TONLE SAP DEVELOPMENT SCENARIO IMPACTS AND GUIDELINES

Transcription

1 Draft MRCS / WUP-FIN Report: TONLE SAP DEVELOPMENT SCENARIO IMPACTS AND GUIDELINES April 2003 Left floating rice field, photo by U. Haapala. Right Tonle Sap fish catch, photo by Van Zaalinge, N. (2002)

2 Water Utilization Program - Modelling of the Flow Regime and Water Quality of the Tonle Sap MRCS / WUP-FIN TONLE SAP DEVELOPMENT SCENARIO IMPACTS AND GUIDELINES Appril 2003 Jorma Koponen, Juha Sarkkula, Marko Keskinen, Olli Varis, Seppo Hellsten, Elise Järvenpää, Tanja Dubrovin Edited by Teemu Jantunen Finnish Environment Institute EIA Ltd. Mechelininkatu 34 A Tekniikantie 21 B Helsinki Espoo Finland Finland Tel: Tel: Fax: Fax: Mobile: juha.sarkkula@vyh.fi koponen@eia.fi 1

3 Table of Contents 1 INTRODUCTION PROJECT SUMMARY GENERAL DESCRIPTION OF MEKONG BASIN AND THE TONLE SAP LAKE THE PHYSICO-CHEMICAL CONDITIONS OF THE TONLE SAP LAKE LINKAGES BETWEEN FLO ODING, SEDIMENTS, WATER QUALITY AND ENVIRONMENTAL INDIC ATORS SUMMARY HYDROLOGICAL FACTORS Water level fluctuation Water level duration W ATER QUALITY Oxygen Sediment load DETERMINATION OF ENVI RONMENTAL INDICATORS GENERAL IMPACTS OF WATER LEVEL FLUCTUATION Maximum water level Minimum water level Water level fluctuation range Timing of flood Duration and regularity of flood IMPACTS ON THE LAKE PRODUCTIVITY FISH CATCH IMPACTS Summary Hydrodynamic influences on fisheries Relationship between fish catch and flood level Physico-chemical conditions affecting fish catch per hectare and fish growth Conclusions FLOATING RICE FARMING IMPACTS HABITAT IMPACTS Objectives of the study Field studies Soil type variation at floodplain Rice cultivation as a part of ecosystem Vegetation types and floristic diversity Development of vegetation Comparison of different vegetation typologies Vegetation types as habitats Invasive plant species HUMAN IMPACT AND ECOLOGY TRANSLATION OF MODEL RESULTS INTO AGRICULTURAL, NAVIGATIONAL A ND ECOLOGICAL IMPACTS IMPACT -MODEL FOR PREDICTION OF ECOLOGICAL IMPACT INFLUENCE OF BUILT STRUCTURES ON THE NATURAL RESOURCES AND BIODIVERSITY OF THE TONLE SAP Phase I Database collection and impact analysis Phase II - Strategy for guiding future development RESERVOIR MANAGEMENT NAVIGATIONAL IMPACTS FISHERIES IMPACTS MODEL SCENARIOS NATURAL VARIATION DO and net sedimentation

4 4.1.2 Radiocarbon analysis DAM TRAPPING EXTENT OF TRIBUTARIES INFLUENCE W ATERSHED SCENARIOS SOCIO - ECONO MIC ANALYSIS SOCIO-ECONOMIC ANALYSIS OF THE TONLE SAP MODELLING PROJECT Introduction Zoning of the villages Database analysis Participatory village surveys Socio-economic policy model Migration and urbanization Final socio-economic analysis LINKING SOCIO-ECONOMIC ISSUES WITH THE MODEL RESULTS THE APPLICABILITY OF DRIFT IN WUP AND BDP FOR THE MEKONG RIVER Introduction The role of DRIFT in planning process DRIFT in WUP-BDP Conclusions GUIDELINES AND RECOMMENDATIONS MONITORING OF TONLE SAP LAKE AND TRIBUTARIES SEDIMENTATION IN THE TONLE SAP LAKE AND FLOOD PLAIN BIOLOGICAL PRODUCTIVITY OF THE TONLE SAP LAKE AND FLOOD PLAIN HARMFUL SUBSTANCES IMPACTS RICE FARMING A CCEPTABLE REVERSE WET SEASON FLOW TO THE TONLE SAP MINIMUM FLOW DEMANDS IN MEKONG DELTA ENVIRONMENTAL AND SOCIO-ECONOMIC CONDITIONS TRAINING, CAPACITY BUILDING AND SUSTAINABILITY OF THE MODEL SYSTEM WUP - FIN TOOLS IN THE BAS IN-WIDE CONTEXT PLATFORM CONCEPT BASIN-WIDE MANAGEMENT TOOL REQUIREMENTS FURTHER USES OF THE WUP-FIN TOOLS TRAINING, FUTURE USE AND MAINTENANCE OF THE MODEL S YSTEM SUMMARY PRESENT SITUATION WUP-FIN project status Problems to be addressed Users, stakeholders and beneficiaries of WUP-FIN Model System List of users, stakeholders and beneficiaries PROJECT CONTINUATION JUNE -DECEMBER Overall objectives and corresponding indicators Project purpose and corresponding indicators Results and corresponding indicators Activities Institutional capacity Participation and ownership REFERENCES lt pl 3Dm:UEdl nig karvas;evgclkti rubpabti5. lt plkunpabtwk nig m:uedltwk 3D

5 1 Introduction 1.1 Project summary This report is a part of the project Modelling of the flow regime and water quality of the Tonle Sap, which belongs to the Water Utilization Program (WUP) of Mekong River Commission (MRC). It is funded by the Development Cooperation Department, Ministry of Foreign Affairs Finland. Project has started in June 2001 and will end in June WUP- FIN is a complementary component of WUP. It provides advanced modelling and analysis tools for impact assessment also in the basin-wide setting. The main project objectives are: to develop a set of analytical tools to assist in the maintenance of desirable conditions of the Tonle Sap system to ensure that model components are available, and that the modelling framework allows future adaptation to include new modules, to analyze and predict impacts of proposed actions on the aquatic ecosystem and other water uses and functions of social and economic, and regional and global, importance to assist, through on-the-job and other training, in increasing the modelling capability of the NMC s, the line agencies and the MRCS and help create a sustainable modelling group within the NMC s and the MRCS. Project consists of field measurements, modelling, socio-economic analysis and preparation of management tools as well as training program. Advanced hydrological, hydrodynamic, water quality and biological models are used in the project General description of Mekong Basin and the Tonle Sap Lake The Mekong river has one flood pulse a year. During the wet monsoon (May- November) the discharge is 30 times greater than in the dry season (December-April) at Pakse southern Lao PDR) and 53 times at Kratie (Cambodia). Floodplains cover some 70,000 km 2. The degree of inundation depends on the strength of the monsoon, as % of the discharge is generated during wet season. The Tonle Sap Lake floodplains in the hart of Cambodia contain the largest continuous areas of natural wetlands habitats remaining in the Mekong system. One of the striking characteristics of the Mekong s hydrologic regime is the flow regulation by the Tonle Sap Lake in Cambodia, the largest permanent freshwater body in Southeast Asia. The lake is connected to the Mekong by the Tonle Sap River at Phnom Penh (see Figure 1.1). Due to higher water levels in the Mekong during most of the wet season the Tonle Sap River flows toward the lake thereby enlarging it 3 to 6 times from 2,700 km 2 to 9,000-16,000 km 2. In the dry season the flow direction is reversed. Then the lake supplies water to the Mekong and thereby raises the dry season water levels in the delta for some 5-6 months (see also Van Zalinge et al., 2003). 4

6 Figure 1.1. Mekong River system in Cambodia and Viet Nam. Since 1924 hydrographic data are available from Pakse and a few other places along the Mekong River. They show a considerable inter-annual variation in wet season river discharge (by a factor of two), which determines the extent of floodplain inundation. Weather patterns associated with the El-Niño phenomenon are thought to be partly causing these variatio ns. However, the average wet season discharge in the last twenty years ( ) appears to be at least 10% lower than in (34 years), while the inter-annual variations have become more extreme. The downward trend seems to be independent of fluctuations in rainfall and has been linked to dam building activities that started in the late fifties (Nam Sokleang 2000). The variation in flood levels in the period is shown in Figure 1.2. The lowest levels occurred in 1998 and the highest in

7 Figure 2. Tonle Sap waterlevels Waterlevels (m) Average May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr Month Figure 1.2. Variation in flood levels in the period The physico-chemical conditions of the Tonle Sap Lake The weather in the lake area is dominated by the monsoon. During the wet season in May October winds are predominantly from south-west and during the dry season in November April from north-east. Wind velocities are typically low, on the average 2 3 m/s, except during short storms. The low wind velocities combined with the sheltering effect of vegetation make the inundated forest quite calm environment. Calm physical conditions facilitate net sedimentation and decrease aeration. Average yearly precipitation varies from 1300 mm in the south to 1500 mm in the northern part of the area. Precipitation distribution is characteristically heterogeneous so that drought and flooding can occur at the same time in nearby areas. The dry season lake bottom within the innermost contour line is quite flat. The low water lake depth is typically about 1 m and the water level raises 7 9 meters during the flooding. Lake water temperature varies between 28 and 33 C. The lake water is well oxygenated during the dry season because of the effective wind and wave induced mixing. During the flood inundated areas are to a large extent anoxic. Sediment rich water enters the Tonle Sap Lake from the Mekong through the Tonle Sap River or as an overland flow and to some extent from tributaries. During the dry season mixing and resuspension are effective and the lake water is quite turbid limiting phytoplankton growth. However, high dissolved oxygen over-saturation values are encountered in the dry season lake which indicates active phytoplankton growth near the surface. During the high flood the near surface waters clear especially in the floodplains. The water quality samples indicate that phosphorus may be the limiting nutrient for primary production during that period. Algal blooms have not been observed in the lake probably because of high grazing and nutrient and light limitation. 6

8 2 Linkages between flooding, sediments, water quality and environmental indicators 2.1 Summary As a conclusion, many impacts and indicators are highly correlating with each other in the Tonle Sap lake. It can be clearly stated that elevation of flood is playing a key role in general ecology. Most of the impacts are related to height of flood; higher flood produces larger amount of fish and keeps different habitats viable. Therefore all measures lowering or even delaying annual flood, will have negative impact on ecology of the Tonle Sap. Despite of lower production of floating rice during high flood, other indicators are highly reflecting the importance of high flood. Baran & Cain (2001) found in their preliminary study of flood-fish relationship quite similar indicators such as water level, duration of the flood, timing of the flood, regularity of flooding and quality of the flooded zone (habitats). In addition to these directly flood related factors migrations and dry season refuges are playing a significant role. 2.2 Hydrological factors Water level fluctuation Preliminary analysis of the water levels by WUP-FIN project showed the paucity of the data and a clear change in datum levels of water gauges: the observations collected before year 1962 showed to be much lower at the measurement station of Kompong Loung, which represents the most representative lake level measurements. Sopharit (1997) showed in his study that the difference was 2.5 meters, which can be used as correction factor. On the other hand there was a long gap of missing values Kompong Loung between WUP-FIN project developed an equation, which can be used when calculating lake water levels from Prek Dam values (Figure 2.1-Figure 2.2). It should be noted, that database includes some obvious errors such as very large variations between subsequent days. In spite of these errors, the water level data is good enough for proper estimation of ecological factors. Average water level values are presented in Table

9 Figure 2.1. Water level fluctuation averages in Kampong-Luong during , , (corrected), , (calculated of the Prek Dam values) and Figure 2.2. Water level fluctuation in Kampong-Luong between Values of years are calculated from the Prek Dam values. 8

10 Table 2.1. Average values of water levels in Tonle Sap in and in Earlier values calculated from Prek Dam values Water level duration Water level duration is one of the key factors affecting on the zonation of different biotopes. Water level duration curves are quite linear describing slow rise of water levels Figure 2.3. There is a slight difference in the shape of the uppermost curve of the years and , but it is obviously due to values based on simulations. Slowly reducing water levels below elevation of 2 meters are seen as mildly sloping curve between durations of %. Figure 2.3. Water level duration in Kampong-Luong and Values of years are calculated from Prek Dam values. 2.3 Water quality Water quality data has been collected by the MRCS WUP-FIN project since summer The water quality samples have been mostly analyzed in the Cambodian Ministry of Water Resources and Meteorology laboratory. Inter-calibration has been conducted with an 9

11 accredited laboratory in Finland. Over 2000 water quality samples and soundings have been processed so far. In addition several recording meters have been utilized for continuous measurement of oxygen, turbidity, conductivity, temperature and ph. This water quality data has been supplemented with recording flow, water level and meteorological measurements and regular MRCS monitoring data (see Figure 2.4). Figure 2.4. Location of WUP-FIN measurement points. Yellow boxes are RCM9 registering current and water quality meters. Other sites include 2 meteorological stations, registering water quality meters, water level meters and water quality sampling points Oxygen The lake water is well oxygenated during the dry season because of the effective wind mixing. The oxygen conditions are however quite different in the inundated areas during the wet season (Figure 2.5 upper cross section). The flooded forests and wetlands are characterized by anoxic conditions except near the surface. The reasons for anoxia are the calm physical conditions decreasing oxygen mixing and transport and decay of the organic material. Anoxic water can well up to the surface. There is some indication of this in the floodplain cross-section. The lower cross section shows the oxygen conditions in the lake proper. The water is well oxygenated especially near the surface. Often the central lake water is well oxygenated from top to bottom even during the high flood. According to measurements the characteristic feature of the floodplains is the large scale anoxia. Model reproduces this phenomenon well (Figure 2.6). 10

12 mg/l 10 m Figure 2.5. The Tonle Sap Lake and the water quality measurement cross sections. Floodplain water depths are shown on the left hand side with 1 m intervals. Circles show water quality sampling points in October Measured October 2002 oxygen west-east cross section from the floodplain and north-south cross section from the middle part of the lake are shown on the right hand side. Oxygen, PHT1 (red) and RF mg/l /08/ /09/2002 Figure 2.6. Measured oxygen time series from the middle part of the lake on the edge of the floodplain (red area) and western end rice field (green area). 02/10/ /11/ Sediment load The yearly sediment cycle of Tonle Sap is characterized by high sediment input during the flood period, sedimentation into the floodplain during the rise of the flood and outflow of the cleared water into the Mekong during the receding flood. The clearing of the water can be seen in the Figure 2.7 where the monthly sediment flow in Tonle Sap River is plotted as the function of the average monthly flow. Negative values (sediment outflow) are much lower than the positive ones. The sediment mass flow measurements should be further developed because the monthly sampling frequency is not adequate to capture the highly varying concentrations during the flood season. It is to a large extent unknown 11

13 whether the peak concentration has been observed or if the observed peak value is representative of longer time period. In the future recording sediment and flow meters should be deployed at least in the Tonle Sap River but ideally also in the main tributaries. Monthly sediment flow in Prek Kdam Sediment flow (tn) Average monthly discharge (m3/s) Figure 2.7. Monthly sediment flow in the Tonle Sap River, Prek Kdam, plotted as a function of monthly average flow. Positive values are into the Tonle Sap Lake and negative ones out. Year 1998 and 1999 data not complete. Figure 2.8 shows the calculated net sedimentation during the raising flood from May to September. Calculation is done using EIA 3D hydrodynamic and water quality model that has been calibrated with the field measurements. Measured tributary inflows, sediment concentrations and winds have been used in the simulation. The net sedimentation pattern corresponds to the morphology of the lake observed in the nature: natural levees can be observed on the lake shores and the constriction of the middle of the lake has probably been formed by sedimentation. 12

14 Figure 2.8. Calculated net sedimentation during the rising flood between May September. 2.4 Determination of environmental indicators Determination of good environmental indicators is a demanding issue. Good indicator describes properly changes in environment with the following properties: Sensitivity for temporal changes Sensitivity for spatial changes Reversibility Predictive properties Ecological significance Easiness and cost-efficiency of follow up Intelligibility and applicability of results Direct response for environmental change Reliability of historical data Low amount of annual and seasonal fluctuation Good control of uncertainties Insensitivity for global environmental trends Determination of ecological indicator is described in Figure 2.9. It should be noted that indicator can be abiotic or biotic, although common thinking is focused on biotic indicators. According to most of the authors, the flood properties are the most determinant frame-setting ecological factor of Tonle Sap area. On the other hand the changes in land use 13

15 and eutrophication issues are changing the environment whereas the climatic changes can enhance the effect of waves and exposure. Present set of ecological indicators is described to consider as widely as possible the obvious changes in environment. It should be noted that some of the indicators are based on findings of this study and some only on general relationship between the impact and indicator. Figure 2.9. General relationship between environmental impact and ecological consequence. Upper horizontal arrow indicates abiotic indicator and lower biotic indicator. 2.5 General impacts of water level fluctuation Floodplain vegetation is strictly related to hydrology and therefore all changes in water level fluctuation and timing of flood will affect directly on vegetation structure. On the other hand, the floodplain vegetation is also affected by human use and therefore natural zonation is partly limited. The most important properties of water level fluctuation are presented in Figure It should be noted, that most hydrological factors are linked together and large fluctuation range means usually higher maximum water levels and/or lower minimum water levels. In following chapters different hydrological impact factors with obvious ecological indicators are explained in detail. 14

