Long-Term Monitoring and Regression Modeling of Shallow Water Tables (SWTs) and Salinity Dynamics in an Arid Irrigated Region of Central Asia

Long-Term Monitoring and Regression Modeling of Shallow Water Tables (SWTs) and Salinity Dynamics in an Arid Irrigated Region of Central Asia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Long-Term Monitoring and Regression Modeling of Shallow Water Tables (SWTs) and Salinity Dynamics in an Arid Irrigated Region of Central Asia Nilufar Rajabova, Mexriban Allanazarova, Toshev Shakhriyor, Rakhimov Nodirjon, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9247677/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract This study investigates long-term dynamics of SWTs and mineralization in arid irrigated ecosystems under climate variability, using the Takhtakopir district of the Republic of Karakalpakstan (north-western Uzbekistan) as a case study. Empirical observations from 256 monitoring wells collected during 1990–2024 were analyzed to evaluate temporal variations in SWTs and total dissolved solids (TDS) and assess their agroecological implications. Results show pronounced long-term variability in SWTs. Average annual SWTs ranged from 1.7 to 4.5 m, indicating substantial instability of the regional hydro-ecological system. A marked deepening occurred during 2000–2004, when the mean depth increased to 309.70 ± 111.45 cm from 178.99 ± 6.15 cm in 1990–1994, an increase of ~ 71%. Recent measurements (2020–2024) indicate an average depth of 282.32 ± 30.67 cm, reflecting a continuing trend toward deeper water tables and reduced capillary contribution to soil moisture. Water mineralization remained high, with TDS ranging from 2800 to 3700 mg L⁻¹, indicating persistent soil salinization risks. The study area’s SWT differs from other Central Asian regions: Khorezm (0.9–1.4 m, salinity, waterlogging), Fergana (1.5–3 m, increased evapotranspiration), and North-West China (2.97–6.33 m, lower salinity, higher water deficit). Regression-based projections suggest that during 2026–2050, SWTs may decline by ~ 1.81 cm yr⁻¹, while TDS may decrease by ~ 8 mg L⁻¹ yr⁻¹. These trends may reduce salinity risks but could increase soil moisture deficits, potentially affecting agroecosystem stability. Overall, the findings underscore the importance of long-term SWT monitoring and integrated water-management strategies to support ecological sustainability in arid irrigated regions. Earth and environmental sciences/Climate sciences Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Hydrology Shallow water table Groundwater mineralization Total dissolved solids (TDS) Arid irrigated ecosystems Soil salinization Climate change impacts Predictive modeling Figures Figure 1 Figure 2 Figure 3 1. Introduction 1.1. Degradation of the Shallow Water Resources under Climate Change Conditions: Global Challenges and Scientific Significance Currently, under climate change conditions, in agro-ecosystems adapted to agriculture, the SWT is sharply declining, and the degree of its mineralization is increasing, becoming one of the most pressing global ecological problems [1]. Especially in arid and semi-arid regions, intensified evaporation processes, increasing anthropogenic pressure on water resources, and low efficiency of irrigation systems lead to rapid dynamics of the SWT. As a result, soil moisture in irrigated agro-ecosystems decreases sharply, causing negative ecological consequences such as reduced crop yields, soil degradation, and a decline in biodiversity [2, 3]. Global climate change has fundamentally altered hydrological and hydrometeorological processes, significantly reducing water availability and increasing soil degradation worldwide compared to historical conditions [4–6]. According to the Food and Agriculture Organization (FAO), approximately 833 million hectares of land worldwide are affected by salinization, accounting for nearly 10% of terrestrial areas and over 20% of irrigated lands [7, 8]. Each year, secondary salinization renders 1.5 million hectares of irrigated land unusable, causing economic losses exceeding 27 billion USD globally. These processes accelerate particularly in arid and semi-arid zones, where evaporation rates are several times higher than precipitation [9, 3, 10]. According to the Intergovernmental Panel on Climate Change (IPCC), the global average air temperature has increased by 1.1°C compared to the pre-industrial era, and by 2100, it is projected to rise by 1.0–5.7°C depending on emission scenarios. Rising temperatures enhance evaporation, destabilize precipitation patterns, and increase drought events. This directly affects the recharge, reserves, and quality of groundwater. Currently, groundwater supplies 50% of global drinking water, 40% of industrial water needs, and approximately 38% of irrigation water, making it a strategically important source for water security [11–14]. The Central Asia region is one of the most climate-sensitive areas. Observational data indicate that since the beginning of the 20th century, air temperature in the region has increased by 1–2°C, and in the near future, evaporation is expected to rise by 10–15% [15]. The region’s average annual precipitation is only 170 mm, while potential evaporation ranges from 1500 to 2000 mm/year, resulting in a persistent negative water balance. Consequently, irrigated agriculture dominates, and during drought periods, groundwater serves as a critical strategic reserve [16]. Most large irrigated agro-ecosystems in this region are located in the Republic of Uzbekistan. Of the country’s 5.2 million hectares of agricultural land, approximately 4.2 million hectares (80%) are irrigated. However, irrigation systems are inefficient, with studies showing that up to 70% of water is lost during transportation and on fields. Over the past century, the expansion of irrigated areas from 1.3 million hectares in 1900 to 4.2 million hectares in 2000 has sharply increased anthropogenic pressure on water and soil resources [17]. The use of groundwater in Uzbekistan has also rapidly increased, with the annual permitted limit at 6.8 km³, while current use reaches 7.5 km³/year, exceeding sustainable limits. Currently, 6.4% of irrigation water comes from groundwater, and this proportion increases during drought years. The annual recharge of groundwater is estimated at 23–27 km³, of which approximately 63% originates from anthropogenic sources, such as irrigation channels, reservoirs, and field seepage. This disrupts the natural hydrogeological balance and accelerates salinization processes [18–20]. Soil salinization in irrigated agro-ecosystems is often caused by evaporation of the SWT, capillary rise, and negative anthropogenic factors. A sharp decline in the shallow water table disrupts optimal soil moisture regimes, leading to decreased crop yields, soil degradation, and reduced agro-ecosystem stability. Therefore, studying the spatial and seasonal dynamics of the SWT and its mineralization is of significant scientific and practical importance for ensuring agricultural sustainability, strengthening food security, and maintaining ecological balance [21, 22]. The Republic of Karakalpakstan, located in the Aral Sea basin, is the most ecologically vulnerable region of Uzbekistan. Covering 166,600 km², it accounts for 37.1% of the country’s territory, 21.3% of irrigated lands, and 48.5% of pasture resources. The climate is sharply continental and extremely arid, with an average annual precipitation of 110 mm and evaporation 9–10 times higher than precipitation. During summer, temperatures can rise up to 46°C, accelerating soil moisture loss and salt accumulation [23]. Historical hydromelioration data show that during 1965–1970, expansion of irrigation systems caused the shallow water table to rise to only 1.2 m in many areas of Karakalpakstan, intensifying secondary salinization. Between 2007–2012, reconstruction of collector-drainage systems lowered the SWT to 2.8–3.0 m in some areas; however, this occurred alongside increased irrigation water demand and drying of the topsoil layer [24, 25]. Recent monitoring indicates significant spatial heterogeneity in the region. In particular, almost all districts of Karakalpakstan, especially Turtkul, Takhtakopir, and Shumanay districts, experienced fluctuations in the SWT of 1.0–2.0 m over short periods, complicating irrigation management, yield stability, and water resource planning [26, 3, 27]. 1.2. Climatic and Agricultural Pressure in an Arid Region: Justification for Selecting the Takhtakopir District as a Study Area The study area was selected as the Takhtakopir district, located in the northeastern part of the Republic of Karakalpakstan. The district lies on the left bank of the lower reaches of the Amu Darya River and is geographically characterized by arid and semi-desert zones. Administratively, it borders the Beruniy district to the south, the Ellikqala district to the southeast, the Qoraozak district to the west, the Moynaq district to the northwest, and the Republic of Kazakhstan to the northeast and east. The district center is the town of Takhtakopir, approximately located at geographic coordinates 43°01′21″ N latitude and 60°17′19″ E longitude [28, 29]. The total area of the Takhtakopir district is approximately 21.1 thousand km², of which 34,672 hectares are irrigated lands. Among these, 5,096 hectares are considered damaged primarily due to malfunctions in the irrigation network. The district’s relief is mainly flat, with occasional low elevations of the Beltov ridges and sandy massifs. The northeastern part of the district borders the Kyzylkum Desert, where sandy dunes, takyr (salt flats), and saline soils are widespread. The Borshin mountain is one of the relatively elevated relief elements in the region, with a height of 35–37 m above the surrounding plains. The climate is sharply continental, with pronounced seasonal temperature variations. The annual average air temperature is around 11°C. In winter, the average temperature in January is − 6°C, with minimum temperatures potentially dropping to − 35°C. In summer, the average July temperature reaches 27°C, with maximums up to 43°C. The annual precipitation is approximately 100 mm, mostly falling during winter and spring. Such climatic conditions are characterized by high evaporation, water scarcity, and an increased risk of soil salinization. The soil cover of the Takhtakopir district is diverse, predominantly comprising saline, swamp-meadow, gray, takyr, sandy, and brown soils. Due to its proximity to the Amu Darya delta, the relatively shallow groundwater in some areas has intensified secondary salinization processes. Agriculture in the district is mainly specialized in cotton, cereals, rice cultivation, and livestock farming. Irrigation is supplied through the Quvonchyorma canal and its branches (Timpiy, Bozyop, Jilvonyop, Badrakyop). The pastures adjacent to the Kyzylkum area serve as important resources for livestock, especially sheep and Karakul breeding. The availability of irrigated lands supports the development of intensive farming; however, high dependence on water resources and the risk of salinization remain primary factors limiting the sustainability of agro-ecosystems. Therefore, considering the above information, the study area is an ecologically and agro-hydrologically important research site. It combines arid climatic conditions, complex hydrogeological structures, and intensive agricultural activity, making it suitable for studying the dynamics of the SWT and salinization processes [30–36]. 