Season Period Average temperature (°C)

Expected increase in temperature in 2020 (°C)

Average temperature in 2040 (°C)

Change in periods

Climate change factor for rainfall

Winter November to February

16 to 30 +1.2 +2.2 October to februari

98.35%

Summer March to April 21.5 to 37 +1.0 +2 March to June

98.35%

Monsoon May to October

25 to 34 +0.6 +1.6 July to September

100.37%

Table 5 Climate Change in 2014 Mandalay © 2014, ADB PPTA, Mandalay

In order to construct the rainfall dataset, in 2039 and 2040, the formula underneath is

applied. The existing measurements until 2014 are extrapolated by using the existing set and

multiplied with the corresponding climate change factor per season to the power n which is

from 2014 to 2040, thus 26 years.

𝑅𝑛𝑒𝑤,𝑖 = 𝑅𝑜𝑙𝑑,𝑖 ∗ 𝑐𝑐𝑛

Equation 1 Extrapolation Rain data

Rnew,I = New rainfall value ith in the list per rainfall measurement station. Rold,I = Rainfall value ith in the existing set per rainfall measurement station cc = Climate change factor for rainfall, see table X2 n = Number of years after 2013 to 2040; n=1 to 26 years

2.1.1.9 Agriculture

In the Sedawgyi Irrigation Network there is much agriculture. On the 30th of July 2014 a

field trip was made to the Sedawgyi Dam; see Appendix I-I and Appendix CD for photos. Along

the main road to the dam a quick and dirty estimation has been made about the variety of crops

produced. Main crops produced are (logically) rice, and some other productions in large

quantities are sugar, banana, corn and wheat. For the distributaries a reference is made to

chapter ‘Primary and secondary canals’, also to Appendix II-B.2: ‘Sedawgyi Dam Network

Irrigation Map’& Appendix II-B.3: Mandalay Canal Irrigation System



2.1.1.9.1 Agricultural Areas

The Sedawgyi Dam Irrigation Network can be divided in four areas as shown in table 6.

Area description Township/Weather station

Location Supplied by

DY1 to DY 9 Madaya Along Yenatha Canal Yenatha Canal Pumping Area L1-L16

Patheingyi East of the Mandalay Main canal

Mandalay Main Canal

Western area of the Irrigation network

Patheingyi/Mandalay/Madaya

From Seiktha Cut to Patheingyi DY

Mandalay Main Canal

Southern area of the Irrigation network

Mandalay/ Amarapura From YanKinGon DY to Kinbek DY

Mandalay Canal

Table 6 Four main areas of the network ©2014, Own, Mandalay

A secondary division is done by dividing into townships: Madaya, Mandalay, Amarapura

and Patheingyi. All of the farms are located along the distributaries. There is just an indication of

the size of the agricultural areas per DY. No data are available for crop type or areas per crop

cultivation. So estimation is based on a quick and dirty research in the field, and “Google Earth”

has been used for determining the total area per crop per DY. In Appendix II-B3 a table is given

with all the irrigational areas divided by supply canal and location and Appendix II-B4 gives a

table for Area per crop sort per DY.

Since the applied traditional irrigation techniques are old fashioned, the field irrigation

efficiency is only about 50%. The applied methods and materials are the cause for the low

efficiency. Farmers have been using the family traditional methods and when they are provided

with newer methods or material they lack the capacity to apply it.

2.1.1.10 Variety in crops produced

In the agricultural areas around Mandalay there is a large variety of crops. All of these

crops have different preferences for climate to have an optimal growth. As said there are three

distinct seasons, summer period, winter period and rainy season. A crop can be growing in wet

or dry conditions. In this case only paddy fields have a need for a water layer above the soil of

30-50 cm during the first growing period. Every crop has a different set of characteristics, the

main parameters that determine the optimal growth are:

Crop factor

Crop yield factor

Growing period

Growing season

Percolation

Reference evapotranspiration

Root zone

Starting period

A schematization of the variety in crops characteristics is given in Appendix II- B5 to B10.

Most of the values were already researched by ‘Deltares’, although some values have been

adjusted or added into the file. All of the data that were not already available have been gathered

on the site of the organization ‘FAO’ (Food and Agriculture Organisation of the UN, 2014). In

table X the total area per crop for the whole Sedawgyi Irrigation Network is shown.

Crops Total Area [ha]

Percentage of total area

Summer Paddy 29883 64%

Winter Paddy 29883 64%

Sesame 593 1%

Sunflower 0 0%

Pulses 3236 7%

Corn 2929 6%

Ground nut 446 1%

Garlic 0 0%

Wheat 4059 9%

Soybean 229 0%

Banana 3655 8%

Sugarcane 5279 11%

Vegetables 286 1%

Cattle 684 1%

Total 46939 100% Table 7 Total area per crops produced in the SIN © 2013, own, Mandalay

Note: Summer and winter paddy areas are equal, because the assigned area can be in different

periods. Only one of the assigned areas is included in the calculated sum.

Summation of the assigned areas for all specified crops and other agricultural in

Mandalay are shown in table 7. Therefore some crops are included, but not modelled. These

crops were not seen in Mandalay, but definitely grown in Myanmar and are probably around

Mandalay as well.

Many banana and mango cultivations were seen in the field, but it was not possible to

model these. So they are excluded from the model. It was not possible to model these, due to the

fact that growing period exceeds a single simulation year which will lead to no production of

crops.

For a small summary about the characteristics applied for the crops reference is made to

Appendix I-B2: ‘Background information crop data’& Appendix I-D: ‘RIBASIM Background’

2.2 Water Resources

The analysis of the water resources system is covering the supply and demand by a variety

of aspects in the system. First the supply side is covered, which consists logically of the Sedawgyi

Lake and local rainfall as an additional source. Secondly, the demand side consisting of multiple

elements such as water usage by Mandalay inhabitants, loss flow and a constant flow in the

Moat. (base flow for water quality reasons).

2.2.1 Supply

First the Sedawgyi water balance will be handled, hereafter the rainfall measured at the

different stations and the corresponding inflow.

2.2.1.1 Sedawgyi Lake

The Sedawgyi dam is located at the Chaungmagyi river in Madaya and is the main supply

for the irrigation network. The main objective of the dam is to supply enough water to increase



the agricultural output in Mandalay, Yenatha and the pump irrigation areas. These objectives

have been planned under the project by provision of sufficient irrigation canals for growing

crops. The irrigation construction works are integrated with the agricultural and fisheries

development program. Secondary benefits could be derived from the generation of hydropower

at the dam site and for the increase of water supply to Mandalay. (Irrigation Department, 2014)

Consequently, the dam can regulate the discharges from the Chaungmagyi river as

required, resulting in an increased acreage of about 32000 acres on top of the existing acreage of

95000.

It is not clear what the main function is of the Sedawgyi dam. The Super-intendant said it

is used for both irrigation and hydropower4. Nevertheless, it was clearly visible that during

drought water is accumulated for hydropower resulting in a shortage of water for irrigation. On

the other hand, during the rainy season the water level is too high in the lake, so the spill gates

have to be opened. This leads to a large flow going downstream of the dam into the irrigation

network. A lot of water is wasted this way because in the rainy season it is unused by the

farmers. This all leads to a low overall efficiency of water usage.

The annual and daily water balance of the last years was supplied by the Irrigation

Department. The annual water balances for Sedawgyi Lake is included in the Appendices B.10 &,

CD. The inflows of the water balance are inflow by Chaungmagyi River and rainfall at the lake.

This rainfall is measured at the Madaya meteorological monitoring station. The overall rainfall in

the project area is measured at four stations, being Mandalay, Amarapura, Patheingyi and

Madaya. All of the DYs are sorted within one of the weather stations. This is presented in table 8

and in Appendix II-B3

Township Mandalay Amarapura Patheingyi Madaya

Mandalay Main Canal DY’s

Shwe Ta Chaung Tadaing She Shwe Ta Chaung Seiktha

Patheingyi Tamok So Kabed Feeder Cut Kyauk Mi Kinbak Lundaung ShweTaChaung Tadaing She Nanda Lat Kaung Kyauk Than Bat Alebon Patheingyi Htanbingon Yankingtaung Lundaung Yekyi Nanda 168 Minor Wangingon Kyauk Mi Tadaing She

Yenatha Canal DY’s

DY1 to DY7

Pumping Lift Area L1 to L16 L1 to L16 Table 8 Distributaries per rain measurement station © 2014, ID, Mandalay

4 Appendix I-I: Interview with head of Sedawgyi Dam & Appendix CD; Photos of fieldtrips, Sedawgyi Dam

In table 8 the largest DY’s are in bold which have the largest size of the agricultural area

in the corresponding weather station above. As mentioned, the half monthly data for the rainfall

per measurement station are included in the CD.

The precipitation at Sedawgyi Lake and over the cultivation fields are given in mm/day.

This has been converted to a half monthly basis in mm/ (15 or 16) days, also taking leap years

into account. There is nevertheless a large difference in the capacity between the lake and the

fields, as the fields have a “rectangular” shape, but the lake is a reservoir in which the surface

area and the volume increase during rainy periods when the water level rises.

