Department of Bari, National Research Council (CNR), Water Research Institute, via F. De Blasio, 5, 70132, Bari, Italy.
Environ Monit Assess. 2018 Apr 25;190(5):310. doi: 10.1007/s10661-018-6671-x.
In recent years, geophysics is increasingly used to study the flow and transport processes in the vadose zone. Particularly, when the vadose zone is made up of rocks, it is difficult to install sensors in the subsurface to measure hydrological state variables directly. In these cases, the electrical resistivity tomography (ERT) represents a useful tool to monitor the hydrodynamics of the infiltration and to estimate hydraulic parameters and state variables, such as hydraulic conductivity and water content. We propose an integrated approach aimed at predicting water content dynamics in calcarenite, a sedimentary carbonatic porous rock. The uncoupled hydrogeophysical approach proposed consists in 4D ERT monitoring conducted during an infiltrometer test under falling head conditions. Capacitance probes were installed to measure water content at different depths to validate the estimations derived from ERT. A numerical procedure, based on a data assimilation technique, was accomplished by combining the model (i.e., Richards' equation) with the observations in order to provide reliable water content estimations. We have used a new data assimilation method that is easy to implement, based on the ensemble Kalman filter coupled with Brownian bridges. This approach is particularly suitable for strongly non-linear models, such as Richards' equation, in order to take into account both the model uncertainty and the observation errors. The proposed data assimilation approach was tested for the first time on field data. A reasonable agreement was found between observations and predictions confirming the ability of the integrated approach to predict water content dynamics in the rocky subsoil.
近年来,地球物理学越来越多地被用于研究包气带中的流动和运移过程。特别是当包气带由岩石组成时,很难在地下安装传感器来直接测量水文状态变量。在这些情况下,电阻率层析成像(ERT)是一种有用的工具,可以监测入渗的水动力过程,并估计水力参数和状态变量,如导水率和含水量。我们提出了一种综合方法,旨在预测钙质砂岩中的含水量动态,钙质砂岩是一种沉积碳酸盐多孔岩石。提出的非耦合水文地球物理方法包括在下落水头条件下进行的渗流仪试验中的 4D ERT 监测。安装电容探头以在不同深度测量含水量,以验证从 ERT 得出的估计值。基于数据同化技术的数值程序通过将模型(即 Richards 方程)与观测值相结合来完成,以提供可靠的含水量估计值。我们使用了一种新的数据同化方法,该方法易于实现,基于集合卡尔曼滤波器和布朗桥相结合。该方法特别适用于 Richards 方程等强非线性模型,以便考虑模型不确定性和观测误差。所提出的数据同化方法首次在现场数据上进行了测试。观测值和预测值之间存在合理的一致性,这证实了综合方法预测基岩中含水量动态的能力。