通过集合平滑法的表征双相水系含水层的试验砂箱示踪试验

Abstract

AbstractEstimating aquifer properties and their spatial variability is the most challenging part of groundwater flow and transport simulations. In this work, an ensemble Kalman-based method, the ensemble smoother with multiple data assimilation (ES-MDA), is applied to infer the characteristics of a binary field by means of tracer test data collected in an experimental sandbox. Two different approaches are compared: the first one aims at estimating the hydraulic conductivity over the whole field assuming that the rest of the hydraulic and transport parameters are known by applying the standard ES-MDA method; the second one couples the ES-MDA with a truncated Gaussian model to simultaneously estimate the spatial distribution of two geological lithotypes and their main hydraulic and transport properties. Both procedures are tested following a fully parameterized approach and a pilot point approach. A synthetic case that mimics the sandbox experiment was developed to test the capability of the proposed methods and find out their optimal configurations to be used for the real case. The results show that the ES-MDA coupled with a truncated Gaussian model outperforms the standard ES-MDA and it reproduces well the binary field and the aquifer properties also in the presence of large measurement errors. The fully parametrized and pilot point approaches lead to comparable solutions, with less computation time required by the pilot point approach.