There are no data of the rainfall at the Shan Plateau, and the rainfall measurements of

Patheingyi are not representative for rainfall in a mountainous area. Therefore the rainfall

measurements of Pyin Oo Lwin are applied as representative measurement. Since the Shan

Plateau and Pyin Oo Lwin are both located in mountainous areas, it is to be expected that the

amount of rainfall is more or less similar in both locations.

2.2.2 Demand

The demand for water is the major part of this research. It consists out of a variety of

specific water demands, distinguished as follows: the demand for public water supply

(population, business, and industry), water demand for irrigation, the moat flow (flushing for

water quality), commercial losses, and physical losses.. In the model the allocation of water is

determined by priorities set by either the amount of water or socio-economic significance. For

instance, in almost all cases drinking water for people will have the highest priority.

2.2.2.1 Sedawgyi Reservoir

The full water balance is:

𝑑𝑉𝑟𝑠𝑣𝑑𝑡⁄ =

𝑑𝑄𝑖𝑛𝑑𝑡⁄ −

𝑑𝑄𝑜𝑢𝑡𝑑𝑡⁄ −

𝑑𝑆𝑜𝑢𝑡𝑑𝑡⁄ + 𝐴𝑠𝑢𝑟𝑓𝑎𝑐𝑒,𝑖(

𝑑𝑅𝑖𝑛,𝑖𝑑𝑡⁄ −

𝑑𝐸𝑜𝑢𝑡,𝑖𝑑𝑡⁄ )

Equation 2 Water balance

dVrsv/dt Volume of the reservoir over time [m3/ts] dQin/dt Inflow by Chaungmagyi over time [m3/ts] dQout/dt Outflow through hydropower outlet [m3/ts] dSout/dt Spillage over main gates [m3/ts] Asurface,i Corresponding surface area [m2] dRin,i/dt Rainfall over corresponding lake surface area [mm/ts] dEout,i/dt Evapotranspiration of the lake surface area [mm/ts]

The measured values are summarized in a table for this water balance at Sedawgyi Lake is in Appendix II-B.10. Since the reservoir is not a cylindrical shape, but more like a bowl shape, the volume and corresponding surface area in the reservoir vary in time with the water level, due to in and out flow in the reservoir. The water balance of the reservoir represents this. For retrieving more insight into the volume change, respectively the change in water surface area based on a certain water level an area/volume curve for the Sedawgyi Dam is given, see figure 9 or Appendix II-B11.



Figure 9Area/Capacity curve Sedawgyi Dam © 2013, ID, Mandalay

2.2.2.2 Mandalay city

In Mandalay there is a lot of variety in water demands, by i.e. the inhabitants, losses and

moat flow.

2.2.2.2.1 Key figures

The total population of the city is about 1.2 million, with about 700,000 being connected

to the Mandalay water supply. This is equal to 85,300 households/customers distributed over a

service area of 58 km2. All the customers are charged for a total of 37,700 m3/day compared to

the total volume of water sent into the water system, equaling to 96,000 m3/day. A large deficit

consists between charged and total water in the system, due to the so-called Non Revenue Water

(NRW). Apparently the NRW is 63% of the total water put into the system. Most of the water in

the system is supplied by groundwater (85%) the other 15% is surface water5 , private tube

wells and bottled water.

In total 66% of the people in Mandalay are living in the five urban townships (ADB PPTA,

2014):

Aung Myay Thar San 90%

Chan Aye Thar San 83%

Mahar Aung Myay 72%

Myay Chan Mya Thazi 59%

Pyi Gyi Dagon 6%

Others are supplied from different local resources (ie by private tube wells) and water

venders/bottled water.

5 During modelling the surface water is 15% of the total water input.

0,0020,0040,0060,0080,00100,00120,00140,00160,00

Waters spread [ha]

Water level [m]

Reservoir capacity [ 106 m3]

Reservoir Capacity

Waterspread

Table 9 Summary for supply of the water resources system, © 2013, ADB PPTA, Mandalay

Description Percentage of Supply [%]

Groundwater 85% Surface water + Private tube wells + Bottled water

15%

2.2.2.2.2 Inhabitants of Mandalay

In a research performed by ‘ADB PPTA’ they state that the water demand per person per

day is equal to 101 l/cap/day. The total demand is based on an average from the sum of all

demands from each single township. In 2014 only 0.7 million people of the 1.2 million people

receive water, but the demand is based upon the assumption that everybody has a demand for

water. Only the supply of water varies. Since 15% of the water supply is covered by surface

water the demand from surface water is equal to 15 l/cap/day for all of Mandalay.

Figure 10 Water resources system per township and household©2013, ADB PPTA

2.2.2.2.3 Non Revenue Water and Inhabitants

Non Revenue Water (NRW) is a term for water usage for which the public is not charged.

This NRW consists of two main aspects, namely commercial and physical losses.

Physical losses

o Leakages

o Overflow

Commercial losses

o Under counting

o Illegal connections

o Unbilled consumption

Unbilled consumption forms a high contribution to the total NRW, due to monks,

governmental buildings and the military. These groups do not have to pay for public services.

The difficulty is that there are simply no data about the amount of water for physical or

commercial losses. So a quick and dirty estimation has been executed to acquire some insight

into public water supply. Table X on the next page shows this estimation.



Description Value Unit

Total Inhabitants in 2014 1,220,000 Nr. of people

People Connected to water network 2013

700,000 Nr. of people

Paying Households 85,200 Nr. of customers Supplied water in 2014 96,900 m3/day Non Revenue Water 60,600 m3/day Billed water 36,300 m3/day Billed Water Percentage 37 % NRW Percentage 63% % PWS Calculated 101 l/capita/day 15% by surface water 15 l/capita/day 85% by groundwater 86 l/capita/day

Table 10 Summary estimation demand Mandalay© 2014, ADB PPTA, Mandalay

2.2.2.2.4 Moat flow

The moat is located around the Royal Palace. Every outer side is ca. 2.3 km. The moat in

combination with the Royal Palace is one of the major touristic sights in Mandalay. This is why

the City Council demanded that there should always be a certain minimum flow and a nearly

constant water level inside the moat.

The flow has never been measured, but an estimation of 10 m3/s has been made.

2.2.3 Sedawgyi Irrigation area

All the cultivations need a certain amount of water. The allocation of water is modelled

by the RIBASIM Program. The demand for water is based upon some pre-mentioned

characteristics, such as percolation, pre-saturation, crop factor, yield crop factor and field buffer

storage. See Appendix B5 for the applied values. All of the required data have been acquired via

the FAO (Food and Agriculture Organisation of the UN, 2014).

One of the most common crops after paddy fields is sugarcanes. The sugarcane is applied

as an illustrational crop in Appendix II-B2, because it has a distinctive growth curve. Yet all the

other crops have been researched in a similar way.

2.3 Civil objects and canals

Within the Sedawgyi Irrigation Network the major civil object is the Sedawgyi dam. The

primary and secondary canals are investigated as well. Some ‘hard’ figures are presented in this

chapter.

2.3.1 Sedawgyi Dam

The ‘hard’ data of the Sedawgyi dam consist of: cross-section, hydropower, units,

turbines, etc. A summary of the data is presented in the following table. The extensive data for

‘Salient Technical Features’ and ‘Hydropower Generation Stages’ are shown in Appendix II-B2

and Appendix CD, respectively.

Sedawgyi Dam key values Corresponding surface area

Corresponding capacity

Characteristics [m] [ha] [m3] Length of dam 1255,8 Top of Dam, (above MSL) 131,4 Max Water Level, (above MSL) 129,5 Full Reservoir level, (above MSL) 127,9 2870 4.48*108

Min Operating Level, (above MSL) 111,3 1380 1.04*108 Catchment Area 342,500 Hydropower Installed Nr [MW] Capacity 2 12.5

Table 11 Characteristics Sedawgyi Dam © March2014, ID, Mandalay,

A cross-section and an overhead view are displayed in Appendix II-A5 & Appendix II-A6.

2.3.2 Canals

The canals discussed here are the primary respectively the secondary canals. No data are

available for any of the cross-sections of the canals and in fact they also are not necessary for a

RIBASIM-model. Reference is made to Appendix II –B2 in which the maximum is flow given that

will be used to calibrate the model.

2.3.2.1 Moat Canal

The moat canal dimensions are measured with ‘Google Maps’ and the depth is estimated.

As mentioned the outer length of the square is 2300 meters, the inner length of the depth is

2160 m, while the width of the canal is about 70 m. Although the canal width varies slightly over

the length, this is a fair measurement.



2.4 Data Analysis

Many data have been supplied by a variety of sources. However some of the data were not

so reliable or data were simply not available. So some estimates were made, based on visual

experience during a fieldtrip, by simplifying the problem or just by an educated assumption.

Here an overview is given of the gaps in the data.

2.4.1 Data gaps

Many data that were required were simply not available. Due to measurements not

executed or faulted operating systems. A good example of this is an automatic measurement

device for the Ayeyarwaddy water level. The machine did work, but it ran out of paper and ink.

As spare parts were not available these elements were evidently not renewed. Photos of this

‘funny’ situation are included on the Appendix CD. The following list is a representation of all

encountered data gaps.

Mapping data

o The lack of data and information about cross-sections, water levels, depths

concerning canals is more of a nuisance.

o No information about agricultural area (size of farms, number of farms, kind of

cultivation, etc.)

