annex 1. trade-offs between hydropower and … · annex 1: trade-offs between hydropower and...

MK3

Optimising cascades of hydropower

AGRICULTURE & IRRIGATION

ANNEX 1.

TRADE-OFFS BETWEEN HYDROPOWER AND IRRIGATION DEVELOPMENT AND THEIR CUMULATIVE HYDROLOGICAL IMPACTS

A Case Study from the Sesan River

August 2013

Timo A. Räsänen. Olivier Joffre, Someth Paradis and Kummu Matti

MEKONG CPWF| Optimising cascades of hydropower (MK3) ANNEX 1: Trade-offs between hydropower and irrigation development and their cumulative hydrological impacts –A case study from Sesan River

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T A B L E O F C O N T E N T S

1 CROP WATER REQUIREMENT AND IRRIGATION SCHEDULE ....................................................... 2 1.1 Introduction .................................................................................................................................. 2 1.2 Data and Methods ........................................................................................................................ 2 1.2.1 Water balance in paddy fields .................................................................................................... 2 1.2.2 Crop evapotranspiration ............................................................................................................ 2 1.2.3 Effective rainfall ......................................................................................................................... 2 1.2.4 Rainfall and temperature data ................................................................................................... 3 1.2.5 Rice growth stage and crop coefficient ...................................................................................... 3 1.2.6 Soil type ...................................................................................................................................... 3 1.2.7 Irrigation scheduling .................................................................................................................. 3 1.3 Results .......................................................................................................................................... 4 1.4 Final remarks ................................................................................................................................ 5

2 SESAN CATCHMENT HYDROPOWER MODELLING ...................................................................... 6 2.1 Introduction .................................................................................................................................. 6 2.2 Hydropower development in the Sesan River basin .................................................................... 6 2.3 Data and methods ........................................................................................................................ 7 2.3.1 Data............................................................................................................................................ 7 2.3.2 Hydropower operations modelling ............................................................................................. 8 2.4 Results ........................................................................................................................................ 10 2.4.1 Reservoir shape ........................................................................................................................ 10 2.4.2 Hydropower plant energy production characteristics .............................................................. 11 2.4.3 Simulated discharge ................................................................................................................. 12 2.4.4 Simulated reservoir storage volumes ....................................................................................... 14 2.4.5 Simulated energy production ................................................................................................... 14 2.5 Final remarks .............................................................................................................................. 17

REFERENCES ..................................................................................................................................... 18


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1 C R O P W A T E R R E Q U I R E M E N T A N D I R R I G A T I O N S C H E D U L E

1 . 1 I N T R O D U C T I O N

Soil water balance for paddy fields was calculated using FAO CROPWAT 8.0 (Allen, et al., 1998 ) for 2001 to 2007. The main purpose of this soil water balance analysis was to calculate the rice crop water requirements and irrigation schedules for the wet and dry seasons for two sites that are supposed to be high suitable for paddy rice cultivation. The data and methodology used for water balance calculations together with the main results are explained in this report.

1 . 2 D A T A A N D M E T H O D S

1 . 2 . 1 W a t e r b a l a n c e i n p a d d y f i e l d s The water balance in a paddy field was calculated using field storage and water volumes entering and leaving the field. Field storage consisted of ponded water and soil moisture . The inflow to the field depended on precipitation , irrigation , surface inflow and seepage inflow , while the outflow depended on crop evapotranspiration , infiltration , surface outflow and seepage outflow . Therefore, the water balance equation was:

( ) ( ) ( )

( ) was the change of field storage and all terms were expressed either in millimetres or in cubic metres. The water balance for the paddy fields was calculated for the whole irrigated area at two locations for both the rainy and dry seasons.

In this study, surface drainage, runoff and seepage from one plot to another was assumed to be negligible since these parameters were not available at the time of the study. In Cambodia, paddy fields are characterised by high bunds without drainage and water is distributed and used very carefully. Therefore, consumptive use consisted principally of crop evapotranspiration and infiltration. Watanabe (1999) also reported that in a plot-to-plot irrigation system, water consumption consisted principally of total evapotranspiration and total infiltration. Hence, the supply terms are only precipitation and irrigation.

