Aral Sea Basin Research Articles

Afforestation of Degraded Croplands as a Water-Saving Option in Irrigated Region of the Aral Sea Basin

Climate change is likely to decrease surface water availability in Central Asia, thereby necessitating land use adaptations in irrigated regions. The introduction of trees to marginally productive croplands with shallow groundwater was suggested for irrigation water-saving and improving the land’s productivity. Considering the possible trade-offs with water availability in large-scale afforestation, our study predicted the impacts on water balance components in the lower reaches of the Amudarya River to facilitate afforestation planning using the Soil and Water Assessment Tool (SWAT). The land-use scenarios used for modeling analysis considered the afforestation of 62% and 100% of marginally productive croplands under average and low irrigation water supply identified from historical land-use maps. The results indicate a dramatic decrease in the examined water balance components in all afforestation scenarios based largely on the reduced irrigation demand of trees compared to the main crops. Specifically, replacing current crops (mostly cotton) with trees on all marginal land (approximately 663 km2) in the study region with an average water availability would save 1037 mln m3 of gross irrigation input within the study region and lower the annual drainage discharge by 504 mln m3. These effects have a considerable potential to support irrigation water management and enhance drainage functions in adapting to future water supply limitations.

Agricultural impacts drive longitudinal variations of riverine water quality of the Aral Sea basin (Amu Darya and Syr Darya Rivers), Central Asia

River ecosystems are under increasing stress in the background of global change and ever-growing anthropogenic impacts in Central Asia. However, available water quality data in this region are insufficient for a reliable assessment of the current status, which come as no surprise that the limited knowledge of regulating processes for further prediction of solute variations hinders the development of sustainable management strategies. Here, we analyzed a dataset of various water quality variables from two sampling campaigns in 2019 in the catchments of two major rivers in Central Asia—the Amu Darya and Syr Darya Rivers. Our results suggested high spatial heterogeneity of salinity and major ion components along the longitudinal directions in both river catchments, pointing to an increasing influence of human activities toward downstream areas. We linked the modeling outputs from the global nutrient model (IMAGE-GNM) to riverine nutrients to elucidate the effect of different natural and anthropogenic sources in dictating the longitudinal variations of the riverine nutrient concentrations (N and P). Diffuse nutrient loadings dominated the export flux into the rivers, whereas leaching and surface runoff constituted the major fractions for N and P, respectively. Discharge of agricultural irrigation water into the rivers was the major cause of the increases in nutrients and salinity. Given that the conditions in Central Asia are highly susceptible to climate change, our findings call for more efforts to establish holistic management of water quality.

A genomic perspective on an old question: Salmo trouts or Salmo trutta (Teleostei: Salmonidae)?

There are particular challenges in defining the taxonomic status of recently radiated groups due to the low level of phylogenetic signal. Members of the Salmo trutta species-complex, which mostly evolved during and following the Pleistocene, show high morphological and ecological diversity that, along with their very wide geographic distribution, have led to morphological description of 47 extant nominal species. However, many of these species have not been supported by previous phylogenetic studies, which could be partly due to lack of significant genetic differences among them, the limited resolution offered by molecular methods previously used, as well as the often local scale of these studies. The development of next-generation sequencing (NGS) and related analytical tools have enhanced our ability to address such challenging questions. In this study, Genotyping-by-Sequencing (GBS) of 15,169 filtered SNPs and mitochondrial DNA (mtDNA) D-loop sequences were combined to assess the phylogenetic relationships among 166 brown trouts representing 21 described species and three undescribed groups collected from 84 localities throughout their natural distribution in Europe, west Asia, and North Africa. The data were analysed using different clustering algorithms (admixture analysis and discriminant analysis of principal components-DAPC), a Bayes Factor Delimitation (BFD) test, species tree reconstruction, gene flow tests (three- and four-population tests), and Rogue taxa identification tests. Genomic contributions of the Atlantic lineage brown trout were found in all major sea basins excluding the North African and Aral Sea basins, suggesting introgressive hybridization of native brown trouts driven by stocking using strains of the Atlantic lineage. After removing the phylogenetic noise caused by the Atlantic brown trout, admixture clusters and DAPC clustering based on GBS data, respectively, resolved 11 and 13 clusters among the previously described brown trout species, which were also supported by BFD test results. Our results suggest that natural hybridization between different brown trout lineages has probably played an important role in the origin of several of the putative species, including S. marmoratus, S. carpio, S. farioides, S. pellegrini, S. caspius (in the Kura River drainage) and Salmo sp. in the Danube River basin. Overall, our results support a multi-species taxonomy for brown trouts. They also resolve some species in the Adriatic-Mediterranean and Black Sea drainages as members of very closely related genomic clusters that may need taxonomic revision. However, any final conclusions pertaining to the taxonomy of the brown trout complex should be based on an integrative approach combining genomic, morphological, and ecological data. To avoid challenges in taxonomy and conservation of species complexes like brown trouts, it is suggested to describe species based on genomic clusters of populations instead of describing species based only on morphologically differentiated single type populations.

