Civil Engineering
Computational approaches for annual maximum river flow series

https://doi.org/10.1016/j.asej.2015.07.016Get rights and content
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Abstract

Studies of annual peak discharge and its temporal variations are widely used in the planning and decision making process of water resources management. Very recently, soft computing techniques are gaining ground for time series analysis of hydrological events such as rainfall and runoff. In this study Artificial Neural Network (ANN) has been used in combination with wavelet to model the annual maximum flow discharge of rivers. The results of ANN-Wavelet (WANN) model indicate overall low coherence (R2 = 0.39) better than ANN (R2 = 0.31) in isolation. In the present analysis, the authors also conceded a probabilistic distributional analysis of river flow time series which has greater potential to better reflect peak flow dynamics. The results highlight that the overall performance of probability distribution models is superior to WANN model. Instead of that WANN is better than probabilistic models to find the global maxima of the series.

Keywords

Probability
Wavelet
ANN
Kosi
Peak discharge

Cited by (0)

Mr. Harinarayan Tiwari is Research Scholar in Department of Water Resources Development & Management, IIT Roorkee. He did his B.Sc. (Civil Engg.) (Hons.) in BIT Sindri (Jharkhand) in 2009 and M.Tech. from Department of Water Resources Development & Management, IIT Roorkee in 2012. He has to credit six research projects with 28 (16 published +12 communicated) papers in national-international journals and conferences. He got four awards during his M.Tech. in IIT Roorkee.

Mr. Subash Pd. Rai is Research Scholar in Department of Water Resources Development & Management, IIT Roorkee. He did his B.Tech. (Civil Engg.) in BIT Sindri (Jharkhand) in 2012 and M.Tech. from Department of Water Resources Development & Management, IIT Roorkee in 2014. He has to credit two research projects with four papers in international journals and conferences.

Mr. Nayan Sharma is Professor in Dept. of Water Resources Development & Management, IIT Roorkee. Prof. Sharma has acquired wide-ranging academic as well as professional field experience in diverse disciplines of WRDM namely river engineering; mathematical and physical modeling of large alluvial streams and irrigation canal systems; hydraulic structures for hydro power and irrigation systems; and remote sensing applications for river morphology and flood-plain studies. In course of last 29 years with IIT-Roorkee, Prof. Sharma has been the supervisor of 18 Ph.D. theses. He has to credit 115 research publications in national and international journals and reputed conference proceedings.

Mr. Dheeraj Kumar is Research Scholar in Department of Water Resources Development & Management, IIT Roorkee. He has a credit of eight research/consultancy projects with fourteen papers in national-international journals and conferences.

Peer review under responsibility of Ain Shams University.

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