Flood forecasting and River modelling of the Mekong basin

It is a paper from FAO organization that related to forecast Flood and simulate River Basin in the Mekong basin. This paper addresses the topic of floods in this river and its tributaries. In the Mekong, the ratio between 10% low flows and 10% high flood discharge is approximately 50. Years with severe floods were 1961, 1966, 1971, 1978, 1984, 1991 and 1995. Despite the high discharges, it is not common for Mekong River floods to cause casualties. The principal problem from floods is damage to crops and infrastructure. In 1995, for example, severe floods caused substantial damage in the Vientiane Plain of Laos. During that monsoon, an area of approximately 40 000 ha was flooded resulting in a damage estimated at US21 million.

Technical Session III (Contd.)

Flood forecasting and river modelling of the Mekong Basin

Introduction

The Mekong is ranked among the largest rivers of the world The river drains

an area of approximately 600 000 km2, covering parts of China, Myanmar, Thailand, Laos, Cambodia and Viet Nam (Figure 1) At Kratie, close to the upstream part of the Mekong Delta, the average annual discharge equals 437 billion m3/s, or an average discharge of around 14 000 m3/s Downstream of Kratie, the river enters the extremely flat and low lying Mekong Delta

This paper addresses the topic of floods in this river and its tributaries In the Mekong, the ratio between 10% low flows and 10% high flood discharge is approximately 50 Years with severe floods were 1961, 1966, 1971, 1978,

1984, 1991 and 1995 Despite the high discharges, it is not common for Mekong River floods to cause casualties The principal problem from floods is damage to crops and infrastructure In 1995, for example, severe floods caused substantial damage in the Vientiane Plain of Laos During that

monsoon, an area of approximately 40 000 ha was flooded resulting in a damage estimated at US$21 million

In view of the frequency of the floods, a good forecasting system is a necessity

to improve the preparedness of the population to floods and to support

evacuation plans Since 1970 the Mekong Secretariat (now called the Mekong River Commission Secretariat, or MRCS) has operated a flood forecasting system for the Mekong River during the flood prone months from July to October

Over the past decades many dikes were built along the Mekong River, in particular along the borders with Thailand Secondary effects of these dikes are the increase in downstream flood levels as a result of the reduction in floodplain storage, the faster propagation of floods along the river and impeded drainage of tributaries, causing local floods

However, there are also other factors contributing to a reduction of flood levels In the Mekong Basin many reservoirs have been built or are under

construction, which store water from the rainy season for use during the dry season, either for hydro-electric power production and/or for irrigation water supply Incidentally, such reservoirs may have a negative impact on flood levels as a result of changing lag times between peaks or the delay in

conveyance of water from the watersheds

Adri Verwey, River Modelling Specialist, WL/Delft Hydraulics, Netherlands

FIGURE 1

Basin of Lower Mekong River

Mathematical simulation models can be very instrumental in evaluating the effects of reservoirs and their operation on the Mekong River floods Flood forecasting models, in general, are of great help in improving the operation of reservoirs and avoiding unnecessary spilling of water Mathematical models can also lead to an improved understanding of the flood phenomena and provide insight into the causes of flooding In this manner, more appropriate measures can be taken to reduce flood damage.

As an example, one might look at a country like Bangladesh, where in 1986 UNDP and the World Bank supported the creation of the Surface Water Simulation Modelling Centre (SWSMC) Currently this centre has a staff of 42 and is in charge of flood forecasting and flood control modelling for the

country At SWSMC flood forecasts are produced at 32 stations spread over the whole country Many of the simulations made relate to the design of controlled flooding systems

The simulation models used and their supporting techniques have improved substantially over the past years One important factor to this is the increase incomputer speed and memory capacity As a spin-off of this development, also many new technologies have emerged, which open up many new possibilities

in flood modelling and in land and water development projects more in

general

The MRCS flood forecasting centre

Flood forecasts at MRCS are prepared on weekdays during the months July toOctober Data are received from 22 rainfall stations and from 37 hydrologic stations between 07.00 and 09.00 hours daily Water level forecasts are produced for the stations Chiang Saen, Luang Prabang, Chiang Khan,

Vientiane, Nong Khai, Nakhon Phanom, Thakhek, Savannakhet, Mukdahan, Pakse and Kratie and are sent to the member countries by fax around midday

In alert situations the forecasts are also produced during the weekends An example of the report is shown in Figure 2

Data received are transmitted via Fixed Frequency Radio Transmission Apparently this system is quite frequently out of order at some stations

However, within the Improvement of Hydro-Met Project, funded by the

Governments of Japan and Australia, the number of stations is being extendedand/or rehabilitated The improved system will still be based upon radio

transmission of data

Flood forecasting at MRCS is based upon a SSARR model calibrated in 1970

It comprises the Mekong from Chiang Saen at Thailand's border with Myanmar

to Kratie in Cambodia The model consists of eight principal reaches, each of which has a number of watershed models attached to the nodes Some of these watershed models also have channel routing components The

schematization is shown in Figure 3

At MRCS the probable rain depths are estimated from information received from the Thai Department of Meteorology This information includes current

rainfall data at ground stations and their forecasts These forecasts are also based upon weather charts and ground radar imageries.

