Abstract
The computation of flood magnitude and its likely occurrence to design different hydraulic structures are major challenges to the research community. The present study has been carried out to identify the homogeneous regions in the Mahanadi basin in Chhattisgarh part (data from 26 gauge/discharge sites) of India using conventional and clustering-based homogeneity tests and then computation and identification of probability-weighted moment and L-moment-based best regional distributions for different regions. Different simple to complex distributions like Extreme Value-I, Generalized Extreme Value, Logistic, Generalized Logistic, Generalized Pareto, Normal and Log-normal, Wakeby-4, and Wakeby-5 was used in the analysis through standardizing procedure to compute regional distributions. The best-fit distribution selected by simulating several series and compute L-kurtosis along with the L-moment ratio diagram. The homogeneity analysis confirmed that this basin can broadly be divided into two different homogeneous regions with 15 and 11 stations in the first (Region-1) and second (Region-2) regions, respectively. The GEV distribution was found best suited for Region-1 while the Generalized Pareto worked well for Region-2. To make results more convenient for field application, catchment area-based equations were converted in the form of Dicken’s or Ryve’s formulae for these regions to estimate flood quantiles of any return period.
Highlights
The flood is an instantaneous hazard resulting from a relatively high flow that may overtop the banks of a stream and cause widespread loss of life (Hallegatte et al 2013), properties, crops, and important installations
The regional FFM (RFFM) is especially useful in the case of limited and no data availability may suffer from multiple sources of uncertainties including stationarity of the series, serial & spatial correlation, sampling variability, heterogeneity of catchments, models, parameters, data, and operational errors (Yen 2002; Hailegeorgis and Alfredsen 2017)
Mishra et al (2009) used regional flood frequency analysis on simulated flood data of Nepal using L-moments for the determination of parameters of six different distributions on annual flood series obtained from the application of the SimHyd hydrologic simulation model and found Generalized Extreme Value (GEV) and Log-Normal as the most suited distributions with superiority of regional approach over the commonly used method of Water and Energy
Summary
The flood is an instantaneous hazard resulting from a relatively high flow that may overtop the banks of a stream and cause widespread loss of life (Hallegatte et al 2013), properties, crops, and important installations. The flood frequency analysis is carried out on annual and peak over threshold values with at-site, at-site regional, and regional only mode based on data availability proved its usefulness in designing structures and flood hazard mapping. In the regional FFM (RFFM), the data from multiple sites in a region are pooled to get a longer series and a best-fit distribution is obtained to suit the region (Castellarin et al 2005). Mishra et al (2009) used regional flood frequency analysis on simulated flood data of Nepal using L-moments for the determination of parameters of six different distributions on annual flood series obtained from the application of the SimHyd hydrologic simulation model and found GEV and Log-Normal as the most suited distributions with superiority of regional approach over the commonly used method of Water and Energy. Several others have carried out at-site, regional, and POT flood frequency modeling in different parts of the world (Jaiswal et al 2004; Bhuyan et al 2010; Qin and Lu, 2014; Apipattanavis et al 2010; Dawdy et al 2012; Ahmed et al 2015; Romali and Yusop 2017; Ganamala and Sundar Kumar 2017; Shah and Prasad 2017; Kumar et al 2018; Wu et al 2018; Guru and Jha 2015b; Bezak et al 2014; Alobaidi et al 2015, Ghadrei et al 2019, etc.)
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