Regional Flood Frequency Analysis using Soft Computing Techniques

<Para ID="Par1">For design of various types of hydraulic structures as well as for taking different flood management measures flood frequency estimates are required. Regional flood frequency analysis is carried out employing L-moments and soft computing techniques viz. artificial neural network (ANN) and fuzzy inference system (FIS) for the lower Godavari subzone 3(f) of India. The study area covers an areal extent of 174,201 km<Superscript>2</Superscript> and annual maximum peak flood data of 17 catchments ranging in size from 35 to 824 km<Superscript>2</Superscript> are used. The data screening is carried out employing L-moments based Discordancy measure (D<Subscript>i</Subscript>) and regional homogeneity is examined based on the heterogeneity measure (H). On the basis of the L-moment ratio diagram and Z <Stack> <Subscript> i </Subscript> <Superscript> dist </Superscript> </Stack> –statistic criteria, Pearson Type III (PE3) distribution is chosen as the suitable frequency distribution for the region. For the region under study, a relationship is developed between mean annual maximum peak flood and area of the catchment using the Levenberg-Marquardt (LM) iteration and the same is coupled with the PE3 based regional flood frequency relationship developed for estimation of floods of various frequencies for the ungauged catchments of the region. The regional flood frequency relationships developed based on L-moments and soft computing techniques are compared. Copyright Springer Science+Business Media Dordrecht 2015