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ARS Home » Pacific West Area » Davis, California » Sustainable Agricultural Water Systems Research » Research » Publications at this Location » Publication #395217

Research Project: Improved Agroecosystem Efficiency and Sustainability in a Changing Environment

Location: Sustainable Agricultural Water Systems Research

Title: A computationally efficient hydrologic modeling framework to simulate surface-subsurface hydrological processes at the hillslope scale

item CHEN, LIN - University Of California, Riverside
item SIMUNEK, J - University Of California, Riverside
item Bradford, Scott
item AJAMI, HOORI - University Of California, Riverside
item Meles, Menberu

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/23/2022
Publication Date: 11/1/2022
Citation: Chen, L., Simunek, J., Bradford, S.A., Ajami, H., Meles, M.B. 2022. A computationally efficient hydrologic modeling framework to simulate surface-subsurface hydrological processes at the hillslope scale. Journal of Hydrology. 614. Article 128539.

Interpretive Summary: Computer models are useful tools to understand and predict water runoff and flow in soils. However, existing physically based models are not very efficient and require long run times, especially at large scales. A simplified physical model was developed that combined existing one-dimensional models for runoff and water flow in soil. Application of this simplified model to a range of scenarios (rainstorm events, soil properties, and surface slopes) demonstrated that the developed model showed good agreement with the more complex conventional model, but ran faster and can account for other processes that are usually neglected. The simplified model therefore shows great promise for larger scale model applications. Results from this study will be interest to scientists, engineers, and government regulators concerned with predicting water flow and contaminant transport at the watershed scale.

Technical Abstract: Considering surface and subsurface interactions is imperative to predict water movement, water quantity and quality in the environment. However, substantial execution time and over-parameterization presently limit the applicability of integrated hydrologic models at larger scales. Herein, a new efficient coupling routine for one-dimensional (1D) surface–subsurface modeling was developed by externally coupling two widely used open-source codes. KINEROS2 (K2) solves the 1D kinematic wave equation for overland flow, and HYDRUS-1D (H1D) solves the Richards equation for subsurface flow. A novel approach, combined with water balance and boundary condition switching, is used to account for surface ponding and water exchange between the two model domains. A weighting factor related to the surface water depth is used to assign the time series of exchange fluxes in one H1D profile to multiple surface nodes in the K2 calculation. This novel approach enables us to represent the entire subsurface below each overland-flow plane by one vertical soil column with different soil layering. When soil properties vary horizontally, multiple soil columns can represent spatial heterogeneities. The performance of the coupled H1D-K2 model is examined by comparing simulation results with the HYDRUS-2D (H2D) model for six benchmark problems. The solution’s robustness, stability, and accuracy are assessed for a wide variety of cases, including multiple rainstorms, different slopes, heterogeneous subsurface, and different bottom boundary conditions resulting in 41 cases. The simulated hydrographs, surface water levels, and water balance components are all in good agreement. Relative mass balance errors are very small, typically not exceeding 4.0% for the coupled H1D-K2 model. Compared with the H2D model, the coupled model achieves a factor of 1.3–10 speedup by applying one H1D soil profile to an entire overland flow plane rather than to individual surface nodes.