Page 125 - AJWEP-v22i3

Asian Journal of Water, Environment and Pollution. Vol. 22, No. 3 (2025), pp. 119-133.
doi: 10.36922/AJWEP025080052

ORIGINAL RESEARCH ARTICLE

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

Mehdi Fuladipanah , Kenjabek Rozumbetov 2,3 , Namal Rathnayake ,
1
4

Valery Erkudov , Mirzohid Koriyev , and Upaka Rathnayake *
6
7
5
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
*Corresponding author: Upaka Rathnayake (upaka.Rathnayake@atu.ie)

Received: February 21, 2025; 1st revised: April 18, 2025; 2nd revised: April 28, 2025; Accepted: May 12, 2025;
Published online: June 4, 2025

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

1. Introduction resource management, agriculture, hydroelectric power
generation, and groundwater replenishment. However,
Hydrometeorological variables – such as precipitation, their inherent stochasticity and complexity necessitate
temperature, streamflow, and evaporation – play a critical advanced analytical approaches to assess trends and
role in sustaining human activities, including water variability accurately. Climate change – driven by

Volume 22 Issue 3 (2025) 119 doi: 10.36922/AJWEP025080052