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| Titel |
Role of climate forecasts and initial conditions in developing streamflow and soil moisture forecasts in a rainfall–runoff regime |
| VerfasserIn |
T. Sinha, A. Sankarasubramanian |
| 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 ; 17, no. 2 ; Nr. 17, no. 2 (2013-02-20), S.721-733 |
| Datensatznummer |
250017720
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| Publikation (Nr.) |
 copernicus.org/hess-17-721-2013.pdf |
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| Zusammenfassung |
| Skillful seasonal streamflow forecasts obtained from climate and land
surface conditions could significantly improve water and energy management.
Since climate forecasts are updated on a monthly basis, we evaluate the
potential in developing operational monthly streamflow forecasts on a
continuous basis throughout the year. Further, basins in the rainfall–runoff
regime critically depend on the forecasted precipitation in the upcoming
months as opposed to snowmelt regimes where initial hydrological conditions
(IHC) play a critical role. The goal of this study is to quantify the role
of updated monthly precipitation forecasts and IHC in forecasting 6-month
lead monthly streamflow and soil moisture for a rainfall–runoff mechanism
dominated basin – Apalachicola River at Chattahoochee, FL. The Variable
Infiltration Capacity (VIC) land surface model is implemented with two
forcings: (a) updated monthly precipitation forecasts from ECHAM4.5
Atmospheric General Circulation Model (AGCM) forced with sea surface
temperature forecasts and (b) daily climatological ensembles. The difference
in skill between the above two quantifies the improvements that could be
attainable using the AGCM forecasts. Monthly retrospective streamflow
forecasts are developed from 1981 to 2010 and streamflow forecasts estimated
from the VIC model are also compared with those predicted by using the
principal component regression (PCR) model. The mean square error (MSE) in
predicting monthly streamflows, using the VIC model, are compared with
the MSE of streamflow climatology under ENSO (El Niño Southern Oscilation) conditions as well as under
normal years. Results indicate that VIC forecasts obtained using ECHAM4.5
are significantly better than VIC forecasts obtained using climatological ensembles
and PCR models over 2–6 month lead time during winter and spring seasons
in capturing streamflow variability and reduced mean square errors. However, at 1-month lead time, streamflow
utilizing the climatological forcing scheme outperformed ECHAM4.5 based
streamflow forecasts during winter and spring, indicating a dominant role of
IHCs up to a 1-month lead time. During ENSO years, streamflow forecasts
exhibit better skill even up to a six-month lead time. Comparisons of the
seasonal soil moisture forecasts, developed using ECHAM4.5 forcings, with
seasonal streamflows also show significant skill, up to a 6-month lead time,
in the four seasons. |
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