Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
LH-moment-based regional flood frequency analysis framework to determine design floods in Krishna River basin
Study region: Krishna River basin, India Study focus: There have been limited efforts to develop the LH-moment-based Regional Flood Frequency Analysis (RFFA) framework for Indian catchments. In this study, the LH-moment-based RFFA is used to determine flood quantiles at ungauged sites within the Krishna River basin in India, corresponding to various return periods. Three probability distributions, namely the generalized extreme value (GEV), generalized logistic (GLO), and generalized Pareto (GPA) are considered for performing the RFFA. New hydrological insights for the region: This study examines two cases for RFFA, viz., the first involves a single region comprising all 24 gauges within the basin, while the second divides the 24 gauges into three hydrologically similar regions based on the global K-means (GKM) clustering algorithm. The discordancy and heterogeneity measures are considered for the screening of the peak flow data and checking the heterogeneity of the formed regions, respectively. The performance of the LH-moment-based RFFA framework is evaluated through the Leave-One-Out Cross-Validation (LOOCV) experiment. In the case of single region, GEV distribution is found to be the most suitable regional distribution, while in the second case, the GEV{GEV}[GPA] is identified as the best-fitted regional distribution for the region 1{2}[3]. Overall, the study demonstrates the efficacy of the higher-order LH-moment-based RFFA framework over the L-moment.
LH-moment-based regional flood frequency analysis framework to determine design floods in Krishna River basin
Study region: Krishna River basin, India Study focus: There have been limited efforts to develop the LH-moment-based Regional Flood Frequency Analysis (RFFA) framework for Indian catchments. In this study, the LH-moment-based RFFA is used to determine flood quantiles at ungauged sites within the Krishna River basin in India, corresponding to various return periods. Three probability distributions, namely the generalized extreme value (GEV), generalized logistic (GLO), and generalized Pareto (GPA) are considered for performing the RFFA. New hydrological insights for the region: This study examines two cases for RFFA, viz., the first involves a single region comprising all 24 gauges within the basin, while the second divides the 24 gauges into three hydrologically similar regions based on the global K-means (GKM) clustering algorithm. The discordancy and heterogeneity measures are considered for the screening of the peak flow data and checking the heterogeneity of the formed regions, respectively. The performance of the LH-moment-based RFFA framework is evaluated through the Leave-One-Out Cross-Validation (LOOCV) experiment. In the case of single region, GEV distribution is found to be the most suitable regional distribution, while in the second case, the GEV{GEV}[GPA] is identified as the best-fitted regional distribution for the region 1{2}[3]. Overall, the study demonstrates the efficacy of the higher-order LH-moment-based RFFA framework over the L-moment.
LH-moment-based regional flood frequency analysis framework to determine design floods in Krishna River basin
Amit Kumar Singh (Autor:in) / Sagar Rohidas Chavan (Autor:in)
2025
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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