Scalability of Grid- and Subbasin-Based Land Surface Modeling Frameworks for Hydrologic Simulations

TitleScalability of Grid- and Subbasin-Based Land Surface Modeling Frameworks for Hydrologic Simulations
Publication TypeJournal Article
Year of Publication2014
JournalScalability of Grid- and Subbasin-Based Land Surface Modeling Frameworks for Hydrologic Simulations
Number6
Pages3116-3184
Abstract / Summary

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., ability to perform consistently across spatial resolutions) in simulating runoff generation. Simulations are produced by the grid- and subbasin-based Community Land Model (CLM) at 0.125o, 0.25o, 0.5o and 1o spatial resolutions over the U.S. Pacific Northwest. Using the 0.125o simulation as the "reference" solution, statistical metrics are calculated by comparing simulations at 0.25o, 0.5o and 1o resolutions with the 0.125o simulation aggregated to the respective resolutions for each approach. Statistical significance test results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o resolutions compared to the 0.125osimulation are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning because of scalability related to air temperature and surface elevation. Scalability of a topographic parameter used in runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes.

URLhttp://onlinelibrary.wiley.com/doi/10.1002/2013JD020493/abstract
DOI10.1002/2013JD020493
Journal: Scalability of Grid- and Subbasin-Based Land Surface Modeling Frameworks for Hydrologic Simulations
Year of Publication: 2014
Number: 6
Pages: 3116-3184

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., ability to perform consistently across spatial resolutions) in simulating runoff generation. Simulations are produced by the grid- and subbasin-based Community Land Model (CLM) at 0.125o, 0.25o, 0.5o and 1o spatial resolutions over the U.S. Pacific Northwest. Using the 0.125o simulation as the "reference" solution, statistical metrics are calculated by comparing simulations at 0.25o, 0.5o and 1o resolutions with the 0.125o simulation aggregated to the respective resolutions for each approach. Statistical significance test results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o resolutions compared to the 0.125osimulation are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning because of scalability related to air temperature and surface elevation. Scalability of a topographic parameter used in runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes.

DOI: 10.1002/2013JD020493
Citation:
2014.  "Scalability of Grid- and Subbasin-Based Land Surface Modeling Frameworks for Hydrologic Simulations."  Scalability of Grid- and Subbasin-Based Land Surface Modeling Frameworks for Hydrologic Simulations 3116-3184.  https://doi.org/10.1002/2013JD020493.