1 . 2 . 2 C r o p e v a p o t r a n s p i r a t i o n

Rice crop evapotranspiration ( ) is one of the most important factors for evaluating water consumption in paddy fields. In this study, was estimated using the single crop coefficient approach (Allen, et al., 1998):

where was crop evapotranspiration (mm/day); was crop coefficient; was reference evapotranspiration (mm/day), which was calculated daily by the FAO Penman-Montheith method using minimum and maximum temperatures. Other parameters were estimated using the temperature:

( ) (

) ( )

( )

where was net radiation at the crop surface (MJ/m2/day), is soil heat flux density (MJ/m

2/day),

is mean daily air temperature at 2 m height (°C), is wind speed at 2 m height (m/s), is mean saturation vapor pressure (kPa), is actual vapor pressure (kPa), is slope of vapour pressure curve (kPa/°C), and is psychrometric constant (kPa/°C).

1 . 2 . 3 E f f e c t i v e r a i n f a l l


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Effective rainfall was calculated using the USDA Soil Conservation Service for a decade (daily rainfall was aggregated per decade) as follows:

( )

for

mm

for

mm

1 . 2 . 4 R a i n f a l l a n d t e m p e r a t u r e d a t a The daily rainfall and temperature data required for paddy field water balance calculations were derived from a hydrological model calibrated for Sesan River catchment. We used two locations in the Sesan catchment to extract the rainfall and temperature data in order to account for differences in hydroclimate within the basin. Location 1 was in the central part of Lower Sesan basin in Cambodia and location 2 was in the central part of Upper Sesan basin in Viet Nam. The two locations reflected the hydroclimate of existing or potential future agricultural areas. The two locations were:

Location 1 (Cambodia): Latitude: 13.862 N Longitude: 106.616 E Altitude: 108 m

Location 2 (Viet Nam): Latitude: 14.444 N Longitude: 107.9 E Altitude: 600 m

1 . 2 . 5 R i c e g r o w t h s t a g e a n d c r o p c o e f f i c i e n t Two types of rice varieties were selected to determine crop water requirements and irrigation scheduling: a medium variety of 125 days for wet season rice and an early variety of 105 days for dry season rice. The growing date for wet season rice started on 15 May, while the growing date for dry season rice began 01 December at the selected sites. The root depth for these types of rice ranged from 30 centimetres to 70 cm. The crop is established by transplanting in Cambodia and by direct sowing in Viet Nam. Therefore, the nursery stage is only applicable to irrigation in Cambodia. Growing length and crop co-efficient (Kc) for both rice varieties for each stage of development were:

- Wet season rice (146 days): 21 days and Kc = 0.60-1.10 for the nursery stage, 60 days and Kc

= 0.50-1.10 for the vegetative stage, 25 days and Kc = 1.00-1.20 for the reproductive stage,

and 40 days and Kc = 0.70-1.05 for the late season stage.

- Dry season rice (119 days): 14 days and Kc = 0.50-1.00 for the nursery stage, 55 days and Kc

= 0.60-1. 05 for the vegetative stage, 20 days and Kc = 1.00-1.20 for the reproductive stage,

and 30 days and Kc = 0.70-1.00 for the late season stage.

1 . 2 . 6 S o i l t y p e Soil type was assumed to be sandy loam for Site 1 (Cambodia) and loam for Site 2 (Viet Nam). Puddling depth was set to 0.30 m for both sites. Maximum percolation was set to 3.1 mm/day for sandy loam in Cambodia and 3.4 mm/day for loam in Viet Nam.

1 . 2 . 7 I r r i g a t i o n s c h e d u l i n g


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Irrigation was scheduled twice to prepare the land. The first application (pre-puddling) brought the soil to saturation and the second application (puddling) flooded the paddy fields. For each application, soil was refilled to saturation and then to a standing water depth of 100 mm.

It was assumed that wet season (rainfed) rice was not irrigated and dry season rice underwent a seven-day irrigation rotation of 100 mm each time. Irrigated water was distributed from plot to plot, which is typical of irrigation in Cambodia. Irrigation efficiency for both sites was set to 70 percent, bearing in mind unlined conveyance canals and plot to plot irrigation. Yield reductions due to soil moisture stress (percentage of the maximum production achievable in the area under optimal conditions) was not considered in this study.

1 . 3 R E S U L T S The rice crop water requirements and irrigation schedules were calculated for the wet and dry seasons from 2001 to 2007 for two sites in the Sesan catchment. The results of the calculation are presented in Table 1. Rainfall in Cambodia was found to be a little more than in Viet Nam. Similarly, evapotranspiration in Cambodia was generally higher than in Viet Nam. Irrigation for wet season rice in both locations was used only for land preparation (pre-puddling and puddling) and not to grow crops. Large amounts of water were needed during land preparation since there usually was not enough rainfall at the beginning of the growing season. Average water requirements for land preparation at the field level was 190 mm for Cambodia and 153 mm for Viet Nam. On the other hand, dry season cultivation was dependent on irrigation. Net irrigation requirements for each field in the dry season was 930 mm in Cambodia and 874 mm in Viet Nam, while the gross irrigation requirement was 1,328 mm in Cambodia and 1,248 mm in Viet Nam.

