Proof of concept of regional scale hydrologic simulations at hydrologic resolution utilizing massively parallel computer resources

[1] We present the results of a unique, parallel scaling study using a 3-D variably saturated flow problem including land surface processes that ranges from a single processor to a maximum number of 16,384 processors. In the applied finite difference framework and for a fixed problem size per processor, this results in a maximum number of approximately 8 × 109 grid cells (unknowns). Detailed timing information shows that the applied simulation platform ParFlow exhibits excellent parallel efficiency. This study demonstrates that regional scale hydrologic simulations on the order of 103 km2 are feasible at hydrologic resolution (∼100–101 m laterally, 10−2–10−1 m vertically) with reasonable computation times, which has been previously assumed to be an intractable computational problem.

[1]  P. Huyakorn,et al.  A fully coupled physically-based spatially-distributed model for evaluating surface/subsurface flow , 2004 .

[2]  R. Maxwell,et al.  Integrated surface-groundwater flow modeling: A free-surface overland flow boundary condition in a parallel groundwater flow model , 2006 .

[3]  Jim E. Jones,et al.  Approved for Public Release; Further Dissemination Unlimited Newton-krylov-multigrid Solvers for Large-scale, Highly Heterogeneous, Variably Saturated Flow Problems , 2022 .

[4]  Peter A. Troch,et al.  The need for a virtual hydrologic laboratory for PUB , 2005 .

[5]  Rao S. Govindaraju,et al.  Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas , 2008 .

[6]  Jianping Huang,et al.  Dissimilarity of Scalar Transport in the Convective Boundary Layer in Inhomogeneous Landscapes , 2009 .

[7]  Chin-Hoh Moeng,et al.  The Influence of Idealized Heterogeneity on Wet and Dry Planetary Boundary Layers Coupled to the Land Surface. , 2005 .

[8]  C. Duffy,et al.  A semidiscrete finite volume formulation for multiprocess watershed simulation , 2007 .

[9]  K. Loague,et al.  Hydrologic‐Response simulations for the R‐5 catchment with a comprehensive physics‐based model , 2001 .

[10]  R. Freeze,et al.  Blueprint for a physically-based, digitally-simulated hydrologic response model , 1969 .

[11]  Reed M. Maxwell,et al.  Development of a Coupled Land Surface and Groundwater Model , 2005 .

[12]  R. Dickinson,et al.  The Common Land Model , 2003 .

[13]  R. Maxwell,et al.  The groundwater land-surface atmosphere connection: Soil moisture effects on the atmospheric boundary layer in fully-coupled simulations , 2007 .

[14]  Stefan Kollet,et al.  Influence of soil heterogeneity on evapotranspiration under shallow water table conditions: transient, stochastic simulations , 2009 .

[15]  Jeffrey J. McDonnell,et al.  Testing nutrient flushing hypotheses at the hillslope scale: A virtual experiment approach , 2006 .

[16]  Clemens Simmer,et al.  The Influence of Hydrologic Modeling on the Predicted Local Weather: Two-Way Coupling of a Mesoscale Weather Prediction Model and a Land Surface Hydrologic Model , 2002 .

[17]  Zong-Liang Yang,et al.  Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data , 2007 .

[18]  R. Maxwell,et al.  Demonstrating fractal scaling of baseflow residence time distributions using a fully‐coupled groundwater and land surface model , 2008 .

[19]  R. Maxwell,et al.  Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model , 2008 .

[20]  Robert D. Falgout,et al.  The Design and Implementation of hypre, a Library of Parallel High Performance Preconditioners , 2006 .

[21]  Young-Jin Park,et al.  An assessment of the tracer‐based approach to quantifying groundwater contributions to streamflow , 2006 .

[22]  R. Ababou,et al.  Implementation of the three‐dimensional turning bands random field generator , 1989 .