Report on Water Availability

Transcription

1 TA No CAM TONLE SAP LOWLAND STABILIZATION PROJECT CAMBODIA Report on Water Availability Receiver: Asian Development Bank September 2006 In cooperation with:

2 GLOSSARY CONTENTS IV 0 SUMMARY 1 1 INTRODUCTION 6 2 OTHER SOURCES OF INFORMATION 6 3 RIVER FLOW INFORMATION IN THE PROJECT AREA Sources of data and data analysis Long-term trends in river flow Seasonal patterns in river flow Volumetric water availability Specific discharges Flood flows 22 4 INUNDATION AROUND GREAT LAKE Significance for water availability Sources of data on lake levels Long-term pattern of lake level Seasonal pattern of lake level 26 5 RAINFALL INFORMATION IN THE PROJECT AREA Sources of data and data analysis Long-term trends in Rainfall Geographical patterns in rainfall Seasonal rainfall distribution Number of raindays Annual maximum one-day rainfall 45 6 EVAPORATION Significance for water availability Seasonal variations in evaporation Relationship between evaporation and rainfall 48 7 ONSET OF RAIN AND LENGTH OF DRY SPELLS 51 8 GROUNDWATER 55 9 WATER USE OVERVIEW OF WATER AVAILABILITY 59 ANNEX 1. TOTAL MONTHLY VOLUMETRIC DISCHARGES 62 ii

3 ANNEX 2. SPECIFIC MONTHLY VOLUMETRIC DISCHARGES 80 ANNEX 3. ANNUAL MAXIMUM DAILY DISCHARGES 100 ANNEX 4. MEAN MONTHLY AND ANNUAL RAINFALLS 104 ANNEX 5. MEAN MONTHLY AND ANNUAL RAINDAYS 108 ANNEX 6. ANNUAL MAXIMUM ONE-DAY RAINFALLS 112 ANNEX 7. EVAPORATION ESTIMATES 116 ANNEX 8. SELECTED INFORMATION SOURCES 122 ANNEX 9. RIVER BASIN MAPS 126 iii

4 GLOSSARY ADB AEI ARI BCM DoH&RW DoM HYMOS MAF MCM MOWRAM MRC TSLS (P) Asian Development Bank Annual Exceedance Interval Annual Recurrence Interval Billion cubic metres Department of Hydrology and River Works, MOWRAM Department of Meteorology, MOWRAM Database management system in use at DoH&RW Mean annual flood Million cubic metres Ministry of Water Resources and Meteorology Mekong River Commission Tonle Sap Lowland Stabilisation (Project) iv

5 0 SUMMARY The purpose of this report is to summarise the available information on water resources in the sub-basins of the Tonle Sap basin. It considers: River flows totals, specific discharges, and annual maxima Lake levels, Tonle Sap Great Lake Rainfall totals, raindays, annual maxima, onset of rain at the start of the wet season, incidence of dry spells Evapotranspiration and related meteorological variables Sources of information The principal source of data has been the HYMOS database maintained by the Department of Hydrology & River Works (DoH&RW), MOWRAM. This database contains daily water level observations for over forty monitoring stations around the Great Lake, and daily rainfall observations for over eighty raingauges. An initial step in the work was to prepare two complementary MOWRAM data reports: River flow monitoring stations, Tonle Sap basin and Rainfall monitoring stations, Tonle Sap basin. Other relevant reports have been surveyed. The Northwest Irrigation Sector Project already has provided valuable compilations, and the four river basin and water use studies that are ongoing (September 2006) will provide a sound basis for project selection and design in the basins concerned. The MRC project Consolidation of hydro-meteorological data and multifunctional roles of Tonle Sap Lake and its vicinities, Phase III and associated MRC projects also are of relevance, although they provide basin-scale information that is not directly applicable to sub-project design. River flows Hydrological data for 23 river monitoring stations from the DoH&RW database have been analysed. The stations tend to be on the largest rivers, and the data are representative of the distinctive hydrological conditions in the river basins concerned. The data should be of particular relevance to any sub-projects that would draw water from those rivers, but may not be readily extended to other sub-basins. Long-term observations at two stations reveal no significant trends in mean annual flows, but do indicate very substantial variation about the long-term mean almost a five-fold range for the Stung Sangke at Battambang. Flows are highly seasonal, with low or even zero flows during the dry season (December to May), rising quickly to a peak in the wet season, in September-October. In any one month, there is generally a wide range in mean monthly flow from year to year from 0.8 m 3 /s to 44 m 3 /s during June in Stung Mongkol Borey, for example. The data show graphically that runof-river flows in Cambodia are quite unreliable, as a basis for confident and economical resource development. Computations of volumetric water availability (in million cubic metres per month or year) show the large volumes of water that flow to the Tonle Sap Great Lake, but again there is great inter-annual variability. Most of the four years out of five annual flow volumes are 60-80% of the mean annual volumes for each station. However, flow volumes at the beginning of the 1

