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

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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

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. Water is the most precious natural resource to the world. Imbalance between water supply and demand has caused problems to the management and users. People suffer from flood but when drought occurs, we lack of water for consumption, loss of revenue generated by farming, especially for agricultural country. Frequent historical records of floods and droughts especially in the north of Thailand. My research focus on the northern part of Thailand because it is headwater contributing to flow downstream. The 4 basins in the north, Ping, Wang, Yom and Nan, all together forms the Chao Phraya River basin where capital and business centers are located. In some subbasins of Ping, Wang, Yom and Nan, there are only limited number of flow gauges. This is a challenge how to forecast flow in these ungauged catchments. The techninque of regionalisation is then needed to quantify water availability aimimg for better management in water resources.

25 Basins of Thailand 12 24 19 This is the map of Thailand which is divided into 25 basins. The north basins that I am working on are shown with pink border. 21 6 18 15 13 1 16 22 10 7 4 8 2 11 3 20 14 23 5 17 9 25

25 Basins of Thailand: elevations above sea level In this picture, the green represent high elvevation and the red represents low ares. Looking at the four basins in the north, they are similar in that they have higher elevation in the north and the elevation is decreasing when going downward the catchments. So water flows from the north to the central of the country. By doing the risk assessment for the basin upstream can prevent the risk that may take place downstream.

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. Currently, risk is estimated using aggregated measures of water abundance or scarcity.

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.  

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

Phase I: Data assessment and determination of the study sites

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: Basin Area (km2) Flow gauges Rain gauges Tele gauges Ping 33,898 47 63 (16) 12 Wang 10,791 5 18 Yom 23,616 14 32 (1) Nan 34,330 23 51 (5) * Numbers in brackets refer to the station with hourly rainfall.

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.

Thank you