In-situ soil parametrization from multi-layer moisture data

TL;DR

This paper presents an inversion methodology to derive comprehensive soil parameters from multi-layer moisture data, accounting for water dynamics, hysteresis, and bulk density effects, enhancing soil modeling accuracy.

Contribution

It introduces a novel inversion approach that integrates multiple soil properties from moisture data, improving parameter estimation for soil simulation models.

Findings

Method successfully retrieves soil parameters from moisture data.

Inversion results align better with experimental bulk density values.

Not all data sets provide sufficient information for convergence.

Abstract

Inversion methodology has been used to obtain, from multi-layer soil probes records, a complete soil parametrisation, namely water retention curve, unsaturated conductivity curve and bulk density at 4 depths. The approach integrates water dynamics, hysteresis and the effect of bulk density on conductivity to extract soil parameters required from most simulation models. The method is applied to sub-sets of data collection, allowing to understand that not every data-sets contains the information required for method convergence. A comparison with experimental bulk-density values show that inversion could give information even with a better adherence to model, as it considers the effect of roots and skeleton. The method may be applied to any type of multi-layer water content probes giving the opportunity to enrich soil parameter availability and reliability.