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首页> 外文期刊>Vadose Zone Journal >Root Zone Soil Moisture Assessment Using Remote Sensing and Vadose Zone Modeling
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Root Zone Soil Moisture Assessment Using Remote Sensing and Vadose Zone Modeling

机译:利用遥感和渗流带模拟对根区土壤水分进行评估

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摘要

Soil moisture is an important hydrologic state variable critical to successful hydroclimatic and environmental predictions. Soil moisture varies both in space and time because of spatio-temporal variations in precipitation, soil properties, topographic features, and vegetation characteristics. In recent years, air- and space-borne remote sensing campaigns have successfully demonstrated the use of passive microwave remote sensing to map soil moisture status near the soil surface (0–0.05 m below the ground) at various spatial scales. In this study root zone (e.g., 0–0.6 m below the ground) soil moisture distributions were estimated across the Little Washita watershed (Oklahoma) by assimilating near-surface soil moisture data from remote sensing measurements using the Electronically Scanned Thinned Array Radiometer (ESTAR) with an ensemble Kalman filter (EnKF) technique coupled with a numerical one-dimensional vadose zone flow model (HYDRUS-ET). The resulting distributed root zone soil moisture assessment tool (SMAT) is based on the concept of having parallel noninteracting streamtubes (hydrologic units) within a geographic information system (GIS) platform. The simulated soil moisture distribution at various depths and locations within the watershed were compared with measured profile soil moisture data using time domain reflectometry (TDR). A reasonable agreement was found under favorable conditions between footprint-scale model estimations and point-scale field soil moisture measurements in the root zone. However, uncertainties introduced by precipitation and soil hydraulic properties caused suboptimal performance of the integrated model. The SMAT holds great promise and offers flexibility to incorporate various data assimilation techniques, scaling, and other hydrological complexities across large landscapes. The integrated model can be useful for simulating profile soil moisture estimation and for predicting transient soil moisture behavior for a range of hydrological and environmental applications.
机译:土壤水分是成功进行水文气候和环境预测的重要水文状态变量关键 。土壤 的水分在空间和时间上都会变化,这是由于降水,土壤性质,地形特征, 和植被特征的时空变化。近年来,空载和空载 遥感运动已成功地证明了 使用无源微波遥感来绘制附近土壤湿度 状态的图在各种空间尺度上的土壤表面(地下0-0.05 m) 。在本研究的根区(例如,地下0–0.6 m),通过吸收 估算了整个小Washita流域(俄克拉荷马州)的土壤水分分布 。 sup>使用集成的卡尔曼滤波器(EnKF)技术结合电子扫描稀疏阵列辐射计(ESTAR)的遥感测量得到的近地土壤水分数据 一维数值渗流区流模型(HYDRUS-ET)。 所得的分布式根区土壤水分评估工具 工具(SMAT)基于这一概念地理信息 系统(GIS)平台中具有平行的非相互作用的 流管(水文单元)的问题。使用时域反射计 (TDR)将流域内不同深度和位置的模拟土壤水分分布 与实测土壤水分数据进行了比较。在足迹尺度模型估计与根域土壤湿度测量的点尺度场 之间的有利条件下,找到了合理的协议。但是,降水和土壤水力学特性引入的不确定性 导致集成模型的 次优性能。 SMAT拥有 的美好承诺,并提供了灵活性,可以在整个大景观中合并各种 数据同化技术,缩放和其他水文 复杂性。集成模型可以 用于模拟剖面土壤湿度估算, 用于预测水文和环境应用范围内的瞬时土壤水分行为。 sup>

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  • 来源
    《Vadose Zone Journal》 |2006年第1期|296-307|共12页
  • 作者单位

    Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX 77843-2117;

    Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX 77843-2117;

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