16 Figure General overview of water level fluctuation with hydrological impact factors (boxes) Maximum water level Mimosa pigra can easily cover abandoned fields created as a consequence of high flood. High flood also benefits dispersal of Mimosa by spreading its floating seed effectively. Therefore the high flood can be theoretically considered as negative factor from the viewpoint of Mimosa invasion. Theoretically it is difficult to calculate the effect of high flood, because there is no follow up data of invasion. All environmental indicators shows essential role of the elevation of flood, which can be determined partly as driving force, but also as generalized abiotic indicator itself. It should be noted that it cumulates all others factors such as habitat availability and among others discharges in Tonle Sap River. Sarkkula et al. (2003) showed that flood is also playing a key role in transport of silt and nutrients. Possible pathway via primary production of wetland plants to herbivorous fish biomass is obviously one of the key issue in ecosystem health. The general impacts and indicative properties of maximum water level are described in following Figure Uncertain relationships are equipped with question marks. As a conclusion higher water level means larger variety of habitats as well as higher primary production including both periphyton and terrestrial plants. This stimulates higher herbivorous fish production and later carnivorous fish. As discussed earlier maximum flood level includes several relevant but also highly interlinked factors, which affect significantly on productivity of floodplain. 15

17 Figure Relationship between the elevation of the flood and ecology. Lower means lower flood, lower number of inflowing nutrients etc., higher means higher flood etc Minimum water level Minimum water level is essential from limnological point of view; in principle it divides permanent water body and flooding zone from each other (Figure 2.12). Minimum water level does not differ significantly between different years, because it is related to sea level. The permanent water body below 1.2 meters elevation is highly turbid and therefore unsuitable habitat for aquatic submersed vegetation. On the other hand lower water levels would mean more aquatic helophytic vegetation near the shoreline; comparison between JICA classification and present situation showed an increase of grass vegetation near the mouth of the lake. It is maybe related to low water levels of last few years or increased sedimentation related to watershed erosion. Relationship between the amount of flooded forests and minimum water level is unclear, but it is quite obvious that most of the flooded forest can benefit of the lower minimum water levels. The most representative forests are situated near the edge of lake and high minimum water level with increased wave erosion can affect negatively on their distribution. It can be stated that lower minimum water level can lead to higher biodiversity of species related to flooded zone, but on the other hand it can be crucial for pelagial species. It can also have adverse effect of sedimentation, which can take place already at the edge of pelagial zone due to sheltering properties of aquatic vegetation. This can lead to lower production of flooded forests and changes in primary production of floodplain. The consequences of changes in minimum water level are therefore difficult to predict; 16

18 therefore we cannot give any good indicators except amount of aquatic grasses which can be estimated via aerial photos or satellite images. Baran & Cain (2001) as well as Tana (2000) emphasized the importance of dryseason refugees for fish production. Lower water levels mean also less places for fishes to survive during dry season. Therefore the consequences of very low water level can also be quite negative as total. Figure Relationship between the minimum water level and ecology. + and signs represent short-term effect, long-term effects are largely unknown Water level fluctuation range Wide fluctuation range of water level will keep variety of different habitats high and enhance the zonation of floodplain (Figure 2.13). Smaller variation will degrade zonation and promote agricultural land-use at the upper part of floodplain. Ecological consequences are quite similar compared to other flood level related factors, which are discussed in chapter 2.5.1*. 17

19 Figure Relationship between the water level fluctuation range and ecology Timing of flood Timing of flood rise and drop are important ecological factors in Tonle Sap floodplain (Figure 2.14). Fast and early rise will harm significantly floating rice production, but on the other hand fish production will obviously benefit of the situation. Floating rice varieties may benefit of late flood, because stem should be as long as possible before the flood rises. On the other hand wider spawning and eating areas are available for fishes as a consequence of early flood. Fast recession of flood affects negatively on fish production, because the growing time of young fishes is more limited or part of fish eggs are affected by desiccation. According to locals the recession rice production benefits of rapid drop due to better availability of fields. Recession rice production plays only a minor role in total rice production, but it represent partly dry season cropping and is therefore quite important in food production. It is also stated that importance is increasing due to new productive varieties. 18

20 Figure Relationship between the timing of the flood and ecology Duration and regularity of flood Duration of flood is strictly related to other properties of water level fluctuation such as timing and total fluctuation range (Figure 2.15). In exact terms the longer duration means that high water level are more common and the shorter duration means opposite. Longer duration changes significantly zonation and promotes e.g. water hyacinth growth. It has been shown in several cases, that regulated water courses are extremely sensitive for overgrown of aquatic weeds such as water hyacinth, water lettuce (Pistia stratiotes) and giant salvinia (Salvinia molesta) (eg. Pieterse et al. 2001). Longer duration may benefit fish production, but with longer run the effects are negative due to changes in zonation. 19

21 Figure Relationship between the duration of the flood and ecology. Regularity of flooding is also playing important role in floodplain ecology (Figure 2.16.). Spawning success of fish is higher if rise of flood is regular without any significant drawbacks. On the other hand, Van Zaalinge et al. (2003) noted that the irregular rise of flood in induced best growth of riel; factors behind of two-peaked flood are partly unknown, but are maybe related to nutrient releasing properties of soil during wetting and desiccation. Most of the human activities also benefit regularity of flooding including fishing and agricultural activities. Validation of known relationships suffers inadequate data set and complicated linkages between different factors. 20

22 Figure Relationship between the regularity of the flood and ecology. 2.6 Impacts on the Lake productivity Tonle Sap forms a unique ecosystem. Owing large variation of water level it forms a nature made regulatory system, which have a significant role in food production offering extremely high fish production and also remarkable wide areas for cultivation of rice. Globally there are very few ecosystems, which can provide similar areas. The key factor in high productivity of Tonle Sap is the fluctuating water level providing a great variety of different habitats for spawning and preying fishes. However, the great fish catch about tn/y is mainly due to great amount of migrating fishes from lower delta and River Mekong (Zaalinge 2002). On the other hand the incoming nutrient and silt rich water forms a basis for the high production. Temporarily flooded areas are essential for the high productivity of Tonle Sap. Their composition and proportion should be defined and factors (seasonality and duration of flooding, soil properties, exposure) affecting on their presence should be determined properly. Frequency and duration of flooding forms a basis for zonation of aquatic habitats in Tonle Sap basin. Therefore the relationships between the factors affecting on the composition of littoral habitats and previous hydrological regimes should be defined. On the other hand to reach an exact quantitative estimation a good elevation model is needed. In addition to above mentioned factors clearly focused field works and use of existing data should be utilized for the determination of critical components and indicators of littoral aquatic habitats 21

23 2.7 Fish catch impacts Summary Observations on the bagnet (Dai) fishery for migrating fish in the Tonle Sap River, Cambodia, during indicate that year-to-year variations in maximum Mekong river flood levels and related Tonle Sap floodplain inundation strongly affect the yield of this fishery, which is dominated by short-lived species. The effect of variations in the height of the flood on the fish yield and on the average size of some major species are considered in the light of indicators and processes affecting the productivity of the lake, such as sedimentation and floodplain dissolved oxygen conditions. It is hypothesized that sediments carried by the Mekong waters to the Tonle Sap Lake bring in the essential nutrients that feed into the lake s food webs. The higher the flood the more sediment is brought in. This leads to improved survival and growth of fish and hence of fishery yields. Areas of high sedimentation rate and favorable oxygen conditions in the floodplain are coinciding. When defining the conditions for an acceptable reverse flow to the Tonle Sap, both water quantity and quality impacts need to be taken into account. Upstream developments, like construction of dams and reservoirs may lead to significant trapping of sediments and nutrients and reduce the fertility of the Tonle Sap system. This work is part of modelling at the Mekong River Commission Secretariat aimed at predicting the consequences of modifications in the Mekong s hydrological regime and environmental conditions for the livelihoods of the basin s population Hydrodynamic influences on fisheries One factor affecting the fish production is the transport of fish spawn and larvae from the Mekong to the Tonle Sap. Dredging, building of structures and changing flood regime alter the hydrodynamic characteristics of the flow and thus the areas where the spawn enters. Figure 2.17 shows the fate of the Mekong fish spawn during flooding. 22

24 Figure Modelled floating of fish spawn in Tonle Sap during flooding Relationship between fish catch and flood level Maximum water levels represents together with water level fluctuation range a key factor in floodplain hydrology (Figure 2.10). Higher floods means directly higher fish production (Figure 2.18) as noted by Van Zaalinge (2000). Van Zaalinge et al. (2003) showed the importance of flood elevation and Dai-fishery catch; correlation reached a high value (R 2 = 0.9) in Figure However, it is strongly influenced by the season, in which year both the maximum flood level and the catch were very low. Spawning success of fishes is related to available spawning grounds. High flood means also that fishing activities are dispersed more evenly at wider areas giving better possibilities for young fishes to survive. It should be also noted that main species in the Dai-fishery is riel (Henicorhynchus siamensis), which totals 39 % of the catch (Van Zaalinge et al. 2003). According the Lambert & Sarah (1997) this species uses inundated areas for feeding plant remnants and periphyton; the spawning areas and even spawning time is unclear. It is quite obvious that the species benefit so largely of large flood. On the other hand the fishing lot catch of snakehead (Channa micropeltes) was highest one year after high flood (Van Zaalinge et al. 2003). As a prey it can obviously benefit of high production of other species. High fish catch plays also important role in nutrient balance of lake, because a great deal of phosphorous and nutrients are removed as fish biomass. Lower fish catch can lead to eutrophication of water body. 23

25 Based on calculation of Van Zaalinge et al. (2003) the following relationship between the catch of Dai-fishery (CD n ) and elevation of flood on same year (MHW n ): Eq. 1) CD n = (1846*MHW n ) (R 2 = 0.803) Enhanced catch is mainly related to increased weight of a dominating specimen riel, which weight (CR n ) can be estimated according to following: Eq. 2) CR n = (1.5533*MHW n ) (R 2 = 0.614) Similarly the fishing lot catch of common prey snakehead (CS n+1 ) followed the flood elevation of previous year: Eg. 3) CS n+1 =(123.9* MHW n ) (R 2 = 0.610) 12 16,000 Maximum water level (m) Water level Catch 14,000 12,000 10,000 8,000 Fish catch (t) Dai fishery season 6,000 Figure Relationship between the maximum flood level of the season and the fish catch of the Dai or Bagnet fishery in the Tonle Sap Rriver. 24

26 Figure Dai fishery yield and maximum Tonle Sap water levels, Physico-chemical conditions affecting fish catch per hectare and fish growth The present study has identified three main physico-chemical factors that may have a central influence on the fish catch, behavior and growth: 1) sedimentation, 2) oxygen conditions in the floodplains and 3) transport of fish spawn and larvae. We hypothesize that nutrient bearing sediment is connected with primary production driving the fish growth. Oxygen conditions obviously affect where fish can live and reproduce and how different species have developed strategies for avoiding unfavorable conditions. Transport determines where upstream Mekong fish spawn and larvae end up and start their growth. Based on model calculations sedimentation appears to concentrate near the lake edge. The high net sedimentation areas in the north-west, central and south-east parts of the lake in the Figure 2.8 correspond to the high fisheries production areas. It is natural to assume correspondence between effective sedimentation, primary production and enhanced fish growth. Changes in the sediment load can cause major changes in the fish production. Thus upstream dam projects, changes in land use and erosion and climatological changes may affect fish production in Tonle Sap. According to both extensive measurements (Figure 2.5) and model simulations floodplains are by and large oxygen poor environments. Because of oxygen transport and dispersion, border areas between the well oxygenated lake proper and tributaries and floodplains have more favorable oxygen conditions than areas deeper in the floodplains. Open areas inside the floodplains such as lakes and fields offer better oxygen environments and safety zones for fish. However, flow can transport large masses of anoxic water both in the horizontal and vertical direction and trap or kill fish in these limited areas. One explanation for the observed fish deaths may be the anoxic water transport. Combined effect of sedimentation, favorable oxygen conditions and drifting of the spawn and larvae form the basic matrix for fish production. Future research should clarify their role so that the critical issues for lake management could be defined more precisely. 25

27 2.7.5 Conclusions Based on the observed relationships, we suggest that the sediment load of the water brought in by the Mekong River provides the nutrients necessary for the food chain that leads to the wealth of fish of the Tonle Sap Lake. As we have seen above, these sediments are largely being trapped at the interface between the oxygen-rich waters of the lake and rivers and the oxygen-poor waters of the floodplain, giving rise to a rich riparian vegetation of tall trees. The waters above the floodplain are much clearer than the lake waters, as nearly all sediments have been filtered out. This explains why the catch per hectare appears to be stable no matter whether natural habitats or agricultural lands are flooded. The biological productivity is derived from the sediments in the waters of the lake, rivers and especially their border areas and not from the extensive floodplains themselves. The sediments contain the nutrients needed by the phytoplankton. However, phytoplankton blooms do not occur in the lake, because of intensive grazing by zooplankton and fish. Stomach contents of a number of Tonle Sap species are described by Lamberts (2001). Many species such as the opportunists, feed on phyto- and zooplankton, while others, such as snakeheads (Channidae) prey on the plankton eaters. In the oxygenpoor waters of the flooded forests few fish species are found permanently. The airbreathing species of the family Channidae probably use the forest for nest building and venture out for feeding. Our present understanding is that also the sediment load of the Mekong waters varies from year to year and that higher floods bring in more sediments than lower floods. We have seen that the growth of the opportunist fish species, Riel (Henicorhynchus siamensis), appears to benefit from higher floods. This suggests that the quantity of nutrients carried in the sediment load may be a limiting factor at low floods. Highly migratory species, such as Riel, produce large numbers of offspring and can sustain high mortality rates. The greater abundance of food available at higher flood levels is likely to bring about increased survival of the young fish. The increased survival and better growth translate into higher catches. How constant the sediment load has been over time needs to be further clarified. The closure of the Manwan dam in China in 1993 led to an approximate halving of the total suspended solids in the river water at Chiang Saen (north Thailand) afterwards (MRC 2002). The effect was still noticeable at Pakse in the southern Lao PDR, but had apparently disappeared in Cambodia. The regional developments utilizing Mekong water, such as extensive damming of tributaries and the main river (in China), as well as irrigation, may lead to lower downstream flood levels and excessive upstream trapping of sediments, and thereby have a negative effect on the fertility of the Tonle Sap system, which appears to depend on high flood levels with a high sediment load. Further plans for Mekong water utilization should be strictly subjected to thorough assessments of the environmental and fishery impacts, especially on the Tonle Sap system. 2.8 Floating rice farming impacts As discussed in chapter 2.8.4*, Tonle Sap area is characterised by different rice varieties. Typical floating rice varieties are also adapted to slowly rising water level and therefore very sensitive against the changes in water level rising speed. During the last 26

28 years several districts have reported huge losses of floating rice production as a consequence of rapidly rising flood. Year dataset of floating rice production was collected from Ministry of Agriculture. Differences between the yields and different hydrological years were significant varying from 0.9 to 1.8 tn ha -1. On the other hand, the loss of floating rice production measured as a ratio between cultivated and harvested fields correlated negatively with the elevation of flood (Figure 2.20). During the years of a high flood, significant losses in floating rice production were observed. There are obviously two reasons for loss. Firstly most fields are too deeply inundated and crop is lost, second option might be related to lower production of floating rice, which concentrates farmers to put their efforts on receding rice. The loss in floating rice production (FR pl ) can be calculated based on the flood elevation of previous year: Eq. 4) FR pl = (11.829* MHW n ) (R 2 = ) Conclusion from the floating rice study: high correlation between the flood level and the floating rice loss (percentage of non-harvested area of the total cultivated area) / MAFF data (obs loss is ca. 50 % in the data file) in Figure 2.20 big differences in the success of floating rice farming between different areas of Tonle Sap floodplain (data collected from MAFF provincial Depts) in Figure 2.21 reasons for the area differences to be studied (differences in areas and cultivation, data quality). 80 Loss of floating rice (%) y = x R 2 = Elevation of flood (m) Figure Relationship between the elevation of flood (m) and loss of floating rice (%). Loss is calculated as a difference between cultivated and harvested area. 27

29 Floating rice loss by province % BNT%loss SR%loss Psat%loss BB%loss Kgthom%loss Kgchh%loss Year Figure Yearly floating rice loss in different provinces. 2.9 Habitat impacts Objectives of the study Present research is focused especially on Definition and quantification of links between hydrography and environmental indicators. The tasks include: 1. Collection and analysis of satellite data and other aerial photos 2. Determination of the areas of different flooding, soil-type, vegetation cover and exposure. 3. Import of data into GIS 4. Determination of composition and proportion of key-biotopes (habitats) 5. Analysis and synthesis of the local people interviews in respect to the habitats and flood properties and their impact on fisheries 6. Determination of links between hydrological regimes and other factors and littoral habitats including fish production. Figure 2.22 includes a schematic view of the Tonle Sap flow regime and water quality model. Circled area includes the area of this subtask and shows its position to general modelling environment. The main aim of this subtask is definition the environmental indicators for hydrological and limnological environment. Especially the focus is on flooded area where most of the processes take place. Tonle Sap ecosystem is heavily influenced by anthropogenic activities. Large floodplain has been hunting and fishing area, whereas uppermost part of flood zone is effectively used for agricultural purposes. In addition to normal rain fed or irrigated rice cultivation large areas are cleared for floating and recession rice fields. The natural vegetation of the floodplain has experienced long-term human use and is therefore partly 28