1.3. Distinction and Necessity of the Study The object of this study is the SWT in the 0–5 m depth ranges from the soil surface in the Takhtakopir district, located in the northwestern part of Uzbekistan within the Republic of Karakalpakstan. The research focuses on 250 observation wells that measure the SWT and salinity levels, analyzing their temporal variations over multiple years through detailed, specific investigations. The distinctive contribution of this study, addressing a gap in previous research, lies in the fact that, to date, no comprehensive scientific investigations have been conducted on the SWT and its salinization in the Takhtakopir district, considering the complex continental climate of the Republic of Karakalpakstan and the integrated effects of anthropogenic factors. In other words, most prior studies have examined water salinization only at a general spatial scale, without adequately analyzing the spatio-temporal variations of salinization or the interactions of multiple factors—such as groundwater level, water mineralization, soil mechanical composition, crop types, and climatic conditions—at a regional level. Filling this scientific gap is the main relevance of the present study. The results of this research are not only practically significant for irrigated areas in the Takhtakopir district but also for regions across Central Asia where the SWT faces high risks of salinization and declining water tables. Internationally, these findings can inform strategies for managing shallow water tables and soil salinization, fulfilling key scientific objectives. Moreover, the main logical hypothesis of this study is that, under climate change conditions in arid and semi-arid regions, the conventional mechanism—namely, excessive evaporation of the SWT and the deposition of salts on the soil surface leading to soil degradation—is well known. This research aims to determine how this process occurs in the arid Takhtakopir district, either validating or refuting the hypothesis, and based on the findings, to develop a new, region-specific scientific hypothesis. Accordingly, it analyzes the temporal changes in variable indicators such as groundwater salinity over the years using mathematical, statistical, and geostatistical methods. Ultimately, the study seeks to create a predictive mathematical model and provide recommendations for improving the ecological condition of the region. 2. Materials and Methods 2.1. Study Area and Research Methodology The study was conducted during 1990–2024 in the irrigated areas of the Takhtakopir district, with the main empirical part of the research carried out based on a total of 256 observation wells (Fig. 1 ) to determine SWTs and water mineralization, as well as to evaluate their seasonal dynamics. The status of the shallow groundwater was investigated through observation wells located at 0–5(6) m depths from the soil surface. The empirical part of this research was conducted in the soil and water laboratory of the Meliorative Expedition under the Ministry of Water Resources of the Republic of Karakalpakstan, and was based on both long-term monitoring data of the organization and collected field data (Table 1 ). Water samples were collected monthly throughout the year, and the depth of the SWT relative to the soil surface was measured in the field, with its temporal variations recorded. Groundwater mineralization was determined in the laboratory using the gravimetric method: the initial mass of water samples was measured on an analytical balance, then fully dried in a thermostatic water bath (using a TDS measurement device), and the mass of the resulting dry residue was reweighed to calculate the total dissolved solids (TDS) accurately [3, 36]. The field and laboratory data obtained through this empirical analysis were subjected to statistical processing to identify the spatio-temporal patterns of the SWT and groundwater salinization, as well as to assess their anticipated future ecological conditions (Table 1 ). In the field, the SWT was monitored using a specialized electronic water level meter (driver), which was lowered into the well. The reading was recorded when the sensor made contact with the water surface. Measurements at each point were repeated at least three times, and the average values were calculated. All data were systematically recorded by date, time, and well identification number. 3. Results and Discussion 3.1. Dynamics of the SWT In the study area, the SWT observed in wells during 1990–2024 varied within a wide range of annual average depths from 166.67 cm to 452.33 cm relative to the soil surface. These values are measured downward from the soil surface, and an increase in the indicator indicates deepening of the water table, i.e., the groundwater is moving farther from the soil surface. The large amplitude fluctuations observed demonstrate the hydrological system’s relative temporal instability and its high sensitivity to climatic and anthropogenic factors. During 1990–1999, the SWT remained relatively stable, with average depths ranging from 170 to 190 cm. Specifically, during 1990–1994, the average depth was 178.99 ± 6.15 cm, and during 1995–1999, it was 181.04 ± 9.33 cm. The low standard deviation values indicate that the water table was close to the soil surface, and the hydrological regime was relatively stable. This condition allowed capillary rise to maintain moisture in the root zone, creating favorable conditions for agro-ecosystems. However, the period 2000–2004 stands out as a turning point in the shallow water table dynamics. During this period, the average depth increased to 309.70 ± 111.45 cm, representing a 71.1% deepening compared to 1995–1999. The very high standard deviation indicates significant hydrological irregularities during these years. Notably, in 2001–2002, depths of 432–452 cm were recorded, which sharply reduced the groundwater’s role in maintaining soil moisture. In the subsequent period (2005–2009), the water table rose closer to the soil surface, with an average depth of 229.36 ± 53.16 cm. This represents a 25.9% decrease relative to the previous period, indicating the short-term adaptability of the hydrological system. However, the relatively high standard deviation (± 53.16 cm) shows that fluctuations persisted during this period. During 2010–2014, the average SWT depth was 208.38 ± 20.07 cm, decreasing by 9.14% compared to the previous period. In 2015–2019, this value further decreased to 201.55 ± 25.82 cm, showing an additional 3.28% decline. Although the trend of rising closer to the surface continued, the rate of change slowed, indicating a relatively stabilized phase. Nevertheless, the water table had not fully returned to the natural equilibrium level observed in the 1990s. The most recent period (2020–2024) indicates a renewed phase of deepening of the SWT. During this period, the average depth reached 282.32 ± 30.67 cm, representing a sharp 40.07% increase compared to 2015–2019. This trend is strongly associated with regional warming, increased evaporation, and heightened anthropogenic pressure on water resources, reflecting a significant reduction in the soil’s ability to be replenished through capillary rise (Table 1 ). 3.2. Annual Dynamics of TDS The annual average TDS (Total Dissolved Solids) values of the SWT observed in the study area during 1991–2024 exhibited significant variability. These fluctuations are critically important for assessing water quality, hydrological stability, and the ecological condition of the region. From this perspective, analyzing TDS values in five-year intervals allowed identification of long-term trends and short-term fluctuations within the hydrological system. During 1991–1995, the average TDS ranged from 3,122 ± 351 mg/L, with minimum and maximum values of 2,837 mg/L and 3,596 mg/L, respectively. Although mineralization was relatively high during this period, the standard deviation was low, indicating short-term stability of the hydrological system. This suggests that the mineral content of groundwater significantly contributed to salinization within the agro-ecosystem’s edaphic environment. In 1996–2000, TDS increased to an average of 3,199 ± 496 mg/L, reaching a maximum of 3,767 mg/L. This reflects increased hydrological instability and notable changes in water quality. The heightened salinization during this period may have adversely affected soil properties and irrigation efficiency. During 2001–2005, the average TDS was 2,902 ± 857 mg/L, with maximum and minimum values of 4,009 mg/L and 2,241 mg/L, respectively. The very high standard deviation indicates considerable disruption in the hydrological system. TDS during this period not only fluctuated but also exhibited extreme increases and decreases compared to previous years, likely resulting from combined climatic and anthropogenic impacts. Between 2006–2010, the average TDS rose to 3,660 ± 282 mg/L, with a maximum of 4,000 mg/L, reflecting high levels of groundwater salinization. However, the lower standard deviation suggests that short-term hydrological stability was maintained. This period highlighted the need for monitoring water quality and implementing measures to restore water balance. From 2011–2015, the average TDS decreased to 3,199 ± 154 mg/L, with minimum and maximum values ranging from 2,940–3,420 mg/L. This decline and reduced variability indicate short-term stability and relative normalization of water resources. During this period, mineralization remained at moderate levels, showing that water quality did not deteriorate significantly. For 2016–2020, TDS sharply declined to 2,952 ± 333 mg/L, with a minimum of 2,440 mg/L and a maximum of 3,370 mg/L, indicating fluctuations in groundwater mineralization. Although the hydrological system demonstrated short-term adaptability, the salinization risk remained within a significant hazard category. During 2021–2024, the average TDS further decreased to 2,838 ± 177 mg/L, with maximum and minimum values of 3,000 mg/L and 2,610 mg/L, respectively. This decline reflects a trend of improvement in groundwater mineralization within the hydrological system (Table 1 ). 3.3. Mathematical modeling of the SWT and salinity based on linear regression Based on the last 34–35 years of data from the monitoring wells of the designated shallow water, a mathematical model was developed using a linear regression equation (Eq. 1) to describe the water table and mineralization dynamics. Y = a + bX (1); Here: Y represents the annual average SWT depth (cm) and TDS values (mg/L), X is the time index (forecast years), a is the initial regression intercept, and b is the annual average rate of change [37, 38]. According to the results of the developed mathematical model, between 2026 and 2050, the SWT is projected to decline by 1.81 cm per year, while TDS is expected to decrease by 8 mg/L annually. Based on this hypothesis, the anticipated conditions for the next periods can be analyzed as follows: During 2026–2029, the average water table is expected to be 200.2 ± 2.7 cm, and TDS 2,928.8 ± 9 mg/L, indicating a decline in the water table while TDS remains relatively high, suggesting a continued risk of soil salinization. For 2030–2034, the water table is projected at 207.4 cm, and TDS at 2,884 mg/L, reflecting a potentially complex ecological condition. On one hand, the decrease in TDS reduces the risk of soil salinization, but the further decline in the water table may increase the risk of insufficient soil moisture at the surface. Between 2035–2039, the water table is expected to reach an average of 216.1 cm, and TDS 2,840 mg/L, showing long-term consistent declining trends for both variables. Similarly, during 2040–2044, the water table and TDS are projected to decrease steadily to 227.0 cm and 2,805 mg/L, respectively. Finally, for 2045–2050, the water table is anticipated to be 236.8 cm, and TDS 2,775 mg/L. During this period, the continued decrease in TDS further reduces the risk of soil salinization. Table 1 Annual mean SW depth and TDS concentration (cm, mg/L) and comparison of empirical and predicted values for each five-year interval (1990–2024) Empirical data Predicted data Period Mean ± SD (sm) Min Max Period Mean ± SD (sm) Min Max 1990–1992 180.03 ± 7.89 174.75 189.1 2025–2027 198.38 ± 1.81 196.57 200.19 1993–1995 180.69 ± 6.99 173.33 187.25 