Freshwater lakes around the world are increasingly threatened by climate change and human activities, particularly in arid and semi-arid regions, where they serve as critical ecological and economic resources. As China's largest inland freshwater lake, Bosten Lake has undergone dramatic changes over the past two decades, reflecting the dual pressures of climate variability and anthropogenic influences. This study investigates the long-term changes in Bosten Lake's water level, area, and volume from 2002 to 2022 using satellite remote sensing and meteorological data. The results indicate fluctuations with an overall declining trend, with lake level dropping from 1047.093 to 1046.996 m, area decreasing from 1077.190 to 995.800 km2, and water volume reducing by 2.715 km3. Key drivers of these changes include evaporation, variations in precipitation, and ecological water transfer policies. This research not only provides crucial insights into the ecological management of the Bosten Lake basin but also offers valuable reference points for water resource management in similar regions globally.

  • To provide continuous and accurate data on level, area, and water volume change in Bosten Lake for nearly 20 years.

  • Lakes in the study phase change in 2013 and 2020 as the important node, and present three trends: ‘down – up – down again’.

  • The dynamics of the Bosten lake are considerably influenced by evaporation and ecological water transfer policies within the basin.

As nodes in the interaction of land surface systems such as the atmosphere, biosphere, lithosphere, hydrosphere, and terrestrial hydrosphere, lakes are extremely sensitive to global climate change, especially inland lakes in arid areas, which are indicators of climate change and environmental variability in the basin (Zheng 2017). Freshwater lakes in arid regions are important freshwater resources in their location and have regional economic, ecological, and environmental functions. The region's large freshwater lakes are generally recharged by precipitation and alpine snow and ice melt, making it one of the most sensitive geographic units in terms of response to climate fluctuations (Kaplan & Avdan 2017; Rodell et al. 2018; Zhang et al. 2019). Both too-low and too-high water levels in lakes can have adverse impacts (Yao et al. 2018), in which too low a drop in water level will lead to shrinking wetland areas, degradation of vegetation, and reduction of biodiversity. While too high a water level and expansion of water surface area will exacerbate soil salinization and agricultural losses, increasing food risks, and exceeding a certain ecological water level, will also produce a series of flood disasters, causing certain socio-economic losses (Wan et al. 2006; Bai et al. 2011; Guo et al. 2015). Located in the northeastern Tarim Basin, Bosten Lake is a typical arid zone lake in Xinjiang. As the largest inland freshwater lake in China, it is an important water resource in the basin, and for the arid climate zone with low precipitation, the lake plays a role in supporting the ecosystem of the region (Yang 2020). Although Bosten Lake plays a critical role in regional water resource management, the extent to which climate change and human activities have contributed to its hydrological variations over the past two decades remains unclear. This study aims to address these gaps by providing comprehensive, long-term monitoring of Bosten Lake's water dynamics.

The study of the lake watershed area is the basis of the lake hydrology research (Schultz & Engman 2000). The development of satellite remote sensing technology provides strong support for real-time dynamic monitoring of lake changes, especially the application of high-resolution remote sensing satellites that provide effective data for the study of changes in lake areas. Landsat, with its advantages of long time-series observation, relatively high accuracy, and convenient download, has become a widely used remote sensing data source for scientific research. Landsat is of great significance for monitoring the continuous change of the lake area, which can be used to reflect the rise and fall of lakes within a short period and the trend of multi-year changes (Sokolov et al. 2022). Traditional monitoring of lake water levels relies on field measurements at hydrological stations, which requires a large amount of human and material inputs despite its high accuracy. Due to the limitations of natural conditions and spatial distribution, it is difficult to obtain long-term continuous observation data for remote inland lakes. Moreover, traditional water level monitoring has a low sharing degree, which further increases the difficulty of data collection (He et al. 2020). In contrast, satellite radar altimetry has a wide monitoring range and the ability to make periodic observations to capture multiple dynamic changes in terrestrial water bodies (Sun et al. 2022). The results of several studies have demonstrated the excellence of satellite altimetry in effectively monitoring the dynamics of lake water levels (Crétaux et al. 2005; Cooley et al. 2021). Radar altimetry satellites (e.g., TOPEX/Poseidon, Jason-1, Jason-2, Jason-3) have the characteristics of real-time and all-weather (Birkett 1995), especially for rivers and lakes distributed in high mountains, plateaus, or remote areas lacking surface hydrological observation stations; real-time monitoring of water level changes can greatly make up for the shortage of water level observation data in these lakes (Zhang et al. 2014). At the same time, time-series water level databases of large lakes, reservoirs, and rivers around the world based on these satellite altimeter data have been established, such as Hydroweb (Crétaux et al. 2011), DAHITI (Schwatke et al. 2015), and G-REALM (Birkett et al. 2011). The establishment of a lake water level database will help to continue many aspects of lake research, such as the use of algorithms to explore the far-reaching impact of lake water level fluctuations on key water quality parameters (Li et al. 2019). Current studies on the changes in water levels and surface areas of inland lakes often rely on existing global lake datasets or single-sensor, low-resolution remote sensing data (Chen et al. 2020). While these data sources are useful for large-scale analyses, they fall short in providing the precision needed for finer-scale monitoring, particularly for long-term assessments of specific lakes of interest. Accurate monitoring of water volume changes in individual lakes remains relatively scarce. To address this limitation, newer, higher-resolution satellite altimetry datasets offer promising opportunities for more detailed lake studies. Among these, Jason-series satellite data stand out due to their higher spatial resolution, improved accuracy, and the advantage of long-term continuity compared to most previous altimetry missions. The higher resolution and continuity of Jason's data offer significant advantages for precise, long-term hydrological monitoring at local scales (Peng et al. 2024; Ross et al. 2024).

