【摘要】 土壤水分不足是黄土高原丘陵区植被建设的主要限制因子,土壤水分的空间分布受外界气象因子、土地利用与复杂地形等的影响,关系比较复杂。本研究利用黄土丘陵区纸坊沟流域的土壤水分试验资料,建立了基于GIS的BP神经网络模型,模型中同时考虑了多个因子对土壤水分空间分布的影响,利用实测资料对网络进行训练后对整个流域进行了预测,预测结果与实际情况较为一致,表明应用GIS与BP神经网络研究区域复杂地形下的土壤水分分布规律是可行的。更多还原

【Abstract】 The main limiting factor of vegetation construction in hilly areas of Loess Plateau is soil moisture.The spatial distribution of soil moisture is influenced by meteorological factors,land-uses and complex topographies,making soil moisture-vegetation relationship pretty complex.This paper utilized data from soil moisture tests in the hilly Loess Plateau of Zhifanggou catchment to build a GIS-based BP neural network model.The model technique includes multiple factor influences on spatial distribution of soil moisture.Field data was used in training the net which then used to forecast soil moisture of the cachment.The forecast result is in good agreement with practical situations,showing the feasibility of GIS-based BP neural network in analyzing soil moisture distribution regulation in highly complex regional topographic terrains.更多还原