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Managing and protecting this crucial resource has become even more difficult due to industrialization and agricultural and urban hazards such as direct groundwater pollution. For many environmental factors, conditions complicating heterogeneity and instability hinder the application of conventional ΓΜ techniques to pollute groundwater. AI and ML-integrated solutions provide unprecedented solutions to these challenges with better means of predicting, detecting, and managing contaminated water sources. More specifically, this chapter discusses how advanced technologies such as AI and ML are integrated into efforts to regulate contamination in groundwater and improve its management. It equally examines different types of AI-based models applicable to risk estimation of contamination, effective pollution interventions, and enhanced organizational decisions. Furthermore, the chapter presents successful examples of AI and ML applications for monitoring groundwater quality, identifying pollution sources, and developing sustainable management strategies. In this chapter, the authors demonstrate how AI and ML technologies can change the approach to groundwater pollution prevention and the management of water resources.

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Artificial Intelligence and Machine Learning Applications in Groundwater Pollution Control and Resource Management

  • 章节

  • 发表日期：

    2025年

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  • A. Saranya,
  • Vedprakash Maralapalle,
  • Aijaz Ahmad Zende,
  • Shital Marlapalle,
  • Rajiv Iyer

摘要

Managing and protecting this crucial resource has become even more difficult due to industrialization and agricultural and urban hazards such as direct groundwater pollution. For many environmental factors, conditions complicating heterogeneity and instability hinder the application of conventional ΓΜ techniques to pollute groundwater. AI and ML-integrated solutions provide unprecedented solutions to these challenges with better means of predicting, detecting, and managing contaminated water sources. More specifically, this chapter discusses how advanced technologies such as AI and ML are integrated into efforts to regulate contamination in groundwater and improve its management. It equally examines different types of AI-based models applicable to risk estimation of contamination, effective pollution interventions, and enhanced organizational decisions. Furthermore, the chapter presents successful examples of AI and ML applications for monitoring groundwater quality, identifying pollution sources, and developing sustainable management strategies. In this chapter, the authors demonstrate how AI and ML technologies can change the approach to groundwater pollution prevention and the management of water resources.