Cambodia (855-23) 42 26 201, Lao PDR (856-21) 21 7013, Thailand 398 9816

or 339 4010, and Viet Nam (844) 82 56929 National Mekong Committee Nongkhai (042) 42 0327, UBon (045) 31 1969 and Mukdahan (042) 61 1027 Hydrology Centres

From: Hydrology Unit, HRD and Environment Division, MRC Secretariat

Subject Flood Forecast in 1997

Date: Tuesday, 05 August 1997 At Pakse, the water level is going down below the flood stage.

Observd Rainfall (mm)

Zero Gauge above MSL (m)

Flood Stage (m)

07 Aug

08 Aug

09 Aug

10 Aug

Chiang

Saen 2,363 0.6 357.310 11.50 5.88 5.89 5.78 5.66 5.55 5.64Luang

Prabang 2,010 NR 267.195 18.00 11.68 11.64 11.58 11.45 11.32 11.38Chiang

Khan 1,717 33.5 194.118 17.32 11.24 11.13 11.04 10.97 10.93 10.85Vientiane 1,580 21.0 158.040 11.50 8.48 8.45 8.23 8.05 7.95 7.85

Nong Khai 1,550 22.2 153.648 12.20 9.29 9.34 9.12 8.94 8.85 8.74 Paksane 1,395 39.4 142.125 14.50 12.33

Nakhon

Phanom 1,217 0.8 132.680 12.60 11.00 10.88 10.77 10.60 10.36 10.12

Thakhek 1,216 2.4 129.629 13.50 12.40 12.28 12.17 12.00 11.76 11.52 Savannakhe

t 1,125 3.5 125.022 13.00 10.26 10.13 10.07 9.87 9.63 9.39

Mukdahan 1,128 0.5 124.219 12.50 11.34 11.21 11.15 10.95 10.71 10.47 Ubon NR 105.074 5.98

Tan Chau 220 n/a 0.000 4.20 n/a

Chau Doc 200 n/a 0.000 3.50 n/a

Charge: 2.1.13/93/JPN/Line 53 Drafted: Tien/Manoroth Concurred: Tanaka

Approved: Sok

The modellers who estimate rainfall data during the lead period of the forecast also use 10-day forecasts based upon the Global Numerical Meteorological Model for reference Data of further refined models are available from the Japan Meteorological Agency Results of their Operational Numerical WeatherPrediction Models cover the Mekong Basin in more detail and forecasts are made available through the internet in the form of bit maps Expected daily rain depths are shown in eight classes on a logarithmic scale

Based upon experience, corrections for topographical deviations from the forecasted rain depths are entered into the average catchment rain depths provided to the SSARR model As the rain infiltration processes were

calibrated on the basis of 6-hourly rain depths, the daily depths are distributed over the day with assigned probabilistic weights of 0.2, 0.4, 0.3 and 0.1

respectively

FIGURE 3

Schematization of the flood forecasting model

Each forecast is based upon computations started four days ahead of the actual time of simulation The simulation is initiated with measured discharges,overwriting the computed ones Soil moisture data are maintained, which implies that the rainfall-runoff models are not being updated.

Operation of the models is still based upon the manual editing of data in ASCIIfiles Data follow the old Fortran convention of formatted data input, which requires very careful checking of the position of digits and causes an

unnecessary risk of mistakes The models are still the same as those

calibrated in the seventies However, corrections are made for systematic errors in catchment runoffs as these have been determined during the years over which the model has been in operation

Model results are analysed carefully before issuing the forecasts Computed discharges are converted into water levels via the known stage-discharge curves Consistency is obtained with these data through the input of initial discharges converted from water levels by means of the same rating curves

Despite all these measures, the quality of the forecasts is not high Although the one-day forecasts appear to produce acceptable results, the five-day forecasts at some stations give peak watér levels which are sometimes out by

a half to one metre

The hydrodynamic model of the mekong

In 1988 Delft Hydraulics was commissioned to conduct a study titled “Scientificand Technical Assistance for Hydro-Meteorlogy and Mathematical Modelling” with the following objectives:

 optimization of the hydro-meteorological network of the Lower Mekong Basin;

 implementation of a database management and data processing system; and

 development of a Master Model of the Lower Mekong River for

simulation of flow and salinity intrusion

The resulting Master Model is a 1-D mathematical flow model of the Mekong River from Chiang Saen to the sea The model was developed with the

objective of becoming a key instrument for planning, analysis and design in the Mekong River Basin In particular, it enables studies on the effects of natural and man-made interference's in the river basin The Master Model wasdeveloped on the basis of Delft Hydraulic's WENDY package (further

developed since into the software package called SOBEK)

The Master Model consists of three parts:

 the River Model for flow simulation in the reach Chiang Saen to Pakse;

 the Delta Tidal Model for flow and salinity intrusion simulation in the reach of the river from Phnom Penh to the sea; and

 the Delta Flood Model, covering the reach from Pakse to the sea FIGURE 4

Verification of water levels simulated with WENDY at Mukdahan

Despite the shortcomings of the maps providing topographic data in the flood plains, the models were caliberated satisfactorily An example of the fit of water levels for a flood wave passing at Mukdahan is shown in Figure 4 In view of the fact that the calibration of this model focused on the fitting of discharges, the differences between computed and measured water levels areacceptable.