Climatic Change and Human Activities Link to Vegetation Dynamics in the Aral Sea Basin Using NDVI

Climatic Change and Human Activities Link to Vegetation Dynamics in the Aral Sea Basin Using NDVI

Mathematical modeling for planning water-food-ecology-energy nexus system under uncertainty: A case study of the Aral Sea Basin

A bi-level decentralized chance-constrained programming (BDCP) method is developed for planning water-food-ecology-energy (WFEE) nexus system. The BDCP method has advantages in balancing the tradeoff between two-level stakeholders in hierarchical structure and reflecting the synergy effect among multiple divisions under random uncertainty. Then, a BDCP-WFEE model is formulated for the Aral Sea Basin, where the upper-level model aims to maximize system benefit, and the multiple divisions at the lower-level model aim to maximize food production, ecological water allocation, and electricity generation. Compared with the conventional single-level model, results obtained from the BDCP-WFEE model under multiple scenarios reveal that (i) the food production would increase by 2.0%–3.6% , implying that the food demand of additional 0.7 million people can be met; (ii) the ecological water allocation would increase by 0.9%–3.0%, denoting that the amount of water to the Aral Sea would reach 23.4 km3 at the end of planning period; (iii) the electricity generation would increase by 5.4%–8.5%. Besides, under the premise of ensuring food security, the proportion of agricultural water allocation in the Aral Sea Basin would reduce by 17.0%, indicating that the BDCP-WFEE model can effectively optimize the water allocation pattern and alleviate the conflict of water resources allocation among competetive users. These findings can provide policy support for managers to solve the problems of water shortage, food crisis, ecological degradation, and electricity insecurity.

Assessment of the Space-Time Dynamics of Soil Salinity in Irrigated Areas Under Climate Change: a Case Study in Sirdarya Province, Uzbekistan

Saline areas are progressively increasing in irrigated lands of the Aral Sea Basin and this obstructs intensive agricultural development and food security in this region. Such circumstances, leading to the expansion of salt-affected areas, are assumed to become climate change, rising of groundwater levels and its mineralizations, poor functioning of the collector-drainage system, and insufficient compliance with agro-technical requirements. These drivers, in turn, lead to the withdrawal of arable land for agricultural purposes and a significant drop in crop yields. Regarding Uzbekistan, this research on soil salinity assessment was conducted in the irrigated areas of the Sirdarya province by analyzing raw data derived from traditional methods from 2000 to 2015, as well as from 2016 to 2019, using the integrated traditional and geographic information systems (GIS)–based methods. Soil salinity maps of the Sirdarya province were created to investigate spatial and temporal changes in soil salinity using the inverse distance weighting (IDW) interpolation method based on the results of field survey and laboratory studies. The results of this research revealed that the IDW interpolation method had a great potential and accuracy to map longitudinal changes in salt-affected irrigated areas. Moreover, it was determined that soil salinity highly depends on local terrain conditions and there is a weak dependence on climatic factors. The main findings of this research advocate agricultural specialists and local farmers to get distinctly encouraged to take the following measures to address the actual soil salinity state in the irrigated areas of the province: targeted and economic use of irrigation water; existing drainage networks are in perfect working condition and monitoring their full effective operation; and, lastly, accelerating the integration of innovative GIS technologies into traditional methods.

Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model.

BackgroundAssociated with the significant decrease in water resources, natural vegetation degradation has also led to many widespread environmental problems in the Aral Sea Basin. However, few studies have examined long-term vegetation dynamics in the Aral Sea Basin or distinguished between natural vegetation and cultivated land when calculating the fractional vegetation cover.MethodsBased on the multi-temporal Moderate Resolution Imaging Spectroradiometer, this study examined the natural vegetation coverage by introducing the Linear Spectral Mixture Model to the Google Earth Engine platform, which greatly reduces the experimental time. Further, trend line analysis, Sen trend analysis, and Mann–Kendall trend test methods were employed to explore the characteristics of natural vegetation cover change in the Aral Sea Basin from 2000 to 2018.ResultsAnalyses of the results suggest three major conclusions. First, the development of irrigated agriculture in the desert area is the main reason for the decrease in downstream water. Second, with the reduction of water, the natural vegetation coverage in the Aral Sea Basin showed an upward trend of 17.77% from 2000 to 2018. Finally, the main driving factor of vegetation cover changes in the Aral Sea Basin is the migration of cultivated land to the desert.

High agricultural water consumption led to the continued shrinkage of the Aral Sea during 1992-2015.

The shrinkage of the Aral Sea started in the 1960s, and it has been continued for decades due to arguably both human and natural causes. However, the change of the Aral Sea in the post-Soviet era and its correlations with other changes in the extent of the basin have yet to be fully investigated. Here, we studied the land cover dynamics of the entire Aral Sea basin during 1992-2015 from the perspective of the surrounding environment, in order to investigate the causes of the Aral Sea further shrinkage in recent years. We used the annual Climate Change Initiative (CCI) land cover dataset to provide a spatiotemporally consistent delineation of land cover throughout the period. We found that: (1) In recent years, the Aral Sea continued shrinkage, approximately 50.38% of its water area in 1992 had dried out and turned into bare land by 2015. (2) The cultivated land area remained stable with a slight increase during the period, suggesting that no large-scale abandonment or expansion of farming extent occurred in the post-Soviet era. (3) Among other land types, urban areas are small and slightly expand at a rate of 0.024×104km2/year, suggesting urbanization, and likely contribute to more water consumption. Our investigation also found that climate warming increased the upstream runoff, which has a positive effect on the water supply of the Aral Sea. The impact of human activity on the Aral Sea is more pronounced than climate change. Therefore, the continued shrinkage of the Aral Sea was likely due to high water consumption of agriculture continues to exert the influence that existed in the 1960s. Other factors, such as urbanization have exacerbated this effect. The study examined the continued shrinkage of the Aral Sea in post-Soviet era, to provide an insight into the driving factors of the complex and still controversial Aral Sea crisis.

