Predicting Monsoon Floods in Rivers Embedding Wavelet Transform, Genetic Algorithm and Neural Network

Rajeev Sahay () and Ayush Srivastava ()

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2014, vol. 28, issue 2, 317 pages

Abstract: Monsoon floods are recurring hazards in most countries of South-East Asia. In this paper, a wavelet transform-genetic algorithm-neural network model (WAGANN) is proposed for forecasting 1-day-ahead monsoon river flows which are difficult to model as they are characterized by irregularly spaced spiky large events and sustained flows of varying duration. Discrete wavelet transform (DWT) is employed for preprocessing the time series and genetic algorithm (GA) for optimizing the initial parameters of an artificial neural network (ANN) prior to the network training. Depending on different inputs, four WAGANN models are developed and evaluated for predicting flows in two Indian Rivers, the Kosi and the Gandak. These rivers are infamous for carrying large flows during monsoon (June to Sept), making the entire North Bihar of India unsafe for habitation or cultivation. When compared, WAGANN models are found to be better than autoregression models (ARs) and GA-optimized ANN models (GANNs) which use original flow time series (OFTS) for inputs, in simulating river flows during monsoon. In addition, WAGANN models predicted relatively reasonable estimates for the extreme flows, showing little bias for underprediction or overprediction. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: ANN; Autoregression; Flood forecasting; India; Rivers; Wavelet transform (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11269-013-0446-5 (text/html)
Access to full text is restricted to subscribers.

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:28:y:2014:i:2:p:301-317

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

DOI: 10.1007/s11269-013-0446-5

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 ().