2028–2030 203.81 ± 1.81 202 205.62 1996–1998 183.75 ± 7.43 175.17 188.17 2031–2033 209.24 ± 1.81 207.43 211.05 1999–2001 291.78 ± 146.10 166.67 452.33 2034–2036 214.67 ± 1.81 212.86 216.48 2002–2004 279.95 ± 132.40 192.42 432.25 2037–2039 220.10 ± 1.81 218.29 221.91 2005–2007 191.62 ± 6.92 183.75 196.75 2040–2042 225.53 ± 1.81 223.72 227.34 2008–2010 249.33 ± 67.65 176.08 309.42 2043–2045 230.96 ± 1.81 229.15 232.77 2011–2013 214.31 ± 12.87 204.67 228.92 2046–2048 236.39 ± 1.81 234.58 238.2 2014–2016 195.97 ± 23.45 180.33 222.92 2049–2050 240.92 ± 1.28 240.01 241.82 2017–2019 214.25 ± 25.35 189.25 239.92 2020–2022 277.06 ± 41.10 232.5 313.5 2023–2024 290.21 ± 5.95 286 294.42 Empirical data Predicted data Period Mean ± SD (TDS, mg/l) Min Max Period Mean ± SD (TDS, mg/l) Min Max 1991–1993 3289.67 ± 380.30 2864 3596 2025–2027 2937.02 ± 8.02 2928.99 2945.04 1994–1996 2948.33 ± 139.60 2837 3105 2028–2030 2912.94 ± 8.03 2904.91 2920.96 1997–1999 3036.67 ± 497.30 2468 3390 2031–2033 2888.86 ± 8.03 2880.83 2896.89 2000–2002 3342.00 ± 953.40 2250 4009 2034–2036 2864.78 ± 8.03 2856.76 2872.81 2003–2005 2446.67 ± 182.70 2241 2590 2037–2039 2840.70 ± 8.03 2832.68 2848.73 2006–2008 3630.00 ± 380.40 3240 4000 2040–2042 2816.63 ± 8.03 2808.6 2824.65 2009–2011 3406.67 ± 335.60 3130 3780 2043–2045 2792.55 ± 8.03 2784.52 2800.57 2012–2014 3104.67 ± 143.20 2940 3200 2046–2048 2768.47 ± 8.03 2760.44 2776.5 2015–2017 3076.67 ± 551.00 2440 3420 2049–2050 2748.41 ± 5.68 2744.39 2752.42 2018–2020 2813.33 ± 219.60 2560 2950 2021–2023 2783.33 ± 198.60 2610 3000 2024 3000.00 ± 0.00 3000 3000 3.4. Multivariate Statistical Analysis of Hydrogeochemical Characteristics of the Water Sources in Arid Agroecosystems In the study area, the impact of two types of water resources—namely, the shallow water and natural underground drinking water—on water quality was assessed through statistical analysis. According to the results obtained using the Pearson correlation coefficient, an increase in the mineralization or salinity of the shallow water corresponded to a parallel increase in the salinity of the natural underground drinking water [3, 35, 36]. Specifically, a strong positive correlation was observed between the mineralization of the SWT (TDS_S) and the mineral content (TDS_G), chloride (Cl⁻), and total hardness (TH) of natural underground drinking water. The correlation coefficients were as follows: TDS_S and TDS_G, r = 0.74; TDS_S and Cl⁻, r = 0.43; TH and Cl⁻, r = 0.94; and TH and SO₄²⁻, r = 0.91, indicating a strong positive relationship between the two types of water resources. This suggests that nitrogen compounds are linked to mineral-rich water sources, likely influenced by agricultural runoff or surface water infiltration. Furthermore, a moderate but weak correlation between NO₃⁻ and TDS_S (r = 0.22) indicates that a portion of nitrate in the groundwater originates from surface water sources. In other words, groundwater quality is significantly affected by the chemical characteristics of surface water, with notable correlations observed for parameters such as TDS, Cl⁻, TH, and NO₃⁻ [3]. Previous studies have also demonstrated that surface water infiltration and leaching of minerals considerably influence groundwater quality, particularly in terms of total dissolved solids, hardness, and nitrate concentrations (Fig. 3 ; see also Figs. S1 and S2 in the Supplementary Material). 3.5. Comparative Analysis of the Study Area from Global and Cross-Regional Perspectives When comparing the SWT levels in the study area at local and global scales, it becomes evident that, while the study site differs significantly from other regions in certain aspects, some similarities can also be observed. Specifically, in irrigated areas of Central Asia and northwestern China, the SWT depths vary considerably across different regions (Table 2 ). Typically, for irrigated lands, the recommended SW level is 2–3 m, as this range minimizes the risks of soil salinization and waterlogging. However, considering the complex ecological characteristics of these ecosystems and the combined effects of climate and anthropogenic factors, this optimal range may not always represent the ideal threshold, and slight deviations are possible [39–43]. Globally recognized optimal ranges allow for regional comparisons. For instance, in the Khorezm region of northwestern Uzbekistan, the SWT consistently remains close to the productive soil layer, with depths ranging from 1.1–1.4 m during non-vegetation periods (particularly during soil leaching phases) and 0.9–1.4 m during peak irrigation [44]. The proximity of the water table to the soil surface exacerbates salinization, increases the risk of waterlogging, and can reduce oxygen availability to plant roots. Spatial variability in this region is low, and water levels show minimal differences across the landscape, primarily due to insufficient water management and suboptimal leaching practices [45, 46]. Conversely, in the Ferghana Valley, located among the mountains of Central Asia and covering eastern Uzbekistan, when the shallow water rises from 3 m to 1.5 m, crop evapotranspiration (ET) significantly increases. Specifically, under rainfed conditions, ET rises from 36 cm to 57.9 cm, while under full irrigation, it increases from 58 cm to 66.5 cm [47]. The contribution of shallow groundwater to ET is substantial due to both its shallowness and the irrigation regime; in high-deficit irrigation and loamy soils, this contribution exceeds 60%. Consequently, higher water table levels increase evaporation but reduce the efficiency of water use by crops. Additionally, salts released through evaporation accumulate in the soil surface layer, promoting secondary soil salinization and land degradation. In the Ferghana Valley, deviations from the optimal shallow groundwater level are largely associated with anthropogenic factors, particularly irrigation practices that are not well-adapted to local conditions [48–50]. In the study site of the Takhtakopir district, the SWT exhibited large-amplitude fluctuations between 1990 and 2024. For example, the average depth was 178.99 ± 6.15 cm in 1990–1994, rising to 309.70 ± 111.45 cm in 2000–2004, representing a 71.1% increase in depth. In the most recent period (2020–2024), the average depth reached 282.32 ± 30.67 cm, indicating a substantial reduction in the soil’s capacity to retain moisture via capillary rise. Comparing the Takhtakopir district with the Ferghana and Khorezm regions, it becomes apparent that the effects of ET and soil salinization depend on the combined influence of climatic and anthropogenic factors. On a broader Central Asian scale, in southeastern Kazakhstan, the shallow water depths range from 0.96 to 4.32 m. In some areas, rice-based irrigation reduces waterlogging, whereas in others, salinization persists [51, 52]. Therefore, adaptive irrigation and drainage restoration play critical roles in enhancing ecological stability and crop productivity. In contrast, in northwestern China, shallow groundwater occurs at much greater depths (2.97–6.33 m), which reduces soil moisture and salinization risk but creates water deficits for crops [53, 54]. This situation is essentially opposite to the issues observed in the aforementioned regions. Considering these similarities and differences, a regional comparison indicates the following: in Khorezm and Ferghana, the SW located near the soil surface increases soil salinization and waterlogging risks; in the Takhtakopir district, deepening shallow groundwater reduces ET and soil moisture, while simultaneously lowering the risk of salinization. Similar ecological issues are partially observed in southeastern Kazakhstan and northwestern China, where the SW levels in agroecosystems affect crop–water dynamics depending on irrigation practices and water management systems. Table 2 Comparative analysis of the SW depth, associated problems, and agroecological consequences across different territories No Continent Country Region The shallow water level (annual/monthly/seasonal) The shallow water level issue Consequences / Outcomes 1 Asia Uzbekistan Khorezm province Non-vegetation period: 1.1–1.4 m; Irrigation period: 0.9–1.4 m Shallow groundwater level Soil salinization, waterlogging, and insufficient oxygen for plant roots 2 Uzbekistan Fergana Valley 3 m to 1.5 m Shallow groundwater level, high evapotranspiration ET increases, the efficiency of plant water use decreases; soil salinization in the top layer 3 Uzbekistan Takhtakupir, Karakalpakstan 1990–1994: 178.99 ± 6.15 cm; 2000–2004: 309.70 ± 111.45 cm; 2020–2024: 282.32 ± 30.67 cm Deepening groundwater level ET and soil moisture decreases, capillary rise is limited 4 Kazakhstan Southeast Kazakhstan 0.96–4.32 m Heterogeneous groundwater level Rice-based irrigation maintains salinization in some areas, reduces waterlogging in others 5 China Northwest China 2.97–6.33 m Deep groundwater level Soil moisture decreases, salinization decreases, but crops face water shortage 4. Conclusions and Recommendations Long-term monitoring and analyses based on linear regression models conducted in the Takhtakopir district demonstrated that SW levels and salinity are highly sensitive to climatic and anthropogenic factors in arid regions. Based on empirical observations and mathematical modeling, the following key conclusions were drawn: The dynamics of the SW in the study area are primarily associated with climate warming, increased evaporation, and the rising load on irrigated lands. Between 1990 and 2024, significant instability and sharp fluctuations were observed. In particular, the rapid deepening of the SW during 2000–2004 confirmed the high sensitivity of the hydrological system to climatic stress. Groundwater salinity, expressed as TDS, remained at elevated levels over the long term, indicating a persistent risk of salinization in irrigated agroecosystems. Periodic fluctuations in TDS values were closely linked to hydrological instability, imbalances in the water budget, and the intensification of anthropogenic impacts. Forecasts based on the linear regression model suggest that between 2026 and 2050, shallow groundwater levels will decrease on average by 1.81 cm per year, while TDS will decline by approximately 8 mg/L per year. Although this trend indicates a relative reduction in salinization risk, the deepening of the shallow water table may exacerbate soil moisture deficits and reduce the stability of agroecosystems. Based on these conclusions, the following recommendations are proposed: In regions with sharply continental climates, such as the Takhtakopir district, sustainable agriculture requires the selection of crop types adapted to local climatic conditions and careful planning of crop rotations. To develop climate-resilient agroecosystems capable of mitigating excessive evaporation during hot summer periods, it is recommended to establish plant communities with high ecological value and to plant trees around micro- and macro-agroecosystems for wind protection and microclimate regulation. To prevent excessive water loss due to evaporation during hot periods, full transition to innovative drip irrigation systems is advised, along with the integration of modern soil moisture monitoring technologies. Such measures can effectively mitigate anticipated future challenges in the region. Declarations Data Availability All data generated or analyzed during this study are included within this article. Acknowledgements This study was conducted under the collaboration agreement (Contract No. 04-73, May 18, 2023) between the National University of Uzbekistan named after Mirzo Ulugbek and the Meliorative Expedition Bureau under the Ministry of Water Resources of the Republic of Karakalpakstan. We sincerely thank both institutions, as well as the Karakalpak State University named after Berdakh, for their support in organizing and conducting this research. Author contributions Nilufar Rajabova is responsible for