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A Survey of Machine and Deep Learning Applications in the Assessment of Water Quality

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Technical and Technological Solutions Towards a Sustainable Society and Circular Economy

Part of the book series: World Sustainability Series ((WSUSE))

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Abstract

Actually, water is an important resource in different domains namely farming, healthcare and tourism, as well as in industry. Every living being is depending on adequate amounts of good quality water for its survival and development. The global water system is driven by both evaporation and transpiration, as well as condensation, rainfall and runoff, and typically reaches the ocean. Predicting water quality based on different parameters is essential for the design, decision making and management of this resource. Over the past two decades, water quality modeling has enjoyed considerable growth through the implementation of machine learning techniques. This review examines the various supervised, unsupervised, semi-supervised, and ensemble machine learning models implemented for the prediction of groundwater quality parameters. Furthermore, this study listed some water domains where machine learning is used to predict and monitor water quality.

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Authors and Affiliations

  1. STI Laboratory, IDMS Team, Faculty of Sciences and Techniques, Moulay Ismail University of Meknes, Errachidia, Morocco

    Mourade Azrour & Souhayla Dargaoui

  2. Laboratory of Spectroscopy, Molecular Modeling, Materials, Nanomaterials, Water and Environment, Faculty of Science, CERNE2D, Mohammed V University, Rabat, Morocco

    Jamal Mabrouki

  3. Technology Higher School Essaouira, Cadi Ayyad University, Marrakesh, Morocco

    Azidine Guezzaz & Said Benkirane

  4. Digital Connectivity Research Laboratory, P. O. Box. 600040, Kampala, Uganda

    Wasswa Shafik

  5. School of Digital Science, Universiti Brunei Darussalam, Jalan Tungku Link, Gadong, 1410, Brunei

    Wasswa Shafik

  6. Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia

    Sultan Ahmad

  7. University Center for Research and Development (UCRD), Department of Computer Science and Engineering, Chandigarh University, Gharuan, Mohali, Punjab, 140413, India

    Sultan Ahmad

Authors
  1. Mourade Azrour
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  2. Souhayla Dargaoui
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  3. Jamal Mabrouki
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  4. Azidine Guezzaz
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  5. Said Benkirane
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  6. Wasswa Shafik
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  7. Sultan Ahmad
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Correspondence to Mourade Azrour .

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Editors and Affiliations

  1. Faculty of Science, Mohammed V University in Rabat, Rabat, Morocco

    Jamal Mabrouki

  2. Computer Sciences Department, Moulay Ismail University of Meknes, Meknes, Morocco

    Azrour Mourade

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Azrour, M. et al. (2024). A Survey of Machine and Deep Learning Applications in the Assessment of Water Quality. In: Mabrouki, J., Mourade, A. (eds) Technical and Technological Solutions Towards a Sustainable Society and Circular Economy. World Sustainability Series. Springer, Cham. https://doi.org/10.1007/978-3-031-56292-1_38

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