Volume 9 Issue 2
Apr.  2016
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Wei-jian Guo, Chuan-hai Wang, Teng-fei Ma, Xian-min Zeng, Hai Yang. 2016: A distributed Grid-Xinanjiang model with integration of subgrid variability of soil storage capacity. Water Science and Engineering, 9(2): 97-105. doi: 10.1016/j.wse.2016.06.003
Citation: Wei-jian Guo, Chuan-hai Wang, Teng-fei Ma, Xian-min Zeng, Hai Yang. 2016: A distributed Grid-Xinanjiang model with integration of subgrid variability of soil storage capacity. Water Science and Engineering, 9(2): 97-105. doi: 10.1016/j.wse.2016.06.003

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

doi: 10.1016/j.wse.2016.06.003
Funds:  This work was supported by the Graduate Students Scientific Research Innovation Plan of Jiangsu Province (Grant No. CXZZ12_0243), the China Scholarship Council Scholarship (Grant No. 201306710013), the State Major Project of Water Pollution Control and Management (Grant No. 2014ZX07101-011), and the Special Fund for Public Welfare of Ministry of Water Resources of China (Grant No. 201501007).
More Information
  • Corresponding author: Wei-jian Guo
  • Received Date: 2015-10-26
  • Rev Recd Date: 2016-03-15
  • 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 Grid-Xinanjiang (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.

     

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