Estimation of hydraulic parameters in a heterogeneous lowlying farmland near Venice
E. Zancanaro, C. Zoccarato, P. Teatini
Dept. of Civil, Environmental and Architectural Engineering,
University of Padova, Padova, Italy
F. Morari
Dept. of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Legnaro, Italy
ABSTRACT
Estimating the hydraulic properties of the vadose zone is essential to understand
soil-water dynamics and achieving appropriate water management in agricultural
lands. Inverse modelling methods are commonly used to estimate hydraulic properties
from field observations. Unlike the extensively applied local search methodologies,
data assimilation techniques can fully account for multiple uncertainties and are
becoming a widely used tool for estimating hydraulic parameters. However, only few
applications on real field tests are available. The main objective of this study was to
estimate the van Genuchten-Mualem (VGM) parameters and the saturated hydraulic
conductivity (Ks) of a heterogeneous low-lying farmland at the margin of the Venice
Lagoon, Italy, characterized by high peat content, sandy drifts, and a very shallow
water table. To this end, two methods were tested, that is, the Ensemble Smoother
(ES) and the Levenberg-Marquardt (LM) algorithm associated with hydrological
modelling performed with Hydrus-1D. Volumetric water content (VWC) observations
were collected at three monitoring sites from May to September 2011. Results on
parameters highlighted that the ES technique effectively reduced the uncertainty of α
and n, but it was less effective on θr and Ks.
The results on VWC showed that the
ES efficiency decreased with the increasing non-linearity of the system (e.g., higher
sand content) and when the variability of the experimental data was lower
(e.g., deepest soil layers where saturation remained permanently close to 1). Both LM
and ES allowed to reproduce the VWC observations in the calibration and validation
phases, with the former and the latter performing better in the case of sandy and
peat soils, respectively. As concerns the method applicability, the ES was less
time-demanding as it efficiently updated all the parameters at once and was less dependent
on the user choices. Finally, the paper points out the importance of previous
knowledge of the VGM parameters (e.g., from lab hydraulic analyses) in defining the
constraints for the optimization.