30 difficult to recognize. In addition to natural ecosystems anthropogenic ecosystems are extremely important for the local population and should therefore be assessed as valuable as natural ecosystems. Figure Schematic view of Tonle Sap modelling project. Circled area represents a focus of this subtask Field studies Main aim of the field studies were the following: To reach a proper view of floodplain zonation by making transect from national road to lake via rivers and/or paths To determinate the key-biotopes and their proportion on the basis of the JICA-landuse classification To check the exact borders of most important biotopes To estimate the situation of the most invasive species (Mimosa, Eichornia) at area To determinate indicator species and status of inundated forest by local interviews. Field trips were directed largely to the same areas, where McDonalds et al. (1997) focused their interest. Due to lack of local botanical knowledge, it was found useful to check the recently visited areas again to reach better view of species composition of the area. Field trips schedule, area and members of team are described in Table 2.2 and Figure 29

31 2.23. In addition to above mentioned places, the vicinities of Kampoung Thom and Siam Reap were visited by S. Hellsten and J. Sarkkula during the high flood period November In addition to visual interpretation of vegetation types with exact GPS-readings field visit included more detailed analysis of species and additional ecological factors. Research sites refer to places with detailed analysis, whereas observation sites include only places with GPS-readings and visual interpretation (Figure 2.23). Species identification was based on preliminary checklist of species with Khmer names by McDonald et al. (1997), but some herbs were checked later in Botanical Museum of Helsinki University. Table 2.2. General information of field trips during the study. Figure The Tonle Sap Lake with different flooding zones. Research sites marked with red dots and observation sites by green dots. 30

32 2.9.3 Soil type variation at floodplain JICA-geological classification divides floodplain of the Tonle Sap into 19 different types between the National Roads 5 and 6 with total area of km 2 (Figure 2.24). According to the classification the floodplain mainly consists of alluvial soils. The lake is surrounded by the organic deposits (swamps) and the lake bed deposits. The deltaic deposits, floodplains and alluvial fans are situated on the upper elevation levels mainly in the vicinity of rivers. The lake area itself (under 1,2 m elevation) has not been classified. The combination of land use- and geology-classifications shows that the flooded forests, flooded shrubs and grasslands and aquatic vegetation grow mainly in the organic deposits (swamps) which are prevalent up to six meter elevation. Receding and floating rice fields, from 1-2 m upwards, are split to three geological soils: floodplains, lake bed deposits and organic deposits. Wet season rice is mainly growing from the 5 meter elevation and accordingly is located in the lake bed and deltaic deposits. Both abandoned field classes are situated primarily in the lake bed deposits. Figure Elevation-geology relationship in the floodplain of the Tonle Sap Lake. Geological classes with minor areas have been removed from the chart, see complete list of geological types Rice cultivation as a part of ecosystem Rice cultivation areas around the lake form an essential part of floodplain ecosystem. Uppermost shrub vegetation is surrounded by large fields of floating rice, which are later replaced by rain fed rice agriculture. Rice ecosystem description is based on information obtained from previous JICA-project (Anonymous 2001a). Description of different rice cultivation practices with relations to annual climate cycle is described in Figure Rainfed lowland rice is almost completely dependent on rainfall and runoff water. Varieties are largely classified as early, medium and late ones. Late varieties are mainly growing at the flood prone low lands. The depth of floodwater varies between 0 25 cm, 31

33 but short time inundation below 50 cm is also allowed. Land preparation takes place between May-August, seedbed phase between June-July and transplanting follows July- August. Harvesting period takes place between November January. Rainfed lowland rice group includes also varieties, which are broadcasted during rainy season (June-August) and harvested November-January. Dry season rice represents less than 10 percent of total cultivated area. It can be divided into fully or partially irrigated second crop after wet season (transplanting May June, harvesting August September) and partially irrigated flood recession rice (transplanting February-March, harvesting April-May). It is quite obvious that latter is most common in Tonle Sap floodplain. Recession rice fields are flooded for 3-5 months before water recession takes place. To secure the survival of young plants, exact timing is needed. Therefore the sowing of nursery bed is done 5-10 days intervals to have different kind of seedlings. Figure Rice cultivation practices and schematic climatic factors of Tonle Sap floodplain. Cultivation practices modified from Anonymous (2001a). Floating rice, which can be called also as deepwater rice is growing in areas, where floodwater varies from 50 cm to 4 meters. Production practices are quite simple including cultivation and broadcasting of seeds. Early planting is needed to increase the possibilities for stem to reach the surface. Rainfed upland rice, forms only small proportion of total cultivation area and grows highland areas. Rice varieties have adapted to live at the ecotone between aquatic and terrestrial ecosystem. In general, seeds can resist one week inundation and seedlings can survive submerged not more than 10 days. Large water level variations of Tonle Sap provide an 32

34 unique and diverse environment for rice and therefore some very specific adaptations are found including floating rice varieties. Surroundings of The Tonle Sap Lake are characterized by continuous belts of rainfed rice agriculture, which is depending on rain, but on the other hand also limited by depth of flood water. High floods can cause significant harm for lowest rice fields. Between the area of (semi-)natural vegetation and rice paddies exists the area of floating and recession rice production. Floating rice species are adapted to rising water level, but too fast rise can lead to death of individuals. Volker (1993) claims that it can survive, when the rise is less than 10 cm per day. According to local experts the recession rice has suffered from too slow decrease of water stand, preventing transplantation. Recent statistics from Tonle Sap area are showing a slight increase in rice production (Figure 2.26). It is very evident that wet season rice is dominant offering more than 90 % of total production, whereas floating and recession rice varieties are playing minor role. Figure Distribution of rice production among different varieties at the area of Tonle Sap (provinces of Kampong Thom, Siem Reap, Battambang, Banteay MeanChey, Pursat and Kompong Chhnang). Floating rice production of 2001 is not included. Source: Ministry of Agriculture, Mr. Rathana Vegetation types and floristic diversity JICA land use classification and vegetation types JICA-land-use classification divides floodplain of the Tonle Sap into 40 different types between the National Roads 5 and 6 with total area of km 2 (Figure 2.27). According to the JICA-land-use classification the widest land-use types are natural vegetation types such as flooded shrub and flooded grasslands. Human modified land use types are paddy fields, abandoned fields covered by grass or shrub and also other crops in smaller amounts. Paddy fields are consisting mainly of the rain fed rice cultivation with 33

35 limited area of irrigated rice. Even though flooded forests do not cover large areas they form a significant vegetation type of the floodplain providing large variety of habitats. It should be noted, that land-use classification is not focused on formation of the functional vegetation types or habitats. Detailed field study with some additional aerial photos at selected areas showed that JICA classification was relatively valid: largest changes were found at the areas of aquatic vegetation and flooded forest. Time difference (5 years) between the field visit and satellite pictures may be significant in some rapidly growing vegetation types. Especially the zone between the shrub vegetation and the agricultural areas is varying; these areas were largely classified as abandoned fields covered by grass and shrub. Temporally changes can also occur between (flooded) shrublands and (flooded) grasslands. Especially aquatic vegetation has a drifting status (water hyacinth) and therefore rapid changes can occur. In fact aquatic vegetation was completely missing in JICA classification and after the field investigation all flooded grass areas situating between the elevation of 1 metre and the flooded forests/shrubs were classified as aquatic vegetation. Ground control points in the delta area of the river Stueng Sangkae and lake delta near Chhnok Tru showed that all classified flooded grasslands situated near water edge were consisting of emergent and floating aquatic vegetation. Figure Distribution of JICA-land use types at the Tonle Sap floodplain. Accurate definition of the flooded forests vegetation type is difficult. The outlet of the Tonle Sap Lake and especially the delta area nearby which were classified as extensive flooded forest zones are largely transformed to shrublands. On the other hand in the northern part of the lake between Siem Reap and Dei Kraham, as well as in the vicinity of Praek Tol the area of the flooded forest is larger. There is a m wide zone just above 1.2 m elevation contour (shoreline of Certeza-survey), which was classified as flooded shrub, but turned out to be the gallery forest. Due to limited possibilities to enter behind flooded tree zone and lack of up-to-date aerial images, it was decided to keep the original classification valid. 34

36 Based on the field trips, literature and expert interviews following types were distinguished (Table 2.3). It should be noted, that it is purely based on JICA-land use types, which were combined to the functional habitat-groups or vegetation types. Detailed view of western part of floodplain showed quite clear relationship between the elevation and vegetation types; natural vegetation was slightly replaced by agricultural lands when mowing upwards from lake area (Figure 2.28). Vegetation types were further linked to elevation model (Certeza-survey) used in WUP-FIN. Preliminary classification showed the following elevation-habitats relationship (Figure 2.29). Table 2.3. Original JICA-land-use types and their transformation into habitat/vegetation types used in this study. Total area of different habitat/vegetation types is presented in Table 2.4. Floodplain is clearly dominated by fields and shrub vegetation, which totals more than 70 % of dry land areas. Detailed analysis of other types is presented in following chapters. 35

37 Figure Detailed view of western side of floodplain and main vegetation types. Vegetation types modified from JICA-land-use types. Contour lines of 2, 5 and 10 meters marked. Figure Elevation-habitats relationship in The Tonle Sap Lake. 36

38 Table 2.4. Total area of different habitat and vegetation types at Tonle Sap floodplain below national roads. 1) Calculated as a share of dry land excluding water bodies Aquatic vegetation Aquatic vegetation consists of some emergent grasses such as Phragmites karka and Echinochloa stagnina (Figure 2.30). Latter species covers often wide areas at shallow zones forming outermost limit of vegetation. Lake or river margin is often dominated by Sesbania javanica. Freely floating species like water hyacinth (Eichornia crassipes) and water salad (Pistia stratiotes) are also typical. Especially water hyacinth can block narrow water ways and channels especially during the time of rising flood (Figure 2.30). Distribution of Pistia and fern Salvinia cucullate were concentrated on the upper parts of the floodplain. As noted also by McDonalds et al. (1997) real submerged species are completely missing, but some ceratophyllids such as Utricularia aurea, charids (Nitella-species) and lemnids (Lemna minor) were observed. Surface creepers capable to increase their stem length with rising water are very common. Different Ipomea-species, Polygonum barbatum and Ludwigia adscendens are typical representatives. Lamberts & Sarath (1997) noted that real nymphaeids such as Lotus are missing at lower areas of floodplain; our observations support their view. Aquatic vegetation covers an area of 57,9 km 2 and is limited between the elevation zones of 0 2 meters (Figure 2.28-Figure 2.29). Depending on flood level, the zone is enhanced easily to upper levels of floodplain, but the size is relatively limited. Aquatic vegetation exists almost totally on organic deposit Flooded forest The Tonle Sap Lake is generally well known of typical flooded or inundated forests as described by McDonald et al. (1997). Flooded forests are formed of relatively tall and densely growing trees: therefore also term gallery forest is used (Figure 2.30). Flooded 37

39 forest is a clear vegetation type, which forms a narrow edge between open lake/river and floodplain (Figure 2.28). Vegetation consists typically of tall (6-12 m) trees such as Barringtonia acutangula and Diospyros cambodiana (Figure 2.31). These trees are growing together woody lianas such as Combretum trifoliatum, Breynia rhamnoided and Acacia thailandica (McDonald et al. 1997). Some recent authors are proposing also term freshwater swamp forest, which is partly confusing due to its temporary inundation by flood waters (Goes & Chamnan 2002). McDonald et al. (1997) used a term gallery forests to avoid confusion between permanently flooded Asian forests. McElwee & Horowitz (1999) used a term swamp forests, because it reflects the status of low-lying characteristics, silty soils and permanent or seasonal flooding according to Hill (1979). Flooded forests covers only km 2 of the floodplain, which is only 1.7 % of the area and much less compared to earlier estimations (Figure 2.28-Figure 2.29, Table 2.4). McDonald et al. (1997) estimate the coverage of 10 % of floodplain, which is about 1500 km2. On the other hand, they are not giving exact area estimations; according our classification flooded forest can cover 3.7 % of natural vegetation types if we exclude all field areas. If flooded grass lands are excluded, we are reaching the number of 4.7 %. According to our observations, the borders between flooded forests and secondary forest/shrubs are very difficult to draw, because most shrublands include also relatively tall trees. It should also be noted, that flooded forests are mainly situated between 1 and 3 meter elevation zone even though they are distributed up to 8 meter elevation. Also river margins are covered by the levee -vegetation. These flooded forest areas are not identified in the JICA-classification probably due to their narrow character (Figure 2.28). Flooded forests are mainly situated on organic deposits, but some minor areas can be found also on lake bed deposits. 38

40 Figure Typical crass dominated aquatic vegetation consisting of Echinochloa stagnina near the mouth of River xx* (upper panel). Water hyacinth is blocking water ways during rising flood in Praek Tol (lower panel). 39

41 Figure Representative gallery forests near Dei Kraham (upper panel). More often trees are surrounded by shallow bushes and a limit between shrub vegetation and forest is difficult to draw (lower panel, left). Ptultrees (Diospyros cambodiana) are often tallest trees of the floodplain (lower panel, right) Flooded shrublands and grasslands Flooded shrublands are very common and widely distributed around the lake. As described in earlier chapter the limit between forest and shrub is difficult to determinate especially near the edge of the lake. Shrublands are characterised by before mentioned tree 40

42 species and some common shrubs such as Vitex holoadeon and Brownlowia paludosa (Figure 2.32). According to McDonalds et al. (1997) the whole floodplain has a high biodiversity consisting more than 200 plant species. Surprisingly the diversity was lowest near the edge of the water and highest on the shrublands. Shrublands are in some more permanently inundated depressions replaced by flooded grasslands. Soil type is typically organic deposits, but there are also some lake bed and deltaic deposits. Some authors are convinced that it is formed by fire (Goes & Chamnan 2002). Distribution of flooded grasslands as a ring parallel to contour lines support similar conclusion (Figure 2.28). It is relatively easy to imagine that these areas are a consequence of burning, because they are not reaching shorelines. Typical grasses are similar than those in aquatic vegetation. Flooded shrub and grass areas are distributed to the whole floodplain and cover totally km 2 of the floodplain, which comprises 43.1 % of total floodplain (Figure 2.28-Figure 2.29, Table 2.4). These vegetation types are therefore essential as habitats of different biota Abandoned fields covered by grass and shrub Abandoned fields form a buffer zone between rice cultivation area and (semi-) natural shrub vegetation (Figure 2.28). Zone is heavily impacted by agricultural activities and near large villages also the pasture pressure is high (Figure 2.32). Depending on flood elevation, lowest part can be also used for floating or recession rice cultivation. Also some slash-and-burn agriculture is practised (Figure 2.30). This zone covers km 2 (17.9 % of the floodplain) mainly between the elevations 4-10 m (Figure 2.28-Figure 2.29, Table 2.4). Due to overgrazing and other protective vegetation removing activities this zone is especially sensitive for invasive species. Largest coverage of Mimosa pigra were noted at the area and bare grounds are suffering of drought. Soil type is mainly dominated by lake deposits, but also some organic deposits especially in shrub covered areas. 41

43 Figure Typical flooded shrubland consisting of small Barringtonia species (upper panel). Abandoned fields near Sangkae (lower panel) Floating and recession rice, wet season rice Lowest areas of active agriculture zone are formed of fields of floating and recession rice (Figure 2.33). The limit between floating rice fields and normal rain-fed fields was difficult to determinate. Floating and receding rice fields are found as minor areas in the whole floodplain area covering km 2, which is only 1.6 % of the area. Soil type is 42

44 typically floodplain, lake bed or organic deposits. Major portion of the rice fields in the 1-2 meter elevation zone are located in the outlet area of the Tonle Sap Lake. Wet season rice fields starts mainly from the level of 5 m and continuous to both side of main roads covering km 2, which is 31.4 % of the total floodplain (Figure Figure 2.29, Table 2.4)). Soil type is typically consisting of lake bed or deltaic deposits. According to agricultural statistics however the amount of floating and receding rice is significantly higher. It is quite obvious that some of the floating rice fields are misinterpreted as paddy fields and abandoned fields in the JICA classification Other areas In addition to above mentioned vegetation types some other land-use types can also be found from floodplain. Garden crops are very common near upper flood limit and also some small forest areas can be found (Figure 2.28-Figure 2.29). Their proportion is only 420,2 km 2 which is only 3 % of the floodplain. Figure Floating rice fields in the beginning of rainy period near Battambang Development of vegetation Preliminary classification showed that the floodplain vegetation is highly interfered by human activities; rice fields are surrounding lakes and a belt of abandoned fields are typical buffer zone between shrub vegetation. There are different opinions of the origin of shrub-vegetation, but in most places local population stated that it is formed as a consequence of cutting the original forest vegetation for different purposes such as collecting of construction material, firewood or agricultural production. Some relatively well-preserved areas included still large flooded forests, which are protected for fish production purposes. 43

