Vadose zone modeling in a small forested catchment: Impact of water pressure head sampling frequency on 1D-model calibration

Abstract

The characterization of vadose zone processes is a primary goal for understanding, predicting, and managing water resources. In this study, the issue of soil water monitoring on a vertical profile in the small forested Strengbach catchment (France) is investigated using numerical modeling with the long-term sequences 1D-Richards’ equation and parameter estimation through an inverse technique. Three matric potential sensors produce the observation data, and the meteorological data is monitored using an automatic weather station. The scientific questions address the selection of the calibration sequence, the initial starting point for inverse optimization and monitoring frequency used in the inverse procedure. As expected, our results show that the highly variable data period used for the calibration provides better estimations when simulating the long-term sequence. For the starting point of the initial parameters, handmade iterative initial parameters estimation leads to better results than a laboratory analysis or set of ROSETTA parameters. Concerning the frequency of monitoring, weekly and daily datasets provide efficient results compared to hourly data. As reported in other articles, the accuracy of the boundary conditions is important for estimating soil hydraulic parameters and accessing water stored in the layered profile.