Rainfall Data

o In the water balance of Sedawgyi reservoir multiple years of inflow are not available

o No short duration/intensity/frequency information since the early 1980’s

Flow Data

o No information concerning dry or wet weather flow

Water balance data

o No data about flow distribution at weirs

o No distinct data of water usage downstream

Mandalay

o No distinct data about how many people there are exactly in Mandalay

o No data about how many monks live in Mandalay and how much water they consume

freely

o No data available for religious, governmental or military consumption of water

2.4.2 Flawed Data

The annual rainfall data were flawed in many ways, since they have mainly been

calculated by hand instead of using a computer. So human error is a major cause, but also

outdated measurement devices led to a low reliability of the data. Fortunately the daily rain data

were of better quality. Some examples of flawed data are enlisted below.

Rainfall data

o The data were filled in by hand, a result is that in one case data from a block of 3 years

and 3 months during the rainy season were copied to a block of the same size during

summer

o Calculations were wrong even when the data were filled in correctly.

2.4.3 Summary of causes of the errors

Many of the data are flawed, basically because they don’t know any better. So capacity

building and improved education should be implemented not only by ‘ADB PPTA’, but

nationwide. Enhancing automation would reduce human error. Another reason for many errors

is the institutional situation. Different institutions from the same government do not know what

the other party is doing. If a measurement device is owned by one party, others are in principle

not allowed to use it.

Finally, there is always some resistance for supplying data to another party, even when

they are working together. Sometimes multiple times asking the same question or data, you may

receive different answers. This seems to be an issue in many countries, and solutions are hard to

find in the existing institutional and socio-economic conditions.

2.4.4 Small conclusion about data errors

Even though many data are flawed or not available, it is necessary to realize that without

data there can be no model. Reasonable data can be acquired by sieving the errors and by

interpolating the unknown data. In this country the accuracy of the model/research is maybe

not so significant if compared to other western world countries. Here it is more significant to

have a real impression of what happens and try to simulate such processes. So to support future

advice to the client, it is more efficient to model and investigate the feasibility of some scenarios.

2.5 Green Cities

‘Green Cities’ is a book by (Asian Development Bank, 2012)about the ideology of

constructing sustainable Asian metropolises. An extended summary of the ‘Green Cities’ book is

in Appendix I-C. In this section only the main ideology behind Green Cities is discussed, along

with the relation to the current study in Mandalay.

“Green Cities are distinguished as cities that have already achieved or are moving toward

long-term environmental sustainability in all of its aspects, from cities that continue to pursue

environmentally unsustainable development trajectories.” (Asian Development Bank, 2012)

“For a city to be considered ‘green’ by ADB’s definition is that these measures must be

undertaken in comprehensive , planned manner that not only positively impacts the city in

question, but also contributes to environmental sustainability at the global level. Which actions a

city collectively undertakes, the manner in which it undertakes these actions and the outcome of

those actions, thus form the criteria for determining how ‘green’ a particular city is.” (Asian

Development Bank, 2012)

2.5.1 Relation to Mandalay/Sedawgyi Irrigation Network modelling

The main relation is that Mandalay is growing and growing fast, it will soon become a

‘Mega city’. However at the moment the city is still under developed, so by starting now and

implementing the ADB’s “Green Cities” design methods in the conceptual or even potential

designs. This manner Mandalay City can become a ‘Smart City’ and beautification of the city

centre. Although there is still a long water to go, by starting now by applying green scenarios, the

city has the potential to become a “Mega City’ of Myanmar. Sustainable Urban Drainage Services

(SUDS) is of the modelled scenarios, which benefits improving the ‘Greenification’ of Mandalay.

The ‘soft’- design criteria, they resemble the ‘Quality of Life’, yet they are hard or impossible

to measure. The ‘Green Cities’ design standard improve the ‘Quality of life’. So, weighing the

separate scenarios with the ‘soft’ design criteria, will give a more clear distinction for the

potential of improving the ‘Quality of life’.


Haarlem Hydraulics & Technical University of Delft | Introduction to RIBASIM 33

3 Introduction to RIBASIM For some readers who do not know RIBASIM, this research could be hard to understand.

Therefore some basics of the RIBASIM software/model are presented in this section. However,

only a small summary regarding the Mandalay Irrigation Network model is given in this report.

In Appendix I-D a report is included, made by (Nauta, Krogt, Velden, Schellekens, Hasman, &

Veen, 2014) about applying RIBASIM to all of the major basins in Myanmar. In this report also an

extended version of the RIBASIM background is given.

3.1 Basics of RIBASIM

RIBASIM stands for River Basin Simulation Model. RIBASIM is a program to model the

water resources in a certain basin area. It consists out of nodes, which are either demand or

supply nodes. RIBASIM than applies the water balance for the whole system by allocating water

supply to all the demand nodes based upon availability of water and priorities. The different

nodes available are inflow/supply, demand, outflow, control or redirecting nodes. The demand

and supply nodes can be fixed or variable, a time series, which can be adjusted to acquire the

most realistic model. Nodes are connected by links. Links are not related to length or width of

the real river. Unless when water quality is modeled the length does not affect the system. A

picture/ map of the model schematization can be generated that more or less represents the

layout of the system, with canal nodes and links at the right geographical position. However,

such physical data are not really relevant or necessary and thus not used in the model.

Basins, such as Mandalay Basin, are the overall modelled system. Selecting a certain

hydrological scenario makes it possible to adjust the accuracy of a simulated time steps of

monthly, half monthly or daily units. By applying different cases one could simulate different

situations for this basin. It is possible to simulate different climate patterns, but also simulate the

effects of potential construction designs. These cases can then be analyzed and compared in

three different ways by graph, in a map or in a textual summary. In the end the results can be

easily exported to Excel or something similar.

Logically there are two scenarios applied in every model, namely the ‘Base Case’ and the

‘Reference Case’. The’ Base Case’ is the current situation used for calibrating the model. The

reference case is the future situation, i.e. the ‘Base Case’ including long term effects such as

autonomous developments with regard to viz. population growth, urbanization, and climate

change. As mentioned before, calibration of this model was expected to be hard, due to

inconsistent or flawed measurements. Thus calibration is done by checking if the results are

realistic.

Some limitations of the model that might be solved in future are for instance:

Add elevation to the model;

Simulate actual flow in a river (water level, flow velocities), just a volume of water is

given over a certain simulated time;

Flood waves are not possible to simulate, also not the flooding risk;

Fixed data for agriculture can only be set for a single year divided in a number of time

steps, so it is not possible to model crops with a longer growing period than one year.

Since it is not the main function of the model, the first three limitations are not actual

problems. But it is mentioned anyway, because it was requested to study this subject. The

RIBASIM model is solely for allocating water resources and including calculations for water

quality.

To enable inclusion of flood risk some additional nodes can be added to the model. In

these recording nodes it is possible to set a constant pre-measured maximum flow per half

month. (Appendix II-B.2 Salient Features of MMC). When the demand flow for a node is more

than the maximum flow it will over flow. However, this is very unlikely to occur due to the lack

of elevation.

3.2 Applied model of the Sedawgyi Irrigation Network Model

The model consists of nodes and links, for both settings can be set. The settings for the

nodes have more variation in input settings compared to the links.

The nodes are separately discussed in order of supply, demand, control, layout and

measure. In the analyses phase the input parameters have been extensively treated (see

Appendix I-D). 3.3 Definitive model

The results of the water resources system schematization into this model are shown in figure X.

Figure 11 RIBASIM model of the Sedawgyi Irrigation Network © 2014, own, Mandalay


Haarlem Hydraulics & Technical University of Delft | Scenarios 35

4 Scenarios The main problem is the low efficiency of the water use. Large cultivations are drying out

and most of the time there is water shortage. The efficiency is so low, because water is

accumulated for hydropower. So the farmers don’t get enough water to produce crops during

summer and winter season. On the other hand, during the rainy season the flow through the

turbines is limited by the maximum capacity. So water gets spilled by opening the spillways.

Even more so, there is too much water flowing into irrigation network which is unused and

causes a potential flooding hazard in the city or along the canals.

The main goal of the scenarios is to improve the water usage efficiency. In the scenarios

some options are designed to improve the efficiency in 2040. The long term effects are the

autonomous developments in 2040. Most of the scenarios are based upon existing design,

potential designs or conceptual designs for future development. These scenarios are all

supported by ‘ADB PPTA’ or M.C.D.C. (Appendix Fieldtrips & Interviews). So all the designs are in

different phases, but the goal of this study is to check the different results per scenario in 2040.

Water shortage is currently already a major issue, but in 2040 the long term effects will

only increase this demand significantly. The results of the scenarios will be tested to efficiency.

However water efficiency can be measured in multiple criteria, these are called the design

criteria. Ultimately, the improvement of the ‘Quality of life’ is basically the main issue.

4.1 Long term effects

Logically in 2040 some others effects are at play then in 2014. The long term effects are for

instance the autonomous developments up to 2040. This means without any influence by the

ADB PPTA. Planned activities not executed by M.C.D.C. are also included in the list of long term

effects as given below, since these planned activities by for instance Madaya City Council will

happen in any case.