The annual requirement for water abstraction for irrigation in the Upper and Lower Sesan catchments averaged 16,000 m3/ha and 14,800 m3/ha, respectively, of which 2,200 m3/ha and 2,700 m3/ha were for wet season irrigation. The slightly higher irrigation demand in the Lower Sesan catchment resulted mainly from the different hydrometeorological conditions within the basin. The Lower Sesan catchment was on average warmer and drier that the Upper Sesan catchment. The weekly irrigation patterns for dry and wet season rice are shown in Figure 1A and the annual irrigation volumes in Figure 1B. The annual irrigation demand in the Upper and Lower Sesan catchments were lowest in 2002 (15,600 m3 per ha and 13,500 m3 per ha, respectively) and highest in 2003 (16,400 m3 per ha and 15,500 m3 per ha, respectively). Thus, the inter-annual variation was relatively small. An assumed irrigation efficiency of 70 percent resulted in annual water losses in the Upper and Lower Sesan catchments of 4,800 m3 per ha and 4,440 m3 per ha, respectively.


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Table 1 Water balance components for irrigation requirements in Cambodia and Viet Nam

Cambodia (mm) Viet Nam (mm)

Wet rice Rain Eta Perc Net Irri Gros irri Rain Eta Perc Net Irri Gros irri

2001 1657 475 495 188 268

1528 456 495 136 194

2002 1560 518 472 192 274

1554 465 537 153 219

2003 1856 522 537 191 273

1469 473 525 157 225

2004 1496 499 489 190 271

1510 470 535 155 221

2005 1692 493 496 191 272

1546 439 493 154 220

2006 1586 478 471 192 274

1688 450 558 151 216

2007 1255 501 543 186 266

1237 455 641 163 233

Avg. 1586 498 500 190 271 1505 458 541 153 218

Dry rice 2001 48 421 387 913 1304

159 376 394 765 1093

2002 45 439 387 934 1335

22 393 395 912 1303

2003 32 429 387 934 1335

48 380 423 901 1287

2004 10 450 391 965 1379

27 399 395 909 1298

2005 26 433 392 931 1330

16 388 395 897 1282

2006 68 424 388 888 1268

56 377 394 845 1207

2007 20 431 388 941 1345

25 393 395 888 1269

Avg. 36 432 388 930 1328 50 386 399 874 1248

Figure 1. Estimated irrigation abstraction water requirements for the Upper (Viet Nam) and Lower (Cambodia) Sesan catchment on A) weekly and B) annual scales for transplanted irrigated dry and wet season rice.

1 . 4 F I N A L R E M A R K S

This report described briefly the methods used to estimate soil water balance for paddy fields. The calculation was performed without calibration. The results could be refined with observations about

0

500

1000

1500

2000

2500

1 5 9 13 17 21 25 29 33 37 41 45 49

[m3

/ha]

[week]

Cambodia

VietnamA

0

4000

8000

12000

16000

20000

2002 2003 2004 2005 2006 Avg.

[m3

/ha]

[year]

Cambodia

Vietnam

B.


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soil type, when applicable. This parameter determines the water consumption in paddy fields. It is important to note that the meteorological data used in this study were derived by interpolating observations at certain locations, and the rice crop evapotranspiration was calculated solely using the temperature. To more accurately estimate evapotranspiration, it would be better to use a full set of meteorological data. However, given the limitations to data availability in the study area, the results in this report can be used as a preliminary analysis.

