1 MRC-RFMMC TOWARDS A NEW FLOOD FORECASTING SYSTEM FOR THE LOWER MEKONG RIVER BASIN 4 th International Symposium on Flood Defense Toronto, 7 May 2008

2 Introduction Data People Model Introduction Mekong River Commission – Formed in 1995 – Cambodia, Lao PDR, Thailand and Viet Nam – Dialogue partners: China and Myanmar Objectives – Joint management shared water resources – Development of economic potential of the river System Sharing Conclusions Future

3 Introduction Data People Model Introduction Devastating floods in 2000, 2001, 2002 Between 1 and 8 million people affected Flood Management and Mitigation Programme agreed upon Funding about US $ 20 million Operational since 2005 Objectives – Improve flood forecasts and flood data exchange – Develop technical standards and training System Sharing Conclusions Future

4 Introduction Data People Model Introduction System Sharing Conclusions Future “ The Flood Management and Mitigation Programme (FMMP) aims to prevent, minimise or mitigate people ’ s suffering and economic losses due to floods, while preserving the environmental benefits of floods ” “ The Regional Flood Management and Mitigation Centre in Phnom Penh is to provide timely and reliable flood forecasts for the Mekong mainstream. ”

5 Introduction Data People Model Introduction RFMMC flood forecasting at present – Short term 1-5 day forecasts – 23 locations along Mekong River – SSARR model – Published at website – Distributed by – Mandate is Flood Forecast System Sharing Conclusions Future

6 Introduction Data People Model Introduction The objective is to produce a flood forecast. For that we need – data – people – models – system including procedures And this may be the order of importance! System Sharing Conclusion s Future

7 Data Requirements Water level data – Near real time water level main stream – Near real time water level main tributaries Rainfall Data – WMO GTS rainfall data – Existing near real time rainfall data at agencies – Extension of network of near real time rainfall stations Satellite Rainfall Estimates – Satellite Rainfall Estimates – Weather Model Forecasts Introduction Data People Model System Sharing Conclusions Future

8 Synoptic Stations Introduction Data People Model System Sharing Conclusions Future

9 Satellite Rainfall Estimate Introduction Data People Model System Sharing Conclusions Future

10 Rain Gauge Network Network Coverage – Average coverage good in Thailand and Viet Nam – Spatial distribution may need improvement – Both are insufficient in Cambodia and Lao PDR Operation and Maintenance – Thailand and Viet Nam need little support – Cambodia and Laos face problems – Historical stations need attention Introduction Data People Model System Sharing Conclusions Future

11 Analysis Cambodia Department of Hydrology and River Works, Ministry of Water Resources and Meteorology – Presently 5 rainfall stations reported – After upgrade 9 Department of Meteorology (MOWRAM) – Presently 21 rainfall stations near real time – After upgrade 35 – First phase (upgrade of 8 stations) completed – Second phase (6 new stations) almost complete M-HYCOS (telemetry) – 7 stations proposed for upgrade Introduction Data People Model System Sharing Conclusions Future

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14 Analysis Lao PDR Department of Meteorology and Hydrology, Ministry of Agriculture and Forestry – Presently 33 rainfall stations near real time – After upgrade – After extension network up to 50 Introduction Data People Model System Sharing Conclusions Future

15 Analysis explained using map

16 Analysis explained using map

17 Thailand, Viet Nam In Thailand the coverage of near real time rainfall stations within the LMB is very good – No upgrade or new stations needed (?) – No new stations needed – The main issue is timely data transmission In Viet Nam some new stations may be needed on the borders of the LMB – No upgrade of stations needed (?) – The main issue is timely data transmission Introduction Data People Model System Sharing Conclusions Future

18 Introduction Data People Model Data Agreements Much effort went into improving data delivery – MoU Cambodia and Lao PDR – Contracts with hydro-met agencies – Negotiations with other two countries progressing well Expected: – Marked improvement in data availability by 2009 Data availability and quality will need constant attention System Sharing Conclusions Future

19 Introduction Data People Model People The people ensure the quality of the flood forecast – Training in using modeling tools – On the job training building the models – Training communication tools – Training FEWS – modeling environment Refresher training and building of experience by working with the models and FEWS will never stop System Sharing Conclusions Future

20 Introduction Data People Model Models The models are a tool to support the flood forecaster In consultation with member states: implement URBS as a trial model (December 2006) URBS will eventually be one of a suite of different models at the RFMMC System Sharing Conclusions Future

