基于地理空间要素的雅砻江流域面雨量估算

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

反映流域整体降水情势的面雨量一直是水文模型的重要输入参数之一,在泰森多边形雨量法的基础上考虑地理空间要素对降雨空间分布的影响,采用面向对象的遥感信息聚类方法提取出雅砻江流域2项形状因子(周长、面积)和5项地形因子(平均高程、平均坡度、平均坡向、高程差周长比和高程差面积比)。降雨—径流相关性分析结果表明:地形因子雨量法在月尺度上的降雨估算精度高于年尺度,且在月尺度上能更好地反映流域不同区段的降雨空间分布特征;在月、年际降雨变化趋势分析方面,年尺度上的降雨与径流一阶差分后平均相关系数为0. 903,高于月尺度的0. 629,主要由于水电站调蓄过程对流域径流异质性的影响,且影响度随着时间尺度缩小而放大。

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.