Earlier altimetry data, with limited spatial and temporal resolution, have constrained the systematic study of small lake dynamics (Yapiyev et al. 2019). The precision of these studies often fails to meet the accuracy required for water resource analysis in arid regions, particularly for lakes like Bosten Lake, which exhibit significant spatiotemporal variability. Additionally, many existing studies primarily focus on singular aspects such as water level or surface area, without integrating a comprehensive analysis of water level, surface area, and volume. This lack of a holistic approach restricts our understanding of the substantial changes in Bosten Lake and their implications for future development (Li et al. 2021; Peng et al. 2021). Although some recent efforts have combined multi-source remote sensing data for long-term lake analysis (Fu et al. 2024), a more integrated use of diverse remote sensing datasets is urgently needed to improve our understanding of inland lake dynamics, particularly in arid regions. To address these gaps, this study focuses on nearly two decades of detailed monitoring of Bosten Lake. This study integrates Jason-1/2/3 altimetry data with Landsat imagery to establish a framework for long-term monitoring of water dynamics. This methodology not only compensates for the limitations of previous large-scale monitoring studies, which often lacked sufficient data for small lakes and were constrained by the availability of long-term time series, but also provides valuable insights for monitoring similar lakes globally. Furthermore, the climate in the Xinjiang region has experienced significant shifts since the 20th century, transitioning from warm-dry to warm-wet conditions. This climatic change has had a pronounced impact on the runoff patterns of major tributaries feeding Bosten Lake, such as the Kaidu and Peacock Rivers, further destabilizing the lake's water resources. Bosten Lake plays a pivotal role in sustaining the region's economic development and ecological balance, as fluctuations in its water resources and the efficiency of their use have become key indicators of sustainable development in the region. The changes in Bosten Lake's water levels and resources have become a focal point in climate and environmental research, making in-depth monitoring crucial for understanding the behavior of freshwater lakes in arid regions and their role in regional water systems under the influence of global warming. Given the continuous availability of remote sensing and altimetry data, this research focuses on a comprehensive analysis of the water level, area, and volume variations in Bosten Lake over the two-decade period from 2002 to 2022. In addition, it explores the relative contributions of climate factors (e.g., precipitation and evaporation) and human activities (e.g., water resource management and industrial production) to these changes. This research offers valuable insights for future management strategies in the Bosten Lake basin and serves as a reference for studies of similar freshwater lakes in arid regions around the world.