Numerical simulations of dust storms originated from dried lakes in central and southwest Asia: The case of Aral Sea and Sistan Basin

Ephemeral and dried lakes in southwest and central Asia, such as the Aral Sea and Hamouns in east Iran, are major sources of dust storms with an increasing tendency during the last decades due to anthropogenic influence and climate change. This study examines two characteristic dust-storm events originated from these areas on 12–15 July 2016 and 27–28 May 2018. Thermal low-pressure systems over topographic-low areas and the Caspian Sea High, along with pressure gradients and intense surface winds over the dust sources facilitated the dust outbreaks and transport. Three models (DREAM-NMME-MACC, CAMS and WRF-Chem) are synergized to simulate the spatial distribution of AOD and surface dust concentrations during the dust events. The results show that DREAM-NMME-MACC and WRF-Chem exhibit the highest discrepancies (R = 0.15–0.58; RMSE = 83%–125%) in representing the spatial and temporal distribution of dust compared to Terra-MODIS AODs, while CAMS reveals the best performance (R = 0.29–0.77; RSME = 67%–124%). All models significantly underestimate the high MODIS AODs, especially near the source areas, due to different dust schemes, soil conditions, meteorology and dynamic processes for dust emissions that they comprise. Furthermore, notable differences between the models are revealed in simulations of the PM 10 concentrations in Zabol, east Iran, as the models fail to reproduce the temporal evolution and high intensity of the dust event. In general, all models represent better the dust storm originated from Sistan (13–14 July 2016) rather than the Aralkum dust storm (27–28 May 2018), indicating an incapability in representing the soil characteristics in a progressively drying terrain.

Quantitative and qualitative assessment of collector-drainage waters in Aral Sea Basin: trends in Jizzakh region, Republic of Uzbekistan

Reintroduction of highly mineralized Collector-Drainage Waters (CDW) enhances the salinity of inland waterbodies and limits water suitability for downstream users. Detailed quantitative and qualitative research based on the inter-annual and multiyear generation trends of CDW in Central Asia could help to improve the irrigation system for agriculture and furthermore in determining opportunities for reutilization and biodiversity protection. This is the first long-term research designed to study the discharge, salinity, and ionic composition of CDW in the Jizzakh region (Uzbekistan). A database of field measurements of salinity gathered during the field expeditions from 2000 to 2017 was used in the study. Spring season showed highest CDW discharge where April showed maximum while lowermost was recorded for summers, especially during August. All main collectors showed continuous increments in salinity over the last two decades. This was neither in correlation with CDW discharge nor salinity changes from the irrigation water source (Syrdarya river). A considerable increase of collectors’ salinity within the range of 18%–37% was observed from upstream to downstream. The highest salinity values were observed during spring and lowest for summer with even lesser degree for the winter season. Among anions, sulfates were predominant followed by chlorides and bicarbonates; among cations, sodium was predominant followed by calcium and magnesium, which is different from the ionic composition of the water source. The study revealed that increased CDW discharge has not always resulted in low salinity and that high water years have not always caused a decline in CDW salinity showing that CDW discharge and salinity had differential dependence on each other.

Temporal and spatial variations in the terrestrial water storage across Central Asia based on multiple satellite datasets and global hydrological models

Arid regions of Central Asia have sensitive ecosystems that rely heavily on terrestrial water storage which is composed of surface water storage, soil moisture storage and groundwater storage. Therefore, we employed three Gravity Recovery and Climate Experiment (GRACE) satellite datasets and five global hydrological models (GHMs) to explore the terrestrial water storage (TWS) changes over arid regions of Central Asia from 2003 to 2014. We observed significantly decreasing water storage trends in the GRACE data, which were underestimated by the GHMs. After averaging the three GRACE satellite datasets, we found that the water storage was decreasing at a rate of −4.74 mm/year. Contrary to the prevailing declining water storage trends, northeastern Kazakhstan (KAZ), and southern Xinjiang increased their water storage over the same period. The GRACE data showed that Turkmenistan (TKM), Uzbekistan (UZB) and KAZ experienced the most severe water depletions, while Tajikistan (TJK) and northwest China (NW) experienced the least significant depletions. With respect to the major river and lake basins, the Aral Sea Basin exhibited the most serious water loss (-0.60 mm/month to −0.38 mm/month). The water storage positively correlates with the precipitation; and negatively correlates, with a three-month lag, with temperature and potential evapotranspiration (PET). Partial least square regression (PLSR) had the high capability in simulating and predicting the TWS. These results provide scientific evidence and guidance for local policy makers working toward sustainable water resource management, and the resolution of international water resource disputes among Central Asian countries.

