Assessing long-term groundwater level trends in Karakalpakstan using non-parametric statistical methods

Climate change has significantly impacted global hydrometeorological variables, placing increasing stress on groundwater resources. This study investigates long-term groundwater level trends in the Republic of Karakalpakstan, Uzbekistan, using a combination of non-parametric statistical models. The Mann–Kendall test, Spearman’s rank correlation, and innovative polygon trend analysis (IPTA) were applied to assess spatiotemporal variations. To address the limitations of parametric methods, this study utilizes robust, assumption-free trend detection techniques. The results reveal statistically significant increasing trends in groundwater levels across most provinces, particularly in Muynak (Z=3.884, p<0.001) and Republic-wide (Z=3.603, p<0.001). In contrast, provinces such as Turtkul, Ellikkala, and Nukus exhibit no significant trends. The IPTA method highlights seasonal fluctuations, with notable decreases in specific months despite the overall upward trend. These findings emphasize the need for localized groundwater management strategies that consider both seasonal dynamics and long-term changes. By integrating multiple statistical techniques, this study provides a comprehensive evaluation of groundwater variability and offers valuable insights for policymakers and water resource managers in arid regions facing climate-induced water challenges.