concept development, study design, manuscript writing, data analysis, regression modeling, and GIS mapping; Mexriban Allanazarova and Toshev Shakhriyor are responsible for data collection, GIS mapping support, and fieldwork; Rakhimov Nodirjon and Gafurov Timur are responsible for laboratory analysis, data processing, and visualization; Kuralay Tureeva and Luiza Bakhieva assisted in quality control and data organization; Elmira Maturazova contributed to literature review and manuscript editing; Oybek Yeshchanov and Nasiba Navrozboyeva assisted in data collection and fieldwork; Remzi Suleymanov is responsible for supervision and critical review of the manuscript. All authors have reviewed the results and approved the final version of the manuscript. Funding No external funding was received for this study, and all research activities were carried out using institutional resources without financial support from public, commercial, or not-for-profit funding agencies. Ethical Approval and Permissions This study was conducted within the framework of a formal collaboration between the National University of Uzbekistan named after Mirzo Ulugbek and the Meliorative Expedition under the Ministry of Water Resources of the Republic of Karakalpakstan (Contract No. 04-73, dated May 18, 2023). This study was carried out as part of the scientific research program of the Department of Ecology of the National University of Uzbekistan for 2021-2025, entitled “Investigation of bioecological characteristics of flora and fauna under global climate change, conservation of biodiversity, assessment of the ecological state of soil and water resources, and development of scientific and practical bases for the rational use of natural resources,” and it was also conducted within the framework of the practical project “Ensuring the spatial diversity of the regional model of radiation and water-salt balance in the southern part of the Aral Sea basin using geoinformatics methods (No. 5721-122061)” (2022-2025). All research activities, including field sampling and laboratory analysis, were conducted in accordance with the institutional guidelines, regulations, and standard procedures of the Meliorative Expedition. Groundwater and surface water data were obtained from long-term monitoring records of the organization. In addition, fieldwork was carried out jointly with laboratory specialists at designated observation wells for shallow water tables, and water samples were collected and analyzed following standard protocols. All necessary institutional permissions were obtained through the above-mentioned agreement. No human or animal subjects were involved in this study, and no additional ethical approval was required. Competing interests The authors declare no competing interests. Additional information Correspondence and requests for materials should be addressed to N.R. References Anandhi, A., Book, R., & Ozbay, G. (2025). A novel framework to represent hypoxia in coastal systems. Land, 14(6), 1169. https://doi.org/10.3390/land14061169 Rajabova, N., Sherimbetov, V., Sadiq, R., & Farouk Aboukila, A. (2025). 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monitoring wells in the district\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9247677/v1/123cffacfb9cda26c30d00c4.png"},{"id":106544992,"identity":"139f9e43-cae5-4668-8536-7a44b8134689","added_by":"auto","created_at":"2026-04-09 16:43:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":115245,"visible":true,"origin":"","legend":"\u003cp\u003eYearly trend of the SW depth and TDS concentration in the study area\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9247677/v1/807bd3e6e94718a1078bbfe1.png"},{"id":106726870,"identity":"a806935e-a0d4-4367-8c5d-71cef2c17b36","added_by":"auto","created_at":"2026-04-12 18:37:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":74482,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation matrix of hydrogeochemical parameters\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9247677/v1/f5697e62ead409f585543099.png"},{"id":106728071,"identity":"ba46a5a5-27f3-420e-b7a3-b31dd573cc99","added_by":"auto","created_at":"2026-04-12 18:41:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1675907,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9247677/v1/fe8ce5e1-71b3-491a-9a45-9527549812f6.pdf"},{"id":106544991,"identity":"3c8e4786-6be5-4479-80ad-8c70dc3b42dc","added_by":"auto","created_at":"2026-04-09 16:43:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":657806,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9247677/v1/d99f5c88758efbc4198b5627.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Long-Term Monitoring and Regression Modeling of Shallow Water Tables (SWTs) and Salinity Dynamics in an Arid Irrigated Region of Central Asia","fulltext":[{"header":"1. Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1. Degradation of the Shallow Water Resources under Climate Change Conditions: Global Challenges and Scientific Significance\u003c/h2\u003e \u003cp\u003eCurrently, under climate change conditions, in agro-ecosystems adapted to agriculture, the SWT is sharply declining, and the degree of its mineralization is increasing, becoming one of the most pressing global ecological problems [1]. Especially in arid and semi-arid regions, intensified evaporation processes, increasing anthropogenic pressure on water resources, and low efficiency of irrigation systems lead to rapid dynamics of the SWT. As a result, soil moisture in irrigated agro-ecosystems decreases sharply, causing negative ecological consequences such as reduced crop yields, soil degradation, and a decline in biodiversity [2, 3].\u003c/p\u003e \u003cp\u003eGlobal climate change has fundamentally altered hydrological and hydrometeorological processes, significantly reducing water availability and increasing soil degradation worldwide compared to historical conditions [4\u0026ndash;6]. According to the Food and Agriculture Organization (FAO), approximately 833\u0026nbsp;million hectares of land worldwide are affected by salinization, accounting for nearly 10% of terrestrial areas and over 20% of irrigated lands [7, 8]. Each year, secondary salinization renders 1.5\u0026nbsp;million hectares of irrigated land unusable, causing economic losses exceeding 27\u0026nbsp;billion USD globally. These processes accelerate particularly in arid and semi-arid zones, where evaporation rates are several times higher than precipitation [9, 3, 10].\u003c/p\u003e \u003cp\u003eAccording to the Intergovernmental Panel on Climate Change (IPCC), the global average air temperature has increased by 1.1\u0026deg;C compared to the pre-industrial era, and by 2100, it is projected to rise by 1.0\u0026ndash;5.7\u0026deg;C depending on emission scenarios. Rising temperatures enhance evaporation, destabilize precipitation patterns, and increase drought events. This directly affects the recharge, reserves, and quality of groundwater. Currently, groundwater supplies 50% of global drinking water, 40% of industrial water needs, and approximately 38% of irrigation water, making it a strategically important source for water security [11\u0026ndash;14].\u003c/p\u003e \u003cp\u003eThe Central Asia region is one of the most climate-sensitive areas. Observational data indicate that since the beginning of the 20th century, air temperature in the region has increased by 1\u0026ndash;2\u0026deg;C, and in the near future, evaporation is expected to rise by 10\u0026ndash;15% [15]. The region\u0026rsquo;s average annual precipitation is only 170 mm, while potential evaporation ranges from 1500 to 2000 mm/year, resulting in a persistent negative water balance. Consequently, irrigated agriculture dominates, and during drought periods, groundwater serves as a critical strategic reserve [16]. Most large irrigated agro-ecosystems in this region are located in the Republic of Uzbekistan. Of the country\u0026rsquo;s 5.2\u0026nbsp;million hectares of agricultural land, approximately 4.2\u0026nbsp;million hectares (80%) are irrigated. However, irrigation systems are inefficient, with studies showing that up to 70% of water is lost during transportation and on fields. Over the past century, the expansion of irrigated areas from 1.3\u0026nbsp;million hectares in 1900 to 4.2\u0026nbsp;million hectares in 2000 has sharply increased anthropogenic pressure on water and soil resources [17].\u003c/p\u003e \u003cp\u003eThe use of groundwater in Uzbekistan has also rapidly increased, with the annual permitted limit at 6.8 km\u0026sup3;, while current use reaches 7.5 km\u0026sup3;/year, exceeding sustainable limits. Currently, 6.4% of irrigation water comes from groundwater, and this proportion increases during drought years. The annual recharge of groundwater is estimated at 23\u0026ndash;27 km\u0026sup3;, of which approximately 63% originates from anthropogenic sources, such as irrigation channels, reservoirs, and field seepage. This disrupts the natural hydrogeological balance and accelerates salinization processes [18\u0026ndash;20].\u003c/p\u003e \u003cp\u003eSoil salinization in irrigated agro-ecosystems is often caused by evaporation of the SWT, capillary rise, and negative anthropogenic factors. A sharp decline in the shallow water table disrupts optimal soil moisture regimes, leading to decreased crop yields, soil degradation, and reduced agro-ecosystem stability. Therefore, studying the spatial and seasonal dynamics of the SWT and its mineralization is of significant scientific and practical importance for ensuring agricultural sustainability, strengthening food security, and maintaining ecological balance [21, 22].\u003c/p\u003e \u003cp\u003eThe Republic of Karakalpakstan, located in the Aral Sea basin, is the most ecologically vulnerable region of Uzbekistan. Covering 166,600 km\u0026sup2;, it accounts for 37.1% of the country\u0026rsquo;s territory, 21.3% of irrigated lands, and 48.5% of pasture resources. The climate is sharply continental and extremely arid, with an average annual precipitation of 110 mm and evaporation 9\u0026ndash;10 times higher than precipitation. During summer, temperatures can rise up to 46\u0026deg;C, accelerating soil moisture loss and salt accumulation [23].\u003c/p\u003e \u003cp\u003eHistorical hydromelioration data show that during 1965\u0026ndash;1970, expansion of irrigation systems caused the shallow water table to rise to only 1.2 m in many areas of Karakalpakstan, intensifying secondary salinization. Between 2007\u0026ndash;2012, reconstruction of collector-drainage systems lowered the SWT to 2.8\u0026ndash;3.0 m in some areas; however, this occurred alongside increased irrigation water demand and drying of the topsoil layer [24, 25].\u003c/p\u003e \u003cp\u003eRecent monitoring indicates significant spatial heterogeneity in the region. In particular, almost all districts of Karakalpakstan, especially Turtkul, Takhtakopir, and Shumanay districts, experienced fluctuations in the SWT of 1.0\u0026ndash;2.0 m over short periods, complicating irrigation management, yield stability, and water resource planning [26, 3, 27].\u003c/p\u003e \u003cp\u003e \u003cb\u003e1.2. Climatic and Agricultural Pressure in an Arid Region: Justification for Selecting the Takhtakopir District as a Study Area\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe study area was selected as the Takhtakopir district, located in the northeastern part of the Republic of Karakalpakstan. The district lies on the left bank of the lower reaches of the Amu Darya River and is geographically characterized by arid and semi-desert zones. Administratively, it borders the Beruniy district to the south, the Ellikqala district to the southeast, the Qoraozak district to the west, the Moynaq district to the northwest, and the Republic of Kazakhstan to the northeast and east. The district center is the town of Takhtakopir, approximately located at geographic coordinates 43\u0026deg;01\u0026prime;21\u0026Prime; N latitude and 60\u0026deg;17\u0026prime;19\u0026Prime; E longitude [28, 29].