Challenges and Solutions for Biogas Production from Agriculture Waste in the Aral Sea Basin

Energy plays an essential role in the modern society and can serve as one of the vital parameters of socio-economic development. Despite developments in technology, over three billion persons living in rural parts of the low- and middle-income countries continue to cover their energy needs for cooking through traditional ways by burning biomass resources. This paper as a case study focuses on the Aral Sea region of Uzbekistan, possessing a well-developed agricultural production with high livestock numbers and intensive crop production. The manure of the livestock farms is not used efficiently and the energy supply of the farms depends primarily on centrally produced gas and electricity. Some areas are not yet connected to the gas grid. Agriculture causes huge environmental damages in its current form. The benefit of biogas production would therefore be fivefold: (1) local energy source, (2) mitigation of environmental impacts, (3) reducing CH4-emissions, (4) producing organic fertilizer as a side product and (5) additional earnings for farmers.

A copula-based stochastic fractional programming method for optimizing water-food-energy nexus system under uncertainty in the Aral Sea basin

Abstract A copula-based stochastic fractional programming (CSFP) method is developed for optimizing water-food-energy nexus (WFEN) system, which can tackle random variables under conflicting objectives and analyze the interrelationship between marginal benefit and system-failure risk. Then, a CSFP-WFEN model is formulated for the Aral Sea basin and multiple scenarios with individual- and joint-probabilistic risks related to water resources, arable land, and hydropower generation are examined. Synthesizing the results under all scenarios, hydropower generation would decrease by 11.9% and crop area would increase by 12.4% by 2035 under severe water scarcity. Agricultural water would decrease with time (from 69.1% in 2021 to 53.9% in 2035), and the share of wheat farmland would increase by 16.4% for food security. Compared with the traditional stochastic fractional programming (SFP) and copula-based stochastic programming (CSP) methods, the marginal benefit from CSFP would be improved 1.7% and water would be saved 9.2%. To support sustainable development of the study basin, some suggestions can be derived from the results: (i) since agriculture is still the largest water user in the future, it is desired to reduce its water consumption through improving irrigation efficiency and adjusting crop planting structure; (ii) effectively reducing Uzbekistan’s water consumption can improve water allocations to other countries and relieve regional conflicts caused by water shortage; (iii) compared to the single management pattern, the integrated optimization of water, food and energy nexus not only has higher efficiency of resources allocation and utilization, but also allows an increased robustness in controlling system-failure risk under joint probabilistic constraints.

Historical Aspects Of The Environmental Policy Strategy In The Field Of Sustainable Development Of The Southern Aral Sea Region At The Present Stage

The article discusses the issues related to the solution of problems to improve the situation in the Aral Sea basin, which also included measures to save the Aral Sea region. In order to strengthen mutual understanding and trust between all Central Asian countries and establish openness in relations, the Republic of Uzbekistan considers it necessary to undertake joint efforts to find mutually beneficial solutions to resolve the issue of rational and fair use of water resources in Central Asia.

Development of a large-scale remote sensing ecological index in arid areas and its application in the Aral Sea Basin