45 The amount of inundated forests differs widely between different research and the origin of vegetation is still unclear. Old descriptive studies of Rollet (1972a,b,c) do not give any relevant information concerning the forested areas. Vegetation map from sedimentological study of Carbonnel & Guiscafré (1963) refers back to year 1932, which might mean original study of Bejaud (1932). Vegetation map was scanned and areas between national roads were estimated (Figure 2.34-Figure 2.35). Vegetation map defines all present field areas as sparse forest, whereas a detailed view from some present forest area shows that savanna forest areas resemble flooded forests (Figure 2.28 and Figure 2.34). On the other hand savanna with few trees resemble the flooded shrubs. There is no clear information of the method of the field investigations, but at least the larger forests are situated near the river banks. As a conclusion an interpretation of results of Carbonnel & Cuiscafré (1963) is problematic (Figure 2.35). Non-forested areas are very difficult to separate from other areas. Sparse forests gives a value of 65,8 % of total land area if water areas are excluded. This is obviously too small value compared to values of non-forested areas in other investigations (see Figure 2.36). Savannas with few trees reach a value of 24 % of land area, which is quite near the present share (33.9 %) of shrublands. On the other hand, savanna forest covered almost 10 % of land area, which can be comparable to present areas of flooded forest after human activities. Figure Detailed view of western part of Tonle Sap in Dark lines represent savanna forests and narrow lines savanna with few trees (Carbonnel & Guiscafré 1963). 44

46 Figure Different vegetation types and estimation of their areas (Carbonnel & Guiscafré 1963). Recent development of forested areas is also partly confusing, but some similar trends are available (Figure 2.26). Rot (2002) combines data from Battambang fishing lots number 1 to 12, which totals 1448 km 2 area of floodplain. Forest cover was estimated from maps without any aerial photos (Roth, pers.comm.). Original area of forest before 1965 was 1117 km 2, but before km 2 was cleared. Between years total 32.5 km 2 was cleared including 29,9 km 2 burned areas and 6.9 km 2 cut areas. Forest cover in 1992 was only 792,4 km 2, which means that only 55 % of area was covered by forests instead of original 77 % (Figure 2.36). Ahmed et al. (1996) describe that in 1973 there was 9370 km 2 around the Lake, but in the total area has been reduced to 6300 km 2. If the total floodplain is without lake around km 2, forest (of which 40% is considered secondary or degraded forests), covers only 6300 km 2. This totals only 52 % of area (Figure 2.36). Anonymous (2002) describes also forest degradation statistics, where almost km 2 of floodplain was divided to recession rice fields, flooded grasslands and forests. Destruction of forests has been quite similar, which means decreasing trend from 84 % to 58 % (Figure 2.36). Combining of forested JICA land-use types gives a value of 39 %, which is the lowest observed value. Despite of limitations of the different analysis, the results showed very similar decreasing trend of forest cover. On the other hand, most of the studies are maybe based on similar topographic maps and a real field/remote sensing data is obviously missing. Obvious reason for destruction of forests is always easy to say, but difficult to justify by detailed way. Most authors blame firewood collecting, charcoal production, Samrasfishing, slash-and-burn agriculture and simply cutting of trees. Rot (2002) describes that total 97,8 % of total lost of forest areas between was due to burning. Ahmed et al. (1996) claims also that French government have cut 2500 km 2 of forests in for maize cultivation in the surroundings of lake. Recent work of Roudy (2002) concludes similar results. 45

47 Figure Distribution of forest and non-forest area according to different sources. Refer Rot (2002), Ahmed et al. (1996) and Anonymous (2002) for details. Relationship between the human impact and disappearance of flooded forests were investigated by following relatively simple test. All the villages situated below 10 m elevation within Tonle Sap drainage basin were selected. The 10 km and 5 km circles around villages were chosen by ArcView and all the flooded forests inside circles were picked. Area of flooded forest below 10 m elevation totalled 198,07 km 2. Forests are mainly located in narrow belt surrounding the lake within the 1-2 m elevation zone, but some areas located as high as 5-6 meter zone. According to JICA-classification the largest areas of flooded forest are situated on the Chhnok Tru delta and its surroundings, but there are several forest areas near the villages too. The largest areas of flooded forests outside the villages are in the western shore of the lake in the province of Battambang and in the eastern side of the delta area in the province of Kampong Chhnang. Results showed that 174,6 km 2 of the flooded forest located within 10 km circles divided in 96 separate areas. Within the circle of 5 km there were 72 flooded forest with total area of 86,1 km 2. Total 88,2 % of the flooded forests are located within 10 km distance from the villages and 43,5 % within 5 km distance. These results are not supporting the theory that fuel wood consumption has significantly reduced amount of forests. On the other hand, it is also well known that especially floating villages are favouring the places with tall, protecting trees. Therefore the results are not fully reliable Comparison of different vegetation typologies Vegetation classification of this study is simply based on land-use types, which enabled relatively exact determination of their vertical position. Comparison of our classification to other approaches lift up some differences. McDonald et al. (1997) divided the vegetation into four different types 1) Aquatic herbaceous vegetation consists of perennial herbs that grow as floating mats. 2) Gallery forests occupy the areas near lake littoral and forms therefore a stretch of tall trees around the lake. They are followed by the 3) Short-tree vegetation, which turns into 4) Shrubland vegetation at the upper level. 46

48 Vegetation structures are partly mixed and there is clear overlap in the horizontal division. Classification differs from our approach by division of short-tree and shrubs. As noted by McDonald et al. (1997) shrub vegetation is in most places very difficult to reach. River banks and lake margins are covered by short-tree vegetation whereas shrub vegetation can be found at isolated places. NEDECO-consulting group presents a slightly different division of habitat types of the area (Anonymous 1998). They have divided the floodplain to 1) short-tree and shrubland vegetation (covering 80 % of area), 2) stunted swamp forest (covering less than 10 % of area), 3) herbaceous vegetation and 4) submerged aquatic vegetation. Division follows largely our approach and can be used simultaneously. However, submerged aquatic vegetation is not very descriptive, because most of the plants are emergent. WWF classification scheme includes the whole area as a Tonle Sap freshwater swamp forests ecoregion, which is divided into short-tree shrubland and stunted forest with some seasonally inundated grasslands (Anonymous 2002). Obviously it also originates from NEDECO-report (Anonymous 1998). Van Oertzen (2002) divides major wetlands of Mekong area into marshes, swamps, peatlands and floodplain wetlands. Flooded forests are included to freshwater swamp forest. Lamberts & Sarath (1997) used also another classification theme, where they divided the habitats to 1) shrublands, 2) grasslands, 3) permanent waters (pools, lakes), 4) Lotusfields, 5) rice-fields, 6) forests and 7) open-water lake. The classification was applied only to quite limited area in Siem Reap area, but it can be applied on whole area. It does not differ from our approach significantly. Bonheur & Lane (2002) divided the vegetation types with very similar way; they are not mentioning original source of the data, but it is obviously based on same JICA classification. They have calculated the amount of different land use types as following (our results in brackets): 1) open lake km 2 ( km 2 with aquatic vegetation), 2) tall flooded forest km 2 ( km 2 ), 3) flooded forest with shrub km 2 ( km 2 ), 4) flooded forest with shrub abandoned agricultural use km 2 ( km 2 ), 5) flooded grassland or veal covered by grass km 2 ( km 2 ), 6) flooded grassland or veal abandoned agricultural use km 2 ( km 2 ) and 7) agricultural land km 2 ( km 2 includes rice-fields and village crop areas). Different vegetation types are not following each other very clearly as was noted also by McDonalds et al. (1997). Figure 2.37 describes the most common species of different zones; main types are highly overlapping and some common species are growing from lake edge up to 5 meters elevation level, where the natural types are restricted by surrounding rice fields. 47

49 Figure Schematic view of the main vegetation types and main species of Tonle Sap. Vertical distribution data is an estimation based on the McDonald et al. (1997) Vegetation types as habitats Despite of high influence of human activities, floodplain vegetation forms a great variety of habitats for aquatic fauna. Fish habitats are one of the most important habitats due to crucial role of fishery in floodplain. Lamberts & Sarath (1997) study provides some basic information of the habitats and their distribution on the lake although the results are 48

50 geographically limited only to Kampong Kleang and Chong Kneas areas. Based on the experimental gill net fishing, it was found that the highest diversity of fish species exists at the crass land and rice field areas (Figure 2.38). Figure Number of fish species caught in the different habitats in the experimental gill net fishing (Lambert & Sarath 1997). Also the catch was highest near the grass lands, but flooded forests played also as significant role. One of the most common fish species is Trey Riel (Henicrhynchus sp.), which is according to stomach content analysis eating mainly detritus and plant remnants. Flooded grass and shrub form quite suitable habitats for such a fish. They are obviously also playing a significant role in the nutrient circulation of the floodplain. Lamberts & Sarath (1997) divided functionally all biotypes according to depth gradient to the following four zones. Inundated rice fields are shallow zone presenting highly productive environment with high amount of nutrients and resuspended sediments. Main food resources are obviously phyto- and zooplankton. Shrublands are located at lower elevation and having rather deep water column and owns lower turbidity. Obviously periphytic growth of algae is much larger and plays important role in nutrient cycling. Forests present most stable environment with higher transparency and phytoplankton production. They plays also quite important role in wave protection purposes. Open lake represents quite homogenous environment, but the conditions vary largely depending on water level in lake. Production is mainly consisting of phytoplankton, zooplankton and zoobenthos. Their main conclusion was that the most suitable way to protect the environment is to preserve whole variety of biotopes. Results of Lamberts & Sarath (1997) are a bit confusing related to general trend of the importance so flooded forests for fishery. Especially the decrease of flooded forest has been estimated to have a lethal effect on fish production (Roth 2001). Tana (2000) proposes that deep delta areas are playing an important role as fish habitats during dry season and flooded forests are too sensitive area to provide stable living habitat for fishes. On the other hand there is a clear relationship between flooding level and fish production (van Zaalinge 2000, 2002, van Zaalinge et al. 2003, Baran & Cain 2001). 49

51 Role of the flooded forests as fish habitats are important. In general these tall forest are a gate to floodplain habitats and therefore fishing pressure is very heavy. They also act as huge erosion barriers providing a shelter against wave erosion and reducing resuspension of sedimented material. On the other hand their role as shelter providing structure for fishing boats and equipments is essential and therefore their role as habitats cannot be neglected. Forest area plays also crucial role as nesting ground of bird colonies (Goes & Chamnan 2002). Most nesting birds are using large trees as nesting sites and are indirectly also depending on fish resources provided by flooded forests. Bonheur & Lane (2002) compares diversity of different biological units in Tonle Sap area (Figure 2.39). It should be noted that the number of plant species is relatively low compared to number of fish species; the number of common plant species is also very low. There is no data of the distribution of species, but is very obvious that highest number of species is met in areas dominated by wooden vegetation. Figure Number of different biological units in Tonle Sap region according to Bonheur and Lane (2002) Invasive plant species Water hyacinth Water hyacinth (Eichornia crassipes) is a common part of edge forming vegetation in channels, rivers, sheltered bays and later after flooding period among other vegetation. According to local population it has been present since 1980 ies, although in some reports it has been noted to arrive since 1996 ies (Hirsch & Cheong 1996). Rollet (1972a) confirms that it is very common on the edge of vegetation of lakes and rivers in the beginning of 1970 ies. Water hyacinth is one of the most troublesome and harmful aquatic weeds, which have been reported causing problems in large lakes, reservoirs and rivers (e.g. Pieterse 50

52 1999). It originates from South America and due to its exotic hyacinth like flowers, it is sold as an ornamental. It spread started at the end of the nineteenth century in Northern America, whereas Africa it has recently spread through the continent (Pieterse 1999). It favours especially stable standing waters and can cover whole water surface. However, it has never reported to cause problems in the lakes with fluctuating water levels. Interviews of local population strengthened the opinion, that water hyacinth is a minor problem in Tonle Sap. Local population is also widely using water hyacinth for fish attractions and sometimes also as fertilizer of the fields or as cattle feed (Figure 2.38). It should be noted that water hyacinth is very noxious in stable water conditions and therefore all changes in water level fluctuation can cause significant changes in distribution of plant. It can be seen in small permanent ponds of the surroundings of Phnom Penh, where the whole water surface is covered by floating water hyacinth mat Giant Mimosa Giant Mimosa (Mimosa pigra) has caused a lot of problems in tropical Australia and Asia during the last years (Anonymous 1998, Marko 1999, Walden et al. 2002). It is an endemic species from Central America and extremely capable to survive in various ecological environments. In has entered the Northern Territory of Australia prior to the 1890 ies through the Darwins Botanic Gardens (Walden et al. 2002). Major spread took place in the 1970s as consequence of heavy flooding and overgrazing of Asiatic water buffalo. Walden et al. (2002) describe the spread at Adelaide River floodplain; in 1975 only a few mimosa plants were found, by 1978 infestation covered hectares and by hectares. By 1984 total hectares were invaded, whereas the latest figures from year 1989 proposed an area of hectares. Nowadays it is a big problem in Indonesia and Vietnam especially in the areas of National parks, where no active eradication program exists. Success of Mimosa pigra is based on its wide range of different habitats from wet sites to dry areas. It can resist inundation for several months and it is able to recover after burning or cutting at various bottom substrates from sand to silt. It is able to tolerate anaerobic substrates by sprouting adventitious roots that can absorb oxygen (Walden et al. 2002). It can also resprout from the remaining stem-base if cut of broken. The plants mature also quickly and can produce seeds after first years of growth. Seeds can float and they are even covered with bristles enabling to adhere to animals and clothing. Seed production is high ranging from per year according to Lonsdale et al. (1988). It can effectively form monospecific stands, which are able to cover whole land surface and compete other vegetation. In addition to these spreading properties there are hardly any effective control measures against Mimosa. Manual removal is suitable for young seedlings whereas fire can be used to remove taller plants. Natural competition by herbs is also suitable especially when reduction of grazing pressure takes places simultaneously (Walden et al. 2002). Chemical control is also widely used in Australia and Thailand, whereas biological control agents hardly exists. According to local population it has been seen in the Tonle Sap Lake first in the beginning of 1990 ies. Present field survey showed that it is widely distributed from lowlevel lake banks (+1.5 m) to the abandoned fields under heavy pasture pressure (+ 6 7 m). Mimosa stands were found in diverse places ranging from eroded shorelines to abandoned 51

53 fields. However, it cannot replace existing vegetation and therefore the areas with dense existing vegetation were practically free of Mimosa. Mimosa pigra has not been invaded in the northern part of the Tonle Sap Lake floodplain, mostly due to the dense vegetation (shrublands, fields) existing on the area. Largest and almost impermeable thickets of Mimosa were found at the areas of abandoned fields circulating in the southern part of the lake. The most abundant Giant Mimosa fields were observed in the Pursat region in areas classified as flooded grass and abandoned fields. Other dense Giant Mimosa stands occur in the delta area of the Tonle Sap. There are also large Giant Mimosa areas around Seam Reap. These areas are pinpointed already in the 1998 by NEDECO (Anonymus 1998). The report states that Giant Mimosa is only locally problematic in the Tonle Sap area. On the basis of the field trips it can be said that problems are already regionally significant. Potential area of Mimosa pigra infestation is therefore at least km 2, which totals 20 % of maximum flooding zone. It can be clearly stated that Mimosa is a major problem, which in addition to natural vegetation cover can also threaten floodplain fishery. One effective method of removal of Mimosa could be manual removal combined with flood effect. Walden et al. (1992) noted that according to Thamasara (1985) flooding will kill cut stumps after submersion of more than 30 days. Figure Typical fish attraction made of floating water hyacinth. Float is often surrounded by gillnets. 52

54 Figure Giant mimosa is invading commonly areas under pasturage or abandoned fields Human impact and ecology In addition to flood properties the whole ecosystem is affected by anthropogenic activities. Heavy population pressure has changed the amount of flooded forest and upper parts of the floodplain are transformed to agricultural lands. Land-use changes outside of floodplain have also significant effect on ecology (Figure 2.42). Increased erosion of watershed may cause also changes in floodplain indirectly by changing flood properties but also directly by affecting sedimentation of small rivers. Distribution of different land-use types is a clear consequence of human impact. Some obvious non-direct impacts are collected to Figure It is obvious that the changes in flooded forests and shrublands can cause changes in fish production. Increased pasturage will also lead to enhanced Mimosa problem, because it will benefit of competition free grounds available after overgrazing of cattle. It was also seen newly created accumulated sand banks were quite favourable habitats of Mimosa pigra and therefore increased erosion will also directly affects on Mimosa invasion. Indirect effect of anthropogenic activities via climatic change can have also significant impacts on ecology of Tonle Sap. In addition to changes in hydrology, increased wind action may cause changes in distribution of flooded forests (Figure 2.43). During field trip it was noted that most exposed parts of flooded forest were partly degrading, which might be related to changes in wind action. It should be noted that flooded forest are quite resistant against eutrophication. Most species are adapted to live submerged and in anoxia for a long period and real submerged aquatic species are completely missing. On the other hand floating species such as water hyacinth will clearly benefit of obvious eutrophication and maybe cause changes for other parts of ecosystem. 53

55 Figure Relationship between the land-use and ecology. Figure Relationship between the increased wind action and ecology. 3 Translation of model results into agricultural, navigational and ecological impacts Table 3.1 summarizes linkages between human activities and accompanied impacts/indicators and the model results that are used in assessing the impacts. Because the emphasis of the project has clearly been in primary data collection and construction of the impact analysis tools mentioned in the table, this chapter doesn t discuss in depth the use of the model in impact assessment. Chapter 3.1 describes ecological impact analysis tool and the rest of the chapters possible use of the system in real case impact analysis, management and planning works that have come up recently. 54

