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Article

Flood Frequency Estimation in Data-Sparse Wainganga Basin, India, Using Continuous Simulation

UK Centre for Ecology & Hydrology, Wallingford OX10 8BB, UK
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Academic Editor: Paolo Mignosa
Water 2022, 14(18), 2887; https://doi.org/10.3390/w14182887
Received: 10 August 2022 / Revised: 8 September 2022 / Accepted: 9 September 2022 / Published: 15 September 2022
(This article belongs to the Section Hydrology)
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. View Full-Text
Keywords: continuous simulation; flood frequency estimation; L-moments; probability distributed model; PDM; generalized Pareto distribution continuous simulation; flood frequency estimation; L-moments; probability distributed model; PDM; generalized Pareto distribution
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MDPI and ACS Style

Vesuviano, G.; Griffin, A.; Stewart, E. Flood Frequency Estimation in Data-Sparse Wainganga Basin, India, Using Continuous Simulation. Water 2022, 14, 2887. https://doi.org/10.3390/w14182887

AMA Style

Vesuviano G, Griffin A, Stewart E. Flood Frequency Estimation in Data-Sparse Wainganga Basin, India, Using Continuous Simulation. Water. 2022; 14(18):2887. https://doi.org/10.3390/w14182887

Chicago/Turabian Style

Vesuviano, Gianni, Adam Griffin, and Elizabeth Stewart. 2022. "Flood Frequency Estimation in Data-Sparse Wainganga Basin, India, Using Continuous Simulation" Water 14, no. 18: 2887. https://doi.org/10.3390/w14182887

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