JWSS - Journal of Water and Soil Science

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Estimation of unsaturated soil hydraulic and solute transport properties by Inverse modeling has thus far been limited mostly to analyses of one-dimensional experiments in the laboratory, often assuming steady-state conditions. This is partly because of the high cost and difficulties in accurately measuring and collecting adequate field-scale data sets, and partly because of difficulties in describing spatial and temporal variability in the soil hydraulic properties. In this study we estimated soil hydraulic and solute transport parameters from several two-dimensional furrow irrigation experiments under transient conditions. Three blocked-end furrow irrigation experiments were carried out, each of the same duration but with different amounts of infiltrating water and solutes resulting from water depths of 6, 10, and 14 cm in the furrows. Two more experiments were carried out with the same amounts of applied water and solute, and hence for different durations, on furrows with water depths of 6 and 10 cm. The saturated hydraulic conductivity (K_s) and solute transport parameters in the physical equilibrium convection-dispersion (CDE) and physical nonequilibrium mobile/ immobile (MIM) transport models were inversely estimated using the Levenberg-Marquardt optimization algorithm in combination with the HYDRUS-2D numerical code. Estimated K_s-values ranged from 0.0389 to 0.0996 cm min^-1, with a coefficient of variation of 48%. Estimated immobile water contents (θ_im) were more or less constant at a relatively low average value of 0.025 cm³ cm^-3, whereas the first-order exchange coefficient (ω) varied between 0.10 and 19.52 min^-1. The longitudinal dispersivity (D_L) ranged from 2.6 to 32.8 cm, and the transverse dispersivity (D_T) from 0.03 to 2.20 cm. D_L showed some dependency on water level and irrigation/solute application time in the furrows, but no obvious effect was found on K_s and other transport parameters. Agreement between measured and predicted infiltration rates was satisfactory, whereas soil water contents were somewhat overestimated and solute concentrations underestimated. Differences between predicted solute distributions obtained with the CDE and MIM transport models were relatively small. This finding and the value of optimized parameters indicate that observed data were sufficiently well described using the simpler CDE model, and that immobile water did not play a major role in the transport process.

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Modeling of flow and transport processes in variably saturated porous media requires detailed knowledge of the soil hydraulic properties. The hydraulic properties to be determined by the inverse problem solution are the unsaturated hydraulic conductivity K(h) and the water retention curve θ(h). The inverse modeling approach assumes that both θ(h) and K(h) as well as transport parameters can be determined simultaneously from transient flow data by numerical inversion of the governing flow and transport equations. In order to find answers to the questions of uniqueness, identifiability and stability of different experimental setups, a new numerical experiment of redistribution was carried out. To study the shape of the objective function near its minimum, response surfaces for the estimated parameters were generated. The sensitivity of model outputs with respect to changes in input parameters was also computed and analyzed. Results of the redistribution experiment suggest that the non-uniqueness increases when the model output variables are not sensitive enough to the optimized parameters. As expected, the estimated values of parameters were sensitive to the magnitude of error in the measured data. In this experiment, the parameter estimation based on the pressure head observations provides unique solution. Due to preferential flow in the sample, tensiometric observations may provide poor results for inverse problem solution. Taking into account information about saturated hydraulic conductivity, Ks improved the likelihood of uniqueness and reduced the errors in parameter estimation of the shape parameters (α, n). It was found that the sensitivity analysis could be a useful tool to design the optimal time and location distribution of experimental observations.

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Soil moisture is one of the main input parameters in many models for monitoring and predicting crop yield. The ability of mathematical models has allowed correct application of brackish water and selection of management options. The purpose of this research was to evaluate the performance of HYDRUS-2D for simulating soil volumetric water content in a heterogeneous heavy soil under field conditions. Three volumes of irrigation water (10, 15 and 20 L) and three salinity levels of irrigation water (1.279, 2.5 and 5 dSm^-1) were exerted in a linear drip irrigation system with three replications. In order to check the amount of soil volumetric water content, soil profiles were drilled to 40 cm depth and vertical wall of drip irrigation line was networked. Soil volumetric water content was measured with a TDR MiniTrase kit 6050X3K1B model. The observed soil moisture values were compared with the simulated ones using statistical indices (i.e. nRMSE and CRM).  The results indicated that mean soil volumetric water content distribution in irrigation water with different levels of salinities was in the range of field capacity. The range of nRMSE values varied from 0.91 to 2.07 percent in different replications. According to calculated nRMSE values, performance of the simulation model, was ranked as excellent for simulation of soil volumetric water content. Range of CRM values was shown to be from -0.0080 to 0.0170 that was really low. Results of these two statistics indicate high ability of the model in simulating soil volumetric water content using estimating hydraulic parameters by inverse solution.