At the time of the model development, there were still some problems in improving the quality of the hydrodynamic models The developers of the Mekong River Model conclude that an accurate model development is

hampered by:

 large changes in the discharge rating curves from year to year, leading

to considerable deviations of actual ratings from the average rating curve applied to calibrate the model; and

 lack of data from tributaries, with only some 60 % of the catchment area between the model limits gauged

However, since these observations were made the scope for further

improvement of the models looks better Since the calibration of the models, more reliable data have become available River cross-sections have been monitored through a FINADA sponsored river survey project The cross-sections have been stored in a database and can be linked to the Mekong Master Model The availability of discharge data from tributaries has improved since the start of the Hydro-Met Project In addition, there is a considerable scope for further improvement as a result of emerging technologies, as

discussed in the sequel

Emerging technologies

Over various decades computer speed and storage capacities are increasing

by 50% yearly or a factor of more than 50 over each decade This simply means that what a computer does now in an hour, will be done in a minute tenyears from now Over twenty years, or half the professional lifetime of an engineer, the work done in one hour is reduced to one second only There is

no indication that there will be a slow down of this trend Computer storage follows a similar trend Whereas the PC had an internal memory of 640 Kb 10 years ago, it now has 32 Mb internal memory This results in the development

of technologies, which were unheard of or just in experimental phase 10 years ago

DGPS technology

One of these areas of progress is the collection of topographic data The combination of satellite technology and fast computer processing speed has opened up new possibilities for collecting flood plain levels on the basis of differential GPS systems (DGPS) The combination of laser beam scanning applied from a helicopter flying at approximately 100 m altitude, together with

a DGPS in real-time-kinetic-on-the-flight mode, has delivered digital terrain levels of flood plains in The Netherlands with an accuracy of 0.5 m The laser altimetry method can also be applied from small planes flying at a 500–1000 maltitude These planes can move at speeds of 200–300 km/hour in order to allow a correct registration of their position In one go, scans are made of a track of 400 m width This implies the scanning of more than 100 km2 during one hour The number of points scanned is approximately 600 per ha The accuracy of the vertical levels on the maps produced is 5 to 10 cm if powerful post-processing software is used

In the scans, vegetation can be separated from the ground level, if the

vegetation is somewhat permeable Trees, for examples, are recognized and can be filtered from the surface level The problem with paddy fields would be the somewhat unknown depth of water on various plots, as the laser beams would pass the vegetation, but are reflected at the water surface Sampling at ground level would allow the removal of the systematic error, thus leaving onlythe standard deviation resulting from the variations in water depths at the fields

Technically the method is more or less proven technology It is expected that

by the year 2000 the complete area of the Netherlands has been resurveyed this way However, the method is still rather costly at prices charged having anorder of magnitude of US$5/ha This is more than the unit price charged in Laos for conventional surveying It is expected that these prices will go down

as the initial investment costs are being recovered, possibly to levels of US$ 1– 2/ha The data collected can easily be processed in the form of a digital terrain model, which has big advantages both for modelling and for the generalprocess of land and water development

The potential of this method is the possibility of collecting highly accurate information on flood plain topographies The potential for model calibration is

in the possibility to scan water levels along the river during a flood period and receive an accurate picture of water level variations all along the Mekong River In other words, it is expected that this methodology will substantially improve the quality of hydrodynamic channel flow models, both in terms of the description of the topography and in terms of the calibration of the models

FIGURE 5

Schematization of a biological neuron

Artificial neural networks

For extracting information from observed patterns new methodologies have come up with the further development of computational speed Data mining techniques, such as the artificial neural networks (ANNs) enable the

recognition of patterns which link the various sources of data Contary to multiple regression techniques, the ANNs do not require prescribed functional

relationships as input The networks contain the flexibility to create both relations and their parameters as an integrated set of data.

FIGURE 6

Example of the structure of an ANN

The idea stems from the way neurons function within the brains (Figure 5) These bio-logical neurons receive signals and pass these on to other neurons either as amplified or as dampened signals This process is simulated by the simplified scheme shown by Figure 6, with amplification functions possibly defined by a sigmoid or logistic threshold function (Figure 7) Through this schematization it is possible to define quite non-linear processes

FIGURE 7

The sigmoid or logistic threshold function

The potential of this technology has been proven in fields as different as hand written character recognition to stock exchange pattern recognition In the fields of hydraulics and hydrology it has been applied to areas as diverse as rainfall-runoff modelling (Figure 8), to mathematical model emulation in systemoptimization, as well as to the establishment of rating curves in areas with backwaters.