56 Human Activities Forcing Model Results Impacts/Indicators Management Options Climate change Land use changes Agricultural practices Clear cutting Precipitation, evaporation Soil properties Soil erosion/ accumulation Hydrological model: Groundwater height Soil water content Water quality Other catchment properties Soil properties (drought) Biodiversity Forestry Agriculture Socio-economic Catchment Management River regulation Climate change Land use changes Agricultural practices Clear cutting Energy production Artificial reservoirs River regulation Flood control Dredging Irrigation Municipal water utilisation Land use changes Clear Cutting Fertiliser use Cattle breeding Sewage water outlet Dredging Agricultural practices Releases from industry Releases from mining Runoff and washout River flow Sediment load Nutrient load Pesticides Heavy metals Acidification Salinisation River model: River flows River sediment and nutrient concentrations Hydrodynamic model: Water level Extent, timing and duration of flooding Water quality model: Sediment transport Nutrient transport Sedimentation, silting Primary production Eutrophication Hypoxia Harmful substances model: Pollution transport Pollution concentrations Table 3.1. Links Between Model Results and Environmental Impacts/Indicators. impacts Primary and secondary production Fish production and mortality Agriculture (irrigation) Navigation Power production Socio-economic impacts Soil/Sediment properties (salinity, drought) Aquatic habitats (ecotones/aquatic vegetation) Fish production and mortality Spatial location, timing and diversity of fish fauna Agriculture (flooded and irrigated fields) Navigation Socio-economic impacts Aquatic habitats Primary and secondary production Fish production and mortality Fish catchability Lake inflow-outflo w regime changes Navigation Socio-economic impacts Bioaccumlation Fish quality Fish diseases Human health Socio-economic impacts Catchment Management Forestation Erosion control River regulation Catchment management River regulation Flood control Dredging Management of flow regime Control of loads (small scale purification) Sediment manipulation (dredging, trapping) Control of aquatic weeds (mowing, biological means) Load control Control of water supply functions 55

57 3.1 IMPACT-model for prediction of ecological impact Determination of indicators focuses finally on submodel, which can be used as a part of the Tonle Sap model (Figure 2.22). It describes relationship between floodplain habitats and water level as well as changes in land use parameters. Input values are received from socio-economic scenarios as well as hydrological changes due to global environmental change via Tonle Sap model. On the other hand as a feedback it can provide a coarse estimation of the impacts of changed habitats on e.g. loading and other parameters used in model. In general, submodel is based on two different Excel/Visual Basic packages (Figure 3.1). REGCEL-calculation program is developed in Finnish Environment Institute to calculate the effects of different water level regulation practices on lakes (see eg. Marttunen et al. 2001, Hellsten et al. 2002). It calculates more than thirty parameters of daily water level values. Critical water levels for the aquatic environment and recreational use have been identified on the basis of field investigations and statistical analysis. The identification of water level characteristics as indicators was made in several research projects recently published in a review by Marttunen et al. (2001). Figure 3.1. Relationship between different subtasks and habitat/impacts calculation programs (REGCEL, IMPACT). Current REGCEL-application includes calculation parameters modified for Tonle Sap situation although also the basic parameters such as annual water level fluctuation and duration of water level are used. REGCEL-program is complemented by IMPACT subprogram, which uses REGCEL parameters to calculate habitat distribution and other qualitative parameters. IMPACT includes also some known relationships between indicators and hydrological parameters. REGCEL calculation needs daily water level values as input and present application uses daily values from Kompoung Loung in analysis. Typical outcome of REGCEL analysis looks as in Table

58 Table 3.2. REGCEL calculation parameters. At the moment, REGCEL calculates the following parameters: MW of the year Day index of first annual MW HW of the year or years Annual fluctuation range Duration of flood Rising speed of flood Lowering speed of flood IMPACT module imports elevation-habitat relationship into calculation and provides knowledge of habitat distributions under the situations of different water levels. Also some known relationships and regressions are combined to module. Typical output of habitat distribution looks like in. 57

59 Table 3.3. Habitat distribution typical output. As a consequence of calculation following ecological factors can be calculated: Catch of Dai-fishery Weight of dominating fish Riel Catch of snakehead Loss of floating rice production (see ). Figure 3.2. Loss of floating rice production. 58

60 It should be noted that both modules are only providing a basis for environmental analysis. More information of relationship between habitats and water levels is needed, to do more reliable evaluations. Effect of increasing eutrophication is also very difficult to estimate due to high productivity of tropical ecosystems. 3.2 Influence of Built Structures on the Natural Resources and Biodiversity of the Tonle Sap Phase I Database collection and impact analysis Built structures such as dams, roads, and flood control works can significantly affect fisheries by blocking migration and spawning areas, altering water quality and quantity, changing the temporal and spatial relationship and nature of the flood cycle, and degrading or fragmenting aquatic habitats. Below is a description of a possible procedure for assessing the impact of built structures especially on fisheries. The assessment of the effect of built structures obviously starts with collection of the data on the structures. The utility and power of the structure database (roads, dams, bridges, dikes etc.) will be greatly enhanced if it is integrated with other relevant data such as topography, river networks, land use, soil type information, water quality information, precipitation, discharges, water levels, infrastructure, population data, socio-economic data etc. The database will be also very useful if it can be connected to analytical tools such as GIS, bio-geo-chemical and statistical models and special spatial and temporal data analysis tools. WUP-FIN has collected such a database comprising of practically all available data, utilizing a graphical GIS-type user interface and supporting directly GIS, modelling and other tools. With a comprehensive and analytical database, information can be synthesized on issues like: what is the extent of influence of any built structure (data analysis, modelling) how will the structure affect flood propagation (terrain analysis or hydrodynamic modelling) how will the structure affect water quantities / water resources (balance study and hydrological modelling) how will the structure affect water quality (measurements, extrapolation from similar areas, combined hydrodynamic and water quality modelling) how will the habitats be affected (flooding, water quality and structure data together with the habitat data) how will fish production be affected (habitat analysis, water quality and sedimentation modelling) what are the effects of each individual construction to the whole system what is the combined effect of various constructions to the whole system how does the effect relate to natural variation of the system what are the external (upstream Mekong) influences on Tonle Sap (modelling)? Visualization is an important means for data analysis and presentation of conclusions. WUP-FIN database includes a large number of combined data processing / visualization 59

61 tools including vectors (flow), distributions (concentrations, any spatial data), GIS layers, maps and animations Phase II - Strategy for guiding future development The purpose of phase II is to develop a strategy and guidelines for planning structural interventions with potentially negative impacts on the ecosystem of, or the livelihoods in, the flooded area of the Tonle Sap. In the second phase a program will be formulated and designed for the collection of the data information needed to be able to make accurate predictions of the influence of built structures. The program will include a comprehensive specification of the additional studies needed to elaborate existing environmental impact assessments where they fail to address the impacts on the TSBR, and the design of any long-term monitoring systems that need to be established. Note will be made of influences external to Cambodia which may need to be taken into account for the long term protection of the TSBR. When drafting strategy for guiding future development, it is necessary utilize a) existing experiences from similar areas, b) local knowledge, c) expert opinions and d) analytical and quantitative estimation tools. Although the last point does not solve everything it gives necessary information on the central processes of the system, its vulnerabilities, and sensitivity to different factors affecting the area. Relying only on experiences and opinions can give wildly erroneous results when basic data and understanding is lacking, as has been the case in the Tonle Sap area. One of the key issues in strategy drafting is identification of the key factors and indicators. The scope of the impact sectors is potentially very large comprising biodiversity, biosphere reserve areas, fisheries, agriculture, human health and livelihood. The strategy delineation should give guidance on the relative importance on each sector, the main impacts expected and the measures to monitor and mitigate them. 3.3 Reservoir Management The aims of the possible management project are: establishment of a working relationship with local counterparts through a technical research project combining and providing technical expertise and tools for reservoir and river management both for the upstream and downstream countries identifying and filling of the existing data gaps on the upstream water quality and quantity, reservoir operations, reservoir processes and future developments identifying and quantifying downstream effects mitigation of both upstream and downstream harmful effects including reservoirs, river system, floodplains, Tonle Sap and delta. The technical topics that could be studied in the project are: modelling of 3D reservoir hydrodynamics, sediment processes and water quality understanding the filling up of the reservoirs, extent of sediment and nutrient trapping by the reservoirs, establishment of possible mitigation measures modelling of the downstream effects of altered flow, sediment and nutrient regimes establishment of optimal reservoir management practices 60

62 dam break modelling and the effects downstream optionally watershed modelling and management including hydrology, erosion and water resources management. 3.4 Navigational impacts The navigational applications would concentrate on maintenance of navigational channels and construction of harbours. In the navigational channel maintenance silting of dredged channels is a key issue. In Tonle Sap model can be used to asses: - erosion and sedimentation to the dredged channels - most favourable dredging routes from the maintenance point of view - conditions in the lake delta and selection of the best natural channel for navigation. Modelling of the harbor structures serves mostly planning and maintenance of the harbors. Modelling can answer questions like: - what the water quality will be within the harbour and how can it be improved with structural solutions - what are the silting and dredging needs in with alternative structures - what are the effect of chronic small releases of hydrocarbons (oil) or major accidents and how to best protect against them. The most physically sound and accurate way to model harbor structures is to include whole surrounding water body such as Tonle Sap in the model and model the small scale harbor structures with embedded high resolution model. The Tonle Sap 3D hydrodynamic model has this capability. 3.5 Fisheries impacts Possible project would act as a complementary component for other fisheries management and fish production projects providing quantitative information and key linkages between environmental factors and processes, fish production and socio-economic issues. The aims of the project are: - identification and modeling of key physical, biological and chemical processes affecting fish production - integration of the local (village level) knowledge into the process - providing of concrete qualitative and quantitative information for the management level models - increasing involvement of the local stakeholders - increasing competence level of local scientists and managers. Based on the MRCS recommendations, project would concentrate on the Tonle Sap as a key pilot area. Possible extensions of the approach include other Mekong floodplains, Mekong Delta and reservoirs. Also river, reservoir and wetland areas are possible to include in the project scope. 61

63 4 Model scenarios Model scenario work is ongoing. Scenarios must be developed interactively with MRCS and the stakeholders of the riparian countries. In this report mostly natural scenarios will be presented concentrating on flood properties, dissolved oxygen and net sedimentation. These variables have important linkages to the agricultural, navigational and fisheries sectors. Natural scenarios offer a good background on the natural variability of the conditions compared to what the human impacts can be assessed. Other results that have been presented in this paper and in workshops include effluents from floating villages and oil accidents. 4.1 Natural variation Three recent years were selected to represent natural variation in the Tonle Sap system. Year 1998 was exceptionally dry, in 2000 there was peak flood and 1997 is in between representing more typical conditions. The maximum water volume in 2000 was nearly twice that of the year The results of the year 1997 model simulation are presented in figure 4.1. They give overview of the lake conditions in a typical hydrological year. The rest of the chapter deals with the comparison of the years 1998 and 2000 and scenario simulations. The simulation periods start each year first of may and last one year. The outputs are average values (concentrations, bottom flow velocities), end state (net sedimentation) or specific values (flood characteristics). Year 1998 Tonle Sap inflowing sediment concentrations have been estimated for the most part because lack of data. The tributaries incoming concentrations have been estimated based on available data (Carbonnel 1963 and WUP-FIN measurements) DO and net sedimentation The dominant features of comparison between years 1998 and 2000 in the figures are: clear separation of processes and big differences in output parameter values between the lake and the floodplain increasing sedimentation and clearance of the waters in the floodplain, especially near the lake shore and the rivers strong dissolved oxygen depletion in the floodplain (even anoxia in large areas) large differences between different years. 62

64 Figure 4.1. Average simulated physical and water quality characteristics in

65 Figure D model flood and water quality results.comparison between dry year 1998 (left side) and wet year 2000 (right side). Net sedimentation between years 1997, 1998 and 2000 is compared in figure 4.3. The dry year 1998 doesn t only reduce to a large extent sediment input to the lake but also the 64

66 transport of sediments from the Tonle Sap River to the western part of the lake is blocked to a large extents. Figure 4.2. Computed net sedimentation of the Tonle Sap Lake in years 1997, 1998 and The model results can be analyzed with a special tool that calculates characteristic values e.g. different land use types or elevation zones. Below are example charts for the yearly net sedimentation (Figure 4.3). Western part Eastern part Sedimentation 400 (g/m 2 ) Sedimentation 400 (g/m 2 ) agriculture grassland shrubland forest water 0 agriculture grassland shrubland forest water Land use Land use Figure 4.3. Model results for different land use classes (agriculture, grassland, shrubland, forest and water). Sedimentation for the western part (left) and sedimentation for the eastern part (right). Lake ground elevations compared to the mean sea level and land use classes used in the analysis are presented in figure

67 Figure 4.4. Tonle Sap Lake ground elevations and land use patterns Radiocarbon analysis Radiocarbon analysis results on net sedimentation in the lake proper have been presented by Tsukawaki et. al (1997, 2002) in Figure 4.3, confirmed by Penny s results (2002). The net sedimentation rates found by Penny are about 0.15 mm/year over the last 5000 years (central and northern part). D E P T H B E L O W L A K E F L O O R ( C M ) M i l d e n h a l l T s u k a w a k i R A D I O C A R B O N Y E A R S B. P. 1 0 Figure 4.3. Estimated sedimentation rates of the northern part of the Tonle Sap Lake based on the radiocarbon ages of sediments Mildenhall, 1996, Tsukawaki et al., Conclusion on sedimentation studies: historical net sedimentation to the lake ca. 1 mm/year in the time before 5500 years B.P. the connection between the Mekong River and The Tonle Sap Lake established 5500 years B.P. net sedimentation to the northern part The Tonle Sap Lake proper has been in average 0.1 mm/year from 5500 years B.P. until present. The lake is not filling up with sediments! 66

68 Conclusions on the sediment modelling: WUP-FIN net sedimentation modelling fit well with the results of Tsukawaki and Penny (lake proper according to the model results the main sedimentation areas are in the flooded forest and floodplains in the vicinity of the lake proper and the rivers (Figure 4.2) model results are supported by the water quality measurements, where a steep decline of suspended sediments concentrations is found when moving from lake to the floodplain and by the topographic features of the lake where a natural levee has formed on the lake edges. 4.2 Dam trapping Model was run with a dam trapping scenario, where year 2000 flood was used but the sediment load from Mekong was halved. This can represent the effect of the Chinese dams upstream, which according to some estimates could cut half the Mekong sediment load in the future. It can be seen that this scenario would mean dramatic changes to the net sedimentation and productivity of the Tonle Sap Lake. Decrease of the sediment concentrations can already been seen in the mainstream Mekong water quality samples. Figure 4.4. Comparison between 2000 calculated sediment concentrations and net sedimentation, and dam trapping scenario (2000b). 67

69 4.3 Extent of tributaries influence Figure 4.8. The radius of influence of the tributaries. Upper figures average surface concentration (mg/l). Left with sedimentation, right without it. Bottom figure net sedimentation from the tributaries. Figure 4.8. illustrates the radius of influence of the tributaries. The spreading of the harmful substances can studied with the help of the figures. Left hand side figures show distribution of substance that is attached to the sediment or is sedimenting by itself. Upper figure is the average concentration in the surface and the lower figure net sedimentation. Upper right hand side figure is the average distribution of a substance that is not sedimenting. 4.4 Watershed scenarios Scenarios for the VMod watershed model The VMod watershed model can be applied for analysing different scenarios. It is possible to determine e.g. maximum and minimum flow rates caused by the precipitation and/or evaporation changes can be used e.g. for flood design how the possible climate changes may affect on the hydrology in the study area how the ground water pumping has an effect on the ground water height how the irrigation may affect on the hydrology of the whole catchment For selected catchment of Tonle Sap Lake following scenarios were done: Effects of the climate changes for Chinit Catchment The effects of the climate changes were estimated by doing two scenarios for Chinit Catchment: A. evaporation and precipitation will decrease 10 % and 20 % from the values of year 1999, respectively. B. evaporation and precipitation will increase 10 % and 20 % from the values of year 1999, respectively. 68

70 The results of the scenarios were compared to the calculated results of the year Present: Normal evaporation and precipitation: avg. flow in Kompong Thom 78.0 m 3 /s Scenario A: Decreased evaporation and precipitation: avg. flow in Kompong Thom 52.5 m 3 /s Scenario B: Increased evaporation and precipitation: avg. flow in Kompong Thom m 3 /s Hence, the average flow in Kompong Thom is 67.3 % of the normal flow in Scenario A and % of the normal flow in Scenario B. The daily outflows to the lake and ground water depths for the scenarios and the present situation have been presented in 4.9 and 4.10, respectively Scenario A Normal Scenario B Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Flow (m3/s) Nov-99 Dec-99 Jan-00 Figure 4.9 Daily flows (m 3 /s) for Chinit Cathment (outflow to the lake) Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan Ground Water Depth (m) Scenario A Normal Scenario B Figure 4.10 Daily ground water depths (m) for Chinit Cathment (Kompong Thom) Pumping ground water in Chinit Catchment 69