Climate change effects in the Sedawgyi Irrigation Network region;

Reduced return flow to surface water up to 37% in urban areas. As a result of two

processes, such as the increase in urban density and increase of asphalt cover;

Mandalay has increased to approximately 2.3 million inhabitants;

Madaya has increased to about 0.1 million inhabitants and is connected to the Sedawgyi

Reservoir. The NRW- losses are assumed to 25%, mostly commercial.

For support of the long term effects, which are not treated in the main report, see Appendix

I- F.1.

4.2 ADB PPTA Plans

The ‘ADB PPTA’ already has many existing design plans for 2040 to improve the urban

services in Mandalay. The urbanization, public welfare and population increase for Mandalay in

2040 result in significantly higher demands for water that cannot be covered by the existing

system. In Appendix I-F.2, the support information of these plans is presented further. The

following list summarizes the long term design plans.

‘M.C.D.C’ and ‘ADB PPTA’ have increased the total coverage for water supply to 95% in

Mandalay (= ±2.19 million people)

Mandalay has increased usage of surface water to 47%, which is equal to ca 150000 m3

per day (ca. 68 l/capita/day).

‘M.CD.C.’ and ‘ADB PPTA’ have reduced Mandalay’s NRW-losses to 10%

4.3 Design criteria

The improvement of water usage efficiency in 2040 is considered the main goal of the

scenarios. However, the goal is still quite ambitious, so a more specified classification is

required. This is achieved by setting some design criteria, in order to satisfy a clear distinction

between the outcomes of the scenarios. The design criteria are divided in ‘hard’ and ‘soft’

criteria.

The hard design criteria are physical and easily measured:

Reservoir volume

Reservoir spillage

Net in- and out-flow of the reservoir

Generation of hydropower

Actual cultivation areas

Supply/demand ratios for cultivations

Irrigation efficiency

Supply/shortage for PWS

Continuous flow in the moat canal

The soft criteria are harder to measure, since they are a reflection of the ‘Quality of life’.

Obviously this is somewhat vague, but these criteria describe the required effect at best.

Clean drinking water

Continuous distribution of water

No flooding of the urban areas

Mandalay Green City

More variety in cultivated crops and food

Beautification of Mandalay

Reservoir should never be empty

Although not all of these criteria can be modelled with RIBASIM, yet they still have a

major influence in improving the ‘Mandalay Urban Services’. In Appendix I-C , these criteria are

covered more extensively, because there originated from the ‘Green Cities’ ideology by ‘ADB’


Haarlem Hydraulics & Technical University of Delft | Scenarios 37

4.4 Constructing the scenarios

All the scenarios consist out of options, i.e. single measures to improve the water usage

efficiency regarding the design criteria. As mentioned previously, these options are potential

designs or ideas. All these potential options have been collected during the feasibility study done

by the ‘ADB PPTA’. The corresponding information has been acquired by discussing with a

variety of stakeholders, i.e. ‘M.C.D.C., ‘ADB PPTA’ - members and Irrigation Department. In table

X a list is given of all scenarios and their intended results. The first two are standard scenarios

that are applied in every single model, for calibration and visualization of the problems in 2040.

The third scenario is the ‘ADB Reference Case’. In this scenario all the ‘ADB PPTA’ plans for

Mandalay have been implemented. The probability that these plans will be executed is quite

high. At the same time these ‘ADB’ Plans are to increase the ‘Quality of Life’ in and around

Mandalay, which results in a higher demand for water. Therefore this scenario is also applied as

a reference case for the other potential or conceptual scenarios. The ideology behind all

scenarios are given in Appendix I-F3

Index Scenarios Time Description Intended results

1 Base Case 2013 to 2014

Current situation -Visualizing the problems -Calibrating the model

2 Do Nothing Case (DNC)

2035 to 2040

All autonomous long term effects are in effect.

-Visualizing the problems if no action is undertaken -Comparing the other scenario’s

3 ADB Reference Case

2035 to 2040

-Including all long term effects -Including all ADB PPTA Plans

-Increase welfare -Reduce losses -Increased water demand

4 Sustainable Urban Drainage System (SUDS)

2035 to 2040

Construct SUDS in Mandalay and Madaya

-Improve drainage to increase return flow to surface water -Reduce flooding and water spillage - Beautification of Mandalay

5 Capacity Training Agriculture (CTA)

2035 to 2040

Increase the irrigation efficiency by improving the material and capacity of irrigation

- Increased efficiency -More welfare farmers

6 Secondary Open Channel (SOC)

2035 to 2040

-Construct an secondary open channel to redirect flood water from Shan Plateau to the Mandalay Main canal -Redistribute the water over the Southern Sedawgyi Irrigational Area.

-Reduce flood risk -More water supply -Increased cultivation areas

7 Separation of Water Resources Systems (SWRS)

2035 to 2040

-Irrigation area gets solely supplied by Sedawgyi Dam -Mandalay is supplied solely by other sources

-Reduce water demand

Figure 12 Summary of the scenarios © 2014, ADB PPTA & M.C.D.C. , Mandalay

Scenario 1. ‘Base Case’

The ‘Base Case’ scenario is applied to visualize the current situation of the Sedawgyi

Irrigation Network. Also it is used for the calibration of the model settings.

Scenario 2. ‘Do Nothing Case’

In this case only the autonomous long term effects applicable in 2040 are simulated. The

modelled changes are: climate change, Madaya is added to the Sedawgyi Water

Resources system, and urbanization of Mandalay. Due to the long term effects, a decrease

in all supply is expected, since the drought has increased significantly.

Scenario 3. ‘ADB Reference Case’

In this case the three long term plans of ‘M.C.D.C.’-‘ADB-PPTA‘ have been included. The

growth of Mandalay is corresponding with the increased water demand. This increased

demand needs to be covered throughout Mandalay by increasing the network coverage,

decreasing NRW and increasing the reliability of the surface water delivery. This could

potentially be done from the rivers, or from the Sedawgyi reservoir. In any case, the

demand for PWS will increase, which will result in a lower supply/demand ratio for the

cultivated areas.

Scenario 4. Sustainable Urban Drainage

Systems

Since SUDS will increase the soil

permeability and the drainage, the

return flow to the surface water will

increase in the urban areas to 75%.

SUDs also aim to reduce flooding in the

city and beautify the city. However, it is

not expected to make a large difference

for the water resources system as such.

Scenario 5. Capacity Training Agriculture.

By improving skills, materials,

irrigation techniques and capacity of

the farmers, there could be a significant increase of the total irrigation efficiency. As a

result, a large increase in cultivated area may happen, since the specific water demand is

expected to lower in such case.

Scenario 6. Secondary Uncontrolled Inflow (SUI)

In this scenario an open channel will capture the flood flow from the Shan Plateau and

redirect it for irrigational purposes in the Southern Sedawgyi irrigation areas. Therefore

a lower water demand for the southern area will lead to more water availability in the

remaining areas.

Scenario 7. Separation of the water resources systems (SWRS).

Mandalay City will solely be supplied by groundwater and surface water resources, but

not from Sedawgyi Water Resources system. If all Sedawgyi water can be used for

irrigation, the water supply/demand ratio is expected to increase.

Figure 13 Artist Impression SUDS in an urban area © 2013, ADB, Manila


Haarlem Hydraulics & Technical University of Delft | Simulations with RIBASIM 39

5 Simulations with RIBASIM The simulations with RIBASIM were performed to get some insight into the feasibility and

impact of all the scenarios on the water resources system. The scenarios were only assessed on

basis of the design criteria. First is the ‘Base Case’ simulation; second is the ‘Do Nothing Case’-

scenario, including all the autonomous long term effects. Third is the ‘ADB Reference Case’ in

which all long term plans of the ‘ADB PPTA’ are included. Since this case serves as the reference

case, all the resulting scenarios will be modelled including these ‘Long Term Plans’. Finally, all

resulting scenarios, including the long term effects and the long term plans by ‘ADB’, will be

simulated. All the results of the simulations are treated in the next chapter. However, the results

of the ’Base Case’ will be handled in this section, since it is required for the calibration of the

model. All the scenarios will only be discussed briefly in the main rapport, and more extensively

in Appendices I-G & II-C.

5.1 Base Case

The ‘Base Case’-scenario is applied for calibrating the model. This fine tuning of the model

can be done by adjusting the water allocation and priorities of certain nodes. The measured data

will be compared to the simulated data in order to reach a difference of max. 40%. The elements

that will be reviewed for calibration are the reservoir volume [m3], hydropower generation

[GWh] and the Actual cultivated areas [ha].

5.1.1 Measured data

The measured data are provided by multiple instances as M.C.D.C. or the ID. In the table

below a guide for finding the data files are given.

Description Location in report

Volume in reservoir [m3] Appendix CD Hydropower generation [GWh] Appendix CD

Cultivated areas Appendix II-B4 & C1 Figure 14 guide for report

Cultivated areas have planned values by the ID and actual measured values. For every

single node, the highest of the two values is applied. So most nodes have the planned value as

input and the lowest measured values are simulated. However, in the Shwe-Ta-Chaung DY2 area,

located in the Patheingyi rainfall area, a higher measured value than planned by ID was

observed.

