西北干旱区土壤水力参数空间变异与模拟

Spatial Variability and Simulation of Soil Hydraulic Parameters in Arid Northwest China

为探明西北干旱区土壤水力参数的空间分布特征,在新疆地区布设107个样点,获取表层(0~5 cm)Ks(土壤饱和导水率)、FC(田间持水量)和PWP(永久萎蔫系数)数据,采用经典统计学和地统计学分析土壤水力参数的空间变异特征,并利用逐步回归和传递函数方程对Ks、FC和PWP进行模拟。结果表明:新疆地区Ks、FC和PWP平均值分别为10.999 mm·h^-1、0.162 g·g^-1和0.077 g·g^-1,变异系数为39.88%~96.07%,均表现为中等程度变异。在区域尺度上Ks、FC和PWP具有强空间依赖性,变程为97~291km。与经自变量数据转换构建的传递函数方程相比,多元逐步回归方程预测土壤水力参数精度更高,且方程使用更便利。基于土地利用、容重、土壤质地、有机碳含量和坡向的多元逐步回归方程,预测Ks、FC和PWP的决定系数R2分别为0.290、0.494和0.491,均方根误差(RMSE)分别为2.540 mm·h^-1,0.039 g·g^-1和0.023 g·g^-1。这些方程的建立,有利于西北干旱区土壤水力参数的快速估算,同时可为该地区的农业灌溉和生态水文模型提供关键参数。

Soil saturated hydraulic conductivity(Ks),field capacity(FC)and permanent witling percentage(PWP)are the important soil hydraulic parameters.These parameters are also the critical factors in bio-hydrologic models.In order to understand the regional-scale spatial variability of these hydraulic parameters,the Ks,FC and PWP data(0-5 cm soil layer in depth)were obtained from 107 sampling sites in Xinjiang.Both traditional statistics and geostatistics were used to explore the spatial variations of Ks,FC and PWP.Estimations of these parameters were further conducted by multiple stepwise regression(MSR)and pedotransfer functions(PTFs).The results indicated that the mean values of Ks,FC and PWP were 10.999 mm·h&-1,0.162 g·g^-1 and 0.077 g·g^-1 respectively.These three hydraulic parameters varied moderately with Cvs of 39.88%-96.07%,and had strong spatial correlations in a range of 97-291 km in Xinjiang.MSR performed better than PTFs in estimating soil hydraulic parameters.Based on the land use,bulk density,soil texture,soil organic carbon content and slope aspect,the determination coefficients of the MSR models for Ks,FC and PWP were 0.290,0.494 and 0.491,and the root mean square errors were 2.540 mm·h^-1,0.039 g·g^-1 and 0.023 g·g^-1,respectively.The development of these equations is beneficial to the rapid estimation of soil hydraulic parameters and can thus provide the key parameters for the agricultural irrigation and eco-hydrological models in arid Northwest China.