黄土高原西部土壤水分时空变化模拟研究——以安家坡流域为例

土壤水作为陆地水循环和水量平衡的一个重要组成部分,在土壤-植被-大气连续体物质与能量转化中起着重要的作用,成为陆面过程研究中的重要参量.选择黄土高原西部的安家坡流域,采用多点长序列观测方法,对该区域土壤水分的时空变化规律进行研究.结果表明:坡向和土地利用类型是小流域土壤水分变异的重要影响因素,得出了不同立地条件下土壤水分的剖面变化与时间的动态规律.在此基础上,利用土壤湿度指数结合主要影响因素预测土壤水分的时空变化,旨在为黄土高原大中尺度的土壤水分模拟提供思路.

GIS-Assisted Modeling Spatial and Temporal Variations of Soil Water Content in Anjiapo Catchment of the Western Loess Plateau

Understanding of the spatial and temporal variability of soil water content(SWC) can provide an important baseline for assessing ecological(for restoration) and economic(for agriculture) conditions at micro-and meso-scales.To characterize the soil water content,a small catchment,Anjiapo(10 km2) in the semiarid western Loess Plateau was selected.Soil moisture has been measured at 36 sites for 16 years in the catchment.Several conclusions can be drawn from the analytical results of data: 1) wetter soil moisture conditions occur in two periods(one period from April to May,the other from the late August to October).2) SWC varies with slope position,aspect and land use type.SWC is higher in low slope position than in higher slope position,higher in north-facing slope than in south-facing slope,and higher in cropland than in shrub land and forestland.3) a hydrological active layer of soil moisture generally occurs at 0~40 cm depth from surface in grassland and forestland,0~30 cm in wasteland,0~100 cm in farmland.The soil moisture in the active layer is affected by meteorological,biological,and anthropogenic factors and exhibits larger amplitude of variations than other layers.Wetness index model was used to predict the temporal and spatial variation of soil moisture patterns in this study.Comparing predicted soil moisture with the observed soil water content shows that the correlation is significant in April,August and September at the 0.01 level,while the correlation is significant in other May,June and July at the 0.05 level.According to the empirical relationship between the wetness index and observed soil water content,the wetness index can be converted into soil water content to serve for water resource assessment and ecological restoration.The objective is to build physical processes-based model that can explain the variability of soil water content and that can be applicable to larger scales and other bio-climatically similar area.