Scalability of Grid- and Subbasin-based Land Surface Modeling Approaches for Hydrologic Simulations

TitleScalability of Grid- and Subbasin-based Land Surface Modeling Approaches for Hydrologic Simulations
Publication TypeJournal Article
Year of Publication2014
JournalJournal of Geophysical Research - Atmospheres
Date Published03/2014
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 at 0.125°, 0.25°, 0.5°, and 1° spatial resolutions over the U.S. Pacific Northwest. Using the 0.125° simulation as the "reference" solution, statistical metrics are calculated by comparing simulations at 0.25°, 0.5°, and 1° resolutions with the 0.125° simulation 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 0.25°, 0.5°, and 1° resolutions compared to the 0.125° simulation 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 multiscale modeling of hydrological processes.

DOI10.1002/2013JD020493
Journal: Journal of Geophysical Research - Atmospheres
Year of Publication: 2014
Date Published: 03/2014

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 at 0.125°, 0.25°, 0.5°, and 1° spatial resolutions over the U.S. Pacific Northwest. Using the 0.125° simulation as the "reference" solution, statistical metrics are calculated by comparing simulations at 0.25°, 0.5°, and 1° resolutions with the 0.125° simulation 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 0.25°, 0.5°, and 1° resolutions compared to the 0.125° simulation 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 multiscale modeling of hydrological processes.

DOI: 10.1002/2013JD020493
Citation:
Tesfa, TK, L Leung, M Huang, H Li, N Voisin, and MS Wigmosta.  2014.  "Scalability of Grid- and Subbasin-based Land Surface Modeling Approaches for Hydrologic Simulations."  Journal of Geophysical Research - Atmospheres.  https://doi.org/10.1002/2013JD020493.