2 S E S A N C A T C H M E N T H Y D R O P O W E R M O D E L L I N G

2 . 1 I N T R O D U C T I O N This paper describes the approach for modelling the hydropower operations in the Sesan River catchment. The purpose of this paper is to give an overall description of the methods and results. This work was done as a part of the CGIAR Challenge MK3 project in the summer and autumn of 2011. The purpose of MK3 is to study the various possible uses of reservoirs and the related effects on the Sesan River catchment. The objectives of the modelling presented in this paper were to 1) simulate baseline hydropower operations and 2) to establish a model setup for simulations and assessment for the multiple uses of water in hydropower reservoirs. The modelling was done using the distributed hydrological model, VMod, which is part of the broader modelling suite IWRM (Koponen et al., 2010). We also used the generalised dynamic programming tool, CSUDP (Labadie J, 2003). VMod simulated the catchment hydrology and provided inputs (mainly about discharge) to CSUDP. CSUDP in turn simulated the baseline hydropower operations as well as operations involving multiple uses of the reservoirs on a catchment scale. This provided estimates of the future baseline hydropower operation and a flexible approach to assess the multiple uses of a hydropower reservoir, such as the trade-offs between hydropower generation and irrigation. A similar approach was used by Räsänen, et al. (2012) to assess the hydrological impacts of hydropower development in the Upper Mekong basin. The methodology in this report was intended to give coarse assessments of future development options, and more detailed analyses would be needed before the development plans are implemented.

The modelling is described in five chapters:

Chapter 2.2 describes the hydropower development and modelled hydropower projects in

Sesan catchment

Chapter 2.3 describes the data, models and methodology

Chapter 2.4 describes modelling results of hydropower baseline operations

Chapter 2.5 gives the final remarks on the modelling work

2 . 2 H Y D R O P O W E R D E V E L O P M E N T I N T H E S E S A N R I V E R B A S I N The Sesan River catchment covers 18,684 km

2 and is shared by Cambodia and Viet Nam. The Sesan

River flows from the central highlands of Viet Nam to the lowlands of Cambodia, where it joins two other large rivers, the Srepok and Sekong, before discharging to the Mekong. The annual average discharge of Sesan is approximately 650 m

3/s (20.5 km

3) (Räsänen, 2011). The hydrology of the Sesan

River is presented in more detail in the 3S River basin VMod hydrological modelling report (Räsänen, 2011).

The Sesan River catchment currently has six operational hydropower dams and seven more planned or under construction (3S Basins, 2011). We considered 11 dams (Figure ,Table 2) in our model, and left out the O Chum 2 dam since it is not expected to significantly affect the catchment. The main characteristics of the 11 simulated hydropower projects in the Sesan catchment are given in Table 2. In our model, we also considered the Lower Sesan 2 dam, which is located downstream of the


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confluence of the Sesan and Srepok Rivers. Sesan 2 is the most downstream dam in the cascade and will be most affected by the upstream dams. The cascade of 11 reservoirs has a total regulating capacity equal to 15.2 percent of the total annual discharge of Sesan River.

Figure 2. The location of the hydropower projects in the Sesan catchment as in hydrological model, VMod.

2 . 3 D A T A A N D M E T H O D S A hydropower baseline was generated based on hydrological modelling and baseline hydropower operation modelling. The hydrological model, VMod, provided the discharge into each reservoir, which was then used as an input for dynamic programming tool, CSUDP. CSUDP estimated the baseline operations (decision to release or store water) of each hydropower project so that the energy production of each project was maximised. This generated a hydropower baseline with weekly data including water releases, reservoir water levels and energy production for November 2001 to October 2007. The model setup was used as the base for assessing the multiple-uses of water in hydropower reservoirs and the resulting catchment scale implications. The modelling with CSUDP is described in this report and the hydrological modelling was described in earlier report (Räsänen, 2011)

2 . 3 . 1 D a t a Data used for CSUDP consists of:

weekly discharge data at each dam location (Räsänen, 2011)

dam and reservoir characteristics (seeTable 2) (MRC, 2009)

hydropower production characteristics (seeTable 2) (MRC, 2009)

and the Digital Elevation Model (DEM) (Jarvis and Reuter, 2008)


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Table 2. Main characteristics of the 11 hydropower projects in the Sesan catchment (MRC, 2009).

Upper kontum

Plei Krong Yali

Se San 3

Se San 3A

Se San 4

Se San 1

Prek Liang 2

Prek Liang 1

Lower Sesan 3

Lower Sesan 2

Commission year 2011 2008 2001 2006 2007 2009 ? NA NA NA 2016

Active storage [mcm]

122.7 948 779 3.8 4 264.2 3.4 180 110 323 379.4

Reservoir area [km2]

7.4 53.3 65 3.4 8.5 58.4 10.6 11.9 7 414 394

Reservoir full supply level [m]

1170 570 515 304 239 215 141 515 330 150 75

Reservoir minimum supply level [m]

1143 537 490 303.2 238.5 210 140 496 310 147 74

Average flow [m3/s]

15.2 128 262 274 283 328.9 395 17.7 27.2 500 1304

Design flow [m3/s]

