Yiding’s coauthors were Motomu Ibaraki, Ohio State University; Richard Niswonger, U.S. Geology Survey; and Sorab Panday, GSI Environmental.
Yiding Zhang is a Senior Staff Professional based in California with experience in hydrogeology, water resources, numerical and analytical modeling, data visualization, and data analysis with machine learning and data mining approaches. He supports a variety of geologic and hydrogeologic modeling projects using Earth Volumetric Studio (EVS), MODFLOW, GMS, Python, and machine learning tools.
Groundwater is the leading international journal focused exclusively on groundwater. Since 1963, it has published a dynamic mix of papers on topics including groundwater flow and well hydraulics, hydrogeochemistry and contaminant hydrogeology, application of geophysics, groundwater management and policy, and history of groundwater hydrology.
Abstract
The χMD matrix solver package is incorporated into USGS groundwater modeling software, such as MODFLOW-NWT, MODFLOW-USG, and MT3D. The solver is used to solve matrices assembled through numerical discretization of the groundwater flow equation, and solute transport equations. χMD has demonstrated its higher robustness, faster execution speed, and more efficient memory usage compared to the existing solvers for many types of groundwater flow problems. χMD uses preconditioned iterative Krylov-subspace methods and consists of preconditioning and acceleration modules. Because the solver package uses a variety of preconditioning features including level-based incomplete lower-upper (ILU) factorization method with a drop tolerance scheme, users must choose optimal preconditioning parameters to improve execution speed and robustness. In order to examine how the preconditioning parameters, ILU factorization level, and drop tolerance values affect the overall performance of the matrix solver, we evaluated five different groundwater model applications using MODFLOW-USG that include different numerical complexities. For those five cases, the number of discretization nodes varied from 10,000 cells to 730,300 cells. From the analysis, we found that the preconditioning parameters greatly affect execution times and memory usage of the preconditioning and acceleration procedures. In addition, a combination of the ILU level between five to seven and the drop tolerance value between 10−2 and 10−3 usually resulted in shorter overall execution time. Our study suggests that the users can elicit higher performance and robustness of the χMD matrix solver using this combination of the parameters and enhance computational efficiency of solving groundwater and solute transport problems.
More Information
About the article: https://doi.org/10.1111/gwat.13110
About Publication: https://ngwa.onlinelibrary.wiley.com/journal/17456584
For consultation regarding groundwater modeling, contact Yiding Zang at YZhang@Geosyntec.com
Learn more about Yiding: https://www.linkedin.com/in/francisyidingzhang/
