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Field-Scale Water Flow Simulations Using Ensembles of Pedotransfer Functions for Soil Water Retention

机译:利用Pedotransfer函数集合进行土壤水保持的田间尺度水流模拟

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摘要

Using pedotransfer functions (PTF) to estimate soil hydraulic properties may be necessary in soil water flow simulations for large-scale projects or in pilot studies. The accuracy of a PTF outside of its development dataset is generally unknown. The existence of multiple models that are developed and tested in one region, but may perform relatively poorly in other regions, is also common in meteorology, where multimodel ensemble prediction techniques have been developed (i.e., those using an averaged prediction from several models) to address this problem. The objective of this work was to estimate the applicability of an ensemble of PTFs for water regime simulations. Measured soil water contents and pressure heads of 60 points at five depths in a 6-m transect of a layered loamy soil were collected during an extremely wet year in Belgium. Soil water fluxes were measured with passive capillary lysimeters at two depths. Water retention was measured in the laboratory on samples taken at 60 locations at three depths. Contents of soil textural fractions, organic matter content, and bulk density were averaged across the transect and used as input in the ensemble of 22 published PTFs developed from large datasets in different regions. The HYDRUS-1D software was used to simulate water content time series with (i) each of the PTFs from the ensemble and (ii) the laboratory-measured water retention data of each of the 60 locations. Simulations with the PTF ensemble had, on average, two times smaller errors those from using laboratory data. A possible explanation for this is that the PTF estimation gave substantially better approximations of field water retention than the laboratory data. The ensemble prediction appears to be a promising source of soil hydraulic properties to simulate soil water dynamics.
机译:大型项目的土壤水流模拟中或在试验研究中,可能需要使用pedotransfer函数(PTF)估算土壤水力 属性。通常不知道a PTF在其开发数据集之外的准确性。 在一个区域中存在开发并测试过 的多个模型,但是可能在其他地区表现相对较差, 在气象学中也很常见,在气象学中已经开发了多模式集合预测技术(例如,那些使用平均 的技术多个模型的预测)来解决此问题。这项工作的 目标是评估 PTF集合在水情模拟中的适用性。在 期间,在分层的6 m样带中收集了5个深度 的被测土壤 的水含量和60压力头。比利时潮湿的一年。使用被动毛细管溶渗仪在两个深度处测量土壤水通量 。在实验室中,在三个深度的60个位置取样的样品上测量了保水量 。在整个断面 中平均土壤质地成分含量,有机物含量和堆积密度,并将其用作22个已开发的 来自不同区域的大型数据集。使用HYDRUS-1D软件 通过(i)来自集合的PTF的每个 和(ii)实验室测量的 < / sup> 60个位置中每个位置的保水数据。使用实验室数据,使用PTF集成进行的模拟 平均而言,误差 小两倍。 的一种可能解释是,PTF估算比田间持水量给出了比实验室数据更好的近似值。集成 预测似乎是一种有前途的土壤水力 属性,可用于模拟土壤水分动力学。

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  • 来源
    《Vadose Zone Journal》 |2006年第1期|234-247|共14页
  • 作者单位

    Dep. of Earth and Environmental Sciences, Univ. of California, Riverside, CA 92521;

    USDA-ARS, Environmental Microbial Safety Lab., BARC-East, 173 Powder Mill Rd., Beltsville, MD 20705;

    USDA-ARS, George E. Brown, Jr. Salinity Lab., Riverside, CA;

    USDA-ARS Hydrology and Remote Sensing Lab., Beltsville, MD;

    Dep. of Earth and Environmental Sciences, Univ. of California, Riverside, CA 92521;

    SCK-CEN, Belgium;

    USNRC, ONRR, Washington, DC;

    USNRC, ONRR, Washington, DC;

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