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

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

1st Year PhD Student, Environmental and Water Resource Engineering (EWRE) Section

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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.

25 Basins of Thailand

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25 Basins of Thailand: elevations above sea level

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.

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

• 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:

Phase I: Data assessment and determination of the study sites

Basin Area (km2)

Flow gauges

Rain gauges

Tele gauges

Ping 33,898 47 63 (16) 12

Wang 10,791 5 18 0

Yom 23,616 14 32 (1) 0

Nan 34,330 23 51 (5) 0

* 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