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Water Resources Management

, Volume 32, Issue 8, pp 2701–2716 | Cite as

Flow Forecasting in a Watershed using Autoregressive Updating Model

  • Shirisha Pulukuri
  • Venkata Reddy Keesara
  • Pratap Deva
Article
  • 88 Downloads

Abstract

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.

Keywords

Autoregressive model Flow Forecast Lead Event based Runoff Model Error Updating Algorithm 

Notes

Acknowledgements

Authors are thankful to the DST-WTI, India for the financial assistance to carry out this work through project no. DST/TM/WTI/2 K12/47(G). Authors are thankful to Mr. Guy Honore, Project coordinator, Indo German Bilateral Project, for providing data of Banha, Harsul and Khadakohol watersheds through project no. 03IS007.

Funding

The research described in this paper was funded by DST-WTI, India through project no. DST/TM/WTI/2 K12/47(G).

Compliance with ethical standards

Conflict of Interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Shirisha Pulukuri
    • 1
  • Venkata Reddy Keesara
    • 1
  • Pratap Deva
    • 1
  1. 1.National Institute of Technology Warangal (NITW)WarangalIndia

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