A distributed Grid-Xinanjiang model with integration of subgrid variability of soil storage capacity

Realistic hydrological response is sensitive to the spatial variability of landscape properties. For a grid-based distributed rainfall-runoff model with a hypothesis of a uniform grid, the high-frequency information within a grid cell will be gradually lost as the resolution of the digital elevation model(DEM) grows coarser. Therefore, the performance of a hydrological model is usually scale-dependent. This study used the GridXinanjiang(GXAJ) model as an example to investigate the effects of subgrid variability on hydrological response at different scales. With the aim of producing a more reasonable hydrological response and spatial description of the landscape properties, a new distributed rainfall-runoff model integrating the subgrid variability(the GXAJSV model) was developed. In this model, the topographic index is used as an auxiliary variable correlated with the soil storage capacity. The incomplete beta distribution is suggested for simulating the probability distribution of the soil storage capacity within the raster grid. The Yaogu Basin in China was selected for model calibration and validation at different spatial scales.Results demonstrated that the proposed model can effectively eliminate the scale dependence of the GXAJ model and produce a more reasonable hydrological response.

Water level updating model for flow calculation of river networks

Complex water movement and insufficient observation stations are the unfavorable factors in improving the accuracy of flow calculation of river networks. A water level updating model for river networks was set up based on a three-step method at key nodes, and model correction values were collected from gauge stations. To improve the accuracy of water level and discharge forecasts for the entire network, the discrete coefficients of the Saint-Venant equations for river sections were regarded as the media carrying the correction values from observation locations to other cross-sections of the river network system. To examine the applicability, the updating model was applied to flow calculation of an ideal river network and the Chengtong section of the Yangtze River. Comparison of the forecast results with the observed data demonstrates that this updating model can improve the forecast accuracy in both ideal and real river networks.