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| Titel |
Climate information based streamflow and rainfall forecasts for Huai River basin using hierarchical Bayesian modeling |
| VerfasserIn |
X. Chen, Z. Hao, N. Devineni, U. Lall |
| 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. 4 ; Nr. 18, no. 4 (2014-04-29), S.1539-1548 |
| Datensatznummer |
250120341
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| Publikation (Nr.) |
 copernicus.org/hess-18-1539-2014.pdf |
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| Zusammenfassung |
| A Hierarchal Bayesian model is presented for one season-ahead forecasts of
summer rainfall and streamflow using exogenous climate variables for east
central China. The model provides estimates of the posterior forecasted
probability distribution for 12 rainfall and 2 streamflow stations
considering parameter uncertainty, and cross-site correlation. The model has
a multi-level structure with regression coefficients modeled from a common
multi-variate normal distribution resulting in partial pooling of information
across multiple stations and better representation of parameter and
posterior distribution uncertainty. Covariance structure of the residuals
across stations is explicitly modeled. Model performance is tested under
leave-10-out cross-validation. Frequentist and Bayesian performance metrics
used include receiver operating characteristic, reduction of error,
coefficient of efficiency, rank probability skill scores, and coverage by
posterior credible intervals. The ability of the model to reliably forecast season-ahead
regional summer rainfall and streamflow offers potential for
developing adaptive water risk management strategies. |
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