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| Titel |
Calibration and evaluation of a semi-distributed watershed model of Sub-Saharan Africa using GRACE data |
| VerfasserIn |
H. Xie, L. Longuevergne, C. Ringler, B. R. Scanlon |
| 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 ; 16, no. 9 ; Nr. 16, no. 9 (2012-09-03), S.3083-3099 |
| Datensatznummer |
250013455
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| Publikation (Nr.) |
 copernicus.org/hess-16-3083-2012.pdf |
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| Zusammenfassung |
| Irrigation development is rapidly expanding in mostly rainfed Sub-Saharan
Africa. This expansion underscores the need for a more comprehensive
understanding of water resources beyond surface water. Gravity Recovery and
Climate Experiment (GRACE) satellites provide valuable information on
spatio-temporal variability in water storage. The objective of this study
was to calibrate and evaluate a semi-distributed regional-scale hydrologic
model based on the Soil and Water Assessment Tool (SWAT) code for basins in
Sub-Saharan Africa using seven-year (July 2002–April 2009) 10-day GRACE data
and multi-site river discharge data. The analysis was conducted in a
multi-criteria framework. In spite of the uncertainty arising from the
tradeoff in optimising model parameters with respect to two
non-commensurable criteria defined for two fluxes, SWAT was found to perform
well in simulating total water storage variability in most areas of
Sub-Saharan Africa, which have semi-arid and sub-humid climates, and that
among various water storages represented in SWAT, water storage variations
in soil, vadose zone and groundwater are dominant. The study also showed
that the simulated total water storage variations tend to have less
agreement with GRACE data in arid and equatorial humid regions, and
model-based partitioning of total water storage variations into different
water storage compartments may be highly uncertain. Thus, future work will
be needed for model enhancement in these areas with inferior model fit and
for uncertainty reduction in component-wise estimation of water storage
variations. |
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