Coupled hydrogeophysical inversion of an artificial infiltration experiment monitored with ground-penetrating radar: synthetic demonstration

IF 5.7 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
R. Moua, N. Lesparre, Jean-François Girard, B. Belfort, F. Lehmann, Anis Younes
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Thus, we propose to use additional information from other types of reflectors to optimize the quality of the parameter estimation. Water movement and electromagnetic wave propagation in the unsaturated zone are modeled using a one-dimensional hydrogeophysical model. The GPR travel time data are analyzed for different reflectors: a moving reflector (the infiltration wetting front) and three fixed reflectors located at different depths in the soil. Global sensitivity analysis (GSA) is employed to assess the influence of the saturated hydraulic conductivity Ks, the saturated and residual water contents θs and θr, and the Mualem–van Genuchten shape parameters α and n of the soil on the GPR travel time data of the reflectors. Statistical calibration of the soil parameters is then performed using the MCMC method. The impact of the type of reflector (moving or fixed) is then evaluated by analyzing the calibrated model parameters and their confidence intervals for different scenarios. 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Abstract

Abstract. In this study, we investigate the use of ground-penetrating radar (GPR) time-lapse monitoring of artificial soil infiltration experiments. The aim is to evaluate this protocol in the context of estimating the hydrodynamic unsaturated soil parameter values and their associated uncertainties. The originality of this work is to suggest a statistical parameter estimation approach using Markov chain Monte Carlo (MCMC) methods to have direct estimates of the parameter uncertainties. Using the GPR time data from the moving wetting front only does not provide reliable results. Thus, we propose to use additional information from other types of reflectors to optimize the quality of the parameter estimation. Water movement and electromagnetic wave propagation in the unsaturated zone are modeled using a one-dimensional hydrogeophysical model. The GPR travel time data are analyzed for different reflectors: a moving reflector (the infiltration wetting front) and three fixed reflectors located at different depths in the soil. Global sensitivity analysis (GSA) is employed to assess the influence of the saturated hydraulic conductivity Ks, the saturated and residual water contents θs and θr, and the Mualem–van Genuchten shape parameters α and n of the soil on the GPR travel time data of the reflectors. Statistical calibration of the soil parameters is then performed using the MCMC method. The impact of the type of reflector (moving or fixed) is then evaluated by analyzing the calibrated model parameters and their confidence intervals for different scenarios. GSA results show that the sensitivities of the GPR data to the hydrodynamic soil parameters are different between moving and fixed reflectors, whereas fixed reflectors at various depths have similar sensitivities. Ks has a similar and strong influence on the data of both types of reflectors. Concerning the other parameters, for the wetting front, only θs and α have an influence, and only at long time steps since the total variance is zero at the very beginning of the experiment. On the other hand, for the fixed reflectors, the total variance is not zero at the very start and the parameters θs, θr, α and n can have an influence from the very beginning of the infiltration. Results of parameter estimation show that the use of calibration data from the moving or fixed reflectors alone does not enable a good identification of all soil parameters. With the moving reflector, the error between the estimated mean value and the exact target value for θr and α is 9 % and 45 %, respectively, and less than 3 % for the other parameters. The best reduction of the size of the parameter distribution is obtained for n, with a posterior distribution 9 times smaller than the prior one. For the others, this reduction ratio varies between 1 and 5. For the fixed reflectors, the estimated mean values are far from the target values for α, θr and n, representing for a reflector located at 120 cm 15 %, 27 %, and 121 %, respectively. On the other hand, when both data are combined, all soil parameters can be well estimated with narrow confidence intervals. For instance, when using both data from the moving wetting front and a fixed reflector located at 120 cm for calibration, the estimated mean values of the errors of all parameters are less than 5 %. Moreover, all parameter distributions are well reduced, with a maximum reduction for Ks, leading to a posterior distribution being 46 times smaller than the prior one, and the worst but still satisfactory being for θr for which the posterior distribution is 8 times smaller than the prior one. The methodology was applied to fine, medium, and coarse sands with very good results, particularly for the finest soil. The thickness of the unsaturated zone was also tested (0.5, 1, and 2 m) and a better estimation of the hydrodynamic parameters is obtained when the water table is deeper. In addition, the height of water applied in the infiltrometry test influences the speed of the test without affecting the performance of the proposed method.
