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Proceedings of Fifth International Conference on Soft Computing for Problem Solving pp 691–710Cite as

A Broad Literature Survey of Development and Application of Artificial Neural Networks in Rainfall-Runoff Modelling

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 437))

Abstract

Rainfall-Runoff (R-R) modelling is one of the most important and challenging work in the real and present world. In all-purpose, rainfall, temperature, soil moisture and infiltration are highly nonlinear and complicated parameters. These parameters have been used in R-R modelling and this modelling requires highly developed techniques and simulation for accurate forecasting. An artificial neural network (ANN) is a successful technique and it has a capability to design R-R model but selection of appropriate architecture (model) of ANN is most important challenge. To determine the significant development and application of artificial neural network in R-R modelling, a broad literature survey last 35 years (from 1979 to 2014) is done and results are presented in this survey paper. It is concluded that the architectures of ANN, such as back propagation neural network (BPN), radial basis function (RBF), and fuzzy neural network (FNN) are better evaluated over the conceptual and numerical method and worldwide recognized to be modelled the R-R.

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Acknowledgments

We are thankful to India Meteorological Department Pune, India, State Data Center, Raipur, Chhattisgarh, and Bhilai Institute of Technology, Durg, Chhattisgarh, India.

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Authors and Affiliations

  1. Research Center, Bhilai Institute of Technology, Durg, CG, India

    Pradeep Kumar Mishra

  2. Department of Master of Computer Application, Bhilai Institute of Technology, Durg, CG, India

    Sanjeev Karmakar

  3. India Meteorological Department (IMD), Pune, India

    Pulak Guhathakurta

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  1. Pradeep Kumar Mishra
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  2. Sanjeev Karmakar
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  3. Pulak Guhathakurta
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Correspondence to Pradeep Kumar Mishra or Sanjeev Karmakar .

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Editors and Affiliations

  1. Dept of Applied Sci & Eng, Indian Instit of Tech Roorkee, Roorkee, India

    Millie Pant

  2. Department of Mathematics, Indian Inst of Tech Roorkee, Roorkee, India

    Kusum Deep

  3. Dept of Mathematics, South Asian University New Delhi, New Delhi, India

    Jagdish Chand Bansal

  4. Department of Mathematics and Comp Sci, Liverpool Hope University, LIVERPOOL, United Kingdom

    Atulya Nagar

  5. Department of Mathematics, National Inst of Tech Silchar, Silchar, Assam, India

    Kedar Nath Das

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Mishra, P.K., Karmakar, S., Guhathakurta, P. (2016). A Broad Literature Survey of Development and Application of Artificial Neural Networks in Rainfall-Runoff Modelling. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 437. Springer, Singapore. https://doi.org/10.1007/978-981-10-0451-3_62

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  • DOI: https://doi.org/10.1007/978-981-10-0451-3_62

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