\u003c/p\u003e \u003cp\u003eThe total area of the Takhtakopir district is approximately 21.1 thousand km\u0026sup2;, of which 34,672 hectares are irrigated lands. Among these, 5,096 hectares are considered damaged primarily due to malfunctions in the irrigation network. The district\u0026rsquo;s relief is mainly flat, with occasional low elevations of the Beltov ridges and sandy massifs. The northeastern part of the district borders the Kyzylkum Desert, where sandy dunes, takyr (salt flats), and saline soils are widespread. The Borshin mountain is one of the relatively elevated relief elements in the region, with a height of 35\u0026ndash;37 m above the surrounding plains.\u003c/p\u003e \u003cp\u003eThe climate is sharply continental, with pronounced seasonal temperature variations. The annual average air temperature is around 11\u0026deg;C. In winter, the average temperature in January is \u0026minus;\u0026thinsp;6\u0026deg;C, with minimum temperatures potentially dropping to \u0026minus;\u0026thinsp;35\u0026deg;C. In summer, the average July temperature reaches 27\u0026deg;C, with maximums up to 43\u0026deg;C. The annual precipitation is approximately 100 mm, mostly falling during winter and spring. Such climatic conditions are characterized by high evaporation, water scarcity, and an increased risk of soil salinization.\u003c/p\u003e \u003cp\u003eThe soil cover of the Takhtakopir district is diverse, predominantly comprising saline, swamp-meadow, gray, takyr, sandy, and brown soils. Due to its proximity to the Amu Darya delta, the relatively shallow groundwater in some areas has intensified secondary salinization processes. Agriculture in the district is mainly specialized in cotton, cereals, rice cultivation, and livestock farming. Irrigation is supplied through the Quvonchyorma canal and its branches (Timpiy, Bozyop, Jilvonyop, Badrakyop). The pastures adjacent to the Kyzylkum area serve as important resources for livestock, especially sheep and Karakul breeding.\u003c/p\u003e \u003cp\u003eThe availability of irrigated lands supports the development of intensive farming; however, high dependence on water resources and the risk of salinization remain primary factors limiting the sustainability of agro-ecosystems. Therefore, considering the above information, the study area is an ecologically and agro-hydrologically important research site. It combines arid climatic conditions, complex hydrogeological structures, and intensive agricultural activity, making it suitable for studying the dynamics of the SWT and salinization processes [30\u0026ndash;36].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.3. Distinction and Necessity of the Study\u003c/h2\u003e \u003cp\u003eThe object of this study is the SWT in the 0\u0026ndash;5 m depth ranges from the soil surface in the Takhtakopir district, located in the northwestern part of Uzbekistan within the Republic of Karakalpakstan. The research focuses on 250 observation wells that measure the SWT and salinity levels, analyzing their temporal variations over multiple years through detailed, specific investigations.\u003c/p\u003e \u003cp\u003eThe distinctive contribution of this study, addressing a gap in previous research, lies in the fact that, to date, no comprehensive scientific investigations have been conducted on the SWT and its salinization in the Takhtakopir district, considering the complex continental climate of the Republic of Karakalpakstan and the integrated effects of anthropogenic factors. In other words, most prior studies have examined water salinization only at a general spatial scale, without adequately analyzing the spatio-temporal variations of salinization or the interactions of multiple factors\u0026mdash;such as groundwater level, water mineralization, soil mechanical composition, crop types, and climatic conditions\u0026mdash;at a regional level. Filling this scientific gap is the main relevance of the present study.\u003c/p\u003e \u003cp\u003eThe results of this research are not only practically significant for irrigated areas in the Takhtakopir district but also for regions across Central Asia where the SWT faces high risks of salinization and declining water tables. Internationally, these findings can inform strategies for managing shallow water tables and soil salinization, fulfilling key scientific objectives.\u003c/p\u003e \u003cp\u003eMoreover, the main logical hypothesis of this study is that, under climate change conditions in arid and semi-arid regions, the conventional mechanism\u0026mdash;namely, excessive evaporation of the SWT and the deposition of salts on the soil surface leading to soil degradation\u0026mdash;is well known. This research aims to determine how this process occurs in the arid Takhtakopir district, either validating or refuting the hypothesis, and based on the findings, to develop a new, region-specific scientific hypothesis. Accordingly, it analyzes the temporal changes in variable indicators such as groundwater salinity over the years using mathematical, statistical, and geostatistical methods. Ultimately, the study seeks to create a predictive mathematical model and provide recommendations for improving the ecological condition of the region.\u003c/p\u003e \u003c/div\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Area and Research Methodology\u003c/h2\u003e \u003cp\u003eThe study was conducted during 1990\u0026ndash;2024 in the irrigated areas of the Takhtakopir district, with the main empirical part of the research carried out based on a total of 256 observation wells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) to determine SWTs and water mineralization, as well as to evaluate their seasonal dynamics. The status of the shallow groundwater was investigated through observation wells located at 0\u0026ndash;5(6) m depths from the soil surface.\u003c/p\u003e \u003cp\u003eThe empirical part of this research was conducted in the soil and water laboratory of the Meliorative Expedition under the Ministry of Water Resources of the Republic of Karakalpakstan, and was based on both long-term monitoring data of the organization and collected field data (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Water samples were collected monthly throughout the year, and the depth of the SWT relative to the soil surface was measured in the field, with its temporal variations recorded. Groundwater mineralization was determined in the laboratory using the gravimetric method: the initial mass of water samples was measured on an analytical balance, then fully dried in a thermostatic water bath (using a TDS measurement device), and the mass of the resulting dry residue was reweighed to calculate the total dissolved solids (TDS) accurately [3, 36].\u003c/p\u003e \u003cp\u003eThe field and laboratory data obtained through this empirical analysis were subjected to statistical processing to identify the spatio-temporal patterns of the SWT and groundwater salinization, as well as to assess their anticipated future ecological conditions (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the field, the SWT was monitored using a specialized electronic water level meter (driver), which was lowered into the well. The reading was recorded when the sensor made contact with the water surface. Measurements at each point were repeated at least three times, and the average values were calculated. All data were systematically recorded by date, time, and well identification number.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Dynamics of the SWT\u003c/h2\u003e \u003cp\u003eIn the study area, the SWT observed in wells during 1990\u0026ndash;2024 varied within a wide range of annual average depths from 166.67 cm to 452.33 cm relative to the soil surface. These values are measured downward from the soil surface, and an increase in the indicator indicates deepening of the water table, i.e., the groundwater is moving farther from the soil surface. The large amplitude fluctuations observed demonstrate the hydrological system\u0026rsquo;s relative temporal instability and its high sensitivity to climatic and anthropogenic factors.\u003c/p\u003e \u003cp\u003eDuring 1990\u0026ndash;1999, the SWT remained relatively stable, with average depths ranging from 170 to 190 cm. Specifically, during 1990\u0026ndash;1994, the average depth was 178.99\u0026thinsp;\u0026plusmn;\u0026thinsp;6.15 cm, and during 1995\u0026ndash;1999, it was 181.04\u0026thinsp;\u0026plusmn;\u0026thinsp;9.33 cm. The low standard deviation values indicate that the water table was close to the soil surface, and the hydrological regime was relatively stable. This condition allowed capillary rise to maintain moisture in the root zone, creating favorable conditions for agro-ecosystems.\u003c/p\u003e \u003cp\u003eHowever, the period 2000\u0026ndash;2004 stands out as a turning point in the shallow water table dynamics. During this period, the average depth increased to 309.70\u0026thinsp;\u0026plusmn;\u0026thinsp;111.45 cm, representing a 71.1% deepening compared to 1995\u0026ndash;1999. The very high standard deviation indicates significant hydrological irregularities during these years. Notably, in 2001\u0026ndash;2002, depths of 432\u0026ndash;452 cm were recorded, which sharply reduced the groundwater\u0026rsquo;s role in maintaining soil moisture.\u003c/p\u003e \u003cp\u003eIn the subsequent period (2005\u0026ndash;2009), the water table rose closer to the soil surface, with an average depth of 229.36\u0026thinsp;\u0026plusmn;\u0026thinsp;53.16 cm. This represents a 25.9% decrease relative to the previous period, indicating the short-term adaptability of the hydrological system. However, the relatively high standard deviation (\u0026plusmn;\u0026thinsp;53.16 cm) shows that fluctuations persisted during this period.\u003c/p\u003e \u003cp\u003eDuring 2010\u0026ndash;2014, the average SWT depth was 208.38\u0026thinsp;\u0026plusmn;\u0026thinsp;20.07 cm, decreasing by 9.14% compared to the previous period. In 2015\u0026ndash;2019, this value further decreased to 201.55\u0026thinsp;\u0026plusmn;\u0026thinsp;25.82 cm, showing an additional 3.28% decline. Although the trend of rising closer to the surface continued, the rate of change slowed, indicating a relatively stabilized phase. Nevertheless, the water table had not fully returned to the natural equilibrium level observed in the 1990s.\u003c/p\u003e \u003cp\u003eThe most recent period (2020\u0026ndash;2024) indicates a renewed phase of deepening of the SWT. During this period, the average depth reached 282.32\u0026thinsp;\u0026plusmn;\u0026thinsp;30.67 cm, representing a sharp 40.07% increase compared to 2015\u0026ndash;2019. This trend is strongly associated with regional warming, increased evaporation, and heightened anthropogenic pressure on water resources, reflecting a significant reduction in the soil\u0026rsquo;s ability to be replenished through capillary rise (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Annual Dynamics of TDS\u003c/h2\u003e \u003cp\u003eThe annual average TDS (Total Dissolved Solids) values of the SWT observed in the study area during 1991\u0026ndash;2024 exhibited significant variability. These fluctuations are critically important for assessing water quality, hydrological stability, and the ecological condition of the region. From this perspective, analyzing TDS values in five-year intervals allowed identification of long-term trends and short-term fluctuations within the hydrological system.\u003c/p\u003e \u003cp\u003eDuring 1991\u0026ndash;1995, the average TDS ranged from 3,122\u0026thinsp;\u0026plusmn;\u0026thinsp;351 mg/L, with minimum and maximum values of 2,837 mg/L and 3,596 mg/L, respectively. Although mineralization was relatively high during this period, the standard deviation was low, indicating short-term stability of the hydrological system. This suggests that the mineral content of groundwater significantly contributed to salinization within the agro-ecosystem\u0026rsquo;s edaphic environment.