30.5 367.6 424 486 500 719 319 17.7 27.2 500 2119.2

Rated head [m] 904.1 31 190 60.5 21.5 56 32 168 153 58.5 26.2

Installed capacity [MW]

250 100 720 260 96 360 90 25 35 243 480

Mean annual energy [GWh]

1056.4 417.2 3658.6 1225 475 1420.1 479.7 186 189 1977 2311.8

2 . 3 . 2 H y d r o p o w e r o p e r a t i o n s m o d e l l i n g

Hydropower operations were simulated using the generalised dynamic programming tool, CSUDP (Labadie J, 2003). Hydropower operations refer here to decisions to store or release water at each reservoir. The CSUDP is based on discrete dynamic programming, which can be used to solve sequential decision problems such as hydropower cascade operations. Dynamic programming has been widely used to solve various water management decision problems (Labadie, 2004). In this modelling approach, the CSUDP was used to produce an estimate of the baseline operations of 11 hydropower projects at the Sesan River from November 2001 to October 2007. The goal was to maximise the total energy production of each project, beginning with the most upstream dam. We assumed that co-operation between the projects will be minimal since they are owned by different companies. However, the approach presented here models the hydropower projects as a cascade, where all the projects coordinate with each other. This modelling approach generated estimates of weekly energy production, water releases and reservoir storage volumes for each hydropower project.

The modelling of hydropower baseline operations with CSUDP consisted of the following steps:

1. estimating the reservoir shapes (volume-elevation-area relationships)

2. developing the energy rate function e(x) for each hydropower plant

3. estimating the weekly inflows to reservoirs

4. setting up the dams and reservoirs in CSUDP

5. maximising the energy production of the hydropower projects using CSUDP

In the first step, the reservoir shapes were estimated using DEM and dam characteristics. The energy production of hydropower plants is dependent on the available head, and the head varies according


9

to reservoir volume. Therefore, we need to know the relationship between the head and reservoir volume to make decisions about hydropower operations.

In the second step, an energy rate function e(x) (Equation 2) was developed for each hydropower dam using reservoir shapes and hydropower plant characteristics. e(x) is a function of reservoir volume x [million cubic metres] and it describes the energy production potential [megawatt/unit flow] of hydropower plants at all reservoir water level states n (n=200). e(x) contains information about plant capacity [MW], plant efficiency [-], head [m] and reservoir volume [mcm]. Thus, the energy production in CSUDP is dependent on e(x) and on the release decision. The efficiency of energy production at all hydropower plants was assumed to be 90 percent since there was no information available on actual efficiencies. This value would be high for old hydropower plants but reasonable for newer plants.

In the third step, the daily discharges at each reservoir location were estimated using the hydrological model, VMod (Koponen, et al., 2010). The hydrological modelling is described in more detail in the VMod hydrological modelling report (Räsänen, 2011). The daily discharges were converted to weekly discharges and then used as an inflow into reservoirs in CSUDP.

In the fourth step, the hydropower network, reservoir characteristics, e(x) and an objective function (Equation 1) was input into CSUDP. This was done using the graphical user interface of CSUDP and by developing a c-code. The objective function used in CSUDP typically maximises the total energy production of a hydropower cascade. In the hydropower baseline scenario, the objective function was used to maximise the energy production of individual hydropower projects. The objective functions for both cases can be understood from Equation 1 and Equation 2.

ijijjji uxe )(max 11

1

72

1 [MWh] (1)

where,

ijijijj xxxe 2)(

[MWh/unit flow] (2)

xij = reservoir volume [mcm] uij = release volume through turbines [mcm] α, β, γ = constants [-] i = number of time steps [i = 1…72] j = number of hydropower projects [j = 1…12]

In the fifth step, the CSUDP was used to optimise the baseline hydropower operations in order to produce maximal energy. The optimisation of individual hydropower projects with discrete dynamic programming is relatively simple but the optimisation of cascade operations is a multidimensional problem and requires the use of the DPSA (dynamic programming with successive approximation) feature of the CSUDP.

No constraints for reservoir water levels or releases were used in the optimisation procedure. In reality, there are constraints, for example, lower and upper boundaries for reservoir water levels and environmental flows. These constraints ensure that the reservoir is full at the correct times, that it can store water for flood protection and that there is adequate water in the stream to support environmental functions. Thus, the hydropower modelling approach can be further improved by using realistic constraints on reservoir storage levels and water releases. Although the hydropower modelling described here is somewhat simplistic, the approach gives a reasonable approximation of future hydropower operations. Further refinement of the modelling approach was not possible since there was not enough data. Still, the model can be used to assess future water management strategies in the Sesan catchment. CSUDP has been previously used to assess the hydrological impacts of hydropower development in the Upper Mekong basin by Räsänen et al. (2012).