5.1.2 Calibration

The calibration is done to minimalize the difference between the measured data and the

simulated data. Volume in the reservoir, hydropower and cultivated areas in 2013-14 are the

applied measurement values for calibration. The calibration settings are given in tables C.1, C2,

C3 in the Appendix II. The calibration results are in Appendix II-C.4 and C5 and summarized in

the main report.

The approach in the calibration is to allow maximum differences of about 40% to 60%.

This maximum difference has been achieved for any node with the given settings. Although there

is an acceptable fault margin, since the corrupted data do not allow a high accuracy. Also the

random releases of water by the Sedawgyi Dam Staff can’t be modelled.

In figure 15, the reservoir volume over time is shown. As visible in the graph the

simulated reservoir level follows the measured level, but some differences are quite severe. It is

also clearly visible that the calibration is more accurate in 2013. The part in 2013 is more

significant to the 2014, because the data for 2014 were partly measured, partly extrapolated.

The differences were expected, since they are caused by the initial water demand of the nodes in

January. As the differences are reasonably acceptable, these calibration settings are applied in

the model. In Appendix X the calibration results are given, including their accuracy.

Figure 15 Calibration results Reservoir Volume © 2014, Own, Mandalay

Regarding the simulated generated hydropower in Appendix II-C.5, it is noticeable that it

has many deviations of the measured values. These are caused by different initial settings for

releasing the water demand in real life and simulation. The Sedawgyi dam releases water in real

life for irrigation purposes by opening the head sluice gates. Therefore the flow through the

turbines does not increase, so the measured turbine generation does not increase. Within

RIBASIM all the water is either flowing through the turbines or is spilled over in the case of ‘Full

Reservoir Level’, but it is not possible to randomly release water. Therefore, the initial peak is

caused by the instant water demand for irrigation purposes by the model, which all flow directly

through the turbines and result in a high generation of hydropower.

In the remaining time steps it is visible that the fluctuations of the measured values are

caused by human interventions. The RIBASIM simulated data are controlled by the FIRM level

and target level. The FIRM level is a measure to control the water outflow by having a minimum

required storage for downstream demand. The target level is the most optimal level in which the

turbines operate the most optimal, with the least amount of losses.

Consequently, this all results in high fluctuations of the measured hydropower

generation and the more controlled RIBASIM simulated values, as is visible in figure 16.

-2,00E+02

-1,00E+02

0,00E+00

1,00E+02

2,00E+02

3,00E+02

4,00E+02

5,00E+02

6,00E+02

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49

Rsv

Vo

lum

e [

Mm

3]

Timesteps [ts], 1 year = 24 ts

Calibration Sedawgyi Reservoir 2013-2014

Measured Data

Simulated Data

Difference


Haarlem Hydraulics & Technical University of Delft | Simulations with RIBASIM 41

Figure 16 Calibration results Generated Hydropower © 2014, Own, Mandalay

The cultivations have been modelled to have the planned agricultural area as an input and

the measured value as an output. By adjusting the settings for priorities and allocations, the

simulated values must be in an accuracy of ±40% to the measured values. The settings for

calibration 4.4 resulted in the most optimal simulation with the highest accuracy. So these

settings will be applied during the modelling of the scenarios. In Appendix II-C, the calibration

settings and results are given.

5.2 Do Nothing Case

The ‘Do Nothing Scenario’ is applied as a case to give a clear insight of the potential

benefits of the scenarios in the period from 01-01-2039 up to 12-12-2040, in which all of the

settings remain the same as the ‘Base case’-settings, but the long term effects, mentioned in

chapter 4.1, are included. The adaptations and input for the model to include long term effects

are in Appendix I-G2.

5.3 ADB Reference Case

This scenario is similar to the ‘Do Nothing Case’. However, now the long term plans of the

ADB, which are most certain to be finished before 2040, are included. The changes made in the

settings are in Appendix I-G3.1.

5.4 SUDS The settings are similar to the ‘ADB Reference Case’, but the settings for the return flow to

the surface water have been set to 75%, which is a default setting. See Appendix I-G.3.2.

5.5 CTA

The basic settings are again similar to the ‘ADB Reference Case’. The field Irrigation

efficiency is increased step by step to 90%. Although this value is somewhat large, it does give a

more clear representation of the differences with previous scenarios and the maximum benefits

that could be achieved. See Appendix I-G.3.3.

0,00

2,00

4,00

6,00

8,00

10,00

12,00

1 4 7 10 13 16 19 22 25 28 31 34 37 40

Hy

dro

po

we

r [G

Wh

]

Timesteps [ts] 24 ts= 1 year

Calibration Generated Hydropower

Measured

RIBASIM

5.6 SOC

The settings are similar to the ‘ADB Reference Case’. Yet there is a secondary channel

along the east of Mandalay Main Canal in order to capture flood flow coming from the Shan Hills.

This water is redirected into the Sedawgyi Irrigation Network, so it can be used as new inflow

for the water resources system. See Appendix I-G.3.4.

5.7 SWRS

Here the basis settings are similar to the ‘ADB Reference Case’ as well. Only in this model

the nodes that indicate Mandalay have been removed since Mandalay’s PWS will not come from

Sedawgyi anymore. See Appendix I-G.3.5.


Haarlem Hydraulics & Technical University of Delft | RIBASIM results 43

6 RIBASIM results The results will be presented per hard design criteria. The sequence of the criteria, first for

the Sedawgyi Reservoir, is the reservoir volume, spillage, net flow and generated hydropower.

Second is agriculture, in which the actual cultivated area and irrigation efficiency are compared.

Third is the public water supply for Mandalay and Madaya. Final is the moat supply/demand

ratio. All of the large ‘Excel’-files are included on the Appendix CD. Since, all of the graphs and

the corresponding analyses are in the main report, only the irrigation efficiency is treated in

Appendix II-D.1.

The periods considered for comparison are 2013-2014 for the ‘Base Case’, and 2039-2040

for the other cases. One time-step is equal to half a month (15 or 16 days), leap years are

included.

6.1 Sedawgyi reservoir volume

The volume of the reservoir over time per scenarios is given in graph x.

Figure 17 Sedawgyi Reservoir Volume © 2014, Own, Mandalay

As visible, there is a clear distinction in volume between 2013-2014 and 2039-2040. This

is difference is caused by the settings of the model for maintaining the reservoir volume

between FRL-volume and target level volume, which are 448 M m3 and 340 M m3, respectively.

Dead storage level is equal to the minimum intake level at 111 m, with a dead storage volume of

104 M m3, but is never reached. The FRL is exceeded multiple times, resulting in some spillage.

Also it is clear that the random releases for irrigational purposes are not in the model. Only the

expected releases corresponding to the hydropower demand are executed. As a result this will

decrease the water supply available for downstream demands.

0,00

50,00

100,00

150,00

200,00

250,00

300,00

350,00

400,00

450,00

500,00

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49

Volume [m3]

Timesteps 1ts=half month

Sedawgyi Reservoir Volume

BC

DNC

ADB

CTA

SOC

SWRS

6.2 Reservoir spillage

The spillage at Sedawgyi for all scenarios is shown in figures 18 and 19.

Figure 18 Spillage at Sedawgyi for the years 2013-2014 and 2039-2040 © 2014, Own, Mandalay

Figure 19 Yearly spilled flow at Sedawgyi for the years 2013-2014 and 2039-2040 © 2014, Own, Mandalay

In both figures it is visible that the amount of spillage will increase significantly in the long

term. This is basically a direct result of climate change. During the drought period the

precipitation has decreased by 35% compared to 2013 data. In the rainy season the

precipitation in 2040 has increased by 10%. The water is accumulated in the dry periods for

hydropower production, but during the rainy season not enough water can be released through

just the turbines. Thus the water gets spilled over the spillway.

0,00

50,00

100,00

150,00

200,00

250,00

300,00

350,00

400,00

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49

Flo

w S

pil

led

[m

3/

s]

Timesteps

Sedawgyi Reservoir Spilling per scenario

BC

DNC

ADB

SUDS

SOC

SWRS

BC DNC ADB SUDS SOC SWRS

Total Spillage 2014/2040 3,27 693,25 692,38 693,19 691,98 696,63

Total Spillage 2013/2039 397,61 666,46 666,46 666,46 666,46 666,46

0,00200,00400,00600,00800,00

1000,001200,001400,001600,00

Flo

w [

m3

/s]

Sedawgyi Reservoir Spilling per scenario



6.3 Net flow in water resources system

The total inflow over a year into the reservoir is compared with the flow downstream of

the reservoir. The total net flow per scenario is given in figure 20.

Figure 20 Net flow at Sedawgyi Reservoir for the years 2013-2014 and 2039-2040 © 2014, Own, Mandalay

The high peaks for the net flow, for the cases ‘Secondary Open Channel’ and ‘SUDS’, are

corresponding to the high spillage peaks in the previous graph. In which the negative net flow

correspond to large releases in these time steps. Vice versa the positive net flow is the filling up

of the reservoir. The reason, for clustering of the scenarios ‘SOC’& “SUDS’, is due to similarity in

releasing large volumes of water. All the scenarios have the same inflow of the reservoir, but the

total downstream releases differ. So the high peaks are negative sign for water usage, because

the other models do not need as much water from Sedawgyi reservoir.

