A physics-based hydro-geomorphologic simulation utilizing cluster parallel computing

To conduct a large-scale hydrologic-response and landform evolution simulation at high resolution, a complex physics-based numerical model, the Integrated Hydrology Model (InHM), was revised utilizing cluster parallel computing. The parallelized InHM (ParInHM) divides the simulated area into multiple catchments based on geomorphologic features, and generates boundary-value problems for each catchment to construct simulation tasks, which are then dispatched to different computers to start the simulation. Landform evolution is considered during simulating and implemention in one framework. The dynamical Longest-Processing-Time (LPT) first scheduling algorithm is applied to job management. In addition, a pause-integrate- divide-resume routine method is used to ensure the hydrologic validity during the simulation period. The routine repeats until the entire simulation period is finished. ParInHM has been tested in a computer cluster that uses 16 processors for the calculation, to simulate 100 years’ hydrologic-response and soil erosion for the 117-km2 Kaho’olawe Island in the Hawaiian Islands under two different mesh resolutions. The efficiency of ParInHM was evaluated by comparing the performance of the cluster system utilizing different numbers of processors, as well as the performance of non-parallelized system without domain decomposition. The results of this study show that it is feasible to conduct a regional-scale hydrologic-response and sediment transport simulation at high resolution without demanding significant computing resources.

[1]  J. Vanderkwaak Numerical simulation of flow and chemical transport in integrated surface-subsurface hydrologic systems , 1999 .

[2]  Yu-Shu Wu,et al.  An efficient parallel-computing method for modeling nonisothermal multiphase flow and multicomponent transport in porous and fractured media , 2002 .

[3]  S. P. Anderson,et al.  Near-surface hydrologic response for a steep, unchanneled catchment near Coos Bay, Oregon: 2. Physics-based simulations , 2007, American Journal of Science.

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

[5]  Jan Vanderborght,et al.  Proof of concept of regional scale hydrologic simulations at hydrologic resolution utilizing massively parallel computer resources , 2010 .

[6]  Brett F. Sanders,et al.  Performance of Parallel Implementations of an Explicit Finite-Volume Shallow-Water Model , 2006 .

[7]  Benjamin B. Mirus,et al.  First‐order exchange coefficient coupling for simulating surface water–groundwater interactions: parameter sensitivity and consistency with a physics‐based approach , 2009 .

[8]  S. P. Anderson,et al.  Near-surface hydrologic response for a steep, unchanneled catchment near Coos Bay, Oregon: 1. sprinkling experiments , 2007, American Journal of Science.

[9]  Ronaldo I. Borja,et al.  The impacts of hysteresis on variably saturated hydrologic response and slope failure , 2010 .

[10]  Yu-Shu Wu,et al.  Parallel computing simulation of fluid flow in the unsaturated zone of Yucca Mountain, Nevada. , 2003, Journal of contaminant hydrology.

[11]  Timothy Fewtrell,et al.  Parallelisation of storage cell flood models using OpenMP , 2009, Environ. Model. Softw..

[12]  Keith Beven,et al.  Three‐dimensional modelling of hillslope hydrology , 1992 .

[13]  Guangqian Wang,et al.  A semi-implicit three-dimensional numerical model for non-hydrostatic pressure free-surface flows on an unstructured, sigma grid , 2013 .

[14]  Enrique R. Vivoni,et al.  Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment , 2011 .

[15]  Hong Wang,et al.  Formation process of meandering channel by a 2D numerical simulation , 2012 .

[16]  Hao Wang,et al.  Dynamic parallelization of hydrological model simulations , 2011, Environ. Model. Softw..

[17]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[18]  Benjamin B. Mirus,et al.  Assessing the detail needed to capture rainfall‐runoff dynamics with physics‐based hydrologic response simulation , 2011 .

[19]  Steven G. Smith,et al.  ParFlow User's Manual , 2014 .

