YUAN Dingbo, AI Ping, HONG Min, LIAO Hengli, CHEN Binbin, YUE Zhaoxin. Estimation of areal rainfall in Yalong River basin based on geospatial factors[J]. Advances in Water Science, 2018, 29(6): 779-787. DOI: 10.14042/j.cnki.32.1309.2018.06.003
Citation: YUAN Dingbo, AI Ping, HONG Min, LIAO Hengli, CHEN Binbin, YUE Zhaoxin. Estimation of areal rainfall in Yalong River basin based on geospatial factors[J]. Advances in Water Science, 2018, 29(6): 779-787. DOI: 10.14042/j.cnki.32.1309.2018.06.003

Estimation of areal rainfall in Yalong River basin based on geospatial factors

  • Areal rainfall, which reflects the overall precipitation in a basin, has always been an important input parameter of hydrological models. In consideration of the influence of geospatial factors on the spatial distribution of rainfall, object-oriented remote sensing information clustering method is used to extract two shape factors (perimeter and area) and five topographic factors (mean elevation, mean slope, mean aspect, ratio of elevation difference to perimeter, and ratio of elevation difference to area) in the Yalong River basin on the basis of the Thiessen polygon rainfall method. The rainfall-runoff correlation results show that the areal rainfall estimation accuracy on the monthly scale is higher than that on the annual scale by using the topographic factor rainfall method. The spatial distribution characteristics of rainfall in different regions of the Yalong River basin on the monthly scale are also reflected effectively by using the mehod. The monthly and interannual rainfall trend results show that the average correlation coefficient between annual scale rainfall and runoff in the first-order difference is 0.903, which is higher than that of 0.629 on the monthly scale. This difference is mainly due to the influence of the regulation and storage process of hydropower station on runoff heterogeneity along with the enlargement in influence degree as time scale narrows.
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