\u003c/p\u003e \u003cp\u003eIn 1996\u0026ndash;2000, TDS increased to an average of 3,199\u0026thinsp;\u0026plusmn;\u0026thinsp;496 mg/L, reaching a maximum of 3,767 mg/L. This reflects increased hydrological instability and notable changes in water quality. The heightened salinization during this period may have adversely affected soil properties and irrigation efficiency.\u003c/p\u003e \u003cp\u003eDuring 2001\u0026ndash;2005, the average TDS was 2,902\u0026thinsp;\u0026plusmn;\u0026thinsp;857 mg/L, with maximum and minimum values of 4,009 mg/L and 2,241 mg/L, respectively. The very high standard deviation indicates considerable disruption in the hydrological system. TDS during this period not only fluctuated but also exhibited extreme increases and decreases compared to previous years, likely resulting from combined climatic and anthropogenic impacts.\u003c/p\u003e \u003cp\u003eBetween 2006\u0026ndash;2010, the average TDS rose to 3,660\u0026thinsp;\u0026plusmn;\u0026thinsp;282 mg/L, with a maximum of 4,000 mg/L, reflecting high levels of groundwater salinization. However, the lower standard deviation suggests that short-term hydrological stability was maintained. This period highlighted the need for monitoring water quality and implementing measures to restore water balance.\u003c/p\u003e \u003cp\u003eFrom 2011\u0026ndash;2015, the average TDS decreased to 3,199\u0026thinsp;\u0026plusmn;\u0026thinsp;154 mg/L, with minimum and maximum values ranging from 2,940\u0026ndash;3,420 mg/L. This decline and reduced variability indicate short-term stability and relative normalization of water resources. During this period, mineralization remained at moderate levels, showing that water quality did not deteriorate significantly.\u003c/p\u003e \u003cp\u003eFor 2016\u0026ndash;2020, TDS sharply declined to 2,952\u0026thinsp;\u0026plusmn;\u0026thinsp;333 mg/L, with a minimum of 2,440 mg/L and a maximum of 3,370 mg/L, indicating fluctuations in groundwater mineralization. Although the hydrological system demonstrated short-term adaptability, the salinization risk remained within a significant hazard category.\u003c/p\u003e \u003cp\u003eDuring 2021\u0026ndash;2024, the average TDS further decreased to 2,838\u0026thinsp;\u0026plusmn;\u0026thinsp;177 mg/L, with maximum and minimum values of 3,000 mg/L and 2,610 mg/L, respectively. This decline reflects a trend of improvement in groundwater mineralization within the hydrological system (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Mathematical modeling of the SWT and salinity based on linear regression\u003c/h2\u003e \u003cp\u003eBased on the last 34\u0026ndash;35 years of data from the monitoring wells of the designated shallow water, a mathematical model was developed using a linear regression equation (Eq.\u0026nbsp;1) to describe the water table and mineralization dynamics.\u003c/p\u003e \u003cp\u003eY\u0026thinsp;=\u0026thinsp;a\u0026thinsp;+\u0026thinsp;bX (1);\u003c/p\u003e \u003cp\u003eHere: Y represents the annual average SWT depth (cm) and TDS values (mg/L), X is the time index (forecast years), a is the initial regression intercept, and b is the annual average rate of change [37, 38].\u003c/p\u003e \u003cp\u003eAccording to the results of the developed mathematical model, between 2026 and 2050, the SWT is projected to decline by 1.81 cm per year, while TDS is expected to decrease by 8 mg/L annually. Based on this hypothesis, the anticipated conditions for the next periods can be analyzed as follows:\u003c/p\u003e \u003cp\u003eDuring 2026\u0026ndash;2029, the average water table is expected to be 200.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 cm, and TDS 2,928.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9 mg/L, indicating a decline in the water table while TDS remains relatively high, suggesting a continued risk of soil salinization.\u003c/p\u003e \u003cp\u003eFor 2030\u0026ndash;2034, the water table is projected at 207.4 cm, and TDS at 2,884 mg/L, reflecting a potentially complex ecological condition. On one hand, the decrease in TDS reduces the risk of soil salinization, but the further decline in the water table may increase the risk of insufficient soil moisture at the surface.\u003c/p\u003e \u003cp\u003eBetween 2035\u0026ndash;2039, the water table is expected to reach an average of 216.1 cm, and TDS 2,840 mg/L, showing long-term consistent declining trends for both variables. Similarly, during 2040\u0026ndash;2044, the water table and TDS are projected to decrease steadily to 227.0 cm and 2,805 mg/L, respectively.\u003c/p\u003e \u003cp\u003eFinally, for 2045\u0026ndash;2050, the water table is anticipated to be 236.8 cm, and TDS 2,775 mg/L. During this period, the continued decrease in TDS further reduces the risk of soil salinization.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual mean SW depth and TDS concentration (cm, mg/L) and comparison of empirical and predicted values for each five-year interval (1990\u0026ndash;2024)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eEmpirical data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e \u003cp\u003ePredicted data\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (sm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (sm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1990\u0026ndash;1992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180.03\u0026thinsp;\u0026plusmn;\u0026thinsp;7.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e189.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2025\u0026ndash;2027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e198.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e196.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e200.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1993\u0026ndash;1995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180.69\u0026thinsp;\u0026plusmn;\u0026thinsp;6.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e173.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e187.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2028\u0026ndash;2030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e203.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e205.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1996\u0026ndash;1998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183.75\u0026thinsp;\u0026plusmn;\u0026thinsp;7.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2031\u0026ndash;2033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e209.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e207.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e211.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e291.78\u0026thinsp;\u0026plusmn;\u0026thinsp;146.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e166.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e452.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2034\u0026ndash;2036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e214.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e212.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e216.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2002\u0026ndash;2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e279.95\u0026thinsp;\u0026plusmn;\u0026thinsp;132.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e432.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2037\u0026ndash;2039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e220.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e218.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e221.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2005\u0026ndash;2007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e191.62\u0026thinsp;\u0026plusmn;\u0026thinsp;6.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e183.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e196.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2040\u0026ndash;2042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e225.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e223.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e227.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2008\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e249.33\u0026thinsp;\u0026plusmn;\u0026thinsp;67.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e309.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2043\u0026ndash;2045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e230.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e229.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e232.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2011\u0026ndash;2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214.31\u0026thinsp;\u0026plusmn;\u0026thinsp;12.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e204.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e228.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2046\u0026ndash;2048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e236.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e234.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e238.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195.97\u0026thinsp;\u0026plusmn;\u0026thinsp;23.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e222.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2049\u0026ndash;2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e240.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e240.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e241.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2017\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214.25\u0026thinsp;\u0026plusmn;\u0026thinsp;25.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e189.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e239.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" morerows=\"2\" nameend=\"c8\" namest=\"c5\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e277.06\u0026thinsp;\u0026plusmn;\u0026thinsp;41.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e313.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u0026ndash;2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e290.21\u0026thinsp;\u0026plusmn;\u0026thinsp;5.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e294.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eEmpirical data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e \u003cp\u003ePredicted data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (TDS, mg/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (TDS, mg/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1991\u0026ndash;1993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3289.67\u0026thinsp;\u0026plusmn;\u0026thinsp;380.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2025\u0026ndash;2027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2937.02\u0026thinsp;\u0026plusmn;\u0026thinsp;8.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2928.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2945.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1994\u0026ndash;1996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2948.33\u0026thinsp;\u0026plusmn;\u0026thinsp;139.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2028\u0026ndash;2030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2912.94\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2904.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2920.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1997\u0026ndash;1999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3036.67\u0026thinsp;\u0026plusmn;\u0026thinsp;497.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2031\u0026ndash;2033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2888.86\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2880.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2896.