21 URBS What is URBS – Conceptual hydrological flood routing – Parameter-poor – Robust operational – Input primarily rainfall data Advantages – Lack of data from one station or one data supplier permitted – Minimum set of rainfall data from WMO-GTS and Satellite Rainfall Estimate is always available Introduction Data People Model System Sharing Conclusions Future

22 URBS URBS has the following characteristics – Semi-distributed non-linear network model – Combines rainfall-runoff and runoff-routing – Models spatial & temporal variability of rainfall – Proven record in large river basins Introduction Data People Model System Sharing Conclusions Future

23 Implementation First mission March 2007: – Training of staff – Work planning – Project management Follow up: building of URBS models – Flood Centre staff continuously involved – First trial version ready by August 2007 – Now ready for parallel testing 2008 season A lot has been done in a very short time, on a relatively low budget – proof of concept The new model is still untested in forecast mode Introduction Data People Model System Sharing Conclusions Future

24 CatchmentSIM GIS topographic parameterisation & hydrologic analysis software Automatically delineates watersheds & sub- catchments Includes a flexible macro language to fully couple the output with any hydrologic model Uses publicly available digital elevation data from the NASA Shuttle Radar Topography Mission Introduction Data People Model System Sharing Conclusions Future

25 Medium sized tributary Located in the central part of Lao PDR Joins the main river 55km downstream of Thakhek Catchment area of 9,300km 2 Mountainous in the east and flood plain in the west Se Bang Fai Introduction Data People Model System Sharing Conclusions Future

26 Flow at any location Height at any location with a H-Q relationship Se Bang Fai Introduction Data People Model System Sharing Conclusions Future

27 Se Bang Fai Introduction Data People Model System Sharing Conclusions Future

28 Model complex 50 models developed Stage 1 upstream of Kratie – 40 models Stage 2 downstream of Kratie – 10 models Special module for Tonle Sap / Great Lake system Ultimately linked to hydrodynamic models Introduction Data People Model System Sharing Conclusions Future

29 Introduction Data People Model FEWS Delft FEWS selected – Open system, any model can be added – No tie-in with one type of model supplier – Very flexible – configuration to requirements user – User-friendly interface – No comparable alternatives – Used worldwide by major national and international organizations – Software free – license conditions apply – Both stand-alone and on-line distributed System Sharing Conclusions Future

30 Introduction Data People Model Implementation First FEWS missions in March 2008 – Building adapter FEWS-URBS – Implementation data inputs – RFMMC staff involved (continuity) – June 2008: first implementation expected – 2008 flood season: testing, parallel operation The Mekong FEWS is a work in progress, only the first phase will be ready for the 2008 flood season System Sharing Conclusions Future

31 System screenshot MEKONG FEWS

32 Introduction Data People Model Procedures First mission August 2007 – Documenting present situation – Draft report September 2007 – And a manual of the present FFS Second mission March 2008 – Preparation to create two documents: 1. Policy document (in consultation) 2. Operational document (internal) – Implementation for the 2008 flood season System Sharing Conclusions Future

33 Conclusions Data –Upgrade existing historical rain gauge stations –Extend existing rain gauge station network –Use mobile phone – SMS –Use manual rain gauges –Low tech, low budget, low O&M –Complementary to AHNIP and M-HYCOS –Secure direct access to AHNIP and M-HYCOS –Secure GTS connection for RFMMC Introduction Data People Model System Sharing Conclusions Future

34 Conclusions Models –URBS model selected as trial flood forecasting model –Basic and advanced training of staff completed –Program to develop & calibrate 50 models completed (March 2009) –Overall Mekong model set up and working –First model of Cambodian floodplain and Great Lake system operational –Use during 2008 flood season with satellite rainfall and forecasts as inputs Introduction Data People Model System Sharing Conclusions Future

35 Future Data –Conclude all MoU’s and Agreements –Conclude support contracts with involved Agencies –Start working with the Agencies People –RFMMC staff involved in model maintenance and further implementation of FEWS –Regular refresher and advanced training Introduction Data People Model System Sharing Conclusions Future

36 Future Models –Ongoing improvement of the URBS Mekong models –Study into desirability hydrodynamic modeling –Implementation of other models System –Ongoing improvement of FEWS –Implementation of other data sources –Phase II: on-line distributed system (now stand-alone system) –Use, testing and improvement of Operational Procedures Introduction Data People Model System Sharing Conclusions Future

37 Thank you very much for your attention ! Acknowledgments: Terry Malone – SunWater, Australia Marco Hartman, HKV Consultants, Netherlands Astrid Janssen, DELTARES, Netherlands And of course: the RFMMC Team