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Prioritization of Sub-basins of Nilwala River Basin for Flood Exposure using Multi Criteria Decision Analysis

Author:

B. M. L. A. Basnayake

University of Ruhuna, LK
About B. M. L. A.

Senior Lecturer, Department of Civil and Environmental Engineering

 

AMIE(SL), PhD (NUS, Singapore), B.Sc. Eng. (Hons) (Peradeniya), MIAHR


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Abstract

Morphometric analysis is useful to investigate flood proneness of a river basin. Prioritization of a river basin using relevant morphometric parameters and other causative parameters can be performed using Multi Criteria Decision Analysis (MCDA) method. Nilwala river basin is subjected to flooding every year. The aims of this research were to evaluate the morphometric parameters to understand the hydrological behaviour of the Nilwala river basin and to apply Technique of Order of Preference Similarity to the Ideal Solution (TOPSIS) for prioritizing its sub basins for flood exposure. This study considered morphometric parameters, climatic, geologic, and land use factors as causative factors for flooding. Geographic Information System of Environmental Systems Research Institute (ArcGIS) was used to extract parameters using Digital Elevation Model (DEM) of Shuttle Radar Terrain Mission (SRTM), soil map, and land use map of the river basin. TOPSIS was adopted for ranking the sub basins based on the causative factors. The Nilwala river basin was classified into three relative flood exposure zones as high, moderate, and low. The study indicated that analysis of morphometric parameters provides an intuitive information on sub basin characteristics related to flooding. Results showed that 20%, 54%, and 26% of the basin area have high, moderate, and low flood exposure, respectively. High and moderate flood exposure zones are mainly located along the main river course.
How to Cite: Basnayake, B.M.L.A., 2022. Prioritization of Sub-basins of Nilwala River Basin for Flood Exposure using Multi Criteria Decision Analysis. Engineer: Journal of the Institution of Engineers, Sri Lanka, 55(1), pp.23–30. DOI: http://doi.org/10.4038/engineer.v55i1.7483
Published on 10 Jun 2022.
Peer Reviewed

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