草业科学2011，Vol.28Issue(9)：1581-1588,8.
基于GIS的降水多元回归模型在黑河干流山区的应用
An application of multivariate regression model to predict precipitation based on GIS in the Heihe river basin
摘要
Abstract
Based on precipitation data collecting at 21 stations from 1971 to 2000 and five topographic factors （altitude, slope, aspect, longitude and latitude） acquiring from three different resolution digital elevation model （DEM）, the multivariate regression analysis, combined with GIS, was used to develop a precipitation prediction model for the Heihe river basin. The results of this study showed that the multivariate regression model explained 74.5 % of the spatial variability of precipitation over the whole year, and this model had better explanation precipitation for wet season （May-September） than the whole year and dry season. Precipitation during dry season was difficult to simulate owing to little rainfall and a different synoptic system. The 100 m resolution model in the three periods were better than other resolution model to explain the precipitation because the spatial distribution of precipitation was uneven. The 100 m resolution model predicted that the precipitation increased from below 200 at the north-west regions to 700 mm at south-east regions, indicating that a precipitation line exit was observed from northeast to southwest. The 500 m resolution model predicted that the rainfall was ribbon boundaries with a certain degree shift. The 1 000 m resolution model predicted rainfall distribution with a big error. The model established in this study could be potentially applied to other mountains; however, improving the model accuracy was necessary in the future.关键词
降水量/多元回归模型/GIS/黑河干流山区Key words
precipitation/multivariate regression model/GIS/Heihe river basin分类
农业科技引用本文复制引用
梁友嘉,徐中民..基于GIS的降水多元回归模型在黑河干流山区的应用[J].草业科学,2011,28(9):1581-1588,8.基金项目
中国科学院知识创新工程重要方向项目群“地表过程集成系统研究” （）
国家自然科学基金 （）
