Preferential percolation quantified by large water content sensors with artifactual macroporous envelopes

Abstract

For many scientific and practical tasks, it is important to estimate the soil–water percolation fluxes. This paper builds on measurements with large horizontal time‐domain reflectometry water content sensors in a loamy Mollisol. The sensors were installed into pre‐drilled holes and the gaps between them, and the soil was filled with a slurry of local soil with water. This gave rise to envelopes around them that contained artificial macropores. The sensors reacted to intensive rains by a rapid increase of their readings, often above the native soil's porosity, followed by an almost equally rapid decrease. The paper explores the feasibility of quantifying the rapid percolation, based on these anomalous water content peaks, and demonstrates that this is possible in principle, if the processes are simulated by a suitable model. A two‐dimensional dual porosity non‐equilibrium (mobile‐immobile) model was tried. The envelope around the sensor was modelled as an annulus with higher porosity and hydraulic conductivity, which attracts preferential flow and amplifies the percolation signal. With the model at hand, the flux hydrographs can be derived from model simulations and measured precipitation. For contrast, the Durner equilibrium dual porosity model was tried but was found little suitable. However, even the mobile‐immobile model did not perform perfectly. Simulated water contents were similar to the measured ones at some depths but not in the others, and the percolation fluxes were overestimated, compared to cumulative soil–water balance. Efforts to improve model performance were not successful. Hence, the model structure needs to be improved. Copyright © 2015 John Wiley & Sons, Ltd.

Rapid percolation of water through soil macropores affects reading and calibration of large encapsulated TDR sensors

“…We assume that the use of Aqua-Tel-TDR or similar sensors for this purpose will not remain on the qualitative level and can be quantified with the help of a suitable mathematical model, e.g. a dual porosity model (Kogelbauer et al 2015). While the information provided by the sensors that are separated from the native soil by a gap and a layer of slurry may be a little blurred, there is additional information available due to simultaneous measurements at several different depths (three depths in our case), so that identification of main parameters of the model may be feasible.…”