Flow Forecasting in a Watershed using Autoregressive Updating Model
A real-time autoregressive updating model is proposed in this study to forecast the flow in a watershed. The model has two components: (1) Finite Element-Event based distributed rainfall runoff model for runoff simulation and (2) Autoregressive model for updating the error forecast. The efficiency o...
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Veröffentlicht in: | Water resources management 2018-06, Vol.32 (8), p.2701-2716 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | A real-time autoregressive updating model is proposed in this study to forecast the flow in a watershed. The model has two components: (1) Finite Element-Event based distributed rainfall runoff model for runoff simulation and (2) Autoregressive model for updating the error forecast. The efficiency of the runoff updating model depends on the accuracy of the rainfall. Forecasting plays a major role in view of the lead time. In the present study, forecasting is carried out with a lead period of 1 to 3 h. The performance of the integrated model is tested using Nash Sutcliffe efficiency (E) and correlation coefficient (r). The integrated model is applied for Banha, Harsul and Khadakohol watersheds in India. From the results, it can be concluded that the developed model is efficient in flow forecasting on real-time basis in the watersheds. |
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ISSN: | 0920-4741 1573-1650 |
DOI: | 10.1007/s11269-018-1953-1 |