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2000\u0026ndash;2002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3342.00\u0026thinsp;\u0026plusmn;\u0026thinsp;953.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2034\u0026ndash;2036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2864.78\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2856.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2872.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2003\u0026ndash;2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2446.67\u0026thinsp;\u0026plusmn;\u0026thinsp;182.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2037\u0026ndash;2039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2840.70\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2832.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2848.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2006\u0026ndash;2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3630.00\u0026thinsp;\u0026plusmn;\u0026thinsp;380.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2040\u0026ndash;2042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2816.63\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2808.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2824.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2009\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3406.67\u0026thinsp;\u0026plusmn;\u0026thinsp;335.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2043\u0026ndash;2045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2792.55\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2784.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2800.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2012\u0026ndash;2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3104.67\u0026thinsp;\u0026plusmn;\u0026thinsp;143.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2046\u0026ndash;2048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2768.47\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2760.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2776.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2015\u0026ndash;2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3076.67\u0026thinsp;\u0026plusmn;\u0026thinsp;551.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2049\u0026ndash;2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2748.41\u0026thinsp;\u0026plusmn;\u0026thinsp;5.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2744.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2752.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2813.33\u0026thinsp;\u0026plusmn;\u0026thinsp;219.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" morerows=\"2\" nameend=\"c8\" namest=\"c5\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u0026ndash;2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2783.33\u0026thinsp;\u0026plusmn;\u0026thinsp;198.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3000.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Multivariate Statistical Analysis of Hydrogeochemical Characteristics of the Water Sources in Arid Agroecosystems\u003c/h2\u003e \u003cp\u003eIn the study area, the impact of two types of water resources\u0026mdash;namely, the shallow water and natural underground drinking water\u0026mdash;on water quality was assessed through statistical analysis. According to the results obtained using the Pearson correlation coefficient, an increase in the mineralization or salinity of the shallow water corresponded to a parallel increase in the salinity of the natural underground drinking water [3, 35, 36].\u003c/p\u003e \u003cp\u003eSpecifically, a strong positive correlation was observed between the mineralization of the SWT (TDS_S) and the mineral content (TDS_G), chloride (Cl⁻), and total hardness (TH) of natural underground drinking water. The correlation coefficients were as follows: TDS_S and TDS_G, r\u0026thinsp;=\u0026thinsp;0.74; TDS_S and Cl⁻, r\u0026thinsp;=\u0026thinsp;0.43; TH and Cl⁻, r\u0026thinsp;=\u0026thinsp;0.94; and TH and SO₄\u0026sup2;⁻, r\u0026thinsp;=\u0026thinsp;0.91, indicating a strong positive relationship between the two types of water resources. This suggests that nitrogen compounds are linked to mineral-rich water sources, likely influenced by agricultural runoff or surface water infiltration.\u003c/p\u003e \u003cp\u003eFurthermore, a moderate but weak correlation between NO₃⁻ and TDS_S (r\u0026thinsp;=\u0026thinsp;0.22) indicates that a portion of nitrate in the groundwater originates from surface water sources. In other words, groundwater quality is significantly affected by the chemical characteristics of surface water, with notable correlations observed for parameters such as TDS, Cl⁻, TH, and NO₃⁻ [3]. Previous studies have also demonstrated that surface water infiltration and leaching of minerals considerably influence groundwater quality, particularly in terms of total dissolved solids, hardness, and nitrate concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; see also Figs. S1 and S2 in the Supplementary Material).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Comparative Analysis of the Study Area from Global and Cross-Regional Perspectives\u003c/h2\u003e \u003cp\u003eWhen comparing the SWT levels in the study area at local and global scales, it becomes evident that, while the study site differs significantly from other regions in certain aspects, some similarities can also be observed. Specifically, in irrigated areas of Central Asia and northwestern China, the SWT depths vary considerably across different regions (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Typically, for irrigated lands, the recommended SW level is 2\u0026ndash;3 m, as this range minimizes the risks of soil salinization and waterlogging. However, considering the complex ecological characteristics of these ecosystems and the combined effects of climate and anthropogenic factors, this optimal range may not always represent the ideal threshold, and slight deviations are possible [39\u0026ndash;43].\u003c/p\u003e \u003cp\u003eGlobally recognized optimal ranges allow for regional comparisons. For instance, in the Khorezm region of northwestern Uzbekistan, the SWT consistently remains close to the productive soil layer, with depths ranging from 1.1\u0026ndash;1.4 m during non-vegetation periods (particularly during soil leaching phases) and 0.9\u0026ndash;1.4 m during peak irrigation [44]. The proximity of the water table to the soil surface exacerbates salinization, increases the risk of waterlogging, and can reduce oxygen availability to plant roots. Spatial variability in this region is low, and water levels show minimal differences across the landscape, primarily due to insufficient water management and suboptimal leaching practices [45, 46].\u003c/p\u003e \u003cp\u003eConversely, in the Ferghana Valley, located among the mountains of Central Asia and covering eastern Uzbekistan, when the shallow water rises from 3 m to 1.5 m, crop evapotranspiration (ET) significantly increases. Specifically, under rainfed conditions, ET rises from 36 cm to 57.9 cm, while under full irrigation, it increases from 58 cm to 66.5 cm [47]. The contribution of shallow groundwater to ET is substantial due to both its shallowness and the irrigation regime; in high-deficit irrigation and loamy soils, this contribution exceeds 60%. Consequently, higher water table levels increase evaporation but reduce the efficiency of water use by crops. Additionally, salts released through evaporation accumulate in the soil surface layer, promoting secondary soil salinization and land degradation. In the Ferghana Valley, deviations from the optimal shallow groundwater level are largely associated with anthropogenic factors, particularly irrigation practices that are not well-adapted to local conditions [48\u0026ndash;50].\u003c/p\u003e \u003cp\u003eIn the study site of the Takhtakopir district, the SWT exhibited large-amplitude fluctuations between 1990 and 2024. For example, the average depth was 178.99\u0026thinsp;\u0026plusmn;\u0026thinsp;6.15 cm in 1990\u0026ndash;1994, rising to 309.70\u0026thinsp;\u0026plusmn;\u0026thinsp;111.45 cm in 2000\u0026ndash;2004, representing a 71.1% increase in depth. In the most recent period (2020\u0026ndash;2024), the average depth reached 282.32\u0026thinsp;\u0026plusmn;\u0026thinsp;30.67 cm, indicating a substantial reduction in the soil\u0026rsquo;s capacity to retain moisture via capillary rise. Comparing the Takhtakopir district with the Ferghana and Khorezm regions, it becomes apparent that the effects of ET and soil salinization depend on the combined influence of climatic and anthropogenic factors.\u003c/p\u003e \u003cp\u003eOn a broader Central Asian scale, in southeastern Kazakhstan, the shallow water depths range from 0.96 to 4.32 m. In some areas, rice-based irrigation reduces waterlogging, whereas in others, salinization persists [51, 52]. Therefore, adaptive irrigation and drainage restoration play critical roles in enhancing ecological stability and crop productivity. In contrast, in northwestern China, shallow groundwater occurs at much greater depths (2.97\u0026ndash;6.33 m), which reduces soil moisture and salinization risk but creates water deficits for crops [53, 54]. This situation is essentially opposite to the issues observed in the aforementioned regions.\u003c/p\u003e \u003cp\u003eConsidering these similarities and differences, a regional comparison indicates the following: in Khorezm and Ferghana, the SW located near the soil surface increases soil salinization and waterlogging risks; in the Takhtakopir district, deepening shallow groundwater reduces ET and soil moisture, while simultaneously lowering the risk of salinization. Similar ecological issues are partially observed in southeastern Kazakhstan and northwestern China, where the SW levels in agroecosystems affect crop\u0026ndash;water dynamics depending on irrigation practices and water management systems.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative analysis of the SW depth, associated problems, and agroecological consequences across different territories\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe shallow water level (annual/monthly/seasonal)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe shallow water level issue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eConsequences / Outcomes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAsia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUzbekistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKhorezm province\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon-vegetation period: 1.1\u0026ndash;1.4 m; Irrigation period: 0.9\u0026ndash;1.4 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eShallow groundwater level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSoil salinization, waterlogging, and insufficient oxygen for plant roots\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUzbekistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFergana Valley\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 m to 1.5 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eShallow groundwater level, high evapotranspiration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eET increases, the efficiency of plant water use decreases; soil salinization in the top layer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUzbekistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTakhtakupir, Karakalpakstan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1990\u0026ndash;1994: 178.99\u0026thinsp;\u0026plusmn;\u0026thinsp;6.15 cm; 2000\u0026ndash;2004: 309.70\u0026thinsp;\u0026plusmn;\u0026thinsp;111.45 cm; 2020\u0026ndash;2024: 282.32\u0026thinsp;\u0026plusmn;\u0026thinsp;30.67 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDeepening groundwater level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eET and soil moisture decreases, capillary rise is limited\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKazakhstan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSoutheast Kazakhstan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96\u0026ndash;4.32 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHeterogeneous groundwater level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRice-based irrigation maintains salinization in some areas, reduces waterlogging in others\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorthwest China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.97\u0026ndash;6.33 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDeep groundwater level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSoil moisture decreases, salinization decreases, but crops face water shortage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusions and Recommendations","content":"\u003cp\u003eLong-term monitoring and analyses based on linear regression models conducted in the Takhtakopir district demonstrated that SW levels and salinity are highly sensitive to climatic and anthropogenic factors in arid regions. Based on empirical observations and mathematical modeling, the following key conclusions were drawn:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe dynamics of the SW in the study area are primarily associated with climate warming, increased evaporation, and the rising load on irrigated lands. Between 1990 and 2024, significant instability and sharp fluctuations were observed. In particular, the rapid deepening of the SW during 2000\u0026ndash;2004 confirmed the high sensitivity of the hydrological system to climatic stress.