6 wet season, when reliable access to water is most important for farmers, are a small proportion of the annual total (flow volume in June generally is around 5% of total annual volume) and more variable (the four year out of five volume in June is in the range of 5-70% of the average for June). Again, then, run-of-river flows do not provide a reliable basis for agriculture, particularly at the start of the wet season. Specific discharges (discharge per unit area of river basin) have been calculated, to remove the effect of drainage area and make data for rivers more comparable. Nevertheless, there are large differences among rivers, because their basins differ in many other respects geology and soils, vegetation cover, rainfall gradients associated with elevation and proximity to the sea, basin slope, etc. In principal, such factors can be considered in a statistical analysis, but this would be a significant research project that is difficult to justify for present purposes. For project selection and design, the specific discharge data can best be used by transferring data from nearby basins and/or basins that are judged to have similar characteristics. Data for flood flows have been extracted from the HYMOS database, principally in the form of maximum annual flood peaks. Unfortunately, many rating curves are not sufficiently reliable to estimate flood peaks with confidence. For most stations, particularly those with contributing drainage areas greater than 4,000 km 2, the discharge-frequency plots indicate that flood peaks with an Annual Recurrence Interval greater than about 2 years are under-estimated. Estimates of Mean Annual Flood indicate that the Halcrow equations are crudely acceptable for basin areas <3,000 km 2, but the Halcrow Report s insistence that design work must be based on supplementary local information is strongly supported. Inundation around the Great Lake Seasonal inundation around the Tonle Sap Great Lake is significant for possible sub-projects that would involve temporary storage of flood waters for subsequent release for supplementary irrigation of recession rice. The long-term record of lake levels at Kompong Luong shows that the maximum lake level reached each year is highly variable a range of almost three meters, with the average maximum level of m above sea level. Rainfall Rainfall data are available for over 80 stations, but many have records of less than a handful of years, and less than ten stations have more than 30 years of record (in all cases very discontinuous, with many gaps). Mean annual rainfalls are generally in the range 1,000mm to 1,700 mm. There is a clear pattern of declining rainfall towards the northwest. Stations northwest of the lake have annual totals less than 1,200 mm, declining to below 1,000 mm at the Thai border. To the west and southwest of the lake, towards Pailin, annual totals are in the range 1,200-1,350 mm. Annual totals around the eastern end of the lake are in the range 1,250-1,700 mm, and then appear to decline again further towards the southeast. Northeast of the lake, annual totals are in the range 1,350-1,550 mm. Isohyets have not been drawn because the variability in the data is considered to be too great. In practice, a rainfall estimate at a particular location would best be obtained by inspection of the data for the nearest stations, rather than by reference to an isohyetal map. 2

7 The reliable annual rainfall that is received at least four in five years on average also has been calculated for each station. Totals are, of course, less than the mean annual totals, and the geographical pattern is somewhat different. Westwards from the lake, four in five year totals decline from about 1,200 mm to around 1,000 mm at Pailin and 900 mm towards the Thai border. At the eastern end of the lake there is a zone with totals of 1,200-1,400 mm; elsewhere, totals are in the range 1,000-1,200 mm, with a possible rain-shadow area to the southwest of Pursat. Again, it is unrealistic to draw isohyets, and anyone needing data for design at a particular location should consult the data for nearby stations. The seasonal rainfall distribution is broadly similar for all stations in the Project area. There is negligible rainfall in December to February, with a rapid increase in March to May. Monthly totals during the core of the wet season, June to October, vary widely, presumably in response to the convectional rainfall that brings unpredictable heavy downpours that cover small areas. For example, June totals at Battambang range from 42 mm to 276 mm a very unreliable basis for confident agriculture. The number of raindays in each month also shows substantial variability from year to year, particularly during June to October. The largest number of raindays is a very respectable 163 days per year, at Taing Krasaing (Kompong Thom). Mean annual maximum daily rainfalls are in the range mm; the one in ten year maximum daily rainfall is in the range mm; and the 100 year maximum daily rainfall is approximately 230 mm (estimated for Kompong Chhnang station). Evapotranspiration Evaporation data (measured pan evaporation and estimates of evaporation using the Penman equation) are available for several stations in the Project area. Once again, there is an obvious seasonal cycle, with the highest mean monthly evaporation rates measured in March (averaging mm at the various stations), as temperatures are increasing but cloud cover and rainfall have not yet started to increase with the onset of the wet season. The lowest rates are observed in September-October, in the range mm per month). Once again, there is substantial year-to-year variability in evaporation rates at Battambang the mean daily evaporation rate during May ranged from 2.5 mm/day to 6.5 mm/day, for example. Combining the seasonal cycles of rainfall and evaporation, evaporation in general exceeds rainfall during December to April/May. Because of the great inter-annual variability of both rainfall and evaporation, the exact time at which rainfall starts to exceed evaporation at the beginning of the wet season is also highly variable, again introducing great uncertainty for farmers wishing to prepare the ground and plant crops. Onset of rain and length of dry spells The date of the first significant rain (>5 mm) of the wet season generally is in the second half of March, but can be as late as mid-may. However, this date can range, from year to year, over a period of 2 ½ months. The incidence of dry spells (periods with no daily rainfall >0.5 mm) within the wet season also is very variable. Median values generally are days, but can be as high as 64 days (at Kompong Chhnang). The five year dry spell is about three weeks, except at Siem Reap, where it is five weeks. 3

