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A Bayesian Hierarchical Model Combination Framework for Real‐Time Daily Ensemble Streamflow Forecasting Across a Rainfed River Basin
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2022
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Source: Earth's Future, 10(12)
[PDF-4.72 MB]
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Journal Title:Earth's Future
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Description:The frequent occurrence of floods during the rainy season is one of the threats in rainfed river basins, especially in river basins of India. This study implemented a Bayesian hierarchical model combination (BHMC) framework to generate skillful and reliable real-time daily ensemble streamflow forecast and peak flow and demonstrates its utility in the Narmada River basin in Central India for the peak monsoon season (July–August). The framework incorporates information from multiple sources (e.g., deterministic hydrological forecast, meteorological forecast, and observed data) as predictors. The forecasts were validated with a leave-1-year-out cross-validation using accuracy metrics such as BIAS and Pearson correlation coefficient ( R)
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Source:Earth's Future, 10(12)
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DOI:
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ISSN:2328-4277;2328-4277;
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Rights Information:CC BY
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Compliance:Library
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