AccScience Publishing / AJWEP / Online First / DOI: 10.36922/AJWEP025080052
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ORIGINAL RESEARCH ARTICLE

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

Mehdi Fuladipanah1 ,  Kenjabek Rozumbetov2,3 ,  Namal Rathnayake4 ,  Valery Erkudov5 ,  Mirzohid Koriyev6 ,  Upaka Rathnayake7*
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1 Department of Civil Engineering, Ramhormoz Branch, Islamic Azad University, Ramhormoz, Iran
2 Department of Veterinary Diagnostics and Food Safety, Nukus Branch of Samarkand State University of Veterinary Medicine, Animal Husbandry and Biotechnology, Nukus, Uzbekistan
3 Department of General Biology and Physiology, Karakalpak State University, Nukus, Uzbekistan
4 Department of Civil Engineering, Faculty of Engineering, The University of Tokyo, Bunkyo City, Tokyo, Japan
5 Department of Normal Physiology, St. Petersburg State Pediatric Medical University, Saint Petersburg, Russia
6 Department of Natural Sciences, Namangan State Pedagogical Institute, Namangan, Uzbekistan
7 Department of Civil Engineering and Construction, Faculty of Engineering and Design, Atlantic Technological University, Sligo, Ireland
AJWEP, 025080052 https://doi.org/10.36922/AJWEP025080052
Received: 21 February 2025 | Revised: 28 April 2025 | Accepted: 12 May 2025 | Published online: 4 June 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

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.

Keywords
Groundwater trend analysis
Mann–Kendall test
Innovative polygon trend analysis
Climate change impact
Water resource management
Funding
None.
Conflict of interest
Upaka Rathnayake is an Editorial Board Member of this journal but was not in any way involved in the editorial and peer-review process conducted for this paper, directly or indirectly. Separately, other authors declared that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.
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Asian Journal of Water, Environment and Pollution, Electronic ISSN: 1875-8568 Print ISSN: 0972-9860, Published by AccScience Publishing
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