8 Once again, this aspect of the Project area s hydrology shows the great uncertainty that farmers have with regard to water availability at the beginning of the wet season. Groundwater There is limited information on groundwater availability in the TSLSP area, with substantive information principally available for Kompong Chhnang province. The survey of Kompong Chhnang concluded, overall, that Alluvial and Pleistocene aquifers yield small amounts and inferior water quality, high in iron and salinity. Arsenic is locally contained. Basement rock aquifer has greater yield and good water quality. Exploration is difficult. The NWISP hydrogeologist was more positive in his assessment of groundwater potential, although he also commented that deep groundwater is of widespread availability but only occasionally of sufficient yield to be useful for agriculture. He emphasizes (as did the Kompong Chhnang study) the need for a substantial survey of groundwater availability before development proceeds. For TSLSP purposes, it may be concluded that the available information is not sufficient to establish whether the groundwater resource at a particular location would be sufficient to support agricultural development. In these circumstances, reliance on groundwater for sub-projects (other than for household purposes or water-efficient irrigation of high value crops) would be risky. Water use Consumptive water use is an important component of the water balance in a river basin/aquifer, particularly during critical times of year (i.e. the beginning of the wet season) when demand is greatest and availability is most unpredictable. There are no data on water use in the TSLSP area, but this will be remedied when the four river basin studies being carried out under the NWISP are completed, by the end of A recent inventory of irrigation systems on the southern side of the Great Lake (to be released in late 2006) also should provide an indication of agricultural use. It will provide information on locations and command areas, and estimation of water use should be possible if estimates of crop water use and seepage are made. It is understood that the inventory will be extended to other subbasins in the Tonle Sap basin. Overview of water availability The final section of the report draws eight main conclusions that summarise preceding analysis. The underlying emphasis is on the variability and unpredictability of the climate and hydrology of the Tonle Sap basin, as a basis for confident and cost-effective project design. An important conclusion is that, because of this inherent variability, long records of high quality data are required to estimate hydro-meteorological statistics. Few stations presently have adequate lengths of record, and the quality of existing data generally is poor. A sustained programme of hydrometeorological data collection, to international standards, is essential. The analysis shows that water availability is not a factor that controls whether or not a potential sub-project can be considered, but does influence what type of project is possible. A variety of approaches to water management can be used, in addition to supplementary irrigation using runof-river abstraction, to make the most effective use of the available water in the Project area. 4

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10 1 INTRODUCTION The purpose of this report is to summarise the available information on water resources in the sub-basins of the Tonle Sap basin. The focus is on those elements of the hydrological cycle that are of particular relevance to planning and designing water management for agriculture, as a component of the Tonle Sap Lowland Stabilisation Project. In particular, it considers: River flows totals, specific discharges, and annual maxima Lake levels, Tonle Sap Great Lake Rainfall totals, raindays, annual maxima, onset of rain at the start of the wet season, incidence of dry spells Evapotranspiration and related meteorological variables The principal source of data has been the HYMOS database maintained by the Department of Hydrology & River Works (DoH&RW), MOWRAM. This database contains daily water level observations for over forty monitoring stations around the Great Lake, and daily rainfall observations for over eighty raingauges. This source was chosen because it contains by far the most comprehensive and easily used archive that is available. An initial step in the work was to prepare two complementary data reports, which synthesise and present available data in tabular and graphical form, as appropriate. They have been released as MOWRAM reports: River flow monitoring stations, Tonle Sap basin. Department of Hydrology & River Works, MOWRAM (August 2006), and Rainfall monitoring stations, Tonle Sap basin. Department of Meteorology, MOWRAM (August, 2006). Data processing was carried out principally by the TSLS Water Resources Planner and Mr Preap Sameng of DoH&RW. Data presentation and subsequent analysis were largely the responsibility of the Water Resources Planner. The active support of the Director of DoH&RW and the very effective engagement of his staff are gratefully acknowledged. Rainfall records were checked and supplemented by staff of the Department of Meteorology, and the assistance of the Director of Meteorology and her staff is gratefully acknowledged. 2 OTHER SOURCES OF INFORMATION Data extracted from the DoH&RW database were supplemented by data extracted from consultancy reports, particularly for meteorological variables. A number of projects have assembled information of relevance to the Tonle Sap Lowland Stabilisation Project, and/or present the results of some hydrological analyses, particularly of flood flows. Some key reports are listed and briefly described in Annex 8. The Northwest Irrigation Sector Project already has provided valuable compilations of hydro-meteorological data (NWISP, 2003, 2006c). Its current (2006) phase will add substantially to information on the water resources of the Tonle Sap basin, via the river basin and water use studies 6

