Numerical solution of the one‐dimensional Richards' equation is the recommended method for coupling groundwater to the atmosphere through the vadose zone in hyperresolution Earth system models, but requires fine spatial discretization, is computationally expensive, and may not converge due to mathematical degeneracy or when sharp wetting fronts occur. We transformed the one‐dimensional Richards' equation into a new equation that describes the velocity of moisture content values in an unsaturated soil under the actions of capillarity and gravity. We call this new equation the Soil Moisture Velocity Equation (SMVE). The SMVE consists of two terms: an advection‐like term that accounts for gravity and the integrated capillary drive of the wetting front, and a diffusion‐like term that describes the flux due to the shape of the wetting front capillarity profile divided by the vertical gradient of the capillary pressure head. The SMVE advection‐like term can be converted to a relatively easy to solve ordinary differential equation (ODE) using the method of lines and solved using a finite moisture‐content discretization. Comparing against analytical solutions of Richards' equation shows that the SMVE advection‐like term is >99% accurate for calculating infiltration fluxes neglecting the diffusion‐like term. The ODE solution of the SMVE advection‐like term is accurate, computationally efficient and reliable for calculating one‐dimensional vadose zone fluxes in Earth system and large‐scale coupled models of land‐atmosphere interaction. It is also well suited for use in inverse problems such as when repeat remote sensing observations are used to infer soil hydraulic properties or soil moisture.
The OpenDBDDAS Toolkit is a software framework to provide support for more easily creating and expanding dynamic big data-driven application systems (DBDDAS) that are common in environmental systems, many engineering applications, disaster management, traffic management, and manufacturing. In this paper, we describe key features needed to implement a secure MapReduce and Hadoop-like system for high performance clusters that guarantees a certain level of privacy of data from other concurrent users of the system. We also provide examples of a secure MapReduce prototype and compare it to another high performance MapReduce, MR-MPI.
The interaction between surface and subsurface hydrology flow systems is important for water supplies. Accurate, efficient numerical models are needed to estimate the movement of water through unsaturated soil. We investigate a water infiltration model and develop very fast serial and parallel implementations that are suitable for a computer with a graphical processing unit (GPU).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.