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Hydraulic and transport parameter assessment using column infiltration experiments

机译:使用柱渗透实验进行液压和运输参数评估

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The quality of statistical calibration of hydraulic and transport soil properties is studied for infiltration experiments in which, over a given period, tracer-contaminated water is injected into an hypothetical column filled with a homogeneous soil. The saturated hydraulic conductivity, the saturated and residual water contents, the Mualem-van Genuchten shape parameters and the longitudinal dispersivity are estimated in a Bayesian framework using the Markov chain Monte Carlo (MCMC) sampler. The impact of the kind of measurement sets (water content, pressure inside the column, cumulative outflow and outlet solute concentration) and that of the solute injection duration is investigated by analyzing the calibrated model parameters and their confidence intervals for different scenarios. The results show that the injection period has a significant effect on the quality of the estimation, in particular, on the posterior uncertainty range of the parameters. All hydraulic and transport parameters of the investigated soil can be well estimated from the experiment using only the outlet concentration and cumulative out-flow, which are measured non-intrusively. An improvement of the identifiability of the hydraulic parameters is observed when the pressure data from measurements taken inside the column are also considered in the inversion.
机译:研究了液压和运输土壤性质统计校准的质量,用于渗透实验,在给定期间,将特定时期的污染水注入填充有均匀土壤的假设柱中。使用Markov Chain Monte Carlo(MCMC)采样器估计百叶窗框架估计饱和液压导电性,饱和和残留的水含量,饱和和残留的水含量和纵向分散性。通过分析校准的模型参数和不同情景的置信区间,研究了测量组种类(含水量,柱内部,柱,累积流出和出口浓度)和溶质注射持续时间的影响。结果表明,注射周期对估计的质量有显着影响,特别是参数的后不确定度范围。通过仅使用外出口浓度和累积流动,可以从实验中估计所研究的土壤的所有液压和运输参数,这是非侵入性的。当在反转中也考虑来自柱内的测量的压力数据时,观察到液压参数的可识别性的改进。

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