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2 . 4 R E S U L T S

In this chapter, we present only some of the hydrological, energy production and reservoir shape and energy rate function results from the hydropower baseline operations. Our goal is to provide a general understanding of the outputs of the modelling approach. The presentation of the results focuses on the Yali, Lower Sesan 3 and the cumulative output of 11 hydropower projects. Final results and further analyses are presented in the main report.

2 . 4 . 1 R e s e r v o i r s h a p e Reservoir water level- surface area-reservoir volume relationships were estimated for Upper Kontum, Plei Krong, Yali, Sesan 4 and Lower Sesan 2 reservoirs. The relationship was not estimated for projects with smaller reservoir volumes. Instead, one of the five estimated relationships was adapted to smaller reservoirs according to similarity in reservoir slopes. Examples of reservoir shape parameters are presented in Table 3. They describe the estimated relationship between the reservoir water level, surface area and reservoir volume of the Yali reservoir. A graphical representation of the relationship between the head, volume and head-surface area of the Yali reservoir is shown in Figure 2.

Table 3. The shape parameters of Yali reservoir

base elev h A (km2) V (km3) head (m)

432 515 83 68.55783971 1.060038 0

432 512.5 80.5 58.63067168 0.902991 -2.5

432 510 78 49.18128697 0.7696 -5

432 507.5 75.5 42.33298183 0.659199 -7.5

432 505 73 38.54821147 0.558829 -10

432 500 68 29.14332609 0.389173 -15

432 495 63 19.595463 0.272379 -20

432 490 58 15.70672145 0.185869 -25

432 480 48 9.13669037 0.064489 -35

432 470 38 2.32546044 0.02096 -45

432 460 28 1.11287125 0.003209 -55

432 450 18 0.0858186 0.000527 -65


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Figure 2. The estimated A) head-volume and B) head-surface area relationship of the Yali reservoir.

2 . 4 . 2 H y d r o p o w e r p l a n t e n e r g y p r o d u c t i o n c h a r a c t e r i s t i c s An example of the energy production rate function e(x) is shown in numerical and graphical (Figure 3) forms below. The e(x) presented here is that of the Yali hydropower plant.

470423728136675.0000085.0)( 2 ijijijj xxxe [MWh/unit flow]

xij = reservoir volume [mcm] uij = release volume through turbines [mcm] i = number of time steps [i = 1…72] j = number of hydropower projects [j = 1…12]

Figure 3. Estimated energy production rate e(x) of the Yali hydropower plant. The e(x) describes the energy production potential per unit flow at different reservoir water volumes.

185

190

195

200

205

210

215

220

0 500 1000

Hea

d [

m]

Reservoir storage [mcm]

A) Volume [mcm] - head [m] relationship

185

190

195

200

205

210

215

220

0 20 40 60 80

hea

d [

m]

Reservoir surface area [km2]

B) Area [km2] - head [m] relationship

460

470

480

490

500

510

520

530

0 500 1000

Ener

gy [

MW

h]

Reservoir storage [mcm]

Energy rate function [MWh/ unit flow ]


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2 . 4 . 3 S i m u l a t e d d i s c h a r g e

Simulated weekly natural flow, inflow and reservoir release flow at the Yali and Lower Sesan 3 dams are shown in Figure 4. Natural flow refers to a scenario where there are no dams in the Sesan catchment, while inflow refers to flows into a reservoir that are regulated by upstream dam. Release refers to the combined turbine and spillway release.

Table 4 shows the water balance errors between simulated flow and announced flow (MRC, 2009) at all dam sites.

Figure 4. Simulated weekly natural, inflow and release flows at A) Yali and B) Lower Sesan 3 dam sites.

0

200

400

600

800

1000

1200

1400

1600

44

/20

01

4/2

00

2

16

/20

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28

/20

02

40

/20

02

52

/20

02

12

/20

03

24

/20

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36

/20

03

48

/20

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8/2

00

4

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/20

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32

/20

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44

/20

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4/2

00

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/20

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/20

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/20

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/20

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/20

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24

/20

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/20

06

48

/20

06

7/2

00

7

19

/20

07

31

/20

07

43

/20

07

[m3

/s]

ReleaseInflowNatural

A. Yali

0

500

1000

1500

2000

2500

3000

3500

44

/2…

4/2

00

2

16

/2…

28

/2…

40

/2…

52

/2…

12

/2…

24

/2…

36

/2…

48

/2…

8/2

00

4

20

/2…

32

/2…

44

/2…

4/2

00

5

16

/2…

28

/2…

40

/2…

52

/2…

12

/2…

24

/2…

36

/2…

48

/2…

7/2

00

7

19

/2…

31

/2…

43

/2…

[m3

/s]

ReleaseInflowNatural

B. Lower Sesan 3


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Table 4. Announced (MRC, 2009) and simulated VMod and CSUDP flows at dam sites and their water balance errors.

