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| Titel |
Hydroclimatology of Lake Victoria region using hydrologic model and satellite remote sensing data |
| VerfasserIn |
S. I. Khan, P. Adhikari, Y. Hong, H. Vergara, R. F. Adler, F. Policelli, D. Irwin, T. Korme, L. Okello |
| 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 ; 15, no. 1 ; Nr. 15, no. 1 (2011-01-14), S.107-117 |
| Datensatznummer |
250012589
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| Publikation (Nr.) |
 copernicus.org/hess-15-107-2011.pdf |
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| Zusammenfassung |
| Study of hydro-climatology at a range of temporal scales is important in
understanding and ultimately mitigating the potential severe impacts of
hydrological extreme events such as floods and droughts. Using daily in-situ
data over the last two decades combined with the recently available
multiple-years satellite remote sensing data, we analyzed and simulated,
with a distributed hydrologic model, the hydro-climatology in Nzoia, one of
the major contributing sub-basins of Lake Victoria in the East African
highlands. The basin, with a semi arid climate, has no sustained base flow
contribution to Lake Victoria. The short spell of high discharge showed that
rain is the prime cause of floods in the basin. There is only a marginal
increase in annual mean discharge over the last 21 years. The 2-, 5- and 10-
year peak discharges, for the entire study period showed that more years
since the mid 1990's have had high peak discharges despite having relatively
less annual rain. The study also presents the hydrologic model calibration
and validation results over the Nzoia basin. The spatiotemporal variability
of the water cycle components were quantified using a hydrologic model, with
in-situ and multi-satellite remote sensing datasets. The model is calibrated
using daily observed discharge data for the period between 1985 and 1999,
for which model performance is estimated with a Nash Sutcliffe Efficiency
(NSCE) of 0.87 and 0.23% bias. The model validation showed an error
metrics with NSCE of 0.65 and 1.04% bias. Moreover, the hydrologic
capability of satellite precipitation (TRMM-3B42 V6) is evaluated. In terms
of reconstruction of the water cycle components the spatial distribution and
time series of modeling results for precipitation and runoff showed
considerable agreement with the monthly model runoff estimates and gauge
observations. Runoff values responded to precipitation events that occurred
across the catchment during the wet season from March to early June. The
spatially distributed model inputs, states, and outputs, were found to be
useful for understanding the hydrologic behavior at the catchment scale. The
monthly peak runoff is observed in the months of April, May and November.
The analysis revealed a linear relationship between rainfall and runoff for
both wet and dry seasons. Satellite precipitation forcing data showed the
potential to be used not only for the investigation of water balance but
also for addressing issues pertaining to sustainability of the resources at
the catchment scale. |
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