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ANN Modeling of Groundwater Development for Irrigation

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Groundwater and Water Quality

Part of the book series: Water Science and Technology Library ((WSTL,volume 119))

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Abstract

The groundwater level is required to keep within the permissible limit for sustainable groundwater development in any area. In the present study, an Artificial Neural Network (ANN) model has been developed for groundwater development with respect to state variables of a groundwater system, i.e., a maximum depth to water table for agricultural purposes. The zonal cropping areas are considered as inputs to the ANN model. The methodology has been illustrated in the Yamuna-Hindon Inter basin, India. The ANN model is performed for two different training algorithms like (i) Levenberg–Marquardt (LM) and (ii) Bayesian regularization (BR) and their performance was compared with the backpropagation (BP) algorithm. The prediction accuracy of both algorithms was tested using performance indices viz. mean square error (MSE), root mean square error (RMSE), and correlation coefficient (R2). The performance of both the ANN training algorithms in predicting maximum depth to water table over the study area was found to be almost similarly good. However, the performance of the LM algorithm was found slightly superior to that of the BR algorithm as well as the BP algorithm.

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Author information

Authors and Affiliations

  1. NIT Silchar, Silchar, India

    Pritam Malakar

  2. NIT Agartala, Agartala, India

    Pritam Malakar

  3. Civil Engineering Department, NIT Silchar, Silchar, India

    Susmita Ghosh

Authors
  1. Pritam Malakar
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  2. Susmita Ghosh
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Corresponding author

Correspondence to Susmita Ghosh .

Editor information

Editors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology, Patna, India

    Ramakar Jha

  2. Biol. & Agricultural Engineering, Texas A&M University, College Station, TX, USA

    Vijay P. Singh

  3. Department of Civil Engineering, National Institute of Technology Patna, Patna, India

    Vivekanand Singh

  4. Department of Civil Engineering, National Institute of Technology Patna, Patna, India

    L.B. Roy

  5. Department of Civil Engineering, National Institute of Technology Patna, Patna, India

    Roshni Thendiyath

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Malakar, P., Ghosh, S. (2022). ANN Modeling of Groundwater Development for Irrigation. In: Jha, R., Singh, V.P., Singh, V., Roy, L., Thendiyath, R. (eds) Groundwater and Water Quality. Water Science and Technology Library, vol 119. Springer, Cham. https://doi.org/10.1007/978-3-031-09551-1_10

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