【摘要】 基于遥感的区域土壤水分反演是流域水资源规划管理、农作物灌溉制度制定、区域旱情监测、农作物估产等方面的基础.本文对四种可见光/热红外土壤水分反演方法进行评估对比,这四种土壤水分估算方法包括基于温度植被干旱指数(TVDI)的土壤水分估算方法和三种基于蒸散比/潜在蒸散比的土壤水分估算方法(EFM1,EFM2和EFM3).基于以上四种土壤水分估算方法,本文使用ASTER数据估算了黑河流域中游地区的土壤水分状况,使用研究区内生态水文无线传感器网络和流域水文气象观测站点的土壤水分观测对四个模型进行了验证评估.结果表明,TVDI方法因其干、湿边确定的经验性,会导致土壤水分估算的误差.而基于蒸散比/潜在蒸散比的土壤水分估算方法会在一定程度改善TVDI方法估算的经验性.通过蒸散比/潜在蒸散比的三种方法对比显示基于EFM1和EFM3方法优于EFM2方法.此外,基于热红外的土壤水分估算方法都需要土壤参数信息,土壤参数的不确定性会导致土壤水分估算的误差,高精度的土壤参数会改善基于热红外的土壤水分估算方法的精度.更多还原

【Abstract】 Remote sensing-based estimation of soil moisture is crucial in many aspects including basinscale w ater resource management,irrigation scheduling,regional scale drought monitoring and crop yield forecasting. In this study,w e evaluate the potential of visible/thermal-infrared remote sensing in soil moisture estimation,by assessing the TVDI-based method and three categories of methods based on evaporative fraction/potential evaporation ratio( EFM1,EFM2 and EFM3). In combination w ith ASTER data set,soil moisture in middle reach of the Heihe River Basin is predicted by the above-mentioned four methods and validated by the ground-based measurements from eco-hydrological w ireless sensor netw ork and hydro meteorological observation netw ork in the middle reach of Heihe river basin.Results indicate that uncertainties arise from the empiricism of the TVDI-based method in the process ofdetermining dry and w et edges. On the other hand,the evaporation fraction/potential evaporation ratio methods can to some degree reduce the uncertainties,and among the three methods,EFM1 and EFM3 outperform EFM2. In addition,the thermal-infrared based methods require accurate soil parameters to reproduce the variation of soil moisture.更多还原