11 being carried out in the Dauntry-Svay Donkeo, Boribo-Thlea Maam-Srang, Mongkol Borei, and Svay Chek river basins (NWISP, 2006a and 2006b). It is anticipated that the outputs from these four studies, which will be available by December 2006, will provide a sound basis for project selection and design in the basins concerned and, to some extent, in neighbouring basins. The e-atlas compiled under ADB TA 4427-CAM (Establishment of Tonle Sap Basin Management Organisation) deserves particular mention. It provides a fine overview of the hydrology of the Tonle Sap basin, presenting a variety of maps (including a map of the locations of irrigation systems), as well as river discharge hydrographs and simple hydrological statistics. It provides a broad overview of the basin, so the e-atlas does not provide data usable for sub-project design, but it is valuable for orientation. The hydrographs presented by the e-atlas were computed for in the main sub-basins of the Tonle Sap, as part of the Mekong River Commission (MRC) project Consolidation of hydro-meteorological data and multi-functional roles of Tonle Sap Lake and its vicinities, Phase III (MRC, 2004). The project used the same data contained in the DoH&RW HYMOS database, and the Final Report comments on rating curves and data quality, as well as presenting five-year hydrographs (reproduced in the e-atlas). The project is expressly a basin-wide study, and its outputs are not directly usable for TSLS Project sub-project selection and design. Further analysis is required to provide data that are more directly applicable for selection and design purposes. An associated major study of the Mekong-Tonle Sap system that also presents basin-scale information (including annual water balances for the Tonle Sap basin) is the MRC- WUP-JICA (2004) study on hydro-meteorological monitoring for water quantity rules in Mekong River basin. 3 RIVER FLOW INFORMATION IN THE PROJECT AREA 3.1 Sources of data and data analysis MOWRAM and its predecessors have collected information on lake levels and river flows since at least However, no monitoring stations have operated continuously, and a basin-wide monitoring programme has been established only since about The original data, mostly in the form of daily observations, are held on the HYMOS database that is managed by the Department of Hydrology & River Works (DoH&RW). Hydrological data for the project area have been assembled by a number of consultancies (Annex 8), notably the Halcrow Report (Halcrow, 1994) and the Final Report of the Northwest Irrigation Sector Project (NWISP, 2003). However, they are of restricted value for present purposes, because they use short or incomplete records, or do not present the data in a usable form. The decision was made to thoroughly process the data held on the 7

12 HYMOS database, taking advantage of the considerable amount of data that have been archived in recent years. The Director of H&RW has given free access to the database, and his staff have worked closely with the TSLSP consultant. A MOWRAM report, River flow monitoring stations, Tonle Sap Basin, has been prepared as a companion to this one, and is a joint output of MOWRAM and the TSLSP. It provides the raw material that is analysed and reported upon herein. River flow data for twenty three stations have been analysed (Table 1; stations in bold type). These include the stations for which discharge data have been filed on the HYMOS database, or for which stage-discharge rating curves 1 are available. These enable discharges to be calculated from water level observations. There are other monitoring stations in the basin, for which water level observations have been made, but rating curves have not been filed on the HYMOS database, and therefore discharge cannot be calculated. It should be emphasised that only limited checking of data quality was possible, and there are many possible sources of inaccuracy. This is particularly the case with regard to rating curves, which have not been maintained continuously. The MOWRAM Report presents data primarily in the form of monthly summaries, which should minimise the effects of data inaccuracy at high and low discharges. However, it is probable that computed discharges, particularly in wet-season months, are under-estimates. A future task for the DoH&RW is to carry out a full quality appraisal of the database, and make corrections where possible. River basin boundaries have been digitized by the Project s GIS Specialist (Annex 9). This has enabled basin areas to be up-dated in Table 1. The river flow stations, particularly those with the longest and most reliable records, tend to be on the largest rivers, for the obvious reason that these provide the greatest potential for development of the water resource. These data for large rivers are representative of the rivers themselves, and of the more or less distinctive hydrological characteristics of their drainage basins 2. They should be of particular assistance for planning sub-projects that would draw water from those rivers, but may be of less relevance to sub-projects away from the main rivers. Data for smaller rivers that are located wholly on the lowland area are concentrated in the Pursat basin. Again, therefore, the data might not be readily extended to other basins, for predictive purposes. Discharges at many of the monitoring stations, particularly in the lower reaches of the rivers towards the Great Lake, are affected by abstraction of water further upstream. Measured discharges therefore are less than those that would naturally occur. This effect is greatest when natural flows are lowest, during December through to June. To normalise flows to account for this is a major exercise which is beyond the resources of the Project. 1 A stage-discharge rating curve is a relationship between a series of measurements of water level (or stage) and discharge (or flow). It is usually presented in the form of a graph, with a mathematical equation calculated to best fit the data. HYMOS provides various options for calculating curves, and applying the curves to a set of water level observations. 2 The major tributaries of the Tonle Sap Great Lake rise in the mountain ranges encircling the Tonle Sap basin, where rainfall may be three or four times greater (but is not measured), and vegetation cover, geology and land surface topography are completely different from the lowlands. 8