FIGURE 8

Example of rainfall-runoff results produced with an ANN

In practical use, however, some observations have to be made In the first place it is evident that the method only works if one tries to connect input signals to output signals, which also in the physical system show a clear dependence For example, in a river catchment the level of the groundwater table is not just dependent on the current rainfall (input signal), but also to the antecedent rainfall For this reason it is clear that either antecedent rainfall data have to be given as input signals, or the current groundwater level has to

be entered through regressive definitions

In the second place it has to be stated that the development of the ANN goes through a calibration or training phase, just as the brains need some time to process information on what goes on around us and learn from it However, whereas the intuitive brains are able to think beyond the limits of what has been learnt, the ANNs (so far) are not able to extrapolate and any attempt to

do so is punished in the form of the likelihood to produce nonsense In

principle, this danger of extrapolation is much similar to the extrapolation of fitted curves, such as, for example, traditionally established rating curves used

in hydrology

The conclusion on this technology is that it opens up many interesting

possibilities in the field of flood problems, reservoir operation, water balance computations, rainfall forecasts and many others The technology is extremely powerful under the condition that it is used with a lot of common sense

Hydrodynamic flow modelling in rivers

The numerical description of river flow was developed in the 1970s and the 1980s and has been improved since primarily in terms of numerical

robustness This is of particular importance in flood forecasting, as one is dealing with extreme flow conditions If a model suffers from numerical

problems, it is exactly here that the risk of failure of simulations is highest For this reason, robustness is a property that in the selection of numerical models for flood wave propagation simulation should get a very high priority

Improvements also stem from technological advances in other areas, such as data collection and emulation techniques The progress in the applicability of hydrodynamic models lies mainly in the progress of computer speed In Vietnam, for example, nowadays large, detailed models of the Delta are run frequently to study salt intrusion in relation to various irrigation options,

drainage problems, including the comparison of various alternatives etc

For optimization of systems, hydrodynamic models are currently only used in trial and error approaches If many simulations are required, such as for on-line control of hydraulic systems, emulation techniques replacing the

hydrodynamic models with, are being used In such case, the ANN is trained

on the basis of a selected number of simulations with an accurate

hydrodynamic model After this training, the ANN is applied to study a large number of alternatives and to compare the functioning of these Here, again, it has to be stated that in such processes the ANN should not be used in

extrapolation mode In other words, it should not be used for cases for which ithas not been trained.

Potential improvement in reliability of flood forecasts

The reliability of forecasts can be increased in various ways, such as:

 the improvement of rainfall forecasts;

 improved catchment modelling;

 improved channel routing; and

 improved model updating techniques

In addition, the current possibilities of user interfaces, data bases and GIS systems provide substantial scope for improvements in handling data entry and dissemination of the forecasts

More reliable forecasts are possible in the first place by improving the rainfall forecasts For given meteorological conditions, rainfall forecasts can be made

on the basis of various types of measurements, such as areal rainfall

distributions, atmospheric pressure distributions, wind directions and vapour content Radar measurements are useful, as well as satellite images The problem is in making this information available at the forecasting centre and in extracting the correct information from such data

Another and more accessible source of data for precipitation forecasting is the weather maps MRCS has recently introduced the practice of using the

catchment rainfall from the areal rainfall forecasts produced by the Global Numerical Meteorological Model as a reference in rainfall forecasting This method could be improved further through the calibration of which would establish relationships between catchment integrated rainfall from the weather forecast bit maps and the resulting catchment runoff This approach is

expected to replace the need for a much denser rain gauge network and its associated transmission system in the Mekong Basin This is particularly useful, as the installation of more rainfall gauges is not very practical in remotecatchments in mountainous areas of the Mekong Basin Any approach to floodforecasting which minimizes the need for ground stations should be given favourable consideration

Another improvement is based upon a re-calibration and possible replacement

of the rainfall-runoff models for the Mekong subcatchments Currently, the forecasting system uses eight subcatchments, for which rainfall-runoff

simulation is made This should be extended to the development of runoff models for each individual main tributary, as was already attempted at the beginning of the eighties Besides the SSARR model, a variety of other rainfall runoff models would be suitable, such as the Sacramento model, tank models etc The upgrade of the forecasting system should include extension and re-calibration of sub-catchment models, based upon information collected

rainfall-at MRCS during the past decade

Further improvements are possible by replacing the SSARR channel routing model by a full hydrodynamic model A hydrodynamic model is the only tool enabling flood forecasting in the flat areas of Cambodia and Vietnam The calibration of the WENDY model, as part of the Mekong Master Model project finalized in 1991 has proven that such model can be developed with sufficient accuracy for the Mekong River, despite the shortcomings in accuracy of topographical data The lack of accuracy, in this case, was substituted with knowledge on the flood deformation characteristics and their relation to channel cross-section parameters As discussed, there is now a good scope for further improvement of the hydrodynamic models It is quite unfortunate that so far the hydrodynamic model was never incorporated into the

forecasting system

A clear advantage of incorporating the existing hydrodynamic model in the forecasting system is the readily available possibility to extend the forecasting system to locations in Cambodia and Viet Nam as it includes the Tonle Sap River, the Great Lake and the main branches in the Mekong Delta The principal reason to separate the model parts during their development in the period 1988–1991, at least the model parts 1 and 3, has been the lack of computational speed at that time The various components were running on PC's with an Intel 386 processor With the currently available Pentium

processors combined models would be feasible and the forecasting system could easily be extended on the basis of one single model from Chiang Saen

to the sea

A last element in improving the flood forecasts is an updating procedure, which handles uncertainties in input data Currently, the updating is based upon a simple replacement of computed river discharges by measured ones incase of differences between both data sources However, such procedure does not update the state of catchment storage and this is a deficiency that may contribute significantly to errors in forecasts It is recommended to

replace the updating method by a scientifically sounder approach, such as Kalman filtering

