Artificial Intelligence for Sustainable Water Management: Opportunities, Technologies, and Environmental Trade-offs

Virang Talesara

doi:10.36948/ijfmr.2026.v08i04.83465

Artificial Intelligence for Sustainable Water Management: Opportunities, Technologies, and Environmental Trade-offs

Author(s)	Mr. Virang Talesara
Country	India
Abstract	Water scarcity is one of the major resource challenges of the twenty-first century. Agriculture alone accounts for roughly 70 percent of global freshwater withdrawals, and a significant proportion of that water is lost before reaching plant roots through evaporation, runoff, and inefficient delivery. Urban distribution networks add to the problem: treated water leaks silently through ageing pipes, never reaching consumers. With global food production needing to increase by 70 percent by 2050 to feed a projected population of 9.1 billion, the strain on already-limited freshwater reserves will intensify unless efficiency improves substantially. This review examines how artificial intelligence (AI), the Internet of Things (IoT), unmanned aerial vehicles (UAVs), and digital-twin modelling are being applied across two domains: precision agriculture and urban water infrastructure. In agriculture, AI-driven irrigation, soil-moisture sensing, and UAV-based crop monitoring have produced documented water savings of 30 to 70 percent alongside yield improvements of 20 to 30 percent. In cities, smart metering and AI-based leak detection have measurably reduced water losses in deployed systems across Spain, the United Kingdom, and the United States. The review also examines a less-discussed counterpart: AI's own water cost, specifically the freshwater consumed for data-centre cooling during large-model training and inference. The paper argues that AI's net contribution to water sustainability depends on deliberate choices, including model efficiency, renewable-powered data centres, and transparent water-use reporting, working alongside sound policy and infrastructure support.
Keywords	Artificial Intelligence, Water Conservation, Precision Agriculture, Smart Irrigation, IoT, Leak Detection, Non-Revenue Water, Digital Twin, Green AI, Water Footprint
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 4, July-August 2026
Published On	2026-07-11
DOI	https://doi.org/10.36948/ijfmr.2026.v08i04.83465

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Artificial Intelligence for Sustainable Water Management: Opportunities, Technologies, and Environmental Trade-offs

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