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14 Table 1. Water level and discharge measurement stations. (Stations used in this report are in bold-face). Period of record Area (km 2 ) Location ID Name River Water level Discharge (MRC) (TSLSP) ID Lat Long Coor_X Coor_Y Kampong Chhnang Tonle Sap 24-72, 81-86, 88, Lake level Snoc Trou Tonle Sap Lake level Bac Prea Tributary Great Lake 62-63, Lake level Mongkol Borey Mongkol Borey 62-63, , ,170 4, Sisophon Sisophon 62-63, , , Kralanh Sreng 62-63, , ,175 7, Treng Sangker 63-72, , ,135 2, Battambang Sangker 62-3, 72-3, 81-8, , 72-3, 81-8, ,230 3, Sre Ponleu Sangker Mong Russey Dauntry , Bot Chhvear/UNTAC Siem Reap Prasat Keo Siem Reap Kompong Kdei Chikreng 62-3, , ,920 1, Pursat Pursat 62-3, ,480 4, Taing Leach Pursat ,080 2, Bac Trakoun Pursat 95-97, , , Khum Viel Pursat 95-7, , , Lo Lok Sar Pursat 94-7, Phum Kos Pursat Kbal Hong (up) Pursat 94-7, Kbal Hong (down) Pursat 95, Peam Tributary of Pursat Prey Klong (down) Tributary of Pursat 94-7, , Prey Klong (up) Pursat Sanlong (up) Pursat Sanlong (down) Pursat Svay At Pursat Campang Dauntry

15 Period of record Area (km 2 ) Location ID Name River Water level Discharge (MRC) (TSLSP) ID Lat Long Coor_X Coor_Y Svay Don Keo Tributary of Pursat 62-3, 65-97, , 65-97, Kroch Seuch (up) Dauntry Kroch Seuch (down) Dauntry Wat Liep (down) Pursat Wat Liep (up) Pursat Tlea Maam (1) Pursat Tlea Maam (up) Tributary of Pursat Banteay Krang Krakor Boribo Boribo Kompong Chen Staung 62-3, , ,895 2, Kompong Thom Sen 61-70, , ,670 13, Kompong Putrea Sen 65-9, , ,080 11, Panha Chi Sen Kompong Thmar Chinit 62-3, , ,130 4, Srok Sandan Sen 02 2, Note: Two figures are given for drainage basin area: that listed on the Mekong River Commission web-site (MRC), and an area calculated from drainage basin boundaries digitized in August 2006 by the GIS Specialist of Tonle Sap Lowland Stabilisation Project (TSLSP). The latter is considered to be more accurate. Note: the location coordinates listed have been calculated by the GIS Specialist of Tonle Sap Lowland Stabilisation Project (TSLSP), in consultation with the Director of DoH&RW to identify the correct position of the stations. Many of the coordinates listed on the Mekong River Commission web-site are incorrect. 11

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17 3.2 Long-term trends in river flow Two stations, Battambang and Kompong Thom, have records long enough to reveal long-term trends in river flows (Figure 1, Figure 2). In both cases, there appears to be a tendency for mean annual discharge to increase, but in neither case is the regression coefficient significantly different from zero. Perhaps more important is the substantial scatter of mean annual discharges around the long-term average almost a five-fold range in the case of the Sangke at Battambang. This demonstrates what is widely recognised, that river flows in Cambodia are highly variable from year to year, and quite unreliable as a basis for confident and economical resource development. The data are not adequate to judge whether variability has increased over the years, as is sometimes suggested to have happened as a result of land use change or climate change. 3.3 Seasonal patterns in river flow The data for all the rivers that have been analysed show the same pattern of highly seasonal flows, with low or even zero flows during the dry season, December through to May, and a rapid rise to a peak in the wet season, in September-October. The hydrograph for Peam station on a tributary of the Stung Pursat typifies this pattern for small rivers (Figure 3). Actually, the flow regime at Peam is neater than most, with a sharply defined peak in most years (Figure 4). Other rivers have a common tendency for particular months to have flows that are unusually high or low for the time of year, and to have a much wider range of flows from year to year. Thus, in Stung Mongkol Borey, there is a wide range from the lowest to highest mean monthly flow in all the months when there is significant flow May to November (Figure 5). For example, mean monthly discharge in June varied from 0.8 m 3 /sec to 44 m 3 /sec during the eight years of record, with an average of 14 m 3 /sec and a 4 in 5 year value of 22 m 3 /sec. The overall consequence of such variability is that rivers, particularly small rivers, in the Tonle Sap basin provide an unreliable basis for water management and use that rely on run-of-river flows (i.e. has no artificial storage capacity). 13

18 Figure 1. Mean annual discharge, Stung Sangke at Battambang. Mean monthly discharge, Aug-Nov (m y = x R 2 = Stung Sangke at Battambang Year from 1961 Figure 2. Mean annual discharge, Stung Sen at Kompong Thom y = 0.913x R 2 = Sen at Kompong Thom, mean annual discharge 250 Discharge (m3/se Years from 1961 Figure 3. Hydrograph for Peam station (tributary of Stung Pursat). 14

