Adaptive and Efficient Computing for Subsurface Simulation within ParFlow

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Description

This project is concerned with the PF.WRF model as a means to enable more accurate predictions of wind fluctuations and subsurface storage. As developed at LLNL, PF.WRF couples a groundwater (subsurface) and surface water flow model (ParFlow) to a mesoscale atmospheric model (WRF, Weather Research and Forecasting Model). It was developed as a unique tool to address coupled water balance and wind energy questions that occur across traditionally separated research regimes of the atmosphere, land surface, and subsurface. PF.WRF is capable of simulating fluid, mass, and energy transport processes in groundwater, vadose zone, root zone, and land surface systems, including ... continued below

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PDF-file: 19 pages; size: 0.3 Mbytes

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Tiedeman, H & Woodward, C S November 16, 2010.

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Description

This project is concerned with the PF.WRF model as a means to enable more accurate predictions of wind fluctuations and subsurface storage. As developed at LLNL, PF.WRF couples a groundwater (subsurface) and surface water flow model (ParFlow) to a mesoscale atmospheric model (WRF, Weather Research and Forecasting Model). It was developed as a unique tool to address coupled water balance and wind energy questions that occur across traditionally separated research regimes of the atmosphere, land surface, and subsurface. PF.WRF is capable of simulating fluid, mass, and energy transport processes in groundwater, vadose zone, root zone, and land surface systems, including overland flow, and allows for the WRF model to both directly drive and respond to surface and subsurface hydrologic processes and conditions. The current PF.WRF model is constrained to have uniform spatial gridding below the land surface and matching areal grids with the WRF model at the land surface. There are often cases where it is advantageous for land surface, overland flow and subsurface models to have finer gridding than their atmospheric counterparts. Finer vertical discretization is also advantageous near the land surface (to properly capture feedbacks) yet many applications have a large vertical extent. However, the surface flow is strongly dependent on topography leading to a need for greater lateral resolution in some regions and the subsurface flow is tightly coupled to the atmospheric model near the surface leading to a need for finer vertical resolution. In addition, the interactions (e.g. rain) will be highly variable in space and time across the problem domain so an adaptive scheme is preferred to a static strategy to efficiently use computing and memory resources. As a result, this project focussed on algorithmic research required for development of an adaptive simulation capability in the PF.WRF system and its subsequent use in an application problem in the Central Valley of California. This report documents schemes of use for a future implementation of an adaptive grid capability within the ParFlow subsurface flow simulator in PF.WRF. The methods describe specific handling of the coarse/fine boundaries within a cell-centered discretization of the nonlinear parabolic Richards equation model for variable saturated flow. In addition, we describe development of a spline fit and table lookup method implemented within ParFlow to enhance computational efficiency of variably saturated flow calculations.

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PDF-file: 19 pages; size: 0.3 Mbytes

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  • Report No.: LLNL-TR-462325
  • Grant Number: W-7405-ENG-48
  • DOI: 10.2172/1018745 | External Link
  • Office of Scientific & Technical Information Report Number: 1018745
  • Archival Resource Key: ark:/67531/metadc836262

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Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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Creation Date

  • November 16, 2010

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

Description Last Updated

  • Dec. 6, 2016, 6:46 p.m.

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Tiedeman, H & Woodward, C S. Adaptive and Efficient Computing for Subsurface Simulation within ParFlow, report, November 16, 2010; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc836262/: accessed November 21, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.