A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

Oubeidillah, Abdoul A.; Kao, Shih-Chieh; Ashfaq, Moetasim; Naz, Bibi S.; Tootle, Glenn

doi:10.5194/hess-18-67-2014

Title: A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

Journal Article · Wed Jan 01 00:00:00 EST 2014 · Hydrology and Earth System Sciences (Online)

DOI:https://doi.org/10.5194/hess-18-67-2014· OSTI ID:1114266

Oubeidillah, Abdoul A. ^[1];

^[1];

^[1]; Naz, Bibi S. ^[1]; Tootle, Glenn ^[2]

ORNL
University of Alabama, Tuscaloosa

To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation—including meteorologic forcings, soil, land class, vegetation, and elevation—were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24° (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VIC simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.

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Research Organization:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

DOE Contract Number:: AC05-00OR22725

OSTI ID:: 1114266

Journal Information:: Hydrology and Earth System Sciences (Online), Vol. 18, Issue 1; ISSN 1607-7938

Country of Publication:: United States

Language:: English

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