| description abstract | Spatial heterogeneity and measurement error in parameters representing flow and salt transport properties in irrigated and drained fields make numerical prediction of soil hydrosalinity conditions, crop yield response, and other variables prone to uncertainty. This paper presents a method to account for uncertainty of correlated regionalized parameters in simulating key performance variables using a three-dimensional (3D) flow and transport model, the Colorado State University Irrigation and Drainage (CSUID) model, coupled with multivariate Monte Carlo simulation. Sequential indicator simulation is used to generate 3D correlated realizations for hydraulic conductivity, porosity, residual water content, van Genuchten parameters, and dispersivity. Other semiempirical parameters that control crop water uptake, irrigation efficiency, and subsurface drainage conductance also are randomized. The generated ensembles for each of the considered parameters are processed with the CSUID model to obtain the spatial statistical moments of root-zone hydrosalinity conditions and relative crop yield for an irrigated and drained alfalfa field. In addition, the statistical properties of hydrographs of drainage effluent and salt concentration are explored. Results show that parameter uncertainty significantly affects the predicted hydrosalinity responses, consequently affecting uncertainty in the estimate of relative crop yield throughout the field. Spatial distributions of the coefficient of variation of the ensemble of predicted values of water table depth and soil salinity ranged from 1–21% and 12–31%, respectively, across the field at the end of the 60-day simulated period. Corresponding spatial distributions of the coefficient of variation of the predicted relative yield of alfalfa values ranged from 16–36%. With respect to the simulated period, the temporal distribution of the coefficient of variation of the drainage effluent rate and salt concentration ranged from 23–42% and 1.5–0.8%, respectively. | |