-400,00

-300,00

-200,00

-100,00

0,00

100,00

200,00

300,00

400,00

500,00

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Netflow [m3/s]

Timesteps

Net flow Sedawgyi Reservoir

Base Case 2013-2014

DNC 2039-2040

ADB 2039-2040

SUDS 2039-2040

CTA 2039-2040

SOC 2039-2040

SWRS 2039-2040

6.4 Generation of hydropower

An overview of the generated hydropower is given in figure 21.

Figure 21 , Generated hydropower for the years 2013-2014 and 2039-2040 © 2014, Own, Mandalay

There are some large differences, yet the shape is quite similar. Since, the power demand

has a high allocation and most of the water flows through the turbines, it is visible that the

settings of the model try to remain the water reservoir volume at the given target demand for

hydropower. Also there are no peaks corresponding to human activities. Unless more water

flows through the turbines to release water into the downstream, the peaks correspond to the

reservoir volume at full reservoir level and at the time steps in which the spillage is high. Also

the high peaks for generation of hydropower correspond to the high inflow at Sedawgyi

reservoir. Thus not all water is used efficiently, because the outflow through just the turbines for

generation of hydropower is not sufficient and water gets spilled.

0,00

2,00

4,00

6,00

8,00

10,00

12,00

14,00

0,0

0

3,0

0

6,0

0

9,0

0

12

,00

15

,00

18

,00

21

,00

24

,00

27

,00

30

,00

33

,00

36

,00

39

,00

42

,00

45

,00

48

,00

Generated Hydropower

[GWh]

Timesteps

Generatad Hydropower

BC

DNC

ADB

SUDS

CTA

SOC

SWRS



0,00

1000,00

2000,00

3000,00

4000,00

5000,00

6000,00

7000,00

He

cta

res

Distributaries

Cultivated Areas Sedawgyi Irrigation Network

Total Planned AreaBase CaseDO Nothing CaseADB Reference CaseSUDS CaseCTA CaseSOC CaseSWRS Case

6.5 Actual cultivation areas

In figure 22, an overview is given of all maximum actual cultivations per distributary per

scenario in the periods 2013-2014 and 2039-2040.

Figure 22 Actual cultivations per distributary per scenario in the periods 2013-2014 and 2039-2040 © 2014, Own, Mandalay

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Supply Demand ratios in Sedawgyi Irrigation Network

Base Case

Do Nothing Case

ADB Reference case

SUDS

CTA

SOC

SWRS

Clearly distinguishable in the graph is that the cultivated areas will decrease if nothing is

done. There are some scenarios to reduce the total decrease. This decrease in water cultivated

areas is a direct effect of the lower availability of water as a result of climate change. Yet it can be

seen that the ‘CTA’ scenario, the ‘SOC’- scenario and the ‘ADB Ref Case’ have the most influence

regarding maintaining the cultivated areas and even an increase in a few distributaries, but most

increases will lead to a decrease elsewhere. The ‘SUDS’ scenario and ‘SWRS’ do not have a large

influence to reduce the decrease and are both nearly similar to the ‘Do Nothing Case’.

6.6 Supply/demand ratios for cultivations

In the graph underneath the supply/demand ratios per distributary per scenario are shown for

the period 2013-2014 and 2039-2040.

Figure 23 Supply demand Ratios for Sedawgyi Irrigation network © 2014, Own, Mandalay



In the period 2013-2014, there is significantly more water available for water supply for

irrigation purposes. The increase of the total water demand for Mandalay and the corresponding

urbanization and population growth in 2039-2040 clearly result in a decrease of water supply

for irrigation purposes. Even more, considering climate change that reduces the total water

availability. These two aspects definitely form the major issues regarding the long term water

resources.

The scenarios ‘CTA’ and ‘SWRS’ clearly have the best supply demand ratio regarding the

long term measures. This is logical, because for the ‘CTA’ the irrigation efficiency has been

increased significantly. For the ‘SWRS’- scenario, the large demand by PWS of Mandalay has

been removed. Thus all the water is available for irrigational purposes. Still it is not enough,

since none of the cultivations received 100 % supply-demand. The low supply demand ratios

correspond to the actual cultivation growth in figure 22. These cultivations grew not even close

to the planned cultivated areas by the ID.

6.7 Irrigation efficiency

The irrigation efficiency is the same for all cases, except for the ‘CTA’-case. In this case the

field irrigation efficiency has been increased to 90%. The total irrigation efficiency consists of

three efficiencies, first ‘Field Irrigation Efficiency’, second ‘Normal Period Irrigation Efficiency’

and third ‘Surface Water Conveyance’; this is explained in Appendix I-E.2.6.

BC DNC ADB SUDS CTA SOC SWRS

Gross Supply [Mcm] 13437,7 42476,9 42073,7 42364,2 37967 43351,8 45665,7

Effective Supply [Mcm] 5662,1 13932,6 17765 17897,4 28943 18313,7 19321,3

Overall Irrigation efficiency 42,1 42,2 42,2 42,2 76,2 42,2 42,3

Table 12 Irrigation Efficiency per scenario © 2014, Own, Mandalay

The results in table 12 prove that the scenario ‘CTA’ indeed has a lower gross supply and a

significantly higher effective supply. This higher efficiency was also clearly visible in the graph

for Actual growth of cultivation as well in graph for supply/demand ratios for cultivations.

6.8 Resources for PWS

In the figures 24 and 25 are the Public Water Supply for Mandalay and Madaya are

presented.

Figure 24 Supply and Shortage in Mandalay in the year 2013-2014 and 2039-2040© 2014, Own, Mandalay

In the PWS for Mandalay shortage is the difference between demand and supply. The

demand increases significantly over time, due to the increasing population in the ‘DNC’. Even

though the demand is still based on the same amount of people in the ‘Do Nothing Case’, the

demand per person per day will increase in the long term. Because the network coverage and

thus the NRW are not improved the total of inhabitants served with water is similar.

For all the other cases, the ADB plans for Mandalay have been executed. This results in a

similar demand for water and also a similar division between supply and demand. In the ‘CTA’-

scenario there is more water available for water supply. The other cases don’t have much effect.

The ‘SWRS’- scenario is obviously zero, since Mandalay is supplied by other means than

Sedawgyi Reservoir.

BC DNC ADB SUDS CTA SOC SWRS

Average Monthly Shortage 2014-2040

0,01 0,14 0,65 0,65 0,41 0,65 0,00

Average Monthly supply 2014-2040

0,31 0,34 1,27 1,26 1,50 1,27 0,00

Average Monthly shortage 2013-2039

0,05 0,16 0,69 0,69 0,56 0,70 0,00

Average Monthly supply 2013-2039

0,27 0,33 1,22 1,22 1,36 1,22 0,00

0,000,501,001,502,002,503,003,504,004,50

Flow [m3/s]

Average monthly flow for supply and shortage Mandalay



Figure 25 Supply and Shortage in Mandalay in the year 2039-2040© 2014, Own, Mandalay

In figure 25 one could see that Madaya has such a low demand that all of it is supplied. Some

water flows back with return flow towards the surface water system. This was even increased

with by the SUDS scenario. There is no ‘BC’-scenario for Madaya since it was not yet connected

in 2013 – 2014.

6.9 Continuous flow in the moat canal

Since it is not allowed for the moat to vary a lot in water level, it must have a continuous

flow in the channel. This is modelled as a continuous flow of 10 m3/s and is shown in figure X.

Figure 26 Supply shortage for the moat canal in 2013-2014 and 2014-2040 © 2014, Own, Mandalay

DNC ADB SUDS CTA SOC SWRS

Average Monthly Shortage 2040 0,00 0,00 0,00 0,00 0,00 0,00

Average Monthly Supply 2040 0,03 0,03 0,03 0,03 0,03 0,03

Average Monthly Shortage 2039 0,00 0,00 0,00 0,00 0,00 0,00

Average Monthly supply 2039 0,03 0,03 0,03 0,03 0,03 0,03

0,00

0,01

0,02

0,03

0,04

0,05

0,06

Yearly Supply & Shortage [m3/s]

Average Monthly flow supply and shortage Madaya

BaseCase

DNC ADBSUD

SCTA SOC

SWRS

Average MonthlyShortage 2013-2039

2,05 3,90 3,97 3,91 3,58 3,98 0,00

Average Monthly Shortage2014-2040

0,42 3,99 4,05 3,99 2,95 4,05 0,00

Average Monthly Supply 2014-2040

9,58 6,01 5,95 6,01 7,05 5,95 0,00

Average Monthly Supply 2013-2039

7,95 6,10 6,03 6,09 6,42 6,02 0,00

0,005,00

10,0015,0020,0025,00

Yearly Supply & Shortage [m3/s]

Average Monthly Water Supply-Shortage Moat

The demand is equal for all cases, because there is no variety per scenario. In the long term

it is clear that there is an increase in shortage. So fluctuations in water level will occur or a loss

of flow velocity.


Haarlem Hydraulics & Technical University of Delft | Conclusion and Recommendations

53

7 Conclusion and Recommendations The simulations are performed and the results analysed on basis of the hard design

criteria. So now some conclusions and recommendations will be formulated in this chapter. The

conclusions subsection will be done in a checkmark way and treat every point of interest

separately. First some basic conclusions about the modelling, later more specific conclusions per

scenario are presented.