71 The effects of ground water pumping for the ground water stage and river flow were estimated by creating two scenarios for Chinit Catchment: C. Ground water was pumped 24 hours a day with the rate of 1.0 m 3 /s. The pumping place situated some 1 km east from the Kompong Thom and just next to the river. D. Ground water was pumped 24 hours a day with the rate of 0.5 m 3 /s. The pumping place situated some 1 km east from the Kompong Thom and just next to the river. E. Ground water was pumped 24 hours a day with the rate of 0.3 m 3 /s. The pumping place situated some 1 km east from the Kompong Thom and just next to the river. F. Ground water was pumped 24 hours a day with the rate of 0.15 m 3 /s. The pumping place situated some 1 km east from the Kompong Thom and just next to the river. Present: Scenario C: Scenario D: Scenario E: Scenario F: No ground water pumping: average ground water depth in KT 0.73 m Decreased evaporation and precipitation: average ground water depth at pumping point 3.11 m Increased evaporation and precipitation: average ground water depth at pumping point 5.94 m Increased evaporation and precipitation: average ground water depth at pumping point m Increased evaporation and precipitation: average ground water depth at pumping point m Below the results are presented (4.11 and 4.12) (the parameters for the soil are different to the first case study. Thus, the ground water stages between these two studies cannot be compared): The used aquifer depth for the study was 20 m. The ground water digital stage model is presented in Average ground water depth (m) Pumping rate (m3/s) km from the pumping point Kampong Thom Pumping point Figure 4.11 Average ground water depths (m) plotted against pumping rate (m3/s) 70

72 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 0 Ground water depth (m) Q = 1.0 m3/s Q = 0.5 m3/s Q = 0.3 m3/s Q = 0.15 m3/s Q = 0.0 m3/s Figure 4.12 Daily ground water stage on the pumping point Figure 4.13 Ground water stages as a digital terrain model. The depth from ground surface goes from blue (~1.5 m below the ground surface) to red (~3.0 m below the ground surface). GwQ is the pumping point situated basically in Kompong Thom. The pumping didn t have major influence on the river flow in this scenario. The connection between river flow and ground water depends a lot on the soil type and ground water stage. The parameters used for the scenarios are not based on any g 71

73 5 Socio-economic analysis 5.1 Socio-economic analysis of the Tonle Sap modelling project Introduction Socio-economical issues form an important part of the Tonle Sap Modelling Project. They will be taken into account in the baseline studies, in the development of management tools and in the produced guidelines. One of the aims of the project is that with the help of the outcomes of the project the utilization and protection of the Tonle Sap could be socioculturally acceptable. The main aim of the socio-economic analysis is to achieve basic understanding of the interconnections of the socio-economic and environmental impacts and factors in Tonle Sap area. The socio-economic analysis consists of two main parts: the socio-economic survey and the socio-economic policy model. The socio-economic survey consists from three components: databases analysis, participatory village surveys and other information sources i.e. literature reviews and expert interviews. Database analysis and participatory village surveys form the main components of the survey. The socio-economic policy model looks at the linkages and impacts between different sector policies and development goals. Whereas socio-economic survey increases the understanding of socio-economic situation in the Tonle Sap Area, the policy model has broader and overall approach and is used more directly to support decision making. Figure 5.1 presents an overall structure of the socio-economic analysis of WUP-FIN. Database analysis Other sources Village surveys Other sources SOCIO-ECONOMIC SURVEY WUP-FIN POLICY MODEL Figure 5.1. Structure of the socio-economic analysis of WUP-FIN. RECOMMENDATIONS Zoning of the villages The socio-economic survey must be linked with the other components of the project, and consequently, with the Tonle Sap Lake and its floods. Usually villages are classified 72

74 according to different administrative boundaries, such as provinces and districts. However, this kind of classification does not have direct connection to the lake and its changing water level. Thus, the decision was made to classify the villages according to their topographical location i.e. elevation. Urban areas were classified as their own zone. As a result, the villages of the Tonle Sap Area were divided into four topographic zones (rural zones) and one urban zone (Table 5.1). The values of the topographical location presented in Table 5.1 are above average sea level (asl). Topographical location Population Area [km2] Zone meters Zone meters Zone meters Zone 4 10 m to National Roads Zone 5 Urban areas All zones Between National Roads Table 5.1. Description of zones together with population and area. Figure 5.2 below shows a map of the Tonle Sap Area with different zones and all 1158 villages included in the study area. For more information on the principle of topographic zoning please refer to Keskinen and Rath (2002) and Keskinen (2003). Figure 5.2. Tonle Sap Area bordered with National Roads 5 and Database analysis 73

75 Database analysis includes database reviews, analysis as well as creation of a new GIS-based socio-economic database. The idea is to use the village level data from the different databases to gather extensive quantitative socio-economic information from the study area, and to construct a new GIS-based socio-economic database based on the gathered information. The new database arranges socio-economic information according to different topographical zones, enabling the linking of socio-economic data with the lake, and consequently, with the hydrological model. The socio-economic indicators included in the constructed database consist of various demographic indicators, such as age, population, literacy, occupations and use of natural resources. The main socio-economic databases used in this socio-economic survey are the Population Census 1998 and the Fishing Household Survey (FHS) by MRC and Department of Fisheries. Also several other databases were used to support information derived from the main databases. Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 All zones 0-19 years 56.0% 58.3% 57.0% 56.6% 53.4% 55.9% Literacy 35.7% 44.3% 48.9% 51.2% 66.0% 52.9% Females 50.6% 52.0% 52.2% 52.3% 51.9% 52.0% ETHNIC ORIGIN (FHS) Khmer 82.9% 100.0% 99.8% 94.9% 100.0% 94.6% Chinese 0.2% 0.1% 0.1% Vietnamese 14.0% 0.9% 3.0% Cham 3.0% 3.9% 2.2% Table 5.2. Some social indicators of different zones (Census and FHS). An example of information on different social indicators derived from the constructed database is shown in Table 5.2 above and of some economic indicators (main occupations) in Table 5.3 below. For more detailed information on different socioeconomic factors please refer to Keskinen (2003). Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 All zones CENSUS 1998 Agriculture 26.1% 91.0% 83.5% 77.0% 21.5% 63.4% Trade 10.3% 2.1% 4.9% 8.3% 30.2% 12.0% Fishing 55.2% 2.1% 2.4% 1.4% 0.6% 5.7% FHS Farming 17.1% 86.9% 86.5% 76.4% 31.7% 67.2% Fishing 60.9% 3.6% 3.8% 6.4% 6.3% 15.5% Trade combined 8.0% 1.2% 2.5% 4.4% 28.5% 5.3% Table 5.3. Main occupational involvement in different zones (Census and FHS). 74

76 5.1.4 Participatory village surveys Participatory village surveys (also called field studies) are based on different rapid and participatory appraisal (RRA/PRA) methods. Altogether six participatory village surveys were conducted in the villages situated around the Tonle Sap in the provinces of Kampong Chhanng, Pursat, Battambang, Kampong Thom and Siem Reap. Three first village surveys took place during the dry season when the lake was its shallowest, while three latter ones were conducted just after the rainy season and peak of the flooding. Aim of the village surveys was to collect up-to-date qualitative information on different socio-economic factors. The main focus of the village surveys was on occupations and their seasonal variation, use of natural resources as well as on environmental trends. Village surveys will also give better practical level understanding of local circumstances and enable wider participation of the villagers, the actual stakeholders of the project. Participatory methods used in the village survey were in chronological order: Key informant interview (semi-structured interview) Group discussion (semi-structured interview) Participatory mapping Transect walk and observation Seasonal calendar and occupational preference ranking Time ranking Focus group discussion and ranking on migration/urbanization Final discussion and analysis of the study. The idea is to use the key informant interview to collect more overall information on socio-economic situation in the village. Key informants included usually the village chief, a member of village development committee and a village elder. The group discussion focuses then on main indicators of the village survey, including livelihood and occupations, natural resources and environmental trends. With the help of the results from semi-structured interviews and participatory mapping and a transect walk, study is then concentrated on the issues of seasonality and recent changes in livelihood, natural resources and environment. This is done using two different ranking exercises: seasonal calendar and time ranking. Different visualization methods do not just create a useful final product but are used to facilitate further discussion. Discussions emerged during the exercises were written down and documented in the village survey report. 75

77 Kampong Preah Preak Ta Kong Ansang Sak Kampong Pradam Peam Kraeng Pou Population Level of livelihood Fish catch Area of flooded and other forest Availability of agricultural land Amount of cattle Flooding Water quality Sedimentation Table 5.4. Trends of different natural resources and socio-economic factors. Table 5.4 presents an example of the trends of different factors in all the six surveyed villages while Figure 5.3 presents an example from the result of the seasonal calendar rankings in four villages. For more detailed information on participatory village surveys and their results please refer to Keskinen (2003). Dec Jan 10 8 Preak Ta Kong (10) Feb Dec Jan 10 8 Ansang Sak (10) Feb Nov 6 4 Mar Nov 6 4 Mar 2 2 Oct 0 Apr Oct 0 Apr Sep May Sep May Aug June Aug June July July Dec Jan 10 8 Kampong Pradam (10) Feb Dec Jan 10 8 Peam Kraeng (10) Feb Nov 6 4 Mar Nov 6 4 Mar 2 2 Oct 0 Apr Oct 0 Apr Sep Aug July June May Recession rice (10) Floating rice (10) Sep Aug July June May Figure 5.3. Seasonal variation of rice cultivation. 76

78 5.1.5 Socio-economic policy model In order to understand the impact and effectiveness of different development options for the Tonle Sap Area, a socio-economic policy model was constructed. This model is based on Bayesian causal networks and offers a tool that examines the impact that different sector policies have to certain development goals. Three development goals were derived from the Mekong Agreement 1995 and are: economic growth, poverty reduction and environmental sustainability. Sectors included in the policy model are nature conservation, large-scale and small-scale fisheries, agriculture, road infrastructure, navigation, water and sanitation services, rural development, urban development, education, and governmental and other formal institutions. For more detailed information on WUP-FIN Policy Model please refer to Varis (2003). Figure 5.4 shows an example of analysis result derived from the policy model. The figure shows how much three development goals respond to small changes in sector policies (e.g. education, conservation). The further the line is away from the zero line, the more impact the sector policy has on the development goal. The impact is negative inside the zero line and positive outside of it. It must be emphasized that picture is not final product of the policy model but shows just one possible example of end result that different combinations of sector policies give. SENSITIVITY ANALYSIS Economic growth Poverty reduction Education, public health Urban development Rural development (villages) Formal institutions 20% 15% 10% 5% 0% -5% -10% -15% Conservation Environmental sustainability Small, medium scale fisheries Large-scale fisheries Water and sanitation services Agriculture, irrigation Navigation Roads Figure 5.4. Example of sensitivity analysis derived from WUP-FIN policy model Migration and urbanization Also the interconnections between villagers livelihood, environmental changes and migration were studied under the socio-economic analysis. The specific focus of the 77

79 migration study was on the reason behind the migration (rural push and urban pull), destination of the migration and the type of the migration in Cambodia and particularly in the Tonle Sap Area. Both quantitative and qualitative data was used to give a wide perspective of migration. Three latter participatory village surveys included also participatory exercise on migration. Furthermore, the Population Census and the studies by Oxfam about the migration in Cambodia gave quantitative data for the analysis of migration and urbanization. The study showed that during the five year periods (Census: , village surveys: ) approximately one to three percent of the population from the provinces and villages around the Tonle Sap Lake migrated. The main destinations for these migrants were Phnom Penh, Thailand, Koh Kong, Battambang, Siem Reap and Banteay Meanchey. The participatory village surveys pointed out that villagers were not willing to move but were rather pushed from the villages due to different reasons. These elements, such as the decrease of the rice yield and fish catch, floods, droughts, irregularity of the rainfall, the decrease of water quality and natural resources, together and alone formed the rural push which made the living in the villages unbearable. Thus, the urban pull appears not to be the dominant force of migration in Cambodia, but it rather is the difficult situation in the rural villages that forces the villagers to move. Most of the villagers would like to move to bigger cities where they already have friends or relatives. Also rumors, stories and gossips are a very important source of information for the migrants when they choose the destination of their migration. For more information on migration and urbanization please refer to Haapala (2003). Migration in Cambodia is high mainly due to a complicated history of the country. However, also the volume of recent migration is relatively high. The migration to the urban areas is yet not a big problem in Cambodia, but due to the problems in the rural areas it will definitely increase in the future. The urban areas in Cambodia are not ready to this kind of population growth. The growing urbanization is important to take into account in the decision making so that the unfortunate destinies of other developing countries in this respect can be avoided Final socio-economic analysis Final analysis puts together information derived from the analysis of databases and participatory village surveys as well as from other information sources. Analysis is performed separately for each zone in order to view the socio-economic differences between the zones and, consequently, to find the most important and defining socioeconomic characteristics for each zone. This kind of characterization helps to understand the interconnections that each zone has with the Tonle Sap Lake and also to recognize their vulnerability to the changes in different natural resources and in the environment on the whole. Table 5.5 presents some basic socio-economic characteristics for each zone. For the full analysis refer to Keskinen (2003). 78

80 Zone Definition Basic socio-economic characteristics Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 0 to 6 meters 6 to 8 meters 8 to 10 meters 10 meter to National Roads Urban areas Mostly floating villages; main industry fishing with some involvement in agriculture and trade; lowest level of livelihood; highest incidence of ethnic minorities, particularly of Vietnamese Main industry rice cultivation and particularly floating and recession rice; part-time involvement in fishing significant Main industry rice cultivation; involvement in fishing less significant than in lower zones; regular floods important for rice cultivation Main industry rice cultivation; growing importance of other industries like commerce and manufacturing; better access to the markets and higher level of livelihood than in the lower rural zones Occupational involvement more diverse than in the rural zones; highest level of livelihood and educational level; most developed infrastructure Table 5.5. Basic socio-economic characteristics of each zone. Overall it can be said that people living closest to the Tonle Sap Lake are in many ways in a worse situation than the ones living closer to the National Roads. They are generally poorer, less educated, have fewer livelihood options, do not own agricultural land and depend strongly on common property resources such as water bodies and flooded forests for their livelihood. Also ethnic issues are important as many of the floating villages are inhabited by ethnic Vietnamese. People living further away from the lake rely heavily on rice cultivation for their livelihood. With the rapid population growth, the decreasing availability of agricultural land causes problems in this area. Furthermore, the villagers depending on the cultivation of floating and recession rice are particularly vulnerable to the changes in the flood. The rural zones (Zones 1-4) can be classified into two main groups: the fishing zone (Zone 1) and the agriculture zones (Zones 2-4). Even though fish is an important source of income and protein for the entire Tonle Sap Area, fishing forms the main source of livelihood only in Zone 1. In all other rural zones, rice cultivation is by far the most important source of livelihood. Secondary occupations form an extremely important supplement for the main occupations in all rural zones, particularly during the seasons when the involvement in the main occupation is less. Urban Zone 5 totally differs from the rural zones. The occupational diversity in the urban areas is exactly the opposite of the rural areas. The main source of livelihood in the urban areas is more varied, while the involvement in secondary occupations is significantly less than in the rural areas. Furthermore, the dependence on natural resources is much lower than in the rural areas. People in urban areas are also wealthier, healthier, higher educated and have better access to services and the market. 79

81 The extensive poverty and a significant dependency on natural resources is particularly alarming since the products from all the natural resources are in a clear decline. The main reason for the decline of the natural resources is overexploitation. The decrease of the natural resources and the rapid increase in the population is an unsustainable combination that has resulted in the decrease of the level of livelihood throughout the study area. One possible solution to the decreasing trend of natural resources is more sustainable management of all the resources in the village and commune level. Cooperation and comanagement is needed between the villagers as well as between the government and local and international NGOs. Moreover, cooperation between governmental institutions and line agencies needs to strengthening, particularly between the central government and provincial line agencies. However, the development of village level co-management is only part of the solution. As can be seen from WUP-FIN policy model, development of education and governmental and other formal institutions has biggest overall impact on both economic growth and poverty reduction. Therefore it is extremely important to start development also from higher and much more overall level, aiming to improvements and reinforcements in education as well as in governmental and other formal institutions. 5.2 Linking socio-economic issues with the model results Socio-economic issues are usually included in development projects in order to increase the understanding of the socio-economic reality of local people and to consider these issues in the planning and the implementation of the project. In this way the needs and expectations of local people and other stakeholders can be integrated into the project in comprehensive and sustainable way. However, this has proved to be a rather difficult task. Due to the complexity of socio-economic issues they often form a separate component of the project without being properly linked to the project s other components. This is particularly applicable in different modelling projects where mathematical models are created and used as a tool to understand the reality and, consequently, to support management and decision making. While the model is founded on quantitative data, the analysis of socio-economic issues is usually based on both quantitative and qualitative data. This makes the linking between the socio-economy and the model even more challenging. In the Tonle Sap Modelling Project, the linkages between flooding, water quality, ecology and socio-economics are extremely important. The hydrological model offers a tool to examine these linkages. The difficulty of integrating the socio-economic issues to the whole modelling project, and consequently, to the Tonle Sap Lake and its floods, is addressed by connecting the socio-economic survey to the topography of the study area. This is achieved through grouping of the villages, where villages are divided into five distinctive zones according to topography and urbanization (Table 5.6). The flood and water quality data derived from the hydrological model can then easily be arranged according to the topographic zones. If needed, this data can also be used and analyzed in GIS. The grouping of the study area into five zones also makes the socio-economic information easier to analyze and is particularly reasonable when dealing with the databases which contain enormous amount of quantitative data. It must, however, be remembered that every village is unique and that the zoning presents therefore unavoidably too uniform 80

