Flow Forecasting in a Watershed using Autoregressive Updating Model

• Published in: Water resources management Vol. 32; no. 8; pp. 2701 - 2716
• Main Authors: Pulukuri, Shirisha, Keesara, Venkata Reddy, Deva, Pratap
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2018; Springer Nature B.V
• Subjects: Atmospheric Sciences; Autoregressive models; Autoregressive processes; Civil Engineering; Computer simulation; correlation; Correlation coefficient; Correlation coefficients; Earth and Environmental Science; Earth Sciences; Environment; Finite element method; Forecasting; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology; hydrologic models; Hydrology/Water Resources; India; Lead time; Model accuracy; Model testing; Rain; Rainfall; Rainfall-runoff relationships; Real time; Runoff; Watersheds; India; Lead; Error Updating Algorithm; Flow Forecast; Autoregressive model; Event based Runoff Model
• ISSN: 0920-4741; 1573-1650
• DOI: 10.1007/s11269-018-1953-1

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.