Capacity building at MRCS - HU

In 1994 a Mekong Hydrological Programme Review Mission (HRM) evaluated the Mekong Hydrology Programme (MHP) seeking donor assistance for the execution of various projects The outcome was the recommendation to give priority to institutional strengthening of the Mekong Secretariat, both through capacity building and through the development of support software

After the signing of the new agreement on continued co-operation on the Mekong in 1995 and the formation of MRC, the recommendations were reviewed again in 1997 in the light of the new MRC mandates This review was made by Prof Bogardi, who also headed the 1994 HRM The outcome was a revised report with a recommendation to GON to fund a project with institutional strengthening of MRCS and human resources development as theprincipal objectives, together with the recommendation to start the MHMP programme as a slightly modified and updated version of the HRM proposal of

1994 The MHMP programme proposed envisages the development of a framework within which various software packages already available at

MRCS, or packages that will be acquired, are to be incorporated and

connected in a consistent manner

The recommendations are a recognition of the need to develop an integrated set of tools, instead of the bits and pieces of software installed at MRCS until now However, it would be advisable to combine such programme with well defined consultancy targets of the staff of MRCS As an example, as part of the proposed institutional strengthening it would be advisable to upgrade the current forecasting system

Particularly useful elements of such a programme are on-the-job training programmes, where staff of MRCS works with a variety of specialists in

various topics related to data collection, data storage and retrieval, data processing, flood forecasting, flood control, river morphology, environmental management, water resources management and many other The on-the-job training must be a well planned part of the project and should be

complemented by short seminars given by the visiting specialists prior to the start of the implementation work

Floods in subcatchments: example of the Vientiane Plain

Laos is a mountainous country with a land area of 236 800 km2 and a

population of nearly 5 million Over 80% of the population lives in rural areas, with rice production as the principal source of income Only approximately 9%

of the country is suitable for agricultural production As this limitation puts much strain on the population living in the mountainous areas, the practice of slash-and-burn is increasing, with a decreasing number of years left between successive use of the land for cultivation This practice is a highly damaging cause of deforestation and erosion Laos is one of the poorest countries of Asia, with a gross national product of approximately US$ 260 per caput per annum

The cultivable areas of Laos are mainly situated along the banks of the

Mekong River The level of protection against such floods, so far, is low Floods are a yearly returning threat to the farmers cultivating their crops in the vicinity of the Mekong River

One of the most densely populated areas of the country is the Vientiane Plain, located North of the capital Vientiane, between the Nam Ngum I Reservoir (Figure 9) and the confluence of the Nam Ngum and Mekong Rivers The areahas a population of approximately 600 000 inhabitants and is one of the principal rice producing areas of Laos This area was severely flooded in 1995

In the past, the Vientiane Plain was frequently flooded, a situation which improved after the construction of the Nam Ngum Reservoir in 1971 However,

a large part of the area is still threatened by floods The extent of flood

damage varies from year to year The principal problem of floods is the

restriction the farmers feel in selecting high yielding rice varieties

Consequently, a sustainable agricultural development of the area and a reliable food supply to the growing population of the Vientiane Plain is highly dependent on an improved flood control.

FIGURE 9

The Nam Ngum I catchment

The extent of 1995 flood damage was studied in large detail with the

assistance of FAO This study has led to the preparation of a flood depth map

of the Vientiane Plain The map, which is available at the MAF-DOI office, shows flood depths of 2–5 metres and in some depressions up to 8 metres The flooded area shown is approximately 40 000 ha The map clearly shows that there is hardly any flow from the Mekong into the Vientiane Plain, except, possibly, through back flow into the Nam Ngum

It should be noted that the accuracy of the flood maps is limited, due to the lack of reliable topographic data of the Vientiane Plain The underlying

topographic maps date from 1960 and have a scale of 1:50 000 Levels, however, are not satisfactorily shown, as only 10 meter contour lines and a

number of spot levels are given The preparation of the flood maps was based upon interviews with the local population and the estimated flood depths at all spots investigated were plotted on the 1:50 000 scale topographic maps In the same project, the flood damage was assessed, resulting in an estimated loss to assets and agricultural production of US$ 21 million.