82 picture of the villages situated in the same zone. The basic socio-economic characteristics of each and every zone are introduced in chapter 6.1*. For more detailed analysis please refer to Keskinen (2003). Topographical location Population Area [km2] Zone meters Zone meters Zone meters Zone 4 10 m to National Roads Zone 5 Urban areas All zones Between National Roads Table 5.6. The topographic and urban zones of the study area. Next, an example of preliminary results derived for different topographic zones from the hydrological model are presented. The different flood indicators were extracted for two years, namely 1998 and This was done in order to see the differences between the two different kinds of floods as the flood in 1998 was much lower than usual and the flood in 2000 was exceptionally high. While in an average year the maximum flood height in Kampong Luong water level station is slightly above 8 meters, in 1998 the maximum flood height was 6.22 meters and in meters. Table 5.7 and Table 5.8 below present some basic flood indicators for the years 1998 and 2000 as derived from the hydrological model of the WUP-FIN. Indicators on water quality, such as net sedimentation and oxygen concentration, can be calculated and presented in a similar way. Abbreviation h used in the tables stands for the water height while the Duration means the duration of the flood in days. The presented values are average figures from the whole zones that were divided into 1 km x 1 km grids. Since the flood characteristics differ also between the different parts of the lake, the Tonle Sap Area was divided into the eastern and western part. The line dividing the area into these two parts runs from south to north through the narrowest part of the lake. Thus, the zones are divided into western and eastern parts. Furthermore, as the flood characteristics of the actual The Tonle Sap Lake naturally differ from those of floodplains, the original Zone 1 was divided into Lake and Zone 1 so that Lake consists of the area below the 1 meter contour line and Zone 1 between the 1 meter and 6 meter contour lines. Zone 5, i.e. urban areas, was not included in the calculations as these areas are outside the area flooded by the Tonle Sap Lake. 81

83 YEAR 1998 Area [km2] Max h Average h Duration [d] Time of max h Lake west Oct 3 Zone 1w Oct 7 Zone 2w Oct 15 Zone 3w Zone 4w West part Oct 6 Lake east Oct 2 Zone 1e Oct 3 Zone 2e Oct 5 Zone 3e Zone 4e East part Oct 3 Whole area Oct 5 Table 5.7. The flood indicators of dry year As can be seen from the Table 5.7 and Table 5.8, an enormous difference exists between all the main flood indicators of years 1998 and While the total flooded area in year 1998 was only 8100 km 2, the total flooded area in 2000 amounted to almost km 2. As a result, the dry year of 1998 left the entire Zone 3 without flooding while the flood of 2000 flooded almost the entire Zone 3 and even some areas from Zone 4. The extent of flooded area has naturally remarkable impact on the cultivation of rice that in the Tonle Sap Area is dependent on both rain and the seasonal flooding. While too extensive flooding can damage the rice crops, too low flood can leave fields with an amount of water that is not enough for efficient rice cultivation. In addition, the extent and volume of flooding appears to have strong positive correlation with the fish production that is particularly important for the livelihood of the villagers living in Zone 1. However, the economical importance of fishing reaches far beyond the floating villages in Zone 1 as fishing is important supplement occupation in the majority of the villages in the area and commercial fishing (fishing lots) in the Tonle Sap Lake and the Tonle Sap River is well developed and extensive. 82

84 YEAR 2000 Area [km2] Max h Average h Duration [d] Time of max h Lake west Sep 30 Zone 1w Sep 30 Zone 2w Sep 30 Zone 3w Oct 1 Zone 4w Western part Sep 30 Lake east Oct 7 Zone 1e Oct 3 Zone 2e Oct 8 Zone 3e Oct 8 Zone 4e Oct 19 Eastern part Oct 5 Whole area Oct 3 Table 5.8. The flood indicators of wet year Also the average maximum water height and average water height differ enormously between the years 1998 and For example, in Zone 2 the difference in the maximum water height is more than 2 meters between 1998 and As the floating rice is very vulnerable to the excessive water levels and too rapid rise of the flood, the changes in the maximum water height affect particularly the floating rice cultivation. While Zone 2 is the most dependent on floating rice cultivation, it is also practiced in several areas in Zone 3. The duration of the flood in different zones was naturally much higher during the high flood of year The time of the maximum water height appears to differ between the different years more in western than eastern part of the lake. The height and duration of the flood determines significantly when the cultivation of wet season rice can be started: if the flooding in the rice fields is too extensive, the cultivation must be postponed. Overall it can be said that the flood indicators in the different topographic zones differ considerably between year 1998 and The effect of these differences is particularly dramatic in Zones 2 and 3 where the cultivation of floating rice is most intensive. The damage caused to the infrastructure like roads and houses is more severe during the high flood, and can be notable also in the areas where the flooding does not normally take place, such as in Zone 4. High flood volume has strong positive correlation to the fish production, and consequently to fish catch, that is particularly significant for the livelihoods in Zone 1. Fishing also forms an important supplement for the livelihoods in other zones, particularly in Zones 2 and 3. Exceptionally low flood, on the other hand, reduces the fish production and can leave large areas without enough water for efficient rice cultivation. Furthermore, the variation of different water quality factors, such as net sedimentation and oxygen concentration, affect the production of both fish and rice. The changes in the flood of the Tonle Sap Lake affect greatly the level of livelihood of the villagers living in the Tonle Sap Area and particularly in Zones 1-3. In the villages situated close to the national roads (Zones 4 and 5), the effect of the Tonle Sap s flood is rather insignificant. Although floating villages in Zone 1 are most directly linked with the lake and its flood, the villages influenced most drastically by the changing flood are actually the ones depending on the cultivation of floating rice. Majority of these kinds of villages is situated in Zones 2 and 3. Even though fish production has strong positive 83

85 correlation with the flood volume, changes in the flood affect fish production, and consequently fish catch, less dramatically than the cultivation of floating rice. Thus, the floating villages of Zone 1 appear not to be as vulnerable to the flood changes. However, the economical importance of Tonle Sap s fish catch reaches much wider than just to the villages directly involved in fishing, and it actually has a remarkable impact on the entire Tonle Sap Area and Cambodia. 5.3 The Applicability of DRIFT in WUP and BDP for the Mekong River Introduction DRIFT addresses a crucial step in the analysis and planning of the development of river systems, namely the assessment of ecological and social impacts of river flow changes. It consists of an expert assessment protocol that includes experts from various disciplines. This panel assesses the impacts, given a set of critical and/or characteristic features of river flow situations in a set of future flow scenarios. This Memorandum presents some views to the potential of DRIFT in the MRC s Water Utilization Programme (WUP) and Basin Development Plan (BDP) contexts. The view leans from the experience from the WUP-FIN project for the Tonle Sap Lake The role of DRIFT in planning process The DRIFT has obviously its roots in Environmental Impact Assessment philosophy, particularly in project-level analysis of impacts of a given project to various environmental indicators. Cross-impacts are assessed, and compensations for those affected are considered. Characteristic to DRIFT as proposed by J. King and others in various sources is that a high level of background information on hydrology, ecology, and the social system is readily available. Accordingly, it is assumed that a good selection of various experts who are deeply involved in the research of that particular river system or at least in similar rivers elsewhere is well available DRIFT in WUP-BDP DRIFT offers some features that could potentially benefit the WUP-BDP program of the MRC in the analysis and basin wide planning of the future of the Lower Mekong Basin. However, there are important considerations that should be taken into account: 1. The basic data, understanding and knowledge as well as available expertise on the Mekong are very low. These basics should be developed before any serious planning and assessment process can take place 84

86 2. In the case of the Mekong, the question is not about the impact of one or few single projects, the impact of which should be assessed in a limited geographic area (a few cross-sections etc.) 3. The question is much more about net effects of various activities in a subcontinental scale, driven by a high variety of political, economical, social and environmental derivatives. The social and political issues are very complicated, and the compensation approach proposed by DRIFT is seriously oversimplified 4. The various uncertainties in the environmental flow system are addressed in the DRIFT protocol. However, no systematic analysis of them is proposed. A list of issues is not a systematic analysis. The implications are the following: Issue 1) The assessment of environmental flows should be based on sound hydrological, environmental and social information, data and expertise. The mandate of WUP is to contribute to these. WUP-FIN offers many cornerstones to build upon. These cornerstones include the data collection from the basin, the basin hydrological model, hydrodynamic water quality model, the extensive use of GIS as a combined environmental and socioeconomic database that is connected to the above-mentioned models, as well as the policy model that can relate all this information to the sector policies of the government and other actors in the area. Any assessment procedure DRIFT or another(s) should be constructed upon such a systematic, analytical framework, as a part of such a system. Issues 2) and 3) A sound analysis of the flow impacts of the various activities in the Mekong Basin is absolutely necessary before going into expert panel assessments. The impacts of the dam construction in China and Lao PDR, the thousands of agriculture-related water resources development schemes in Thailand and other countries, the impacts of massive deforestation and other land use changes, the human-settlement and industry-related changes and their impacts are among the crucial drivers of the Mekong Basin. At this point of time, not even the relative importance of these various issues is known in any appropriate level. The discussion in the media as well as among the experts is merely still in a very mythological level without much analytical evidence. Imposing an expert panel into the planning process at this stage would not be advisable in the present conditions. Issue 4) A sound analysis of the uncertainties and risks is important. DRIFT would identify many of them but they should also be analyzed. WUP-FIN offers a sound probabilistic tool kit for such a purpose. The WUP-FIN Policy Model is a custom too that has been constructed upon such a methodology. The methodology could be of great benefit the WUP-BDP process also in other application areas, merely in the analysis of the impacts related to environmental flows. 85

87 5.3.4 Conclusions The tasks that DRIFT is addressing should not be over-emphasized and seen too separately in the basin wide planning process of the Lower Mekong Basin. Given that the WUP has already constructed strong analytical platforms such as those of the WUP-FIN for the Tonle Sap Lake, the environmental flows issue should make the best possible use of those platforms that exist and are under construction, and not ignore them. The WUP-FIN could benefit from the DRIFT approach in the following respects: 1. Now that the tools are very much in place, a systematic analysis of environmental and social impacts could be done in more detail in the future than that can be done within the original extent of the project, which is two years and ends in June An expert panel methodology is an approach that should be seriously considered in the future work of WUP-FIN. However, the approaches used could and should be far more elaborate than those suggested by DRIFT. Perhaps there is a case of developing the DRIFT approach as well if seen valuable in this situation. WUP-FIN products could have a great value in various analytical and planning uses for the Tonle Sap area. 2. The geographical extension of the coverage of the applicability of WUP-FIN type of analytical approaches would be very useful for the basin wide planning process. Without basic understanding of the big framework of the Mekong basin, sessions such as proposed by DRIFT are not credible and may even lead to serious misunderstandings. 86

88 Finally, some points on DRIFT as seen as a possible part of Mekong s basin wide planning process are made in the Table 5.9 below: Strengths Weaknesses Opportunities Threats Pragmatic Attempts to be systematic Enhances crossdisciplinary dialogue Too split, not really holistic, does not push the analysts to harmonized, consistent views. Lists issues but does not put them together. Produces a picture, which is not dynamic and necessarily harmonious. Is philosophically based in studies in relatively small geographic areas where project-type of activities induce large, controllable changes to flows. In WUP-BDP, the problem setting is very different. Table 5.9. Summary of DRIFT in basin wide planning process. DRIFT or some of its features could be useful in WUP-BDP, particularly the expert panel, but the approaches should be more elaborate. In the case of the Tonle Sap, many such approaches are available and the environmental flow analysis could be embedded as one fruitful part of the future work. Its limitations and role should be acknowledged though. If the basic understanding of the environmental, social, economic and political situation and drivers are not systematically improved and addressed the DRIFT procedure may measure attitudes and prejudices that may yield in profoundly biased plans and recommendations. Such recommendations, if put in force, influence the daily life of millions of people that live from the river on a very basic subsistence level. Moreover, the political arena is not easy, and basing recommendations and plans on superficial, potentially prejudgetype of information is extremely risky and not plausible. 87

89 6 Guidelines and recommendations The following chapter lists some tentative guidelines and recommendations derived from the findings and conclusions of the WUP-FIN Project, proposed to be taken into account when assessing future developments in the Tonle Sap area as well as proposals and ideas on how to utilize the TonleSap model system in further studies and sector policy planning. Very much emphasis in this respect is put on the future use of the established model system for supporting the sustainable development in the Tonle Sap area, achieved only by continuous cooperation with the model experts and end users of the respective institutions, and their proper training. 6.1 Monitoring of Tonle Sap Lake and tributaries Water quality monitoring in Tonle Sap tributaries and lake and flood plain has been ongoing within WUP-FIN since June 2001 on monthly basis, in collaboration with the laboratory of the Ministry of Water Resources and Meteorology (MOWRAM). Monitoring network has comprised some 30 sampling and measurement sites in the tributaries, in the lake and in the flood plain. Intensive campaign was done in flood season 2001 in Tonle Sap tributaries for integrated discharge and wq measurements as MRCS/TSD, MOWRAM and its Provincial Departments and WUP-FIN cooperation. During the campaign trianing was provided for the provincial staff in water quality sampling. Tonle Sap water quality monitoring programme should be continued on monthly basis at representative sites in the main tributaries, in the lake and in the flood plain (monitoring strategy and network design will be proposed in the WUP-FIN final report) Specific attention should be paid to rising flood season monitoring in the Tonle Sap River to improve the information of the sediment and nutrient flow into Tonle Sap (e.g. at Prek Dam) and their dependency on the discharges. Sampling should be made weekly at least over the most intensive flood period and supplemented, if possible with continuously recorded data on turbidity (relative to suspended sediment concentration) The data on Mekong sediment/nutrient flux into the Tonle Sap system is of greatest importance for asessing the level and variability of the biological productibvity of the Tonle Sap system. Discharge measurements should be continued during the highest and lowest water levels to improve the rating curve accuracy. The provincial teams are ready to perform the measurements at a few days notice; the price is less than 50 USD per measurement. This information was collected in personal communication with the Pursat Water Resources Department staff in July Knowing the limited resources available, the Cambodian line agencies having the mandate of managing natural resources should make integrated efforts and find synergies in developing and running the monitoring programme for water quantity and quality. 88

90 The (only) national Tonle Sap water quality measurement site in Kompong Loung (KGL1) should be shifted from the vicinity of the floating village to the pelagic area, e.g. to KGL2 in the middle part of the eastern lake basin. A measurement station (tower in the lake) is proposed to be built near Chong Kneas, to provide water level and meteorological data representative for the western lake basin. Temporary station has been running within WUP-FIN project in the vicinity of the floating village since July 2001, until destroyed by unknown citizens in December Laboratory development is a prerequisity for reliable water quality data. At present state of finacial and human resources in Cambodia, cooperation between the relevant laboratories (MOWRAM, MoE, MIME, RUA/Faculty of Fisheries,...) should be strongly favoured. Capacity building is of great importance for improving the quality assurance. The available resources should not be put plainly in technical workshops but in every day cooperation and on-the-job instruction as well. Donor cooperation should be utilised at its maximum, e.g by creating links to DANIDA capacity building programme made for Cambodian line agencies. 6.2 Sedimentation in the Tonle Sap lake and flood plain The lake is not filling up with sediments. Net sedimentation in the lake proper has been about 0.1 mm over last 5000 years and is presently practically zero. Settling and resuspension seem to in balance as concluded by Tsukawaki (1997). Main sedimentation areas are in the flooded areas in the vicinity of Tonle Sap River and the flooded forests and fields in the vicinity of the dry season lake shore and tributaries. Natural levees have been formed in these areas over the last thousands of years, obviously as a result of this uneven distribution of sedimentation. Rather limited amounts of sediments brought by the flood waters seem to reach the middle and upper parts of the wetland typically used for floating rice and flood recession rice farming. This phenomenon may be one explanation to the low productivity of floating and recession rice fields and the nutrient poorness and soil degradation noted in these areas. Sedimentation studies have been made by coring technics and radiocarbon analysis only in the lake proper in late 1990ies. They are recommended to be extended to the flood plain as well, over cross sections reaching from the areas of highest sedimentation rates in the vicinity of the lake and rivers to the agricultural areas in the upper part of the flood plain. Nutrient content analyses in the soil should be included in the studies. Sediment trap measurements should be done in the flood plain to get further information and validation of the modelled sedimentation pattern and the rate of sediment and nutrient supply to the Tonle Sap ecosystem. WUP-FIN has initiated this work in flood season 2002 and plans to continue the work over flood season 2003, provided that the project extension will be approved. 89

