Flow Forecasting in a Watershed using Autoregressive Updating Model

Shirisha Pulukuri (), Venkata Reddy Keesara and Pratap Deva
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Shirisha Pulukuri: National Institute of Technology Warangal (NITW)
Venkata Reddy Keesara: National Institute of Technology Warangal (NITW)
Pratap Deva: National Institute of Technology Warangal (NITW)

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2018, vol. 32, issue 8, No 9, 2716 pages

Abstract: 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 (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11269-018-1953-1

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