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选择合适的插值预测模型对揭示干旱区绿洲地下水与表层土壤特征空间变化特征具有重要意义。根据克里雅绿洲实测地下水(埋深、电导率、水温)与表层土壤(含水率、电导率、土温)数据,系统评价不同空间插值方法(RBF、IDW、Ordinary Kriging)对不同特征预测精度的影响。结果表明:克里雅绿洲区域地下水埋深主要在3 m以下,电导率在5 m S·cm-1以下,温度在15℃以下;表层土壤含水量主要在0.5以下,电导率在2.5 m S·cm-1以下,温度在13℃以下。地下水埋深采用RBF插值的精度较高,电导率采用IDW的精度较高,水温采用RBF的精度较高;表层土壤含水率采用Kriging插值的精度较高,电导率采用RBF的精度较高,土温采用RBF的精度较高;除土壤含水率外,其余指标采用对数转化后插值精度较高。
Choosing a suitable interpolation prediction model is of great significance in revealing the spatial variability of groundwater and surface soil characteristics in the oasis of arid areas. According to the data of groundwater (depth, conductivity, water temperature) and surface soil (moisture content, conductivity, soil temperature) measured in the Keria Oasis, systematic evaluation of different spatial interpolation methods (RBF, IDW and Ordinary Kriging) Impact. The results show that the groundwater depth is mainly below 3 m, the conductivity is below 5 mS · cm-1, the temperature is below 15 ℃, the surface soil moisture content is below 0.5 and the conductivity is 2.5 mS · Cm-1 or less, the temperature is below 13 ℃. RBF interpolation of groundwater depth is more accurate, conductivity of IDW is higher, RBF accuracy is higher, Kriging interpolation of surface soil moisture is more accurate, conductivity of RBF is higher, The accuracy of temperature using RBF is higher; besides the soil moisture content, the interpolation accuracy of logarithm transformation of other indicators is higher.