Hydrology and Earth System Sciences Discussions, 03/02/2017, pp.1-31
We investigate the quantitative effect of unrepresented (i) sensor position uncertainty, (ii) small scale-heterogeneity, and (iii) 2D flow phenomena on estimated effective soil hydraulic material properties. 〈br〉〈br〉 Therefore, a complicated 2D subsurface architecture (ASSESS) was forced with a fluctuating groundwater table. Time Domain Reflectometry (TDR), Ground Penetrating Radar (GPR), and hydraulic potential measurement devices monitored the hydraulic state during the experiment. Since the measurement data are analyzed with an inversion method, starting close to the measurement data is key. Therefore, we developed a method which estimates the initial water content distribution by approximating the soil water characteristic on the basis of TDR measurement data and the position of the groundwater table. In order to reduce parameter bias due to unrepresented model errors, we implemented a structural error analysis to identify uncertain model components which have to be included in the parameter estimation. Hence, focussing on TDR and hydraulic potential data, we realized a 1D and a 2D study with increasingly complex setups: Starting with estimating effective hydraulic material properties, we added the estimation of sensor positions, the estimation of small-scale heterogeneity, or both. 〈br〉〈br〉 The analysis of these studies with a modified Levenberg-Marquardt algorithm demonstrates three main points: (i) The approximated soil water characteristic for the initial water content distribution is reasonably close to inversion results. (ii) Although the material properties resulting from 1D and 2D studies are similar, the 1D studies are likely to yield biased parameters due to unrepresented lateral flow. (iii) Representing and estimating sensor positions as well as small-scale heterogeneity improves the mean absolute error by more than a factor of 2.
Hydrology and Earth System Sciences Discussions