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| Titel |
Predictability of Western Himalayan river flow: melt seasonal inflow into Bhakra Reservoir in northern India |
| VerfasserIn |
I. Pal, U. Lall, A. W. Robertson, M. A. Cane, R. Bansal |
| 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. 6 ; Nr. 17, no. 6 (2013-06-05), S.2131-2146 |
| Datensatznummer |
250018894
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| Publikation (Nr.) |
 copernicus.org/hess-17-2131-2013.pdf |
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| Zusammenfassung |
| Snowmelt-dominated streamflow of the Western Himalayan rivers is an
important water resource during the dry pre-monsoon spring months to meet
the irrigation and hydropower needs in northern India. Here we study the
seasonal prediction of melt-dominated total inflow into the Bhakra Dam in
northern India based on statistical relationships with meteorological
variables during the preceding winter. Total inflow into the Bhakra Dam
includes the Satluj River flow together with a flow diversion from its
tributary, the Beas River. Both are tributaries of the Indus River that
originate from the Western Himalayas, which is an under-studied region.
Average measured winter snow volume at the upper-elevation stations and
corresponding lower-elevation rainfall and temperature of the Satluj River
basin were considered as empirical predictors. Akaike information criteria
(AIC) and Bayesian information criteria (BIC) were used to select the best
subset of inputs from all the possible combinations of predictors for a
multiple linear regression framework. To test for potential issues arising
due to multicollinearity of the predictor variables, cross-validated
prediction skills of the best subset were also compared with the prediction
skills of principal component regression (PCR) and partial least squares
regression (PLSR) techniques, which yielded broadly similar results. As a
whole, the forecasts of the melt season at the end of winter and as the melt
season commences were shown to have potential skill for guiding the
development of stochastic optimization models to manage the trade-off
between irrigation and hydropower releases versus flood control during the
annual fill cycle of the Bhakra Reservoir, a major energy and irrigation
source in the region. |
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