Application of an improved distributed Xinanjiang hydrological model for flood prediction in a karst catchment in South‐Western China

Abstract

AbstractHydrological processes in karst aquifer systems are controlled by highly permeable media, so studying flood processes in karst‐dominated regions is very important; however, it is still a challenge to model the hydrological dynamics in such strongly heterogeneous conditions. This study proposed a distributed Xinanjiang karst hydrological model (DXAJKHM) for simulating the flood processes in karst catchments, which was based on topographical information extracted from a digital elevation model. Considering the dual‐porosity in karst aquifer systems, the DXAJKHM was coupled with a traditional Xinanjiang conceptual hydrological model and utilized two karst reservoirs that simulated both the rapid underground run‐off and the slow underground run‐off in each grid cell. The uncertainty in the model parameters is estimated by the generalized likelihood uncertainty estimation method, and the parameters are determined by the shuffled complex evolution approach optimization algorithm. The simulation results demonstrated that the proposed DXAJKHM satisfactorily simulated the flood processes, and the model has better simulation effects for floods with larger flood peaks. In order to analyse the flood recession error, one run‐off signature index was employed to improve the model runs. This study thus provides a new approach to simulating and predicting floods in karst areas.