For the flood several possible causes have to be mentioned:

 high discharge from the Nam Ngum reservoir, which during the 1995 flood had a maximum inflow of 2 550 m3/s and a maximum outflow of 2

421 m3/s The turbines passed 472 m3/s that day, whereas 1949 m3/s left the reservoir via the spillway at a reservoir level of 213.60 m above mean sea-level (masl) The catchment area upstream of the dam is 8

388 km2 The PMF for the dam has been estimated at 4 545 m3/s at a reservoir level of 214.83 masl;

 high discharge from the Nam Lik river, which joins the Nam Ngum riverjust downstream of the Nam Ngum dam site with a catchment area of 5

212 km2;

 additional local rainfall on the Vientiane Plain and the remaining part of the Lower Nam Ngum catchment, which has an area of 3 363 km2 of the total 16 963 km2 of the complete Nam Ngum catchment; and

 high Mekong River levels, which impede drainage from the Vientiane Plain via the Nam Ngum River

One of the factors that influenced the severity of the floods may have been thedelayed opening of the Nam Ngum I spillway gates So far, reservoir operation

is only based upon the optimization of hydro-electric energy production Yearlyenergy yield has an export value of US$ 20 million, partly as base energy supply and partly as peak energy The higher priced peak power contracts make it interesting to keep the end of the monsoon reservoir levels as high as possible

The export earnings gained from the hydropower production makes it difficult

to give a balanced priority to the conjunctive use of the reservoir for flood control purposes So far, a thorough evaluation of the role the reservoir

operation has played on the generation of the flood damage has not been carried out to sufficient depth, simply due to a lack of understanding of the overall functioning of the system

Hydropower and flood regulation

Hydro-electric power is an important export product of Laos The exploitable potential of hydropower generation in Laos is 18 000 MW Currently, only approximately 2% of this potential has been developed However, the further development of the potential is expected to accelerate, as GOL has been signing contracts for the delivery of electricity to Thailand (1 500 MW by the year 2000) and Viet Nam (1 500 to 2 000 MW by the year 2010) In addition,

the domestic energy consumption is growing at a rate of 8 to 10 percent annually.

Currently, the total installed hydropower capacity is 203 MW The largest hydropower plant is Nam Ngum I, with an installed capacity of 150 MW Of this, 30 MW was installed in 1971, working from the start at the full supply level of 202.50 masl The plant was extended in 1978 with the installation of

an additional 80 MW The system was completed in 1984 by adding another unit of 40 MW

Collection of data just upstream of the Nam Ngum dam site started in 1967 The hydrometric station was abandoned during the filling of the reservoir Since 1971 the recorded reservoir outflows have been filed Lahmeyer

International converted the outflowing discharges into a series of inflowing discharges based upon the recorded reservoir levels and the reservoir

geometry Mean monthly discharges are reported to be reliable A lower accuracy must be attached to the mean daily inflows generated

The area of the Nam Ngum I reservoir is approximately 370 km2 at the level of

212 masl, which is nearly the same as the area of the Vientiane Plain flooded

in 1995 In a very approximate way this leads to the conclusion that every additional meter of flood storage depth created in the reservoir, leads to a one meter reduction in flood depth on the Vientiane Plain Of course, one must be very careful with such a conclusion, as the reduced flood depths also lead to reduced drainage capacities towards the Mekong River, so the effect of creating flood retention volume in the reservoir might be less than expected

In the Vientiane Plain the situation is in fact even more complex, as an

important contribution to floods is given by the discharges from the Nam Lik river Moreover, floods are aggravated by the contribution of local rainfall Such a complex system can only be studied thoroughly through simulations based upon a hydrodynamic modelling package and assuming that for such model development data of a reasonable quality are available

Flood forecasting and simulation modelling for the Vientiane Plain

Although the existence of the reservoir is most likely beneficial to flood control,

a modified operation might have prevented a substantial part of the damage Such statements, however, can only be supported with the development of a thorough knowledge of the flood system through simulation of various

scenarios by means of a hydrodynamic flood simulation model The need for the development of this understanding is felt both in the Ministry of Industry and Handicrafts (MIH - Electricité du Laos) and in the Ministry of Agriculture and Forestry (MAF - Department of Irrigation) There appears to be a clear willingness to cooperate on this issue

The development of the flood simulation model will have the following

components:

 institutional arrangements

 detailing of a ToR

 financing

 appointment of a consultant

 acquisition of the suitable data processing and modelling tools

 hydrological data collection

 topographic survey of the Vientiane Plain

 model calibration and simulations, and

 capacity building in Laos

The institutional arrangement requires the consensus of MIH and MAF on the establishment of a Flood Modelling Centre One possibility might be to create the Centre at the Lao National Mekong Committee (LNMC) in Vientiane, with additional staffing provided by MIH and MAF Currently, LNMC has a total staff

of 11 of which: 3 irrigation engineers, 2 hydrologists, 1 civil engineer, 2

technicians and 3 in the administration It is foreseen to extend the technical staff with 3 more members, funded by GOL Training of this new and/or detached staff would have to get a high priority Part of this training should be on-the-job training programmes under the supervision of international

consultants A close cooperation with MRCS would be possible and

recommended

The ToR would focus on the need to generate the understanding of the behaviour of physical and partly controlled process of flood wave propagation through the Vientiane Plain The model would enable the study of various flood control mechanisms, including the construction of flood protection works,reservoir operation options It would include a tool for the optimization of hydropower production and flood control Preferably and if feasible, it should include rainfall-runoff modelling of the complete Nam Ngum catchment in order to support such reservoir optimization The model should be extended toinclude flood forecasting along the lines described above Full advantage of this model use and minimum losses in energy production could be achieved when the model would be complemented with a flood forecasting system for Nam Ngum I reservoir If based on the same concepts as proposed for the Mekong flood forecasting system, the reservoir inflow forecasting system would not require the (impossible) installation of additional rain gauges in remote upstream locations

