Flood frequency estimation in data-sparse Maharashtra, India

Griffin, Adam ORCID: https://orcid.org/0000-0001-8645-4561; Stewart, Lisa ORCID: https://orcid.org/0000-0003-4246-6645; Formetta, Giuseppe; Kalai, Chingka. 2018 Flood frequency estimation in data-sparse Maharashtra, India. In: 8th Global FRIEND-Water Conference, Beijing, 6-9 Nov 2018. Beijing, UNESCO. (Unpublished)

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Abstract/Summary

Monsoon-related extreme flood events are experienced regularly in the Godavari and Krishna river basins in peninsular India, causing costly damage and disruption to local communities. Being able to estimate the likely magnitude of the 1-in-100 year flood, say, would allow hydrological practitioners to design new structures to prevent such damage or at least withstand it. To this end, catchment descriptor equations were developed through 10 multiple linear regression and stepwise model selection to estimate the median of the annual maximum flow series (QMED), making use of open source and freely available datasets. To allow the estimation of floods with other specified return periods, Hosking-Wallis distribution tests were performed to select the most appropriate distribution to model the annual maxima series; the Generalised Pareto was highlighted as the most able to accurately describe specific stations, and the Pearson Type III was seen to be the distribution most useful at being 15 able to describe extreme flow behaviour across the entire region.

Item Type:	Publication - Conference Item (Paper)
UKCEH and CEH Sections/Science Areas:	Hydro-climate Risks (Science Area 2017-)
NORA Subject Terms:	Hydrology Mathematics
Date made live:	11 Mar 2019 11:45 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/522465

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