Estimating soil hydraulic properties and their uncertainty: the use of stochastic simulation in the inverse modelling of the evaporation method

Abstract

The evaporation method is an easy and reliable procedure for measuring soil hydraulic properties. Inverse modelling has been used to analyse the evaporation data facilitating the prediction of soil hydraulic properties. The conventional approach to solve the inverse solution is the use of the nonlinear least-squares (NLLS) technique. A major problem with such inverse modelling approaches is nonidentifiability, which is a condition where different parameter sets can lead to a similar flow response. In addition, NLLS only attempts to find optimum parameters that give the best fit to the observed data while not recognising the uncertainties in the models and observations made. The discrepancies of the NLLS approach may be alleviated by adopting the concept of generalized likelihood uncertainty estimation (GLUE), which acknowledges that many parameter sets within a model will give similar output to satisfy a given objective function. This is illustrated in this paper by using the GLUE method for estimating soil water retention and hydraulic conductivity from an evaporation experiment encompassing a range of soil types ranging from sand to heavy clay. Results show that the GLUE methodology can provide the estimates of the hydraulic properties and along with its uncertainty. The water retention curve can be predicted well from the range of potential 0 to −1000 cm, but the uncertainty associated with the unsaturated hydraulic conductivity prediction is quite high.