The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia. It is of great significance to the ecological protection and sustainable development of Central Asia to carry out dynamic monitoring and effective evaluation of the eco-environmental quality of the Aral Sea Basin. In this study, the arid remote sensing ecological index (ARSEI) for large-scale arid areas was developed, which coupled the information of the greenness index, the salinity index, the humidity index, the heat index, and the land degradation index of arid areas. The ARSEI was used to monitor and evaluate the eco-environmental quality of the Aral Sea Basin from 2000 to 2019. The results show that the greenness index, the humidity index and the land degradation index had a positive impact on the quality of the ecological environment in the Aral Sea Basin, while the salinity index and the heat index exerted a negative impact on the quality of the ecological environment. The eco-environmental quality of the Aral Sea Basin demonstrated a trend of initial improvement, followed by deterioration, and finally further improvement. The spatial variation of these changes was significant. From 2000 to 2019, grassland and wasteland (saline alkali land and sandy land) in the central and western parts of the basin had the worst ecological environment quality. The areas with poor ecological environment quality are mainly distributed in rivers, wetlands, and cultivated land around lakes. During the period from 2000 to 2019, except for the surrounding areas of the Aral Sea, the ecological environment quality in other areas of the Aral Sea Basin has been improved in general. The correlation coefficients between the change in the eco-environmental quality and the heat index and between the change in the eco-environmental quality and the humidity index were −0.593 and 0.524, respectively. Climate conditions and human activities have led to different combinations of heat and humidity changes in the eco-environmental quality of the Aral Sea Basin. However, human activities had a greater impact. The ARSEI can quantitatively and intuitively reflect the scale and causes of large-scale and long-time period changes of the eco-environmental quality in arid areas; it is very suitable for the study of the eco-environmental quality in arid areas.

Changes of vegetation and its forces driving in the Aral Sea Basin of Central Asia

Global change brings great uncertainty to the fragile ecological environment of arid area. In order to understand the driving role of climatic factors and socio-economic activity on changes, the distribution and change of vegetation in the Aral Sea basin were examined using data from remote sensing, population data sets from 2000 to 2015, transfer matrix, and the centre of gravity model. The salient results of the analysis were as follows. (1) Although the index increased slightly in the past 20 years overall, it fluctuated greatly over that time. From 2000 to 2015, the NDVI decreased in approximately 62% of the area; increased in 24%; and remained unchanged in 14%. (2) From 2000 to 2015, the geographic centre of the area under forest land to the northeast, marking the advancement of urbanization upstream. The geographic centre of grassland moved to the west. (3) The overall impact of precipitation on vegetation was greater than that of temperature. Areas showing a strong correlation were mostly concentrated in forest land; the impact of precipitation on grasslands was weak. (4) The distribution of vegetation was adversely affected by the increase in population and in GDP. The present study is of particular significance to the restoration and reconstruction of the Aral Sea basin ecosystem.

Land cover-adjusted index for the former Aral Sea using Landsat images

The Aral Sea was the fourth largest inland lake on the globe until 1960, with a surface area of about 68,000 km2. Mainly, the huge irrigation projects in many parts of its transboundary catchment were responsible for the catastrophic desiccation and ecological crises of the Aral Sea after second part of 20th century. Ecological crisis surrounding the Aral Sea (lake) regions is one of the critical environmental problems of Central Asia. As a result, monitoring of desertification processes and determining the aerosol concentration in the atmosphere are highly relevant for any attempts to mitigate environmental changes in the Aral Sea basin. Remote sensing is the most appropriate method for studying desertification and dust storms as it easily covers large areas with a high spatial and temporal resolution. Satellite images provide detailed multispectral information about the earth’s surface features, which proves invaluable for the characterization of vegetation, soil, water, and landforms at different scales. Vegetation cover, biomass, and soil properties were analyzed with remote sensing methods (NDVI, SDVI). It is emphasized that vegetation indices have little sensitivity at low leaf area which is common to all desert ecosystems.

Improving water resources management in the irrigated zone of the Aral Sea region

One of the most important objectives in the world is to improve rational water resources management methods. In this regard, the rational management of water resources and optimal water resources distribution, especially on on-farm systems, are considered very important. In this direction, given the negative consequences that have developed over the past more than 40 years in the lower reaches of the Amu Darya River, the need to improve the methods of effective management of water resources in the Aral Sea basin is urgent.

