Real-Time Flow Forecasting in a Watershed Using Rainfall Forecasting Model and Updating Model

P. Shirisha (), K. Venkata Reddy and Deva Pratap
Additional contact information
P. Shirisha: NIT Warangal
K. Venkata Reddy: NIT Warangal
Deva Pratap: NIT Warangal

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2019, vol. 33, issue 14, No 9, 4799-4820

Abstract: Abstract Watershed is the basic unit for studying different hydrologic processes. Flow forecasting in a watershed is dependent upon the rainfall. The effect of erroneous rainfall prediction is a source of uncertainty in flow forecasting. In this study, a model is proposed to improve the flow forecasting on real-time basis. The proposed model has three components (1) Adaptive Grey Rainfall Forecasting Model, (2) Rainfall-Runoff Model and (3) Fuzzy Updating Model. The proposed forecasting model is tested for lead periods of 1 to 3 h with hourly rainfall and discharge data. In this study, four different cases using combination of three models are discussed and the results are compared. The study has been carried out on three Indian watersheds namely Banha, Harsul and Khadakohol. The performance of the model is measured using Nash Sutcliffe Efficiency (E), Correlation Coefficient (r), Error of Peak Discharge (EQpeak) and Error of Time to Peak (ETpeak). It is observed that the case with integration of all three models performed good with a forecasting efficiency of E = 0.950, 0.861, 0.564; and r = 0.991, 0.972, 0.897 for lead-1, 2, 3 respectively for Banha watershed. For Harsul watershed, E = 0.898, 0.704, 0.367; and r = 0.985, 0.949, 0.834 for lead-1, 2, 3 respectively. For Khadakohol watershed, E = 0.968, 0.932, 0.787; and r = 0.994, 0.987, 0.951 for lead-1, 2, 3 respectively. EQpeak is less than 10% for lead-1 for most of the events and increased slightly for lead-2 and lead-3. ETpeak is 0 h for all lead periods of the three watersheds. The proposed model is useful for farmers in planning and monitoring of water resources for crop management and helps in taking necessary actions during heavy rains and floods.

Keywords: Grey model; Real-time forecasting; Runoff model; Updating model; Watershed (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s11269-019-02398-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:33:y:2019:i:14:d:10.1007_s11269-019-02398-2

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-019-02398-2

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().