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

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

[22]  A comparison of observed and simulated hydrograph separations for a field-scale rainfall-runoff experiment. , 2000 .

[23]  K. Loague,et al.  Simulating hydrological response for the R‐5 catchment: comparison of two models and the impact of the roads , 2002 .

[24]  David R. Montgomery,et al.  Physics‐based continuous simulation of long‐term near‐surface hydrologic response for the Coos Bay experimental catchment , 2007 .

[25]  Peter A. Forsyth,et al.  A parallel computational framework to solve flow and transport in integrated surface-subsurface hydrologic systems , 2012, Environ. Model. Softw..

[26]  K. Loague,et al.  Hydrologic‐response‐driven sediment transport at a regional scale, process‐based simulation , 2012 .

[27]  Qihua Ran,et al.  Adding sediment transport to the integrated hydrology model (InHM): Development and testing , 2006 .

[28]  Hao Wang,et al.  A common parallel computing framework for modeling hydrological processes of river basins , 2011, Parallel Comput..

[29]  V. Singh,et al.  Mathematical Modeling of Watershed Hydrology , 2002 .

[30]  C. Simmons,et al.  HydroGeoSphere: A Fully Integrated, Physically Based Hydrological Model , 2012 .

[31]  T. Giambelluca,et al.  Land Misuse and Hydrologic Response: Kaho'olawe, Hawai'i , 1996 .

[32]  Zhaoyin Wang,et al.  Gender of large river deltas and parasitizing rivers , 2012 .

[33]  Jim E. Jones,et al.  Newton–Krylov-multigrid solvers for large-scale, highly heterogeneous, variably saturated flow problems , 2001 .

[34]  Manoj K. Jha,et al.  A DEM‐based parallel computing hydrodynamic and transport model , 2012 .

[35]  Keith Loague,et al.  Further testing of the Integrated Hydrology Model (InHM): event‐based simulations for a small rangeland catchment located near Chickasha, Oklahoma , 2005 .

[36]  Brett F. Sanders,et al.  ParBreZo: A parallel, unstructured grid, Godunov-type, shallow-water code for high-resolution flood inundation modeling at the regional scale , 2010 .

[37]  Chung-Yee Lee,et al.  Multiprocessor scheduling: combining LPT and MULTIFIT , 1988, Discret. Appl. Math..

[38]  Zhiguo He,et al.  Prediction and application for rain induced shallow landslides in natural catchments , 2011, 2011 International Conference on Electric Technology and Civil Engineering (ICETCE).

[39]  Wolfgang Lucht,et al.  Efficient parallelization of a dynamic global vegetation model with river routing , 2010, Environ. Model. Softw..

[40]  Nataliia Kussul,et al.  Grid computing technology for hydrological applications , 2011 .

[41]  K. Loague,et al.  Using simulated hydrologic response to revisit the 1973 Lerida Court landslide , 2010 .

[42]  Vijay P. Singh,et al.  Accuracy of Kinematic Wave and Diffusion Wave Approximations for Flood Routing. I: Steady Analysis , 2008 .

[43]  C. Miao,et al.  Numerical modeling of gravitational erosion in rill systems , 2011 .

[44]  P. E. O'connell,et al.  An introduction to the European Hydrological System — Systeme Hydrologique Europeen, “SHE”, 2: Structure of a physically-based, distributed modelling system , 1986 .

[45]  Qihua Ran,et al.  Further testing of the integrated hydrology model (InHM): multiple‐species sediment transport , 2007 .

[46]  J. Bathurst,et al.  SHESED: a physically based, distributed erosion and sediment yield component for the SHE hydrological modelling system , 1996 .

[47]  Keith Loague,et al.  Rapid simulated hydrologic response within the variably saturated near surface , 2008 .

[48]  Hao Wang,et al.  Maximum speedup ratio curve (MSC) in parallel computing of the binary-tree-based drainage network , 2012, Comput. Geosci..