Abstract
There is an increasing interest in identifying soil hydraulic properties from simplified evaporation experiments. However, the conventional simplified evaporation method includes a deficit due to using the linear assumption and not accounting for uncertainty in parameters. A suggested alternative method is assessing the parameter uncertainties through inverse modeling. We examined the combination of a Bayesian inverse method, namely, DREAM(ZS), and a numerical simulation model, namely, HYDRUS-1D, for parameter inversion with data in simplified evaporation experiments. The likelihood function could be conditioned only on pressure head observations (single-objective (SO)), or on both pressure head and evaporation rate observations (multi-objective (MO)), with different treatments on the top boundary condition. Three synthetic numerical experiments were generated in terms of the soil types of sand, loam and clay to verify the inverse modeling method. The MO approach performed better than the SO approach and linear assumption when the stage 1 evaporation rate was kept constant. However, the SO inversion was more robust when oscillations existed in the potential evaporation rate. Then, the SO inverse modeling was adopted to investigate two real experiments on loamy-sand soils and compared with the linear assumption. The linear assumption could be reliable for wet conditions with stage 1 evaporation but was not always useable for a relatively dry condition, such as that with stage 2 evaporation. The inverse modeling could be more successful in capturing the whole evaporation process of soils when both stage 1 and stage 2 were involved.
Highlights
Soil hydraulic properties (SHPs), i.e., the dependencies of soil water content and hydraulic conductivity on the matrix suction or pressure head, are prerequisite information for quantitative analyses of hydrological processes in the vadose zone [1,2,3,4]
Inverse modeling results were obtained after 60,000 iterations with the differential evolution adaptive metropolis algorithm (DREAM)(ZS) algorithm along three parallel chains to ensure that a stable posterior distribution of each parameter was achieved
The “observation” data in Figure 5 were introduced for inverse modeling, while the average Ep value was applied for the MO approach, as is normally implemented
Summary
Soil hydraulic properties (SHPs), i.e., the dependencies of soil water content and hydraulic conductivity on the matrix suction or pressure head, are prerequisite information for quantitative analyses of hydrological processes in the vadose zone [1,2,3,4]. Most of these methods involve a hydrostatic equilibrium condition, a steady-state flow or a transient flow experiment, such as the pressure plate extractor experiment or the one-step or multi-step outflow experiments [5,6] These experiments provide a series of measured data of water content, pressure head and/or flow rate, which can be used to evaluate SHPs by fitting empirical curves or calibrating numerical models [7]. At the beginning of a simplified evaporation experiment, the saturated hydraulic conductivity is significantly higher than the flux such that the hydraulic gradient may be too small to be measured within the accuracy of pressure transducers. The experiment was improved in some approaches to avoid the disadvantages of the SEM, such as using the WP4 method when observing the permanent wilting point [14,15], enhancing experimental devices to extend the measurement range and precision or using complementary additional data in the wet range [16,17,18,19]
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