Abstract
The Mahanadi River basin is one of the biggest basins of India and serves as a lifeline for the region it passes through. However, the region often experiences an erratic rainfall and climate condition which affects the livelihoods of the people living nearby. Aiming to solve this problem, a novel approach is illustrated in this paper. Application of artificial neural network is a popular technique for prediction of various hydrological parameters as it provides fairly correct results. Here, an attempt has been made to incorporate wavelet transform in ANN, also known as wavelet artificial neural network (W-ANN), to further increase its scope and efficacy. The results were then evaluated using well-known statistical indices. It was concluded that W-ANN has better forecasting capacity than simple ANN model and it can be implemented for prediction of monthly runoff in similar basins and reservoirs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Sahoo, A., Samantaray, S., Ghose, D.K.: Multilayer perceptron and support vector machine trained with grey wolf optimiser for predicting floods in Barak river, India. J. Earth Syst. Sci. 131(2), 1–23 (2022)
Agnihotri, A., Sahoo, A., Diwakar, M.K.: Flood prediction using hybrid ANFIS-ACO model: a case study. In: Inventive Computation and Information Technologies, pp. 169–180. Springer, Singapore (2022)
Samantaray, S., Sumaan, P., Surin, P., Mohanta, N.R., Sahoo, A.: Prophecy of groundwater level using hybrid ANFIS-BBO approach. In: Proceedings of International Conference on Data Science and Applications, pp. 273–283. Springer, Singapore (2022)
Mohanta, N.R., Panda, S.K., Singh, U.K., Sahoo, A., Samantaray, S.: MLP-WOA is a successful algorithm for estimating sediment load in Kalahandi Gauge Station, India. In: Proceedings of International Conference on Data Science and Applications, pp. 319–329. Springer, Singapore (2022)
Sridharam, S., Sahoo, A., Samantaray, S., Ghose, D.K.: Assessment of flow discharge in a river basin through CFBPNN, LRNN and CANFIS. In: Communication Software and Networks, pp. 765–773. Springer, Singapore (2021)
Tokar, A.S., Johnson, P.A.: Rainfall-runoff modelling using artificial neural networks. J. Hydrol. Eng. 232–239 (1999)
Tokar, A.S., Markus, M.: Precipitation-runoff modelling using artificial neural networks and conceptual models. J. Hydrol. Eng. 156–161 (2000)
Ahmadi, M., et al.: Comparison of the performance of SWAT, IHACRES and artificial neural networks models in rainfall-runoff simulation (case study: Kan watershed, Iran). J. Phys. Chem. Earth 65–77 (2019)
Poonia, V., Tiwari, H.L.: Rainfall-runoff modeling for the Hoshangabad basin of Narmada river using artificial neural network. Arab. J. Geosci. 13 (2020)
Mao, G., et al.: Comprehensive comparison of artificial neural networks and long short-term memory networks for rainfall-runoff simulation. J. Phys. Chem. Earth 103026 (2021)
Mitra, S., Nigam, R.: An approach to utilize artificial neural network for runoff prediction: river perspective. J. Mater. Today: Proc. (2021)
Rajaee, T.: Wavelet and ANN combination model for prediction of daily suspended sediment load in rivers. J. Sci. Total Environ. 409, 2917–2928 (2011)
Abghari, H., et al.: Prediction of daily pan evaporation using wavelet neural networks. J. Water Resour. Manag. 26, 3639–3652 (2012)
Venkata Ramana R., et al.: Monthly rainfall prediction using wavelet neural network analysis. J. Water Resour. Manag. 27, 3697–3711 (2013)
Ravansalar, M., Rajaee, T.: Evaluation of wavelet performance via an ANN-based electrical conductivity prediction model. J. Environ. Monit. Assess. 187 (2015)
Shafaei, M., Kisi, O.: Predicting river daily flow using wavelet-artificial neural networks based on regression analyses in comparison with artificial neural networks and support vector machine models. J. Neural Comput. Appl. 28, 15–28 (2017)
Sharghi, E., et al.: Emotional ANN (EANN) and wavelet-ANN (WANN) approaches for Markovian and seasonal based modeling of rainfall-runoff process. J. Water Resour. Manag. 32, 3441–3456 (2018)
Jimmy, S.R., Sahoo, A., Samantaray, S., Ghose, D.K.: Prophecy of runoff in a river basin using various neural networks. In: Communication Software and Networks, pp. 709–718. Springer, Singapore (2021)
Sahoo, A., Samantaray, S., Paul, S.: Efficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India. H2Open J. 4(1), 137–156 (2021)
Mohanta, N.R., Patel, N., Beck, K., Samantaray, S., Sahoo, A.: Efficiency of river flow prediction in river using wavelet-CANFIS: a case study. In: Intelligent Data Engineering and Analytics, pp. 435–443. Springer, Singapore (2021)
Samantaray, S., Sahoo, A., Agnihotri, A.: Assessment of flood frequency using statistical and hybrid neural network method: Mahanadi river basin, India. J. Geol. Soc. India 97(8), 867–880 (2021)
Samantaray, S., Biswakalyani, C., Singh, D.K., Sahoo, A., Prakash Satapathy, D.: Prediction of groundwater fluctuation based on hybrid ANFIS-GWO approach in arid Watershed, India. Soft Comput 1–23 (2022)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sahoo, G.K., Mishra, A., Panda, D.P., Sahoo, A., Samantaray, S., Satapathy, D.P. (2023). Simulation of Monthly Runoff in Mahanadi Basin with W-ANN Approach. In: Bhateja, V., Yang, XS., Lin, J.CW., Das, R. (eds) Evolution in Computational Intelligence. FICTA 2022. Smart Innovation, Systems and Technologies, vol 326. Springer, Singapore. https://doi.org/10.1007/978-981-19-7513-4_44
Download citation
DOI: https://doi.org/10.1007/978-981-19-7513-4_44
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-7512-7
Online ISBN: 978-981-19-7513-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)