Sustainable water allocation under climate change: Deep learning approaches to predict drinking water shortages

Addressing sustainable urban water supply has become one of the most critical challenges for modern megacities, particularly in arid and semi-arid regions where rapid urbanization and climate change converge to exacerbate resource scarcity. Tehran, a metropolis under mounting water stress, exemplifies this global crisis. With population pressures, migration, poor urban planning, and inadequate environmental management intensifying the demand for water, reliance on groundwater surged to over 51 % of the city's total supply by 2021. This unsustainable dependence is compounded by severe aquifer depletion, now declining at an alarming rate of 32 cm annually. This study adopts advanced machine learning approaches…

• UO
  University of Warwick
• NE
  Natural Environment Research Council

  Award: NE/S007350/1