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| Titel |
A large-scale, high-resolution hydrological model parameter data set for climate change impact assessment for the conterminous US |
| VerfasserIn |
A. A. Oubeidillah, S.-C. Kao, M. Ashfaq, B. S. Naz, G. Tootle |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 18, no. 1 ; Nr. 18, no. 1 (2014-01-07), S.67-84 |
| Datensatznummer |
250120245
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| Publikation (Nr.) |
 copernicus.org/hess-18-67-2014.pdf |
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| Zusammenfassung |
| To extend geographical coverage, refine spatial resolution, and improve
modeling efficiency, a computation- and data-intensive effort was conducted
to organize a comprehensive hydrologic data set 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 US at refined 1/24°
(~4 km) spatial resolution. Using high-performance computing
for intensive model calibration, a high-resolution parameter data set 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 US Geological Survey (USGS) WaterWatch monthly runoff observations for
each HUC8. The results showed that this new parameter data set 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 US. We anticipate that through this hydrologic
parameter data set, 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
data set will be provided to interested parties to support further
hydro-climate impact assessment. |
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