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Accuracy Assessment of Predictive SWCC Models for Estimating the van Genuchten Model Parameters

机译:预测SWCC模型的准确性评估,用于估算Van Genuchten模型参数

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Proper determination of the soil-water characteristic curve (SWCC) plays an important role in the accuracy of any modeling attempt involving variably saturated soils such as transient unsaturated seepage analysis. While the SWCC can be directly measured, several predictive models have been developed over the past two decades and are employed in practice because of their simplicity, and the lower cost, and time needed to obtain their input parameters. The predictive models are commonly developed through multiple regression analysis over a large number of measured SWCCs to establish an empirical correlation between the SWCC model parameters and soil index properties such as grain size distribution and Atterberg limits. This study evaluates the performance of seven predictive models to estimate the van Genuchten SWCC model parameters a, n, and θ_r that represent the air entry value (AEV), slope of the curve, and the residual water content, respectively. For this purpose, the transient release and imbibition method (TRIM) device is used in the laboratory to obtain the van Genuchten SWCC of silty sand samples collected from a setback levee. The van Genuchten model parameters measured in the laboratory are compared against those estimated using the predictive models. The comparison shows that using predictive models can lead to over two orders of magnitude difference in a, a ratio of θ_r to θ_s between 0.06 and 0.21, and an n value between 1.25 and 2.85 for the tested soil. The aforementioned differences can lead to significant variations in transient seepage analysis results, a factor which needs to be carefully taken into consideration when using predictive models in practice.
机译:正确测定土壤 - 水特征曲线(SWCC)在任何涉及可变饱和土壤的任何建模尝试的准确性中起重要作用,例如瞬时不饱和渗流分析。虽然SWCC可以直接测量,但在过去的二十年中已经开发了几种预测模型,并且由于它们的简单性以及获得其输入参数所需的较低的成本而在实践中使用。通过在大量测量的SWCC上通过多元回归分析常见地开发预测模型,以建立SWCC模型参数和土壤指数特性之间的经验相关性,例如晶粒尺寸分布和Atterberg限制。本研究评估了七种预测模型的性能,以估计van Genuchten SWCC模型参数A,N和θ_R,其分别表示空气入口值(AEV),曲线的斜率和残留含水量。为此目的,在实验室中使用瞬态释放和吸收方法(修剪)装置,以获得从填充堤坝收集的粉体样品的VAN Genuchten SWCC。将在实验室中测量的Van Genuchten模型参数与使用预测模型的估计进行比较。比较表明,使用预测模型可以导致过度两个数量中的量值差,θ_r至θ_s0.06和0.21之间的比率,和1.25和2.85之间的n值所测试的土壤。上述差异可能导致瞬态渗流分析结果的显着变化,在实践中使用预测模型时需要仔细考虑的因素。

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