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Regional Flood Frequency Analysis Using Entropy-Based Clustering Approach

Basu, Bidroha and Srinivas, VV (2016) Regional Flood Frequency Analysis Using Entropy-Based Clustering Approach. In: JOURNAL OF HYDROLOGIC ENGINEERING, 21 (8).

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Official URL: http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.00013...

Abstract

Hydrologists widely use regional flood frequency analysis to predict flood quantiles for ungauged and sparsely gauged target locations. The analysis involves: (1)use of a regionalization approach to identify a group of watersheds (region) resembling the watershed of target location by searching in watershed-related attribute space, and (2)use of information pooled from the region to perform regional frequency analysis (RFA) for flood quantile estimation. Conventional regionalization approaches prove ineffective for identification of regions in situations where there are outliers in the attribute space. This paper proposes an entropy-based clustering approach (EBCA) to identify regions by accounting for outliers and recommends applying a recently proposed RFA approach on the regions for quantile estimation. The EBCA yielded seven new homogeneous regions in four major river basins (Mahanadi, Godavari, Krishna, and Cauvery) of India. The regions are shown to be effective compared to six existing regions (used by an Indian government organization) and those delineated using global K-means clustering and region-of-influence approaches, in terms of regional homogeneity and utility in arriving at reliable flood quantile estimates for ungauged sites.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the ASCE-AMER SOC CIVIL ENGINEERS, 1801 ALEXANDER BELL DR, RESTON, VA 20191-4400 USA
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Depositing User: Id for Latest eprints
Date Deposited: 22 Oct 2016 07:30
Last Modified: 22 Oct 2016 07:30
URI: http://eprints.iisc.ac.in/id/eprint/54946

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