91 Cooperation contact established with MIME/Geology Department and Kanazawa University Tonle Sap Project has brought up essential primary data and information on historical and present sedimentation processes and should be continued and further developed. One or two on-the-job trainees from the Geology Department should join the WUP-FIN team as soon as possible, mainly focusing on the sedimentation modelling and facilitating further studies and impact assessments in the Tonle Sap flood plain. 6.3 Biological productivity of the Tonle Sap Lake and flood plain The flood waters are known to be in key role in bringing of sediments and nutrients to the flood plains of river basin a making them fertile and productive. The high productivity of the downstream basin can be maintained only when the nutrient cycle is not interrupted by constructing dikes and reservoirs or changing the hydrological regime. Results from research in Amazon flood plains have been thoroughly reported by Junk and colleagues (Junk 1997). The flood pulsing system in the Amazon flood plain is very much similar to the one in Mekong Basin. A similar basic study on the role of floodwater quantity and quality in the flood plain biology should be carried out in the Lower Mekong Basin. The study should clarify the key processes of nutrient uptake to the food web through phytoplankton and periphyton, and finally to fish. An important link and mechanism in nutrient cycling in the flood plain may be the release of nutrients from sediment particles in strongly hypoxic or anoxic conditions, typically prevailing in the flood plains. The study should include laboratory experiments for testing the amount of biologically available nutrients bound to the suspended sediments. Availability of phosphorus seems to be key factor in regulating the biological production of Tonle Sap ecosystem. The WUP-FIN water quality and plankton studies indicate that most of the phytoplankton biomass is produced in the Tonle Sap system during the phosphorus limited high water period. In the plankton community there are also nitrogen fixing cyanobacteria species, which form natural blooms in low water period and are potentially toxic. The toxicity of the blooms should be tested. The Tonle Sap model system offers a platform for integrated data collection and system analysis studies as well as for cooperation between various devoted partners in this field. Cooperation has been initiated between WUP-FIN team, MoE, DoF and Cambodian universities. In this cooperation a strong training and capacity building component should exist, including research exchange with international universities. The Tonle Sap models, data base and findings will be utilized in designing the monitoring network as well as in data and system analysis. 6.4 Harmful substances impacts A baseline study is needed to survey the loads and possible impacts of harmful substances present in the Tonle Sap ecosystem, as result of e.g. mining activities and pestcide use. 90

92 The Tonle Sap catchment-floodplain-lake model system can be utilized in tracing the distribution of the harmful substances (possibly bound to sediments) originating from continuous or episodic pollution, in dry or wet season. The area of sediment deposition in the flood plain gives an indication of the dispersion and fate of the substances brought by the tributary waters from mining sites, and possibly their accumulation in biota. An indicator of long term impacts could be the concentrations in long living fish species, possibly migrating only within a certain tributary. River Sangke flowing from the Pailin mining area would provide a representative pilot study area (The French WUP related project has placed one of the two Tonle Sap monitoring sites in Sangke River). 6.5 Rice farming Recent years of big floods have highlighted the difficulties of floating rice cultivation in the Tonle Sap flood plain. High and steeply rising water levels have destroyed big part, if not all, of the harvest. Much of the damage is due to the fact that the well flood-adapted floating rice varieties were lost during the Khmer Rouge regime when the annual cultivation was not maintained (McKenney and Tola 2002). Floating and recession rice farming represent rather small part (ca. 10 %) of the cultivated rice area in the Tonle Sap, still being of importance for the poorest population to guarantee its food security. There seems to be willingness among the farmers to continue and develop floating rice farming e.g. due to its cost efficiency. The labor requirement for cultivating one hectare of floating rice is about 50 man-days, which is significantly less than the one for recession rice (100 days), rainfed lowland rice (90 days) or upland rice ( days) (Sokha et al. 2002). On the other hand, the difficulties in managing with the high floods as well as maintaining and improving the soil fertility are serious obstacles for the farmers. Natural fertilization of the fields brought by flood waters seems to be very limited, because not much sedimentation seem to reach the floating rice fields. Sediments are trapped mainly by the flooded forests in the vicinity of the lake proper and the rivers. Because of the water depth the use of fertilizers is not common (Lando and Mak 1994). Shift towards developing recession rice farming and the needed infrastructures, where the receding flood waters can be better utilized than presently, has been mentioned as an alternative. A choice between these two options must be done because they are practically taking use of the same farming lands. Development of receding rice practices necessitates infrastructure developments for irrigation, storing of flood waters (dams, dikes, ponds). Built structures impact must be assessed, especilally from fisheries point of view. The Tonle Sap model system can be utilized for this purpose. The flood plain model has been recently under development to be coupled with fine scale hydraulic structures. Plain abandoning the floating rice fields without receding rice or other cultivation use seems to allow the invasion of the nuisance plant Mimosa Pigra to these areas. After attacking the fields it is difficult to combat or to get rid of. 91

93 6.6. Acceptable reverse wet season flow to the Tonle Sap When defining criteria for an acceptable reverse wet season flow to the Tonle Sap, it is necessary to include both water quantity and water quality (sediments, nutrients) characteristics in the assessment. The upstream developments, especially the mainstream dams and reservoirs are a major threat to the downsteam ecosystems by changing the hydrological regime, reducing the water level during floods and reducing the area of the inundated habitats. The reservoirs may trap a significant part of the inflowing sediments and reduce essentially sediment and nutrient transport to the downstream basin and consequently, reduce the fertility and fisheries productivity of the flood plains. Tonle Sap, being the main source for fisheries productivity in the Mekong basin is under specific threat. The data and modelling results indicate strongly how fisheries production is reduced in years of low water levels and low sediment load to the Tonle Sap system. Even if the high water levels could be maintained, the reduced sediment load would mean significant reduction of the areas, where the sediments are deposited and creating basic conditions for high biological productivity. A thorough research and systems analysis is needed to collect the necessary information on the origin, amounts and fate of the Mekong sediments and nutrients, as well as the role of the main dams and reservoirs in changing the sediment transport and sedimentation pattern. The planned scientific-technical cooperation with China may offer a forum for initiating this work. Furthermore, the planned Mekong Information Center in Yunnan could be of high value in collecting and disseminating Mekong information in the riparian countries. 6.7 Minimum flow demands in Mekong delta The Mekong Agreement states the general objective for sharing the flow of Mekong mainstream and for regional collaboration on water resources development (Article 6). The upstream discharge conditions are especially critical for the lowest part of the River Basin, the Mekong delta in Vietnam, for ensuring the ecological health of the river and the necessary water amounts for various water uses, to limit the harmful effects of salinity intrusion and to protect the delta from flood damages. Modelling tools have been developed for the Tonle Sap lake and flood plain in Cambodia by the Syke (FEI) Consortium (MRCS Project ), as supporting activity to Water Utilization Programme. The aim has been to provide enhanced knowledge on flooding and its links to environmental processes and socio-economic functions (agriculture, fisheries and navigation). The need of applying these Tonle Sap tools to the similar critical area in the Mekong delta has been expressed by the Vietnamese National Mekong Committee and line agencies representatives. This would add significantly to the capacity for detailed and realistic analysis of the delta processes and impact assessments. The key issues and problems of agricultural water use in the delta are water shortage and seawater intrusion in the dry season and acidification due to sulphate soils. Water shortage 92

94 highlights the water quality problems like eutrophication, bacterial pollution and the impacts of harmful and toxic substances, including pesticides. Moreover, In the low and flat Mekong delta the major part of the area is flooded several months every year. There is need for the development of flood forecasting and alert systems as well as contingency planning for flood damage mitigation. Advanced mathematical flow models provide feasible and effective tool for addressing and analyzing these problems. Ecpected results of the delta model application are - effects of different development scenarios on sedimentation, water quality, agri- and aquaculture, fisheries etc. - estimation of saline water intrusion in different dry season conditions (3D process) - estimates of minimum and maximum flows to guarantee ecological and human health and needs - guidelines for allocating water between competing water uses (agriculture, industries, municipalities) - effects of upstream developments on flooding - improved flood forecasting accuracy in space and time (depth, flood arrival time and flood duration) - support for contingency planning of flood protection, support for decision making in emergency situations - capability established for Vietnamese experts independent use and maintenance of the developed tools Proposed time frame for model extension to the delta is two years ( ) 6.8 Environmental and socio-economic conditions WUP-FIN socio-economic analysis puts together information derived from databases and participatory village surveys. The Tonle Sap flood plain is divided into five zones based on their elevation from the lake surface. The inter-connections between each zone and the the Tonle Sap lake are analyzed. The aim is to recognize the vulnerability of the zones and their people to the changes in different natural resources and their availability. People living closest to the lake (elevation 0-6 m) are in worse situation than the others (being poorer, less educated, have fewer livelihood options, do not own agricultural land and depend strongly on common property resources): fishing is naturally the dominating occupation. People living further away from the lake depend much on floating and recession rice cultivation being rather vulnerable to the changes in flooding. For the people living in rural areas in zones between 6-10 m elevation, rice cultivation is far the most important source of livelihood. Secondary occupations (fist of all fisheries) form an extremely important supplement and flexibility in their seasonally and from the year to year varying environmental and living conditions. The extensive poverty of the people living in the Tonle Sap flood plain and their great dependency on natural resources is alarming since the products from all natural resources are in clear decline. This combined with rapid population growth is an unsustainable set up. 93

95 WUP-FIN modelling tools include a policy model that describes the impacts of sector policy and environmental scenarios on three development objectives defined in the Mekong Agreement 1995: environmental sustainability, economic growth and poverty reduction. The scenarios are composed of a set of sector and environmental policy options (11 in total) that are thought to be of central importance for the future development of the Tonle Sap environment, natural resources, economy and society (indicated by 28 impact variables). The connection between the policy options and their impacts is built in a link matrix, where the dependencies between all of the options and impacts have been defined as probabilities. Part of the links can be defined on the basis of existing information (qualitative or quantitative) from WUP-FIN Project or any other source, part must be judged by an expert opinion due to the lack of actual data. Each of the development objectives (environmental sustainability, economic growth and poverty reduction) are important for the future of the Tonle Sap area. In many aspects they conflict, but compromises are possible, or in fact necessary for balanced development of the area. The WUP-FIN policy model tries to find win-win solutions between these three development objectives. The first model results indicate that emphasizing some of the sector policies would be crucially important both for the economic growth and poverty reduction, namely education and formal institutions, due to their huge shortcomings presently. Rural development, in turn has a very important social function although it has not much immediate economical implication. Large-scale fisheries would be economically beneficial but counterproductive for poverty reduction. A surprise in the results is that the policies included in the model appear to be realtively toothless to environmental problems, particularly if defined as environmental sustainability. This is obviously due to the following reasons: - The concept of environmental sustainability is not easy to be conceptualized concretely enough so that it would be easy to treat analytically. In our model it is a combination of various issues and problems related to the environment and natural resources. - As the majority of the population of the Tonle Sap area live in villages and make their living from the lake or the floodplain in a fairly direct way, the environmental issues are very closely bound to social is-sues. Social developments therefore are tightly bound to environmental impacts, and typically what happens in model simulations is that improvements in social conditions tend to introduce both positive and negative environmental impacts which cancel each other, seemingly to a great extent. The situation was different if the governance system was more efficient. - The ecosystem of the Tonle Sap Lake is governed by the mighty floods of the Mekong, which raise the water level up to 9 meters, and subsequently the surface area of the lake grows fourfold. The sediments and other mass flows are also dominated by these monsoon floods. There are no handles in the sector policies included in the model that would allow the control of these issues. The first model runs were made with the link matrix designed by the WUP-FIN socioeconomic team. The impact of alternative link matrices to the development objectives 94

96 should be tested. This could be done by selecting a group of experts to design each their own matrix. To initiate this process, the following tentative list of persons is proposed Robyn Johnston, Solieng Mak, MRCS/BDP Ian Campbell, Hans Guttman MRCS/EP Chris Barlow, N.van Zaalinge, MRCS/FP Neou Bonheur, MoE XX, BDP Sub-Working Group for Tonle Sap XX /MAFF, Agronomy Department Bruce McKenney/ Cambodian Development Research Institute Patrik Evans/ FAO Tonle Sap Natural Resources Mnagement Poject Chou Meng Tarr, sociologist Olli Varis/Marko Keskinen/ WUP-FIN other. The design of the personal matrices can be facilitated by WUP-FIN team (Marko Keskinen). Half to one day per person is required to go through the causalities and probabilities. The facilitation by WUP-FIN team means guidance only in methodological sense, not in the definition of the probabilities of the links. The impacts of the different matrices to the results of the model and the response of the development objectives to them will be compared and evaluated. Based on the results and consequent conclusions, an ideal consensus link matrix could be set up, to be used in the development scenario runs. 6.9 Training, capacity building and sustainability of the model system For the successful maintenance and future use of the model system an extensive ownership and stable network of focal people is needed. The sustaining network (=user group) should be composed of representatives of MRCS/TSD, CNMC, line agencies and universities. Training programmes and the university lecture course must be continued. Much emphasis should be put on practical exercises and real life applications. This was the message from the questionnaire made in October 2002 among the WUP-FIN university trainees. Shortcomings in English language make a barrier for learning and reduce the efficiency of the training efforts. It is recommended to include courses in English language in the training programme, with emphasis on water resources vocabulary. Recommendation to MRCS: to compile a WATER RESOURCES DICTIONARY in English and in all six Mekong basin languages (the dictionary made for Baltic Sea countries could serve as starting point...) Trainees should be brought as much as possible into the project work (by scolarships) and 95

97 supervision should be provided for graduate and post-graduate studies on Tonle Sap questions. Trainees from other NMCs and riparian countries line agencies are recommended to be included in the training. As a start up, WUP-A training on Tonle Sap will take place for 1 sharing the Tonle Sap findings and experience with all the riparian NMC s trainees 2 making Tonle Sap modelling approach transparent and open for discussion for all the NMCs 3 promoting the integration between WUP-A and WUP-FIN and allow for the future development and use of the Tonle Sap modelling framework for other similar areas in the Mekong basin (e.g. flood plains, delta) The status of WUP-FIN training programme and use of the Tonle Sap model system has been handled in detail in Chapter 9 7 WUP-FIN tools in the basin-wide context 7.1 Platform concept WUP-FIN data management, modeling and analysis tools are not only capable to describe specific bio-geo-chemical processes but form also a platform for wide range of applications such as: uptake and recharge of groundwater (2D distributed watershed model) surface water uptake, irrigation, power production and other water resources management related activities (2D watershed model including 1D river network) land use change effects (2D watershed model including erosion and land use changes scenarios such as logging) flood forecasting and mitigation (1D, 2D and 3D) hydraulics structures simulation (weirs, levees, dikes, gates, dike and dam breaks, bridges, road embankments etc. integrated in other models such as 3D hydrodynamics) reservoir management; two types of specialized 3D reservoir hydrodynamics and water quality models for both detailed hydrodynamics and processes and decade long simulations in water bodies with high water level variations; model includes sedimentation and nutrient trapping lake and river processes (1D, 2D and hydrodynamics, erosion, water quality etc.) ecology (3D food web models including different size groups of bacteria and phytoand zooplankton; fish population models; bioaccumulation models; aquatic plants; different groups of phytoplankton, cyanobacteria and filamentous algae) benthic processes; bottom sediment processes and storages are described in three layers; temperature, oxygen and carbon content affect the processes; coupled with the 3D models 96

98 water quality; waste water management; mining effects; acidification; salinisation; monitoring support (3D suspended solids, BOD, COD, dissolved oxygen, total and dissolved nutrients etc.) harmful and toxic substances (3D oil and chemical spill models; wide variety of chemicals and chemical processes; heavy metals; pesticides etc.) delta processes including 3D saline intrusion, flooding, tides, complicated hydraulic structures, water quality problems and erosion (integrated 3D modeling tools) coastal applications (3D tides, flooded shores, ocean currents, erosion, coastal water quality etc.) wave models (number of stand alone or coupled models) These application modules have been developed and tested over 25 years in over 230 projects. WUP-FIN data management, modeling and analysis tools are based on a platform concept (see figure 7.1): Available data forms the basis of the tools; data typically includes spatial (GIS) and temporal (monitoring) data Data processing tools are used to analyze, visualize and process data; for the modeling purposes spatial data is typically mapped into the model grid and temporal data interpolated Both data and models are managed through a common interface Data management is separated from the models; because of this the platform is model independent and can support a number of exchangeable models or modules providing the model interfaces (input and output formats) are known The main principle in developing the WUP-FIN tools has been adaptability for future needs. The platform is very advanced and adaptable in order to support any current or future applications. Figure 7.1. Platform concept where both data and models (application modules such as groundwater or reservoir water quality) are managed through a common control and data processing layer. 97

99 The user sees the platform as a modeling workstation and/or GIS environment depending on the application. In figure 8.2 is an example of RLGis (RiverLife Gis) data processing and management environment that is used to process, analyze and visualize heterogeneous data, to make diagnostic water quality simulations, to connect databases (also over internet) and to generate data for models. Figure 7.1. RLGis data processing and management environment. In the figures western end of the Tonle Sap Lake is shown. Data includes river network, soil characteristics, land use, precipitation and flow. 7.2 Basin-wide management tool requirements The aim of this chapter is to analyze what kind of requirements and challenges Mekong environment creates for its management tools. The basis for WUP-FIN TOR has been these requirements and the need for integrated approach. The WUP-FIN tools have been developed not only for Tonle Sap but also to respond for wider basin wide needs. MRB agreement 1995 says in Article 6. Maintenance of Flows on the Mainstream C. To prevent average daily peak flows greater than what naturally occur on the average during the flood season. On the other hand: In recent years, there has been increased severity in floods and droughts. The cause of these floods and droughts (anthropogenic or natural) has not been determined, but they have caused severe damage to various areas of MRB (MRB Diagnostic study, p. 2-9). 98