19 Figure 4. Mean monthly discharges, Peam station, Mean monthly discharge (m3/s) MEAN Tributary of Pursat River at Peam 20 0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Figure 5. Monthly flow regime for Stung Mongkol Borey MAX MIN 20 PERCENTILE 80 PERCENTILE MEAN Mongkol Borey at Mongkol Borey Mean monthly discharge (m3/s) JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 3.4 Volumetric water availability The study by Carbonnel and Guiscafré (1963?), Grand Lac du Cambodge, Sedimentologie et Hydrologie , presented data on total inflows into the Great Lake during a single water year. A total of over 24 BCM (billion cubic metres) was estimated, 85% entering the lake during the four months July-October 1962 (Figure 6). This study is significant because it measured inflows from all major tributaries to the lake. However, it used data for only one year, so it cannot be relied upon to give more than a picture of the hydrologic regime of the Tonle Sap Great Lake. 15

20 Figure 6. Inflows into Tonle Sap Great Lake, (data from Carbonnel and Guiscafré, 1963?) 7,000 6,000 Total monthly runoff (M 5,000 4,000 3,000 2,000 1,000 0 April May June July August September October November December January February March The NWISP Final Report presented a provisional, very approximate water balance for the Tonle Sap basin (Table 2). All river flow estimates are subject to considerable error because of the unreliability of rating curves, particularly on the Tonle Sap river itself. The MRC-WUP-JICA (2004) study has also presented estimates of water balances in the basin. Table 2. Provisional Tonle Sap Great Lake mean annual water balance. (All figures in MCM, except for lake area) JAN FEB MAR APR MAY JUN Lake area (km 2 ) Lake rainfall Tonle Sap inflow (-) (-) (-) (-) (-) 898 Tonle Sap outflow (-) Other tributaries Evaporation JUL AUG SEP OCT NOV DEC YEAR Lake area (km 2 ) Lake rainfall Tonle Sap inflow (-) (-) (-) Tonle Sap outflow (-) (-) (-) Other tributaries Evaporation Total apparent imbalance (by difference) 5380 Source: Table 7.3 of NWISP Final Report, Volume 2, Annex A (March 2003). Other tributary flows are estimates in the MRC/UNDP Natural resources based development strategy for the Tonle Sap area, Cambodia (May 1998) The modern discharge records compiled in the DoH&RW Report on River flow monitoring stations are readily converted from instantaneous discharge in cubic metres per second (m 3 /s) to give volumetric discharge over a 16

21 month or a year, in million cubic metres (MCM). Summary statistics for annual volumetric discharge are presented in Table 3, and the monthly calculations are presented in Annex 1 3. The MEAN values (Table 3) show the large volumes of water that on average flow to the Tonle Sap Great Lake each year, and in principle would be available for filling storage. However, the MAX and MIN values confirm that there is great inter-annual variability. Most of the 20 PERCENTILE values (the annual volumetric discharge exceeded 4 years in 5 on average) are in the range 60-80% of the MEAN values for each station. The volume and reliability of water available at the beginning of the wet season, when many farmers are establishing their crops, is of greater significance than annual volume (Table 4). Volumetric discharges in June are only about 5% of the total annual volumes. Further, June discharges are even more variable than annual discharges; 20 PERCENTILE values are in the range 5-70% of the MEAN values. In other words, the volume of water that is available in June, at the beginning of the planting season, is both comparatively small and highly variable from year to year. 3.5 Specific discharges Specific discharge discharge per unit area, commonly presented in litres/second per square kilometre (l/s/km 2 ) is an important hydrological parameter because it removes the effect of drainage area on river flow and makes data from different rivers more comparable. The data of Carbonnel and Guiscafré indicate a basin-wide average annual specific discharge of 11.4 l/s/km 2, with figures of l/s/km 2 for the large rivers flowing from the high-rainfall mountains encircling the Tonle Sap basin. Again, the monthly pattern is of more practical significance than annual figures (Table 5, Figure 7). The modern discharge records show the marked seasonal differences in specific discharge that would be expected from the earlier discussion. They also show substantial differences between rivers. Most obvious is the high specific discharges of the Stung Sangke, with its headwaters in the Cardamom Mountains receiving heavy rainfall during the Southwest Monsoon. On the other hand, Stung Chikreng and Stung Sreng, draining from the lower country to the north of the Great Lake, have rather low specific discharges year-round. A seeming anomaly is Stung Mongkol Borey, next to the Sangke but with mean monthly specific discharges only a tenth as great. The presence of limestone in the headwaters, the lower topography, and the more inland location of the basin, in a low-rainfall area, are explanations. On the other hand, the Peam tributary of Stung Pursat has unusually high specific discharges. This river drains from an area of forested hill country in the higher rainfall part of Pursat province. Overall, Figure 7 indicates some difficulty in using even specific discharges to extrapolate from rivers for which there are data to others for which there are not. There are large differences in hydrologic regime, and even though these can be explained qualitatively by differences in drainage basin characteristics, there are insufficient data to permit an analysis that could be confidently applied. 3 It is probable that, owing to the unreliability of rating curves at high stages, the discharges presented in the Annex and in Table 3 and Table 4 are under-estimates. 17