Dam site Announced flow (MRC,

2009)

Hydrological model

CSUDP regulated

flow

Water balance error between announced and

CSUDP [m3/s] [m3/s] [m3/s] [%]

Upper Kontum 15.2 15 15 -1.3

Plei Krong 128 103 102 -25.5

Yali 262 261 262 0.0

Se San 3 274 274 275 0.4

Se San 3A 283 286 287 1.4

Se San 4 328.9 321 323 -1.8

Se San 1 - 383 386 -

Prek Liang 2 17.7 52 53 66.6

Prek Liang 1 27.2 54 55 50.5

Lower Sesan 3 500 521 522 4.2

Lower Sesan 2 1304 1260 1276 -2.2


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2 . 4 . 4 S i m u l a t e d r e s e r v o i r s t o r a g e v o l u m e s

Figure 5A and Figure 6B show the simulated weekly active storage water volumes of the Yali and Lower Sesan 3 reservoirs. Figure 5A and Figure 6B also show the patterns of operation during different hydrological years. For example, the timing when the Lower Sesan 3 hydropower project starts to fill its reservoir varied over five weeks, from the first week of June to last week of July.

Figure 5. Simulated weekly active storage water volumes of A) Yali and B) Lower Sesan 3 reservoirs.

2 . 4 . 5 S i m u l a t e d e n e r g y p r o d u c t i o n

Figure 6A, Figure 7B and Figure 7C show the simulated weekly energy productions of Yali, Lower Sesan 3 and the total energy production of the 11 hydropower projects. Figure 7A and 7B show the simulated and announced (MRC, 2009) annual energy productions of Yali, Lower Sesan 3 and the total energy production of the 11 hydropower plants. Table 5 shows the announced (MRC, 2009) and simulated mean annual energy production of all hydropower plants.

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Figure 6. Simulated monthly energy production of A) Yali, B) Lower Sesan 3 and C) total of 11 hydropower projects.

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Figure 7. Simulated and announced (MRC, 2009) annual energy production of A) Yali and Lower Sesan 3 and B) total of 11 hydropower projects.

Table 5. Simulated and announced mean annual energy production of 11 hydropower projects

Announced (MRC, 2009)

[GWh]

Simulated [GWh]

Error [%]

Upper kontum 1056.4 1059.438262 0.3

Plei Krong 417.2 497.4752824 16.1

Yali 3658.6 3858.17107 5.2

Se San 3 1224.6 1229.821612 0.4

Se San 3A 475 454.909904 -4.4

Se San 4 1420.1 1480.814356 4.1

Se San 1 479.7 642.4839152 25.3

Prek Liang 2 186 237.993712 21.8

Prek Liang 1 189 314.6376476 39.9

Lower Sesan 3 1977 1692.337604 -16.8

Lower Sesan 2 2311.8 2222.915174 -4

TOTAL 13395.4 13690.99854 2.2

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2 . 5 F I N A L R E M A R K S

This report presented the modelling approach used to simulate the baseline hydropower operations in the Sesan catchment. The modelling approach is based on the distributed hydrological model, VMod, and the generalised dynamic programming tool, CSUDP. The models provided a description of hydrological processes as well as baseline hydropower operations in the Sesan catchment. The developed modelling approach and baseline simulations were found to be an acceptable tool for assessing the various uses of hydropower reservoirs. The modelling approach replicated the measured catchment hydrology relatively accurately. The simulated hydropower operations were found to be realistic and the simulated energy production corresponded well in most cases to actual energy production. The simulated hydropower operations with CSUDP are a purely mathematical optimisation result and it contains simplistic descriptions of the technical details of the reservoir, dam and power plant. If there were more data on technical details and operational policies of the simulated hydropower projects, the optimisation results would be more realistic. For example, knowing the lower and upper reservoir water level boundaries or details about planned operations would significantly improve the results.

