采用太湖流域浙西区33个站点1989—2013年的降水观测资料，基于广义可加模型建立了该区域年降水空间估算模型，得到了该区域分辨率为1000 m×1000 m的降水栅格数据。借助多种统计指标，分析了不同预测因子对降水空间估算结果的影响，特别比较了是否将高程作为预测因子情况下的年降水量估算差异。结果表明：加入高程因子作为广义可加模型的预测变量后，无论是模型的优良性还是降水空间估算精度均有所提高，能够更合理地描述浙西区降水空间分布受地形影响的特征。此外，从模型偏态效应图来看，浙西区降水量随着纬度的增加明显减小，随着高程的增加显著增大，而随经度的变化则不明显。%With the aid of the observation data obtained from 33 precipitation stations during 1989—2013 in the western region of Zhejiang Province within the Taihu Lake watershed, a predictive model for the annual precipitation spatial estimation has been developed based on the generalized additive models ( GAM ) , by use of them an annual precipitation data set with 1 000 m × 1 000 m spatial resolution in the study area was gained. By several statistical indexes making analysis of influences of different predictive variables on the precipitation spatial estimation results, the accuracy and reliability of GAM based on the interpolation method were evaluated, especially comparing the differences between two kinds of the models in estimating the annual precipitation space whether or not it selects an elevation as the predictive variable. The analysed and estimated results show that, after taking the elevation as the predicative variable, whether the GAM performance or the precipitation spatial estimation accuracy were improved apparently, which can reasonably reflect the precipitation spatial distribution influenced by the topographic factors in the study area. In addition, it is found from the GAM partial effect graphs that the annual precipitation amount obviously decreased with the increase of the latitude and remarkably increased with the increase of the altitude in the study area, however, there were no obvious changes in the annual precipitation amount with the increase of the longitude.
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