22 Figure 7. Specific discharges in sub-basins of the Great Lake (l/s/km 2 ). ) Mean monthly specific discharge (l/s/km Rivers, northeastern side of Great Lake JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Mean monthly specific discharge (l/s/km2) Rivers, southern side of Great Lake JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Mean monthly specific discharge (l/s/km2) Rivers, western end of Great Lake 0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 18

23 Table 3. Summary statistics for annual volumetric discharges (MCM) Mongkol Borey Sisophon Sreng Sangke Sangke Sangke Siem Reap Siem Reap Chikreng MEAN MAX MIN PERCENTILE PERCENTILE Pursat Pursat Pursat Pursat tributary Pursat tributary Pursat tributary Boribo Staung Sen Sen Chinit MEAN MAX MIN PERCENTILE PERCENTILE

24 Table 4. Summary statistics for June volumetric discharges (MCM) Mongkol Borey Sisophon Sreng Sangke Sangke Sangke Siem Reap Siem Reap Chikreng Pursat Dauntry MEAN MAX MIN PERCENTILE PERCENTILE Pursat Pursat Pursat tributary Pursat tributary Pursat tributary Boribo Staung Sen Sen Chinit Pursat tributary MEAN MAX MIN PERCENTILE PERCENTILE

25 Table 5. Mean monthly specific discharges (l/s/km 2 ) Station Area (km 2 ) JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Mongkol Borey 4, Sreng 7, Sangke 2, Sangke 3, Sangke Dauntry 1, Siem Reap Chikreng 1, Pursat 4, Pursat 2, Pursat 4, Pursat 4, Peam tributary Prey Klong tributary Boribo Staung 2, Sen 13, Sen 11, Chinit 4,

26 3.6 Flood flows Flood flows are principally of concern when structures are being designed that have a high capital cost or whose failure could adversely affect downstream populations and/or assets. There have been several efforts to estimate flood flows in sub-basins of the Tonle Sap, notably Stung Chinit. The procedure for estimating flood flows that was developed for the Irrigation Rehabilitation Study in Cambodia (Halcrow, 1994) has been widely quoted and used. It is summarised by a set of equations which relate mean annual flood (MAF, that is, the average of the series of annual maximum flows at a station) to basin area (AREA), and relate the 10-year and 100-year floods Q 10 and Q 100 to the MAF: MAF = AREA 0.9 ; Q 10 = 1.53.MAF; Q 100 = 2.2.MAF The Halcrow report emphasises that this approach, which relies on minimal Cambodian data and relationships for river basins in Thailand and Malaysia, provides only a rough estimate of flood flows. It must be supported by local records or memories of flood water levels to obtain estimates suitable for design purposes. The streamflow data compiled in the DoH&RW Report on River flow monitoring stations are not sufficiently reliable, even now, to make confident estimates of flood flows. Many rating curves do not extend to high stages and discharges, and significant extrapolation beyond the measured range is necessary. Several stations show signs of being affected by loss of flow to distributaries or overbank (annual high water levels tend to be about the same, suggesting that water is overflowing from the channel). Furthermore, particularly for stations in the lower reaches of the rivers, the water level measurement stations are affected by backwater from the Great Lake, so that discharge calculations are inaccurate 4. Subject to the preceding qualifications, annual maximum daily discharges have been extracted from the hydrographs presented in the DoH&RW Report (Annex 3). The annual series for each station has been plotted also as an annual exceedance series (Figure 8, Figure 9). The nearly flat curves of several stations above an ARI of about 2 years indicate the effects of truncation of peak flows by HYMOS at stage heights greater than the range of the rating curve, overbank or distributary flow, or backwater effects. Few of the stations appear to be usable for analysis of extreme events, without a great deal of work on the rating curves, additional research into historical flood levels, estimation of overbank and distributary flows, etc. 4 The studies reported in Mekong River Commission (2004) and MRC-WUP-JICA (2004) use the same data archived in the DoH&RW HYMOS database to develop rating curves and compute discharges. The present writer considers that some of the extrapolations and assumptions required are questionable, given the nature of the original data. Estimates of high flows can be quite inaccurate, as a result of extrapolation of rating curves beyond the measured range. 22

27 Figure 8. Annual exceedance series for river flow stations with 9 or more years of record. Annual maximum discharge (m3/s) Recurrence interval in years Sangke, Battam bang Treng, Kompong K'dei Kompong Putrea Kompong Chen Kum Viel Sen, Kompong Thom 100 Figure 9. Annual exceedance series for river flow stations with 8 or less years of record. Annual maximum discharge (m3/s) 1400.Kompong Thmar Kralanh 1200 Mongkol Borey Boribo 1000 Baktrakoun Peam Taing Leach Recurrence interval in years 23

