Influence of rainfall data scarcity on non-point source pollution prediction: Implications for physically based models

文献类型： 外文期刊

第一作者： Chen, Lei

作者： Chen, Lei;Xu, Jiajia;Li, Shuang;Sun, Cheng;Shen, Zhenyao;Wang, Guobo;Liu, Hongbin;Zhai, Limei

作者机构：

关键词： Information entropy; Non-point source pollution; Rainfall data; Scarcity; Soil and Water Assessment Tool; Three Gorges Reservoir Region

期刊名称：JOURNAL OF HYDROLOGY （ 影响因子：5.722； 五年影响因子：6.033 ）

ISSN： 0022-1694

年卷期： 2018 年 562 卷

页码：

收录情况： SCI

摘要： Hydrological and non-point source pollution (H/NPS) predictions in ungagged basins have become the key problem for watershed studies, especially for those large-scale catchments. However, few studies have explored the comprehensive impacts of rainfall data scarcity on H/NPS predictions. This study focused on: 1) the effects of rainfall spatial scarcity (by removing 11%-67% of stations based on their locations) on the H/NPS results; and 2) the impacts of rainfall temporal scarcity (10%-60% data scarcity in time series); and 3) the development of a new evaluation method that incorporates information entropy. A case study was undertaken using the Soil and Water Assessment Tool (SWAT) in a typical watershed in China. The results of this study highlighted the importance of critical-site rainfall stations that often showed greater influences and cross-tributary impacts on the H/NPS simulations. Higher missing rates above a certain threshold as well as missing locations during the wet periods resulted in poorer simulation results. Compared to traditional indicators, information entropy could serve as a good substitute because it reflects the distribution of spatial variability and the development of temporal heterogeneity. This paper reports important implications for the application of Distributed Hydrological Models and Semi-distributed Hydrological Models, as well as for the optimal design of rainfall gauges among large basins.

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