7.1 Conclusions

The conclusions will start with the overall conclusions, then more into detail.

7.1.1 Overall

The surface water network of the Sedawgyi irrigation area and Mandalay city was

modelled in detail as a basis for the RIBASIM schematization. Information and data about

reservoir operation, hydropower production and reservoir releases on Sedawgyi

dam/reservoir were provided by the local Irrigation Department.

With this model a successful calibration was executed for the water resources conditions

in the Sedawgyi irrigation area and the public water supply for Mandalay city in the

years 2013 - 2014.

The model, not surprisingly, shows clearly that in 2040 as a result of the expected

population growth and increased urbanization, large water shortages will occur for both

public water supply and irrigation, if no additional corrective measures are taken (do-

nothing scenario)

The deterioration of the water supply situation will be strengthened by the expected

climate change effects in 2040.

The conclusion above results in low supply demand ratios, low actual cultivation growth

and more spillage. If no measures are undertaken to reduce these effects, some serious

issues will arise in the Sedawgyi Basin regarding Mandalay city and agriculture.

Some notes have to be stated about the scenarios. The increase dependency of surface

water for PWS in Mandalay will never occur as there are already plans to shift from the

present sources to more river water withdrawal, including for instance a new PWS plant

at the Dokhthawaddy. Nevertheless, the cases have been modelled this way, because it is

always a good modelling incentive to prove from the absurd/extreme values.

7.1.2 Scenarios

All results of the scenarios are discussed separately.

7.1.2.1 Do Nothing Case

It was clearly visible that in all results this case did not make any of the requirements.

The water supply is kept mostly in the reservoir and the water does not get allocated towards

downstream purposes. Obviously this leads to low supply/demand ratios for PWS, Moat,

agriculture etc.

7.1.2.2 ADB Reference Case

Large increase in the network coverage to 95%, a reduced NRW to 10% and increase

dependency on surface water coming from the Sedawgyi leads combined to a significant

increase in water demand. Yet there is still something to say about the 10% NRW, since the

commercial losses, for legalized supply, are not easily adjusted.

Results of this case are that more water is supplied to the PWS of Mandalay and Madaya,

which results in a lower supply for the remaining distributaries. However there is still some

water left for supplying a number of cultivated areas with higher priorities. In the lower

prioritized cultivated areas there are some losses in cultivated areas. This is also visible for the

supply demand ratios in the corresponding areas, which are relatively low in 2039 and 2040

compared to the current situation.

7.1.2.3 SUDS

Sustainable Urban Drainage Systems (SUDS) are strongly recommended to improve

urban drainage and flood management in and around Mandalay city, but will have a relative

small effect on the water resources/water supply conditions.

7.1.2.4 CTA

One of the most effective measures to improve the situation is to increase the irrigation

efficiency, reducing losses in the system and ensuring that irrigation water will be delivered at

the right moment and the right place. Although it is not easily done to convince farmers to apply

new materials and methods, but it is definitely something to consider. The results for a higher

efficiency are excellent. The gross supply is lower and efficient supply higher, so less losses in

irrigation. This corresponds to more water availability overall, which results in higher cultivated

areas and an increase in the potential supply for PWS.

7.1.2.5 SOC

A collector drain at the Shan plateau foothills is strongly recommended as it will be

effective to reduce the flooding problem in Mandalay city, but will not do much for the water

supply situation.

There is some visible increase in the Southern Sedawgyi Irrigation cultivated areas and

the corresponding supply demand ratios. But the increase is not significant. One of the design

flaws in the current model is that it has been modelled as an open channel, while a combination

with canal and detaining pond might be a better solution. In that way the water can be stored

and distributed more evenly over the drought period, instead of just a passing flood wave like in

the current model.

7.1.2.6 SWRS

This is actually the most realistic design, because the ADB PPTA has plans for Mandalay

to be supplied by other measures from surface water. These measures do not include water

supply from the Sedawgyi reservoir.

Separation of the Water Resources System of Mandalay and Sedawgyi is very effective

for increasing the cultivation areas and ensuring the city water supply. These cultivations react

correspondingly by having an acceptable supply demand ratio, if compared to the other cases.


Haarlem Hydraulics & Technical University of Delft | Conclusion and Recommendations

55

7.1.3 Miscellaneous Conclusions

The Asian Development Bank pays a lot of attention to stakeholder participation for

decision making in their projects. On October 18 Focus Group Discussions were held

about floods in the context of the MUSIP project. These meetings were attended by local

inhabitants of flood prone areas, community leaders, NGO’s and representatives of social

groups. One important statement they made was that sometimes areas and people get

flooded due to reservoir releases from Sedawgyi dam. This generally happens without

any warning, and in winter time when water levels are high already.

Floods caused by Sedawgyi reservoir releases generally occur in the North-Eastern parts

of town. Rescue service is provided by the government, but it would be better to provide

flood early warning. Further assistance is given by Red Cross and other NGOs.

7.1.4 Final Conclusion

The Asian Development Bank pays a lot of attention to stakeholder participation for

decision making in their projects. On October 18 Focus Group Discussions were held about

floods in the context of the MUSIP project. These meetings were attended by local inhabitants of

flood prone areas, community leaders, NGO’s and representatives of social groups. One

important statement they made was that sometimes areas and people get flooded due to

reservoir releases from Sedawgyi dam. This generally happens without any warning, and in

winter time when water levels are high already. It can be concluded that a study into an

improved operational scheme and better management of Sedawgyi dam/reservoir will be

necessary sometime in the near future.

Given the current operational settings of the Sedawgyi Dam, it clearly shows that in 2040

Sedawgyi Reservoir could not support both Public Water Supply and irrigation systems. So the

water resources systems of Mandalay and Sedawgyi Irrigation Network should be separated.

Sedawgyi will supply the irrigation and Mandalay will be provided by surface water of the

Ayeyarwaddy and Dokhthawaddy. The modelling results of this study support the choices made

by ‘ADB PPTA’.

If the irrigation efficiency is increased to 90% (i.e. In steps of 50% to 60% to ... to 90%) in

the long term (20 to 25 yrs.) high yields can be achieved, by investments in training, technology

and resources. This will also include lower losses and spillages in the water resources systems.

The current allocation of the dam is not efficient, in such a way that there still is a high

shortage of water supply in the downstream area of the Sedawgyi. In the future the allocation

settings of Sedawgyi Dam should be based upon a hydrological study and including the demands

of all stakeholders.

Since, the ‘ADB PPTA’ already is in a further stage, this study has to be acknowledged by

modelling their choices. So, the Separation of Water Resources System has already been

selected as definitive advice. The modelling results showed the same scenario as best combined

with the increased irrigation efficiency. However, now it is also known that some of the other

scenarios do not influence the situation as much. Yet they definitely have other positive effects

as well. M.C.D.C has to invest in improving the surface water cleaning treatment plans to have

sufficient clean and a secured continuous water availability for PWS of Mandalay. For achieving

high yields of crop productions and a variety in crops with a reducing availability of water by the

long term effects, a modernization of the applied irrigation methods and materials is necessary.

All of this in order to increase the total water usage efficiency in and around Mandalay and to

improve the quality of life.

7.2 Recommendations

It can be concluded from the statements above that a study into an improved operational

scheme and better management of Sedawgyi dam/reservoir will be necessary sometime in

the near future.

It can also be concluded that apparently it is not irrigation that has first priority in the

operation of Sedawgyi dam, but hydropower production. This is quite surprising since

during a visit to the dam in April the Irrigation Department staff claimed that the ID does

not get paid for the hydropower produced.

It is recommended that the allocation of the Sedawgyi will be based on a hydrological

model and stakeholders, instead of the current settings for allocations by the Sedawgyi

Dam

7.2.1 Final recommendation

The most optimal solution is separating the water resources systems for Mandalay PWS

and Irrigation and combine this for the Sedawgyi Network with the increased irrigation

efficiency. In this way the benefits of having the certainty that Mandalay is always supplied by

surface water and little groundwater and the benefits of applying an increased field irrigation

technology, will lead to a significant increase in crop production and cultivated lands.


Haarlem Hydraulics & Technical University of Delft | Evaluation of applied methods 57

8 Evaluation of applied methods The applied methods in this report consist of gathering information, apply it in RIBASIM

and finally to give an expert view of the simulation results. All three sections will be discussed

separately.

Since, the data was flawed, corrupted or missing, the resulting model had a rather low

accuracy. The time needed to receive the data took quite some time.

RIBASIM was an excellent program to model these situations. It is very clear and easy to use

and when stuck Wil van der Krogt has been a major help. The capacity training to the Burmese

people has not gone as expected, because the education level regarding modelling with

computer programs was fully lacking. There is definitely some ground to cover here for the

Burmese engineers.

After working with RIBASIM for three months, the differences in interpreting of the results

have become clear. Peter Kerssens, Wil van der Krogt and Gary Moys have had a big influence

with their expert view in analysing the results and conclusions.

Ultimately, the study has been a major success in aiding the choices made by the “ADB

PPTA” team. M.C.D.C. and ID do now have the model and after some additional workshops their

capacity should be increased to such a standard that they can adjust the model themselves.