Environmental monitoring in construction for hydro-technical structures and land reclamation facilities of Uzbekistan

The article is devoted to the urgent topic of creating a comprehensive geographic information system for environmental monitoring and decision support for hydro-technical structures and land reclamation facilities of Uzbekistan. The research results allow a more substantial assessment of the environmental situation, the fundamental features of the arid zone. For monitoring, a methodology is disclosed, which will help water and water organizations to plan and predict the environmental status in the water sector. The results of a comprehensive analysis of the Aral Sea basin using geographic information systems will help in creating a decision support system. The excessive use of water resources within the Aral Sea basin for agricultural, industrial, and wastewater needs has resulted in the contamination of water resources by a diversity of hazardous chemicals from anthropogenic. Expert questionnaires for environmental measures developed during the reconstruction of hydro-technical structures and land reclamation facilities. They are using the methodology of environmental monitoring. It is possible to evaluate and improve the hydro ecological situation of hydro-technical structures and land reclamation facilities in Uzbekistan

Spatial variation in major water quality types and its relationships with land cover in the middle and lower reaches of Aral Sea Basin

Water resources and environmental issues in the Aral Sea Basin of Central Asia are global concerns. In this study, the water quality variables (i.e., basic physical and chemical attributes, different forms of nutrients, other elements, cations, and anions) from 21 sampling sites in the middle and lower reaches of Aral Sea Basin were measured in 2019 to explore water environmental variations and their causes. Spatial variation in 20 water quality variables was investigated, and the representative water quality types, spatial differences, and their causes were identified via multivariate analysis methods (i.e., principal component analysis and cluster analysis). Furthermore, the effects of land cover on the spatial variation in water quality types were explored. The results showed that: 1) the values of electronic conductivity (EC) and total dissolved solids (TDS) increased from the middle to the lower reaches, and the highest values were in the Aral Sea. This indicates that the concentrations of anions and cations increased from the middle to the lower reaches. For the nutrient variables, high phosphorous concentrations were in the middle reaches of Amu Darya, and high nitrate-nitrogen concentrations were in the Syr Darya. For the different forms of carbon, the highest concentrations were in the Amu Darya, particularly in the delta area of lower reaches. 2) The water quality at all sampling sites can be divided into three water quality types according to the similarity classification of water quality variables. The first type had low concentrations for most water quality variables, which were distributed in the middle reaches of Syr Darya and the Aral Sea. The second type had high concentrations of different forms of nitrogen and phosphorus, which were distributed in the middle and lower reaches of Amu Darya. The third type had high concentrations of carbon, anions, and cations, which were distributed in the Aral Sea. The water quality concentrations of the first and second types were mainly due to rock weathering processes on bare land, and the anions and cations were mainly derived from the weathering of silicates and evaporites. The concentrations of the third type were mainly due to the evaporation and crystallization processes of a dry climate, and the anions and cations were mainly derived from the weathering of silicates and evaporites, which may also be affected by carbonate weathering. 3) With an increase in the buffer zone radius for each sampling point (0.5 km to 10 km), the significant land cover changed from bare land to water, shrubland, grassland, mixed farmland, and vegetation for the first water quality type; the most significant land cover was water. There were no significant relationships between the second water quality type and land cover. For the third water quality type, the significant land cover changed from water to water, mixed farmland, and vegetation - the most significant land cover was water. Therefore, spatial variation in the water quality variables was mainly affected by the local climate conditions (i.e., climatic drought and intensive evapotranspiration) and the mainland cover types (i.e., bare land, water, farmland, grassland, and urban). To improve the water environmental conditions in the middle and lower reaches of Aral Sea Basin, stream flow should be increased to recharge the Aral Sea and weaken the evaporation and crystallization processes in the lower reaches of Aral Sea. Vegetation restoration and a return of farmland to forest and grassland should also be strengthened in the riparian zone, particularly in the middle and lower reaches of Amu Darya and Syr Darya and the Aral Sea.