Estimation of the soil hydraulic properties from field data by solving an inverse problem

Abstract

Estimating unsaturated soil hydraulic properties to predict water dynamics through a vertical soil profile under the effects of irrigation, drainage and evapotranspiration is imperative for managing soils in the arid regions. The aim of this work was to determine the soil water retention curve and the hydraulic permeability function of a bare soil profile in a Tunisian oasis threatened by salinization. The developed model combines a numerical inversion of the unsaturated flow equation with the BOBYQA optimisation algorithm. The direct model solved the Richards equation using a cell-centred finite difference model. Hydraulic properties were described by van Genuchten-Mualem models. Input data for the inverse problem are the infiltration flow, soil water contents and pressure heads measured during ponded infiltration and internal drainage tests. Numerical simulations of these two tests were performed considering a homogeneous single-layer soil profile but a better fitting between measured and simulated water contents was obtained when the soil profile was divided into five sub-layers. The hysteresis phenomenon was highlighted from the soil water retention and the relative permeability curves corresponding to the ponded infiltration and internal drainage tests.

Evaluation of Pedotransfer Functions for Estimating Soil Water Retention Curve of Ap Horizon Soils for Various Soil Series of Reclaimed Tidal Flat Soil

“…The SE of PSDs for the five-soil series were primarily less than 1%, except for the sand (1.13%) of TH and the silt (1.18%) and clay (1.11%) of BC. Soil structure affects hydraulic parameters [31]. These results indicate that the measured values were relatively well grouped around the population.…”

Parameter estimation and uncertainty analysis in hydrological modeling

“…In practice, there is another potential source of uncertainty when the solution of the parameter estimation problem requires setting a threshold or tolerance to accept or reject groups of estimated parameters e* . Here, different tolerance values may result in different magnitude of variability of the results (Guellouz et al, 2020).…”

“…In practice, there is another potential source of uncertainty when the solution of the parameter estimation problem requires setting a threshold or tolerance to accept or reject groups of estimated parameters e* . Here, different tolerance values may result in different magnitude of variability of the results (Guellouz et al, 2020). The uncertainty that affects the results produced by a calibrated model is known as posterior uncertainty , because it is posterior to conditioning the parameters of the calibrated model by the observed data (Anderson et al, 2015; Carrera et al, 2005; Doherty, 2015; Hill, 2006).…”

Assessment of Contamination Management Caused by Copper and Zinc Cations Leaching and Their Impact on the Hydraulic Properties of a Sandy and a Loamy Clay Soil

“…Hydraulic conductivity is a very important parameter in irrigation planning, as it is related to models that predict infiltration and to other hydraulic parameters, such as sorptivity, diffusivity and capacity. Hydraulic conductivity expresses the ability of water to move through soil, it is equal to the velocity of water and it affects soil water dynamics, evapotranspiration and irrigation [3][4][5][6]. Cumulative infiltration along with infiltration rate through the soil affects the water cycle, evapotranspiration, runoff, floods, aquifer recharge, irrigation, and the environment in general.…”