Definitely not everything has been as accurate as it would have been in a western country.

However, if the education level increases, accordingly the data treatment capacity will improve

as well the modelling skills.

9 Assumptions All assumptions made during the current study are enlisted underneath:

Irrigation areas along the Mandalay Main Canal are included in other distributaries, because these could not be modelled otherwise.

Madaya area: MMC Seiktha Mandalay area: NA Patheingyi area: MMC 168 Minor Amarapura area: MMC Kinbak These adjustments led obviously to a too large irrigation area, but also a too large flow

through these links. Same is done for the Yenatha Canal Total applied area per crop sort within a distributary There is no real ratio applied at the Sedaw Weir, just based on downstream demand Simplification of some distributaries areas in to one large node, however this does not

lead to large losses of accuracy, because of the ‘Cropper ‘function within RIBASIM. Averaged demand for PWS of Mandalay is equal for every single person per township All PWS surface water supply is supplied by Sedawgyi Reservoir Simplification of NRW as a distribution loss. In the model there is no clear distinction

between commercial and physical losses. By applying some extreme values during modelling to enhance the differences

between scenarios. This has been done for: o Population growth o Climate change o Irrigation efficiency

10 Recommended topics for further investigation Looking in to the potential risk caused by flood waves in the Shan Hills towards the

irrigation network, since this was not possible within RIBASIM.

Investigate the back water effects of the Ayeyarwaddy in 2040 caused by increasing water

level at sea due to climate change

More intensified research with more detailed/accurate data of rainfall, water balance,

cultivations, etc

Research in to water quality in Ayeyarwaddy and main canals

Study the same basin with updated scenarios by the ‘ADB PPTA’


Haarlem Hydraulics & Technical University of Delft | Bibliography 59

11 Bibliography ADB PPTA. (2014, 07 03). MUSIP. Mandalay: ADB PPTA.

Asian Development Bank. (2012). Green Cities. (M. Lindfield, & F. Steinberg, Eds.) Mandaluyong

City, Philipines: Asian Development Bank.

Bithell, S. L., & Smith, S. (2011, may). The Method for Estimating Crop Irrigation Volumes for the

Tindall Limestone. Retrieved August 13, 2014, from http://www.nt.gov.au/:

http://www.nt.gov.au/

Casey, M. (2008, May 8). Why the cyclone in Myanmar was so deadly. Retrieved 09 4, 2014, from

National Geographic News:

http://news.nationalgeographic.com/news/2008/05/080508-AP-the-perfect.html

Chan, C., & Cheong, A. (2001). Seasonal weather effects on crop evapotranspiration and rice yield.

Seberang Perai: Malaysian Agricultural Research and Development Institute 2001.

Food and Agriculture Organisation of the UN. (2014). Food and Agriculture Organisation.

Retrieved August 12, 2014, from http://www.fao.org/home/en/

GeoNames. (2013). Retrieved 9 3, 2014, from GeoNames:

http://www.geonames.org/MM/largest-cities-in-myanmar-%5Bburma%5D.html

GeoNames Ambassadors. (2011). GeoNames. Retrieved 9 4, 2014, from

http://www.geonames.org/MM/largest-cities-in-myanmar-%5Bburma%5D.html

IPCC. (2007). Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of

Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on

Climate Change. In IPCC, Summary for Policymakers (p. 17). Cambridge: Cambridge

University Press.

Irrigation Department. (2014). Report on Sedawgyi Multipurpose Dam and Irrigation Systems.

Mandalay: Ministry of Agriculture and Irrigation.

Mann Htun. (2014). Mandalay District population in 2014. Mandalay: District General

Administration Department.

NASDAQ. (2014, august 28). Commodity Prices. Retrieved august 28, 2014 , from NASDAQ:

http://www.nasdaq.com/markets/commodities.aspx

Nauta, T., Krogt, W. v., Velden, C. t., Schellekens, J., Hasman, R., & Veen, J. v. (2014). Ribasim

development for major river basins in Myanmar. Delft: Deltares.

Roach, J. (2007, september 5). Bay of Bengal Faces Major Tsunami. Retrieved septermber 4,

2014, from National Geographics News:

http://news.nationalgeographic.com/news/2007/09/070905-tsunami-asia.html

Tin Oo. (02-09-2014). Predicted Design Flood Hydrographs for those mountanious streamlets &

rivulets. Mandalay: ADB PPTA.

World Weater and Climate Information. (2013). Average weather and climate in

Myanmar(Burma). Retrieved 9 4, 2014, from weather and climate: http://www.weather-

and-climate.com/average-monthly-Rainfall-Temperature-Sunshine-in-Myanmar-Burma


Haarlem Hydraulics & Technical University of Delft | List of tables 61

12 List of tables Table 1 List of abbreviations ......................................................................................................................................... 4

Table 2 Inhabitants of Mandalay in 2014 per township © 2014, Mann Htun, Mandalay ................. 15

Table 3 Estimation of population in Mandalay in 2040 ©2014, ADB PPTA, Mandalay .................... 16

Table 4Top 5 largest DY’s in the Irrigation Network fed by the MMC ©2014, Irrigation

Department, Mandalay ................................................................................................................................................. 19

Table 5 Climate Change in 2014 Mandalay © 2014, ADB PPTA, Mandalay ........................................... 22

Table 6 Four main areas of the network ©2014, Own, Mandalay .............................................................. 23

Table 7 Total area per crops produced in the SIN © 2013, own, Mandalay ........................................... 24

Table 8 Distributaries per rain measurement station © 2014, ID, Mandalay ....................................... 25

Table 9 Summary for supply of the water resources system, © 2013, ADB PPTA, Mandalay ........ 27

Table 10 Summary estimation demand Mandalay© 2014, ADB PPTA, Mandalay .............................. 29

Table 11 Characteristics Sedawgyi Dam © March2014, ID, Mandalay, ................................................... 30

Table 12 Irrigation Efficiency per scenario © 2014, Own, Mandalay ....................................................... 49

13 List of figures Figure 1 Boundary limits © September 2014, ADB PPTA, Mandalay ....................................................... 11

Figure 2 Sedawgyi dam irrigation network map, March © 2014 Irrigation Department ................ 14

Figure 3 Population growth rate © 2014, ADB PPTA, Mandalay ................................................................ 16

Figure 4 Topographic map of the project area ©2014, Google Maps & 2013 Maphill.com ............. 17

Figure 5 Locations and causes of flooding in Mandalay city ©2012, TEAM Consultants, Japan ... 19

Figure 6 Average minimum and maximum temperatures in Mandalay©2013, Weather and

Climate Information ....................................................................................................................................................... 20

Figure 7 Average precipitation in Mandalay ©2013, www.weatherandclimateinformation,com

................................................................................................................................................................................................ 21

Figure 8 : Time Series Analysis of annual Rainfall at Mandalay and DDF Curves, © 2014, ADB

PPTA, Mandalay ............................................................................................................................................................... 21

Figure 9Area/Capacity curve Sedawgyi Dam © 2013, ID, Mandalay ........................................................ 27

Figure 10 Water resources system per township and household©2013, ADB PPTA....................... 28

Figure 11 RIBASIM model of the Sedawgyi Irrigation Network © 2014, own, Mandalay ................ 34

Figure 12 Summary of the scenarios © 2014, ADB PPTA & M.C.D.C. , Mandalay ................................. 37

Figure 13 Artist Impression SUDS in an urban area © 2013, ADB, Manila ............................................ 38

Figure 14 guide for report ........................................................................................................................................... 39

Figure 15 Calibration results Reservoir Volume © 2014, Own, Mandalay ............................................. 40

Figure 16 Calibration results Generated Hydropower © 2014, Own, Mandalay ................................. 41

Figure 17 Sedawgyi Reservoir Volume © 2014, Own, Mandalay ............................................................... 43

Figure 18 Spillage at Sedawgyi for the years 2013-2014 and 2039-2040 © 2014, Own, Mandalay

................................................................................................................................................................................................ 44

Figure 19 Yearly spilled flow at Sedawgyi for the years 2013-2014 and 2039-2040 © 2014, Own,

Mandalay ............................................................................................................................................................................ 44

Figure 20 Net flow at Sedawgyi Reservoir for the years 2013-2014 and 2039-2040 © 2014, Own,

Mandalay ............................................................................................................................................................................ 45

Figure 21 , Generated hydropower for the years 2013-2014 and 2039-2040 © 2014, Own,

Mandalay ............................................................................................................................................................................ 46

Figure 22 Actual cultivations per distributary per scenario in the periods 2013-2014 and 2039-

2040 © 2014, Own, Mandalay ................................................................................................................................... 47

Figure 23 Supply demand Ratios for Sedawgyi Irrigation network © 2014, Own, Mandalay ........ 48

Figure 24 Supply and Shortage in Mandalay in the year 2013-2014 and 2039-2040© 2014, Own,

Mandalay ............................................................................................................................................................................ 50

Figure 25 Supply and Shortage in Mandalay in the year 2039-2040© 2014, Own, Mandalay ...... 51

Figure 26 Supply shortage for the moat canal in 2013-2014 and 2014-2040 © 2014, Own,

Mandalay ............................................................................................................................................................................ 51

sedawgyi water resources/irrigation system simulations

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