The total package of modelling support, therefore, would include the following model components:

 flood prediction model of the Vientiane Plain, for the study of the effects of flood propagation through the Plain as a result of the

controlled and/or uncontrolled upstream discharges, Mekong levels and the flood control works which could be constructed in the Plain The tools should preferably be those already in use at MRCS;

 rainfall-runoff models of the catchments of the Nam Lik river and the Nam Ngum river upstream of the reservoir;

 a flood forecasting model for the same catchments, set up along the lines described above;

 a reservoir operation optimization component, based upon a global optimization technique, such as a genetic algorithm approach.

The set of tools would support the following types of studies:

 further develop the understanding of the flood mechanism of the Vientiane Plain This would also allow for a comparison of the floods occurring with and without the reservoir or the routing of other historic floods, such as the 1996 event;

 compare various options of controlled flooding of the Vientiane Plain and prioritize these in terms of various options of protecting parts of theflood plain, e.g construction of low dikes around the higher elevated parts, creation of storage areas etc.;

 optimize the control of the spillway gates of Nam Ngum I by using historic records, possibly complemented with records generated through the used of the rainfall-runoff models fed with historic rains;

 optimization of reservoir operation on the basis of real time control by implementing the flood forecasting model;

Apart from its function of supporting flood control studies, the modelling projectshould be seen as a necessary preceding action to support a Master Plan Study defining a staged development of the Vientiane Plain Such

development would require studies on partial flood control and possibly include controlled flooding concepts Such developments can no longer be based upon an interative approach, without using the informatics and

modelling support available nowadays The Master Plan would be a logical follow-up to the “Nam Ngum River Basic Management” project, announced in

1996 by ADB

One of the major problems encountered in setting up the modelling tools is thelack of accurate topographic data of the Vientiane Plain The 10 m contour lines and the incidental spot levels are by no means sufficient to represent the storage and conveyance components of the system Additional surveying is expensive For the purpose of modelling, land level information on a grid of at least one point per ha would be required Moreover, level and position of all sorts of dikes and roads in the area would have to be collected This last information is rather easy to collect, especially with the current availability of DGPS

Of late, these DGPS instruments can be mounted on a car or a motorbike and even in a back pack, which allows for travelling along roads and dikes crests

By continuous recording or by a stop-and-go method, the position can be stored continuously in terms of x-y-z co-ordinates The method allows for an accuracy in the vertical level of a few centimetres Total cost of the preparation

of a digital terrain model of the Vientiane Plain for modelling purpose would be

of the order of US$ 200 000, depending on how easy it is to get full access to the terrain The data collected could be further processed to support

agricultural development studies However, for the combination with these

studies the more accurate and flexible method of airborne laser altimetry is to

be preferred The cost of this process will most likely be two to three times higher

Detailing of a ToR for a complete modelling project would require a separate mission A rough estimate of the budget required is US$0.8 million for

consultancy input, transfer of tools, training programmes and the additional collection of data The study component of the project would provide Laos with

a pilot investigation, which could be replicated at other flood-prone areas Capacity building has to be an important element of the project Laos has a strong need for capacity building

Flood control: example of Bangladesh

Flood control in the flood plains of the Mekong Basin has already been applied

on a substantial scale in Thailand The primary reason for flood control is the protection of agricultural production In larger river systems, with an often rather predictable time of arrival of the flood peak, the concept of controlled flooding has been introduced Controlled flooding implies that flooding will be allowed, though at a lower frequency and at a time suiting better the cropping pattern The principle behind it is the creation of a delay of the flood, so that usually the crops can be harvested before the area gets inundated

Controlled flooding implies that in the case of extreme floods the waves still find storage for their dampening and show propagation The unsetady flow equations describing the propagation of flood waves show us that the travel time of flood waves is a linear function of the storage available Taking storageaway makes the flood waves travel faster The dampening of a flood wave peak is a quadratic function of the storage, due to the fact that slower

travelling flood waves have a smaller length for a given wave period It is primarily this smaller wave length along the river that leads to the increased dampening

An interesting example of comprehensive flood control is the Flood Action Plan (FAP) of Bangladesh On the basis of above principles, an analysis was made for the whole country regarding suitable measures against floods In Bangladesh there are three principal causes of flooding:

 floods caused by the effects of atmospheric depressions passing over the Bay of Bengal These floods are very severe, can only be forecast with relatively short lead times and may cause many victims Given thenature of the floods in this country, coastal defence works are too costly to cope with this problem;

 floods caused by the flood waves coming down from the Himalayan mountains and propagating via the Ganges and the Brahmaputra Rivers In some years these flood peaks coincide and cause severe flooding The lead time in forecasting, however, is much higher than forthe coastal floods and the number of victims is usually small Dikes areoften attractive investments to improve the agricultural production by

reducing damage and by encouraging the farmers to plant higher yielding rice varieties;

 flash floods of local origin, due to the high local rainfall intensities and depths

