Assessing the influence of rain gauge density and distribution on hydrological model performance in a humid region of China

Summary Hydrological models are important tools for flood forecasting and for the assessment of water resources under current and changing climate. However, the accuracy of hydrological models is limited by many factors, the most important of which, is perhaps the errors in the input data. The influence of the precipitation gauge density and network distribution on the modelling results is still a challenging topic in hydrology studies. One of the reasons for the limited study of this important issue is that it needs a catchment with sufficient size, wide diversity of topography and climate, and dense rain gauges with long and good quality data. In this study, a famous and widely used hydrological model, the Xinanjiang Model, was applied in Xiangjiang River basin to examine the influence of rain gauge density and distribution on the performance of the model in simulating the stream flow. The Xiangjiang River basin, one of the most important economic belts in Hunan Province, China and the primary inflow basin of Dongting Lake – China’s second largest freshwater lake, has dense rain gauge network with long and high quality data. To perform the study, firstly, the mean areal rainfall estimated by different rain gauge densities using various statistical indices as evaluation criteria was analysed. Secondly, the influence of different rain gauge density and distribution on the model performance was rigorously evaluated. The results show that the error range of the indices in analysing mean areal rainfall and simulated runoff narrowed gradually with increasing number of rain gauges up to some threshold, and beyond which the model performance did not show considerable improvements. The methodology and results of this study will provide useful guidelines and valuable reference for studying rainfall influence in hydrological modelling.