Water availability assessment in data scarce catchments: Case Study of Northern Thailand

1. Water availability assessment in data scarce catchments:Case Study of Northern Thailand Supattra Visessri 1st Year PhD Student, Environmental and Water Resource Engineering (EWRE) Section

2. Introduction • Water is the most precious natural resource to the world. • Imbalance between water supply and demand has caused problems to the management and users. • Frequent historical records of floods and droughts especially in the north of Thailand. • The four basins in the north of Thailand form the Chao Phraya River Basin in which the capital and business centers are located. • There are few gauges in some subbasins especially along the border of the basin thus introducing the problem of data scarcity. • Regionalisation is needed to predict water availability and leading to improved water management.

3. 25 Basins of Thailand 12 24 19 6 21 18 15 1 13 16 22 10 7 4 8 11 2 20 3 14 23 5 17 9 25

4. 25 Basins of Thailand: elevations above sea level

5. Current Methodology of Risk Assessment in Thailand • Using aggregated measures of water abundance or scarcity. • Primarily based on a monthly basis and lumped analysis. • Low resolution of temporal and spatial analysis. • The assessment is possible only where data are available.

6. Goal and Objectives • Goal • To improve methodology for flood and drought risk analysis of large river basins under data scarcity. • Detailed objectives • To develop insight into various types of rainfall-runoff models i.e data needs, uncertainties. • To assess the applicability of models used to perform analyses of water-related risks under different environments and data scarcity condition. • To select models and regionalisation methods which make use of the data sets which are available. • To test these models (quantify the uncertainty) and methods using a well gauged pilot catchment, plus other less well gauged catchments. • To evaluate impacts of climate change on water abundance and shortage under data scarce conditions. • To develop recommendations for future strategy at local level.  

7. Research programme • Phase I: Data assessment and determination of the study sites • Phase II: Critical evaluation and selection of rainfall-runoff models • Phase III: Regionalisation (Prediction of flow in ungauged basins) • Phase IV: Climate change scenarios

8. Phase I: Data assessment and determination of the study sites

9. Phase I: Data assessment and determination of the study sites • The most complete period of flow and rainfall data is 01/01/1995-31/12/2006 (12 years). • The number of viable flow gauges with less than 35% of missing record is as below: * Numbers in brackets refer to the station with hourly rainfall.

10. Next step: Assessment of regionalisation method • Regression method Use regression analysis to find the relationship of parameters and catchment descriptors (i.e. area, average precipitation, BFI) of well-gauged catchments. By applying the regression equations to ungauged catchments, parameters of ungauged catchments can be obtained. • Similarity method Take parameter values of a well-gauged catchment without adjusting. • Response Indices method • Find the relationship between response indices (i.e. mean daily flow) and catchment descriptors.

11. Thank you