Policy Choices Matter: Scenario‐Based Decision Support for Water Sustainability in an Arid Region (Yazd–Ardakan Watershed, Iran)

The water crisis in arid regions is rooted in policy choices, governance patterns, and overreliance on supply‐side solutions rather than physical resource scarcity. Yazd province in the central Iranian plateau is a prime example of this situation, where inter‐basin water transfer as the dominant solution, along with population growth and the development of water‐intensive industries, has led to an intensification of structural dependence and a decline in water resource sustainability. With the aim of supporting policy decision‐making, this study presents a scenario‐based framework based on artificial intelligence to assess the consequences of different water policy choices on resource sustainability in the Yazd–Ardakan basin. In this regard, climate, population, and water resource data were analyzed during the period 2003–2023, and the need for water transfer was predicted over the horizon 2024–2050 under five management scenarios using the XGBoost algorithm. The results show that the difference in water transfer needs between the optimistic and pessimistic scenarios is more than 4.5 times (about 40 to more than 180 million cubic meters), indicating the decisive role of demand‐side management policies and groundwater withdrawal control compared to climate factors. Analysis of water sustainability indices (WSI), reservoir storage index (RSI), transfer dependency index (TDI), and Enhanced Water Poverty Index (eWPI) also shows that the continuation of supply‐oriented policies can lead to an exacerbation of water stress and long‐term dependence, whereas demand‐oriented policy packages have the capacity to reduce risk and increase resilience. The findings emphasize that AI‐based tools can, as decision‐support systems, reduce the gap between scientific analysis and practical water policymaking in drylands.