A comparison of sequential and integrated data fusion for estimating hydrologic properties during a synthetic GPR monitored infiltration event

Constraining parameters that govern variably saturated flow is important for applications ranging from quantifying water availability for ecosystems to constraining recharge rates and contaminant fluxes to groundwater. In this study I explore the effectiveness of sequential versus integrated data fusion for estimating unsaturated flow parameters using ground penetrating radar (GPR) data. In Sequential Data Fusion (SDF), geophysical imaging is used to create a map of the geophysical properties of the subsurface. These properties are then transformed to hydrologic properties that can be used to constrain an independent hydrologic inverse problem. In contrast, Integrated Data Fusion (IDF) uses the geophysical data to directly constrain hydrologic properties of interest without performing the intermediate geophysical imaging step. The comparison of SDF and IDF is performed for a synthetic study of 2D infiltration into a homogeneous soil from a constant flux point source located at the ground surface. The focus is on results for the estimation of intrinsic permeability (k) from cross-borehole GPR traveltimes collected throughout the duration of the infiltration event. The target permeability (k=7.4x10-12m 2) is uniform over the 20 meter by 20 meter area modeled in this study; though the soil is homogeneous, water content is both spatially variable and transient. I use TOUGH2 to simulate infiltration, MATLAB to simulate GPR traveltimes, and PEST to perform the parameter estimation. To quantitatively compare SDF and IDF, I calculate the normalized error in estimated permeability for each method. In my study, I investigated the performance of the data fusion methods under varying survey geometries by changing the antenna spacing. In all cases I have found that IDF significantly outperforms SDF. For large antenna separations (1.7--6.7m) SDF produces an average error in estimated permeability of 73% while IDF errors are only 6%. As ray density is increased for antenna separations of 1.0--1.5m, average estimation error for SDF drops to 72%, but is reduced to only 3% for IDF. Also, SDF estimates are consistently biased lower than the target value, while IDF results are unbiased. My results suggest the IDF is a powerful new approach for hydrologic characterization of the subsurface using geophysical measurements.