28 The Mean Annual Flood (Q 2.33, with an ARI = 2.33 years) has been extracted from the tables in Annex 3, to compare with the Halcrow (1994) equation mentioned above (Table 6, Figure 10). Some of the points scatter around the Halcrow line MAF = Area 0.9, but those for stations with basin areas >4,000 km 2 lie well off to the right. This is indicative of the problems mentioned above with regard to rating curves, overbank flow, backwater effects etc. Of course, there are at least two populations of stations in the Tonle Sap basin, the principal ones being the large sub-basins that drain from the encircling mountains, and the smaller sub-basins that drain mainly from the lowlands around the lake. These populations of basins can be expected to have quite different hydrological characteristics. Table 6. Estimates of Mean Annual Flood from Annex 3. ID Name River Area (km 2 ) Area (km 2 ) from GIS MAF (m 3 /s) Mongkol Borey Mongkol Borey 4,170 4, Sisophon Sisophon 4, Kralanh Sreng 8,175 7, Treng Sangker 2,135 2, Battambang Sangker 3,230 3, Sre Ponleu Sangker Mong Russey Dauntry 833 1, Bot Chhvear/UNTAC Siem Reap Prasat Keo Siem Reap Kompong Kdei Chikreng 1,920 1, Pursat Pursat 4,480 4, Taing Leach Pursat 2,080 2, Bac Trakoun Pursat 4, Khum Viel Pursat 4, Peam Tributary of Pursat Prey Klong (down) Tributary of Pursat Svay Don Keo Tributary of Pursat Tlea Maam (up) Tributary of Pursat Boribo Boribo Kompong Chen Staung 1,895 2, Kompong Thom Sen 13,670 13, Kompong Putrea Sen 9,080 11,137 1, Kompong Thmar Chinit 4,130 4, Note: the basin areas computed by the TSLSP GIS specialist have been used in subsequent analysis. 24

29 Figure 10. Mean annual floods (Q 2.33 ) as a function of basin area. The Halcrow (1994) equation is marked Mean annual flood (m3/s) ,000 4,000 6,000 8,000 10,000 12,000 14,000 Basin area (km2). 4 INUNDATION AROUND GREAT LAKE 4.1 Significance for water availability Many communities on the Mekong-Tonle Sap floodplain use the recession rice cultivation method, in which they progressively plant rice as flood waters recede. Supplementary irrigation is enabled by the construction of barrages which are submerged during the annual flood, and which impound water as river/lake water levels fall. This impounded water then can be used as required to supply additional water to crops planted downslope from the barrage. The opportunity to use this approach reliably is controlled by the frequency with which flood waters reach particular elevations and locations around the Great Lake. Local communities undoubtedly know the areas that have been inundated in the past, but may not be able to quantify the frequency with which inundation occurs. To justify, for example, the construction or rehabilitation of a barrage for the purpose of supplementary irrigation of recession crops, some confidence is needed that the barrage will be refilled with an acceptable frequency. 4.2 Sources of data on lake levels Several stations provide data on water levels in the Tonle Sap Great Lake, but Kompong Luong, near Kompong Chhnang, provides the longest record, spanning the period The dataset retrieved from the DoH&RW HYMOS database indicates that there was a step change in datum in 1961, with average water level since 1961 being 2.47 m below that before To use the full record, post-1961 values have been increased by 2.47 m. 25

30 4.3 Long-term pattern of lake level In spite of the adjustment for a change in datum noted above, there appears to be a weak long-term downward trend in lake level. This is particularly so for annual maximum level, for which there is a statistically significant decline of 16.5 mm/year, principally since the 1950s (Figure 11). If this apparent trend is real, it presumably would reflect reduced inflow to the lake from the Mekong and/or the Tonle Sap drainage basin, resulting from lower Mekong and/or Tonle Sap tributary flows, constriction of the Tonle Sap channel/delta, reduced overbank flows across the inundated areas between the Mekong and Tonle Sap, or changes to the local base level set by the river level at Chaktomuk. The maximum lake level cannot decline indefinitely, because it is ultimately fixed by the seasonal rise and fall of river level at Chaktomuk, and there is no reason to expect that maximum levels there will decline in the future. 4.4 Seasonal pattern of lake level Tonle Sap Great Lake has a regular annual cycle, in response to seasonal variations in inflow from the Tonle Sap river basin itself and from the Mekong River. There is a great deal of variation from year to year, and water level on a particular day of the year may differ by as much as 4 m between years (Figure 12). For present purposes, maximum lake level in each year is of greatest interest. On average, maximum lake level reaches m above sea level, but has ranged from m to m (Table 7). The 80 percentile maximum level (reached 4 years in 5) is m. This means that there is 80% confidence that lake level will reach the m contour in a given year. A barrage to retain flood waters would need to have a crest level below this (less a few centimetres for water to flow over the barrage), to ensure that it is inundated with acceptable frequency (assumed here to be four years in five). Figure 11. Long-term trend in water level, Kompong Luong. 14 Kompong Loung (post-1962 data adjusted by 2.48 m for datum change) R 2 = MINIMUM MAXIMUM AVERAGE Water level (m a.s R 2 = R 2 = Year