利用探地雷达监测人工渗透实验的水文地质物理耦合反演:合成演示
摘要。在本研究中,我们研究了利用探地雷达(GPR)进行人工土壤入渗试验的时移监测。目的是在估计水动力非饱和土参数值及其相关不确定性的背景下评估该方案。这项工作的独创性在于提出了一种使用马尔可夫链蒙特卡罗(MCMC)方法对参数不确定性进行直接估计的统计参数估计方法。仅使用移动湿锋的探地雷达时间数据不能提供可靠的结果。因此,我们建议使用其他类型反射器的附加信息来优化参数估计的质量。采用一维水地球物理模型模拟非饱和带的水运动和电磁波传播。分析了不同反射面的探地雷达走时数据:一个移动反射面(入渗湿锋)和三个位于土壤不同深度的固定反射面。采用全局敏感性分析(GSA)评价了饱和导水率Ks、饱和和残余含水量θs和θr以及土壤的Mualem-van Genuchten形状参数α和n对反射器探地雷达走时数据的影响。然后采用MCMC方法对土壤参数进行统计校正。然后,通过分析校准后的模型参数及其在不同情景下的置信区间,评估反射器类型(移动或固定)的影响。GSA结果表明,GPR数据对土壤水动力参数的敏感性在移动反射器和固定反射器之间存在差异,而不同深度的固定反射器具有相似的敏感性。Ks对两种反射器数据的影响相似且强烈。至于其他参数,对于湿锋,只有θs和α有影响,而且只有在很长的时间步长,因为在实验开始时总方差为零。另一方面,对于固定反射镜,总方差在一开始就不为零,θs、θr、α和n等参数从入渗一开始就会产生影响。参数估计结果表明,仅使用移动或固定反射镜的校准数据不能很好地识别所有土壤参数。在运动反射镜条件下,θr和α的估计平均值与精确目标值的误差分别为9%和45%,其他参数的估计平均值与精确目标值的误差小于3%。对于n,参数分布的大小减小得最好,其后验分布比前验分布小9倍。对于其他的,这个还原比率在1到5之间变化。对于固定反射器,估计的平均值与α、θr和n的目标值相差甚远,对于位于120 cm的反射器,分别代表15%、27%和121%。另一方面,当两种数据结合在一起时,所有土壤参数都能以较窄的置信区间得到很好的估计。例如,当同时使用移动湿锋数据和位于120 cm的固定反射镜进行校准时,所有参数的估计误差平均值都小于5%。此外,所有参数分布都得到了很好的缩减,其中Ks的缩减幅度最大,导致后验分布比前验分布小46倍,最差但仍然令人满意的是θr的后验分布比前验分布小8倍。该方法适用于细砂、中砂和粗砂,结果非常好,特别是对于最细的土壤。对非饱和带的厚度(0.5、1和2 m)也进行了测试,当地下水位较深时,可以更好地估计水动力参数。此外,在渗透测试中应用的水的高度影响测试的速度,而不影响所提出的方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Hydrology and Earth System Sciences
Hydrology and Earth System Sciences 地学-地球科学综合
CiteScore
10.10
自引率
7.90%
发文量
273
审稿时长
15 months
期刊介绍: Hydrology and Earth System Sciences (HESS) is a not-for-profit international two-stage open-access journal for the publication of original research in hydrology. HESS encourages and supports fundamental and applied research that advances the understanding of hydrological systems, their role in providing water for ecosystems and society, and the role of the water cycle in the functioning of the Earth system. A multi-disciplinary approach is encouraged that broadens the hydrological perspective and the advancement of hydrological science through integration with other cognate sciences and cross-fertilization across disciplinary boundaries.
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