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Predicting saturated hydraulic conductivity in a sandy grassland using proximally sensed apparent electrical conductivity

机译:使用近端感应视在电导率预测沙质草地的饱和水导率

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Finding a correspondence between soil hydraulic properties, such as saturated hydraulic conductivity (Ks) and apparent electrical conductivity (ECa) as an easily measurable parameter, may be a way forward to estimate the spatial distribution of hydraulic properties at the field scale. In this study, the spatial distributions of Ks, of soil ECa measured by a DUALEM-21S sensor and of soil physical properties were investigated in a sandy grassland. To predict field scale Ks, the statistical relationship between co-located soil Ks, and EMI-ECa was evaluated. Results demonstrated the large spatial variability of all studied properties with Ks being the most variable one (CV = 86.21%) followed by ECa (CV >= 53.77%). A significant negative correlation was found between In-transformed Ks and ECa (r = 0.83; P <= 0.01) at two depths of exploration (0-50 and 0-100 cm). This site specific relation between In Ks and ECa was used to predict saturated hydraulic conductivity over 0-50 cm depth for the whole field. The empirical relation was validated using an independent dataset of measured Ks. The statistical results demonstrate the robustness of this empirical relation with mean estimation error MEE = 0.46 (cm h(-1)), root-mean-square estimation errors RMSEE = 0.74 (cm h(-1)), coefficient of determination r(2) = 0.67 and coefficient of model efficiency Ce = 0.64. The relationship was then used to produce a detailed map of Ks for the whole field. The result will allow model predictions of spatially distributed water content in view of irrigation management. (C) 2016 Elsevier B.V. All rights reserved.
机译:寻找土壤水力特性之间的对应关系,例如饱和水力传导率(Ks)和表观电导率(ECa)作为易于测量的参数,可能是在田间规模上估算水力特性空间分布的一种方法。在这项研究中,调查了在沙质草地上用DUALEM-21S传感器测量的土壤ECa的Ks的空间分布以及土壤物理性质。为了预测田间规模Ks,评估了同地土壤Ks和EMI-ECa之间的统计关系。结果表明,所有研究属性的空间变异性都很大,Ks是变量最大的变量(CV = 86.21%),其次是ECa(CV> = 53.77%)。在两个勘探深度(0-50和0-100 cm)处,In转换的Ks与ECa之间存在显着的负相关(r = 0.83; P <= 0.01)。 In Ks和ECa之间的这种特定于位置的关系用于预测整个油田在0-50 cm深度上的饱和导水率。使用独立的测量Ks数据集验证了经验关系。统计结果证明了这种经验关系的鲁棒性,其平均估计误差MEE = 0.46(cm h(-1)),均方根估计误差RMSEE = 0.74(cm h(-1)),确定系数r( 2)= 0.67,模型效率系数Ce = 0.64。然后使用该关系生成整个场的Ks详细图。考虑到灌溉管理,结果将允许对空间分布的水含量进行模型预测。 (C)2016 Elsevier B.V.保留所有权利。

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