Flood frequency estimation in data-sparse Wainganga Basin, India, using continuous simulation

Vesuviano, Gianni ORCID: https://orcid.org/0000-0003-2157-8875; Griffin, Adam ORCID: https://orcid.org/0000-0001-8645-4561; Stewart, Elizabeth ORCID: https://orcid.org/0000-0003-4246-6645. 2022 Flood frequency estimation in data-sparse Wainganga Basin, India, using continuous simulation. Water, 14 (18), 2887. 22, pp. https://doi.org/10.3390/w14182887

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Abstract/Summary

Monsoon-related extreme flood events are experienced regularly across India, bringing costly damage, disruption and death to local communities. This study provides a route towards estimating the likely magnitude of extreme floods (e.g., the 1-in-100-year flood) at locations without gauged data, helping engineers to design resilient structures. Gridded rainfall and evapotranspiration estimates were used with a continuous simulation hydrological model to estimate annual maximum flow rates at nine locations corresponding with river flow gauging stations in the Wainganga river basin, a data-sparse region of India. Hosking–Wallis distribution tests were performed to identify the most appropriate distribution to model the annual maxima series, selecting the Generalized Pareto and Pearson Type III distributions. The L-moments and flood frequency curves of the modeled annual maxima were compared to gauged values. The Probability Distributed Model (PDM), properly calibrated to capture the dynamics of peak flows, was shown to be effective in approximating the Generalized Pareto distribution for annual maxima, and may be useful in modeling peak flows in areas with sparse data. Confidence in the model structure, parameterization, input data and catchment representation build confidence in the modeled flood estimates; this is particularly relevant if the method is applied in a location where no gauged flows exist for verification.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3390/w14182887
UKCEH and CEH Sections/Science Areas:	Hydro-climate Risks (Science Area 2017-)
ISSN:	2073-4441
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	continuous simulation, flood frequency estimation, L-moments, probability distributed model, PDM, generalized Pareto distribution
NORA Subject Terms:	Hydrology
Date made live:	27 Oct 2022 11:58 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/533435

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