Event Title

Strategies for Large Scale Implementation of a Multiscale, Multiprocess Integrated Hydrologic Model: The Great Salt Lake Basin

Presenter Information

Mukesh Kumar
Christopher J. Duffy

Location

Eccles Conference Center

Event Website

http://water.usu.edu/htm/conference/past-spring-runoff-conferences

Start Date

27-3-2006 10:15 AM

End Date

27-3-2006 10:30 AM

Description

Distributed models simulate hydrologic state variables in space and time while taking into account the heterogeneities in terrain, surface, subsurface properties and meteorological forcings. Computational cost and model complexity increases with its tendency to accurately simulate the large number of interacting physical processes at fine spatio-temporal resolution in a large basin. A hydrologic model run on a coarse spatial discretization of the watershed with a limited number of physical processes, may have a smaller computational demand, but will have limited accuracy and restricted physical reality. So it is imperative to have a modeling strategy which (a) can be adaptively applied at a range of scales in order to study the tradeoffs between computational complexity, accuracy, and predictive uncertainty and, b) which is flexible enough to incorporate different approximations to the process equations depending on model purpose.

Our goal is to develop an efficient, integrated, hydrologic model for the Great Salt Lake basin (~89000 sq. km), that captures the complex topographic, geologic, and climatic gradients within the basin. The proposed strategy and associated hydrologic modeling framework will facilitate a seamless, efficient and accurate integration of the process equations and the data-model. The framework supports implementation of a multiscale, multiresolution, adaptive refinement/de-refinement and nested modeling simulations. Nonetheless, even with an efficient model, simulation on a single processor machine is still not feasible for large regions like the Great Salt Lake Basin.

The paper discusses our implementation of the integrated hydrologic model on parallel processors, demonstrating the speedup and scalability. The value of nested grid design and parallel computation for modeling hydrologic systems is demonstrated with a watershed case study. Finally, implications and plans for the Great Salt Lake basin modeling effort are outlined (funded by NOAA, GAPP).

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Mar 27th, 10:15 AM Mar 27th, 10:30 AM

Strategies for Large Scale Implementation of a Multiscale, Multiprocess Integrated Hydrologic Model: The Great Salt Lake Basin

Eccles Conference Center

Distributed models simulate hydrologic state variables in space and time while taking into account the heterogeneities in terrain, surface, subsurface properties and meteorological forcings. Computational cost and model complexity increases with its tendency to accurately simulate the large number of interacting physical processes at fine spatio-temporal resolution in a large basin. A hydrologic model run on a coarse spatial discretization of the watershed with a limited number of physical processes, may have a smaller computational demand, but will have limited accuracy and restricted physical reality. So it is imperative to have a modeling strategy which (a) can be adaptively applied at a range of scales in order to study the tradeoffs between computational complexity, accuracy, and predictive uncertainty and, b) which is flexible enough to incorporate different approximations to the process equations depending on model purpose.

Our goal is to develop an efficient, integrated, hydrologic model for the Great Salt Lake basin (~89000 sq. km), that captures the complex topographic, geologic, and climatic gradients within the basin. The proposed strategy and associated hydrologic modeling framework will facilitate a seamless, efficient and accurate integration of the process equations and the data-model. The framework supports implementation of a multiscale, multiresolution, adaptive refinement/de-refinement and nested modeling simulations. Nonetheless, even with an efficient model, simulation on a single processor machine is still not feasible for large regions like the Great Salt Lake Basin.

The paper discusses our implementation of the integrated hydrologic model on parallel processors, demonstrating the speedup and scalability. The value of nested grid design and parallel computation for modeling hydrologic systems is demonstrated with a watershed case study. Finally, implications and plans for the Great Salt Lake basin modeling effort are outlined (funded by NOAA, GAPP).

http://digitalcommons.usu.edu/runoff/2006/AllAbstracts/13