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eGroundwater salinity, expressed as TDS, remained at elevated levels over the long term, indicating a persistent risk of salinization in irrigated agroecosystems. Periodic fluctuations in TDS values were closely linked to hydrological instability, imbalances in the water budget, and the intensification of anthropogenic impacts.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eForecasts based on the linear regression model suggest that between 2026 and 2050, shallow groundwater levels will decrease on average by 1.81 cm per year, while TDS will decline by approximately 8 mg/L per year. Although this trend indicates a relative reduction in salinization risk, the deepening of the shallow water table may exacerbate soil moisture deficits and reduce the stability of agroecosystems.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eBased on these conclusions, the following recommendations are proposed:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIn regions with sharply continental climates, such as the Takhtakopir district, sustainable agriculture requires the selection of crop types adapted to local climatic conditions and careful planning of crop rotations. To develop climate-resilient agroecosystems capable of mitigating excessive evaporation during hot summer periods, it is recommended to establish plant communities with high ecological value and to plant trees around micro- and macro-agroecosystems for wind protection and microclimate regulation.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo prevent excessive water loss due to evaporation during hot periods, full transition to innovative drip irrigation systems is advised, along with the integration of modern soil moisture monitoring technologies. Such measures can effectively mitigate anticipated future challenges in the region.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included within this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted under the collaboration agreement (Contract No. 04-73, May 18, 2023) between the National University of Uzbekistan named after Mirzo Ulugbek and the Meliorative Expedition Bureau under the Ministry of Water Resources of the Republic of Karakalpakstan. We sincerely thank both institutions, as well as the Karakalpak State University named after Berdakh, for their support in organizing and conducting this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNilufar Rajabova is responsible for concept development, study design, manuscript writing, data analysis, regression modeling, and GIS mapping; Mexriban Allanazarova and Toshev Shakhriyor are responsible for data collection, GIS mapping support, and fieldwork; Rakhimov Nodirjon and Gafurov Timur are responsible for laboratory analysis, data processing, and visualization; Kuralay Tureeva and Luiza Bakhieva assisted in quality control and data organization; Elmira Maturazova contributed to literature review and manuscript editing; Oybek Yeshchanov and Nasiba Navrozboyeva assisted in data collection and fieldwork; Remzi Suleymanov is responsible for supervision and critical review of the manuscript. All authors have reviewed the results and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo external funding was received for this study, and all research activities were carried out using institutional resources without financial support from public, commercial, or not-for-profit funding agencies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval and Permissions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted within the framework of a formal collaboration between the National University of Uzbekistan named after Mirzo Ulugbek and the Meliorative Expedition under the Ministry of Water Resources of the Republic of Karakalpakstan (Contract No. 04-73, dated May 18, 2023).\u003c/p\u003e\n\u003cp\u003eThis study was carried out as part of the scientific research program of the Department of Ecology of the National University of Uzbekistan for 2021-2025, entitled \u0026ldquo;Investigation of bioecological characteristics of flora and fauna under global climate change, conservation of biodiversity, assessment of the ecological state of soil and water resources, and development of scientific and practical bases for the rational use of natural resources,\u0026rdquo; and it was also conducted within the framework of the practical project \u0026ldquo;Ensuring the spatial diversity of the regional model of radiation and water-salt balance in the southern part of the Aral Sea basin using geoinformatics methods (No. 5721-122061)\u0026rdquo; (2022-2025).\u003c/p\u003e\n\u003cp\u003eAll research activities, including field sampling and laboratory analysis, were conducted in accordance with the institutional guidelines, regulations, and standard procedures of the Meliorative Expedition. Groundwater and surface water data were obtained from long-term monitoring records of the organization. In addition, fieldwork was carried out jointly with laboratory specialists at designated observation wells for shallow water tables, and water samples were collected and analyzed following standard protocols.\u003c/p\u003e\n\u003cp\u003eAll necessary institutional permissions were obtained through the above-mentioned agreement. No human or animal subjects were involved in this study, and no additional ethical approval was required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence and requests for materials should be addressed to N.R.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnandhi, A., Book, R., \u0026amp; Ozbay, G. (2025). A novel framework to represent hypoxia in coastal systems. Land, 14(6), 1169. https://doi.org/10.3390/land14061169 \u003c/li\u003e\n\u003cli\u003eRajabova, N., Sherimbetov, V., Sadiq, R., \u0026amp; Farouk Aboukila, A. (2025). An assessment of collector-drainage water and groundwater\u0026mdash;an application of CCME WQI model. 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Science of the Total Environment, 820, 153222. https://doi.org/10.1016/j.scitotenv.2022.153222\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Shallow water table, Groundwater mineralization, Total dissolved solids (TDS), Arid irrigated ecosystems, Soil salinization, Climate change impacts, Predictive modeling","lastPublishedDoi":"10.21203/rs.3.rs-9247677/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9247677/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates long-term dynamics of SWTs and mineralization in arid irrigated ecosystems under climate variability, using the Takhtakopir district of the Republic of Karakalpakstan (north-western Uzbekistan) as a case study. Empirical observations from 256 monitoring wells collected during 1990\u0026ndash;2024 were analyzed to evaluate temporal variations in SWTs and total dissolved solids (TDS) and assess their agroecological implications.\u003c/p\u003e \u003cp\u003eResults show pronounced long-term variability in SWTs. Average annual SWTs ranged from 1.7 to 4.5 m, indicating substantial instability of the regional hydro-ecological system. A marked deepening occurred during 2000\u0026ndash;2004, when the mean depth increased to 309.70\u0026thinsp;\u0026plusmn;\u0026thinsp;111.45 cm from 178.99\u0026thinsp;\u0026plusmn;\u0026thinsp;6.15 cm in 1990\u0026ndash;1994, an increase of ~\u0026thinsp;71%. Recent measurements (2020\u0026ndash;2024) indicate an average depth of 282.32\u0026thinsp;\u0026plusmn;\u0026thinsp;30.67 cm, reflecting a continuing trend toward deeper water tables and reduced capillary contribution to soil moisture. Water mineralization remained high, with TDS ranging from 2800 to 3700 mg L⁻\u0026sup1;, indicating persistent soil salinization risks.\u003c/p\u003e \u003cp\u003eThe study area\u0026rsquo;s SWT differs from other Central Asian regions: Khorezm (0.9\u0026ndash;1.4 m, salinity, waterlogging), Fergana (1.5\u0026ndash;3 m, increased evapotranspiration), and North-West China (2.97\u0026ndash;6.33 m, lower salinity, higher water deficit).\u003c/p\u003e \u003cp\u003eRegression-based projections suggest that during 2026\u0026ndash;2050, SWTs may decline by ~\u0026thinsp;1.81 cm yr⁻\u0026sup1;, while TDS may decrease by ~\u0026thinsp;8 mg L⁻\u0026sup1; yr⁻\u0026sup1;. These trends may reduce salinity risks but could increase soil moisture deficits, potentially affecting agroecosystem stability. Overall, the findings underscore the importance of long-term SWT monitoring and integrated water-management strategies to support ecological sustainability in arid irrigated regions.\u003c/p\u003e","manuscriptTitle":"Long-Term Monitoring and Regression Modeling of Shallow Water Tables (SWTs) and Salinity Dynamics in an Arid Irrigated Region of Central Asia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 16:43:12","doi":"10.21203/rs.3.rs-9247677/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"97365611357527592380710715956196430653","date":"2026-04-22T07:22:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"127517584853558015932590271324163096291","date":"2026-04-07T09:01:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"103828350330485323132260926326215328296","date":"2026-04-05T21:13:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-05T08:25:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-04T05:29:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-01T13:27:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-01T06:53:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-04-01T06:45:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"032f7b34-435b-407a-8549-dcee24b9ff73","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":65840515,"name":"Earth and environmental sciences/Climate sciences"},{"id":65840516,"name":"Biological sciences/Ecology"},{"id":65840518,"name":"Earth and environmental sciences/Ecology"},{"id":65840520,"name":"Earth and environmental sciences/Environmental sciences"},{"id":65840522,"name":"Earth and environmental sciences/Hydrology"}],"tags":[],"updatedAt":"2026-04-09T16:43:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 16:43:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9247677","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9247677","identity":"rs-9247677","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}