There are increasing effects of climate change and growing urbanization on depleting freshwater supplies worldwide, making sustainable water reuse solutions critically necessary. Urban-origin treated wastewater offers a viable alternative source for agricultural irrigation; however, its application must be carefully managed to ensure safety and efficiency. This review explores cutting-edge methods and the integration of artificial intelligence (AI) to enhance the use of urban treated wastewater in farming. It reviews the latest advancements in treatment techniques such as membrane bioreactors, advanced oxidation processes, and eco-engineered systems, coupled with AI-based tools for forecasting water quality, optimizing irrigation schedules, and evaluating potential hazards. Predictive models using machine learning and deep learning have demonstrated considerable potential in anticipating contaminant removal rates, improving treatment operations, and maintaining compliance with irrigation standards. The review also highlights challenges, including limited datasets, model transparency, and regulatory considerations, emphasizing the necessity for cross-disciplinary collaboration. Collectively, applying AI alongside innovative wastewater management strategies can support sustainable water practices and foster climate-resilient agricultural systems.
| Primary Language | English |
|---|---|
| Subjects | Natural Resource Management |
| Journal Section | Review Article |
| Authors | |
| Submission Date | October 14, 2025 |
| Acceptance Date | November 30, 2025 |
| Early Pub Date | December 3, 2025 |
| Publication Date | December 28, 2025 |
| Published in Issue | Year 2025 Volume: 9 Issue: Special |
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