The modelling approach did not consider the influence of hydropower projects on the Srepok River, upstream of Lower Sesan 2. The modelling approach restricts itself hydropower projects on the Sesan. Although the discharge from Srepok to Lower Sesan 2 was considered in the modelling, it was treated as natural discharge without regulation.

Despite the simplifications in the modelling process, our results concerning hydrology and hydropower operations are a reasonable baseline for assessing the multiple uses of hydropower reservoirs and their implications on a catchment scale. For other assessments, the modelling approach would have to be tweaked further and the results have to be presented appropriately. For example, relative changes referenced to the baseline are a better way to present results than absolute values. The modelling approach can be used for tasks such as identifying the conflicts and trade-offs between water users.

Although the modelling approach proved feasible, it is important to acknowledge that it is designed for a coarse scale scoping of the multiple use options of hydropower reservoirs on a catchment scale. The results are only indicative and cannot be used to justify development actions. Further analyses would be needed before development actions are implemented.


18

REFERENCES 3S Basins, 2011. 3Ss Basins - Sekong, Sesan and Sre Pok Rivers, Accessed 5.9.2011,

http://reta.3sbasin.org/.

Jarvis, A. and Reuter, H., 2008. Hole-filled SRTM for the globe Version 4. CGIAR-CSI SRTM 90m. CGIAR-CSI SRTM 90m database http://srtm.csi.cgiar.org. Accessed April 2010

Koponen, J., Lauri, H., Veijalainen, N. and Sarkkula, J., 2010. HBV and IWRM Watershed Modelling User Guide. MRC Information and Knowledge management Programme, DMS – Detailed Modelling Support for the MRC Project. http://www.eia.fi/index.php/support/download.

Labadie, J., 2004. Optimal operation of multireservoir systems: State of the art review. Journal of Water Resources Planning and Management 130: 93-11.

Labadie J, 2003. Generalised dynamic programming package: CSUDP. Documentation and user guide, version 2.44. http://modsim.engr.colostate.edu/csudp.shtml. Accessed 16 September 2010

MRC, 2009. Hydropower database. Mekong River Commission, Vientiane Lao PDR.

Räsänen, T., 2011. 3S basin VMod 3 km grid hydrological modelling report. Aalto University.

Räsänen, T.A., Koponen, J., Lauri, H. and Kummu, M., 2012. Downstream hydrological impacts of hydropower development in the Upper Mekong Basin. Water Resources Management, 26(11): 3495-3513.

3S BASINS (2011) 3Ss Basins - Sekong, Sesan and Sre Pok Rivers, Accessed 5.9.2011, http://reta.3sbasin.org/.

ALLEN, R. G., PEREIRA, L. S., RAES, D. & SMITH, M. ( 1998 ) Crop Evapotranspiration - Guidelines for Computing Crop Water Requirements. Irrigation and Drainage, Paper 56. Food and Agriculture Organization (FAO) of the United Nations, Rome.

JARVIS, A. & REUTER, H. (2008) Hole-filled SRTM for the globe Version 4. CGIAR-CSI SRTM 90m. CGIAR-CSI SRTM 90m database http://srtm.csi.cgiar.org. Accessed April 2010

KOPONEN, J., LAURI, H., VEIJALAINEN, N. & SARKKULA, J. (2010) HBV and IWRM Watershed Modelling User Guide. MRC Information and Knowledge management Programme, DMS – Detailed Modelling Support for the MRC Project. http://www.eia.fi/index.php/support/download.

LABADIE, J. (2004) Optimal operation of multireservoir systems: State of the art review. Journal of Water Resources Planning and Management 130, 93-11.

LABADIE J (2003) Generalised dynamic programming package: CSUDP. Documentation and user guide, version 2.44. http://modsim.engr.colostate.edu/csudp.shtml. Accessed 16 September 2010

MRC (2009) Hydropower database. Vientiane Lao PDR, Mekong River Commission.

RÄSÄNEN, T. (2011) 3S basin VMod 3 km grid hydrological modelling report. Aalto University.

RÄSÄNEN, T. A., KOPONEN, J., LAURI, H. & KUMMU, M. (2012) Downstream hydrological impacts of hydropower development in the Upper Mekong Basin. Water Resources Management, 26, 3495-3513.

http://reta.3sbasin.org/

http://srtm.csi.cgiar.org/

http://www.eia.fi/index.php/support/download

http://modsim.engr.colostate.edu/csudp.shtml

http://reta.3sbasin.org/

http://srtm.csi.cgiar.org/

http://www.eia.fi/index.php/support/download

http://modsim.engr.colostate.edu/csudp.shtml

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