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Coupled surface-subsurface flow hydrodynamic model for surface irrigation
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: Paper number 131609658, 2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: http://dx.doi.org/10.13031/aim.20131609658) @2013
Authors: Qin-ge Dong, Di Xu, Shaohui Zhang, Meijian Bai, Yinong Li
Keywords: surface irrigation; hybrid coupling method; numerical simulation; saturated-unsaturated flow; Darcy’s law
Abstract. The coupled surface-subsurface flow model for surface irrigation can effectively simulate the non-linear interaction processes of surface-subsurface flow as well as the soil moisture redistribution processes. In this study, a new coupled surface-subsurface flow hydrodynamic model is constructed based on the governing equations of a 1D complete hydrodynamic model, which is solved using the hybrid numerical method, and a 1D subsurface flow model, which is solved using a proposed finite-volume method with fourth-order accuracy. The surface water depth obtained from the continuous equation of the complete hydrodynamic model for surface irrigation is set as the upper boundary condition, and the infiltration water depth value is calculated using the subsurface flow model. Subsequently, the modified new surface water depth is obtained and is still set as the upper boundary condition for the subsurface flow model, the next new surface water depth can then be obtained. In this iteration process, the convergence of surface and infiltration water depth is reached. The converged surface water depth is then fed back to the momentum conservation equation of the complete hydrodynamic model for surface irrigation to maintain the momentum conservation. Then, the coupled surface-subsurface flow can be simulated and the coupling process ia labeled hybrid coupling method. The validation results showed that the proposed coupled model has better simulation accuracy and stability than that of two existed internal iterative coupled models. Moreover, the computational efficiency of the proposed coupled model is 0.7 times higher than those of the other two coupled models.
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