The 78th Geological Congress of Türkiye conducted in Ankara, Türkiye on April 13–17, 2026, brought together geologists, hydrogeologists, water and environmental scientists, and policy makers from various countries to discuss combating water and drought issues in the age of climate change and with a major focus on geological aspects. The Geological Congress of Türkiye has been conducted yearly since 1947. The theme of this year's congress was water, drought, climate change and geology, which aligns with United Nations' Sustainable Development Goals. The aim of this editorial is to point out the significance of AI and other new technological tools in addressing groundwater and water resources issues. It aims to show that AI may be used as an early warning system for groundwater management and governance, which refers to a predictive mechanism that can provide data about potential groundwater depletion and pollution, allowing enough time to take effective preventive actions. Global water bankruptcy is a major threat to human survival. Addressing it requires interdisciplinary cooperation among geologists, hydrogeologists, water and environmental scientists, water managers, and policy makers. A recent report by Madani (2026) cites some alarming statistics regarding global water bankruptcy. For instance, 2. 2 billion people lack safe drinking water, and 4 billion people annually face water shortages lasting at least a month. Since the 1990s, more than half of the large lakes in the world have lost water. Wetland decline is another major environmental issue, with 410 million hectares lost, having ecosystem services valued at over 5. 1 trillion. In addition, depletion of groundwater affects food security and domestic use as approximately 70% of aquifers across the globe showed long-term declining water-level trends. The loss of glaciers has reached 30%, and agriculture, which is responsible for 70% of global freshwater use, is becoming water-limited. Droughts are intensified by human activity and cost over 307 billion yearly. Moreover, as reported by Miao et al. (2026), the global yearly drought in 2025 affected approximately 30% of the global land surface, with approximately 1. 2% of the globe experiencing extreme drought conditions. Due to the impact of climate change on surface water, the demand for groundwater is rapidly increasing, and groundwater depletion is occurring in many regions around the world. As reported by Osman et al. (2024), conventional models such as physical-based or conceptual models do not work accurately for groundwater management because climate change has altered recharge patterns with more episodic rainfall, including intense rainstorms and prolonged droughts, impacting recharge rates. Therefore, to address local, regional, and global water related issues, especially groundwater, new technologies and AI applications should be taken into consideration in groundwater management and governance processes. For instance, research centers should establish interdisciplinary and transdisciplinary approaches for water and environmental scientists, geologists, and hydrologists. These approaches would allow them to study and investigate aquifer recharge conditions, groundwater depletions and pollution. Machine learning and deep learning models can be applied to predict groundwater levels, recharge rates, water quality, flow patterns, and pump efficiency. In conclusion, we should integrate AI into other technological tools such as Internet of Things (IoT) sensors which provide real-time data on groundwater conditions such as water quality, usage, and water levels. AI is also being integrated into GIS, so it can assist with modeling and mapping groundwater systems. Remote sensing could also be integrated into AI since satellites and drones could be effective to efficiently monitor water levels, rainfall patterns, and soil moisture. Consequently, water will be managed in a sustainable and sufficient manner in collaboration with scientists and policymakers. The author declares no conflict of interest. Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
Sarmad Dashti Latif (Wed,) studied this question.