One important difference in relation to other parts of the world where flood control measures were introduced is that Bangladesh has a very controlled approach to flood mitigation works Whereas in the past, many areas of the world developed their flood control works on the basis of trial and error, the approach in Bangladesh has been much more planned, with design options continuously checked on the basis of model simulations

Bangladesh experienced one of the most catastrophic river floods in 1988, immediately after the already high flood of the 1987 monsoon The damage of the 1987 flood had hardly been repaired when most of the results of these efforts was lost again

UNDP, World Bank and various donor countries joined efforts to launch a Flood Action Plan, with a budget of US$ 150 million Of this fund, US$ 55 million would be directed to pilot projects for testing approaches, river bank protection and flood plain management

In terms of planning of projects the country was at that moment already

prepared, as in March 1987 the National Water Plan (NWP) had been

concluded at the Master Plan Organization (MPO) The NWP had assembled

a substantial amount of data and other information, developed a range of planning models and analytical tools and had recommended strategies and programmes Many of these had already been adopted by the government and donor organizations

One of the tools that had been developed at MPO was a suite of surface watersimulation models This project, funded by UNDP and executed under the supervision of the World Bank by the Danish Hydraulic Institute (DHI), had already produced a general model of the main river system in Bangladesh and

a regional model of the South East Region One of the objectives of the projecthad been the development of such regional models for the simulation of the effects and control of various flood control alternatives

Another important objective of the project had been the development of local expertise in the use and development of such models The project, therefore, had a clear capacity building component with the following elements:

 lecture programme organized at the Bangladesh University of

Engineering and Technology;

 participation in a specialized training programme at the consultant's home office;

 participation in some courses abroad;

 on-the-job training under the guidance of expatriate specialists

Especially this last component of the project has been very useful and has partly explained the success of the group which, initiated in 1986, now has a staff of 42 local engineers and is in charge of all modelling support to water control and management projects in Bangladesh It also is in charge of executing all modelling work related to flood forecasting in the country.

Bibliography

Bogardi, J.J., 1997 Report on the Review Mission of the Mekong Hydrology

Programme, MRCS, Bangkok.

Cunge, J.A., Holly, F.M and A Verwey Reprinted 1994 Practical Aspects of

Computational River Hydraulics, Iowa Institute of Hydraulic Research.

DANIDA 1997 Revised Proposal for Flood Forecasting and Effective

Warning Dissemination in the Lower Mekong Basin.

Delft Hydraulics 1989 Network Optimization in the Mekong Basin, Final

Report

Delft Hydraulics 1991 Mekong Master Model, The Mekong Secretariat.

Hasan, M.R 1996 Preparation of Flood Loss Prevention and Management

Plan, Technical Report on Hydrology and Field Data Collection, FAO, Rome.

Hasan, M.R 1997 Preparation of a Comprehensive Flood Loss Prevention

and Management Plan for the Agricultural Sector, Report on Flood Plain

Mapping and Flood Loss Prevention and Management, FAO, Rome

Minns, A.W 1998 Artificial Neural Networks as Subsymbolic Process

Descriptors, Ph.D Thesis, IHE - Balkema, Delft - Rotterdam.

MRCS 1997 The Mekong Hydrology Model Package (Basinwide).

Somboune Manolom, Hydropower and the Environment, Lao PDR,

 to maximize hydropower benefits

 to cover downstream water demands

 to improve year-round navigation

 to reduce flood damages

 to prevent a river from falling dry during droughts

Every storage reservoir provides downstream flood control, whatever the purpose(s) for which the reservoir was built.

Reservoirs have a backwater effect which can worsen flooding along the river immediately upstream of the reservoir With time the backwater effect

becomes more severe due to the deposition of sediment at the tail-end of the reservoir (See Figure 1.)

Low return-period floods, such as the annual flood, are often completely absorbed by the reservoir, without any downstream flooding

FIGURE 1

Effect of reservoirs on floods, upstream and downstream of dam

Engelbertus Oud, Project Manager, and Terence Muir, Senior Hydrologist,

Lahmeyer International, Frankfurt, Germany and Vientiane

People living downstreams of the dam become accustomed used to the new conditions and are often led to believe that floods are a thing of the past

They start to encroach upon the flood plains, build houses and cultivate land, all in a false sense of security If downstream flooding then occurs, the flood damage for the same rate of flow is much higher than before

The flood retention effect of reservoirs, however, is limited and with increasing return intervals of the flood the reduction in flood flow in the downstream river decreases This is clearly illustrated in Figure 2, whereas Figure 3 shows that

in 1995 the inflow peak at the Nam Ngum reservoir was only reduced by 20%.FIGURE 2

Effect of reservoirs on flood peak downstream of dam