Bosten Lake (86°40′–87°56′E, 41°56′–42°14′N) is located in the territory of Bohu County, Xinjiang Uygur Autonomous Region, China, in the southeastern corner of Yanqi Basin in the southern foothills of the Tianshan Mountains. The general trend of topography is higher in the north and lower in the south. From the mountain front to Bosten Lake, it is a successively pre-mountain diluvial alluvial inclined plain, Kaidu River delta, and Bosten Lake basin. The water supply of Bosten Lake mainly comes from mountain snowpack meltwater, atmospheric precipitation, and surface runoff in Kaidu River and Huangshui Ditch, and the water from the lake supplies Peacock River, as shown in Figure 1. The basin of Bosten Lake is located in the center of the Eurasian continent, with abundant solar radiation and heat, a dry climate with little rain, and large evaporation, which is a typically arid continental climate. The average annual temperature in the lakeside zone of Bosten Lake is 8.2–11.5 °C, the average temperature in January ranges from −7.8 to −12.3 °C, and the average temperature in July is 22.9–26.0 °C. The annual precipitation is 47.7–68.1 mm, and more than 80% of the precipitation is concentrated from May to September; the maximum number of days without precipitation is 158–190, and the annual evaporation is 1,880.0–2,785.8 mm. The hydrological dynamics of Bosten Lake are closely linked to the surrounding glaciated mountains, with an estimated glacier area of 332.89 km2 and approximately 700 glaciers in the basin (He & Zhou 2022). As a natural regulator of the spatial and temporal distribution of water resources upstream and downstream of the Kaidu-Peacock River Basin, Lake Bosten serves various functions, such as water quantity control of the Kaidu River, irrigation of farmland in the Peacock River Basin, water use for industry and urban and rural life, purification of water quality in the basin, ecological water demand in the basin, and ecological emergency transfer of water to the middle and lower reaches of the Tarim River. At the same time, it has become the most important water resource reservoir in the Bayinguoleng Mongol Autonomous Prefecture of Xinjiang and has been called the ‘Mother Lake’ of the people of Bazhou. It is the lifeblood of local economic development and the survival of all ethnic groups.
Figure 1

Overview of the study area.

Figure 1

Overview of the study area.

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Data source

Satellite altimetry data

The Jason satellites are a series of ocean observation satellites launched by the French National Space Center in cooperation with the National Oceanic and Atmospheric Administration of the United States. The Jason series of satellites, as a continuation of the TOPEX/Poseidon (T/P) satellites, closely inherited the design of their predecessors but underwent significant upgrades and optimization in terms of technology and performance. The Jason series adopted the more advanced Poseidon dual-frequency radar altimeter, which could more effectively eliminate the effects of the ionosphere and thus improve measurement accuracy. In particular, the target measurement accuracy of Jason-3 was 2.5 cm, and the actual measurement accuracy was 3.3 cm. Jason-1 was launched in December 2001 and ended its service in July 2013. Jason-2 was launched in June 2008, and Jason-3 in January 2016 is operating to the present (Table 1). The altimeter carried by the satellite is mainly used to measure the changes in topography and sea level in the offshore area, and the continuity of satellite observation data can be guaranteed by using these data. Jason satellites operate one cycle per cycle, and each cycle has a total of 254 Pass files (.nc format), which contain data items, such as altitude, time, position, attitude, environmental correction, and backscatter coefficient (Cnes 2017). Passes within the study area were selected for further data screening. The period of this study is 2002–2022, and the Geophysical Data Record (GDR) data from Jason1/2/3 satellites level 2 products were acquired from AVISO (available: https://www.aviso.altimetry.fr/en/data.html) with accurate environmental and earth parameters correction and good quality data. To ensure the continuity and accuracy of the data, the GDR data of orbit numbers 181 and 64 (Figure 2) passing through Bosten Lake, which are covered in the observation range of Jason-1, Jason-2, and Jason-3 satellites, are selected in this paper.
Table 1

Jason's data details

SatelliteOperationAltimeterFootprint/kmMeasurement accuracy/cmRevisit cycle/day
Jason-1 2002–2008 Poseidon-2 2.2 4.2 10 
Jason-2/OSTM 2008–2016 Poseidon-3 2.2 2.5–3.4 10 
Jason-3 2016–current Poseidon-3B 2.2 2.5 10 
SatelliteOperationAltimeterFootprint/kmMeasurement accuracy/cmRevisit cycle/day
Jason-1 2002–2008 Poseidon-2 2.2 4.2 10 
Jason-2/OSTM 2008–2016 Poseidon-3 2.2 2.5–3.4 10 
Jason-3 2016–current Poseidon-3B 2.2 2.5 10 
Figure 2

Distribution of Jason satellite altimetry data.

Figure 2

Distribution of Jason satellite altimetry data.

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Landsat images

Since 1972, the Landsat series of Earth observation missions, co-sponsored by the National Aeronautics and Space Administration (NASA) and the US Geological Survey, has successfully launched seven satellites, of which Landsat 1–5 have been retired, Landsat 6 has not been successfully orbited, and the satellites that are still able to provide images are Landsat-7. Currently, the satellites that can still provide images are Landsat-7, Landsat-8, and Landsat-9 (Cohen & Goward 2004; Wulder et al. 2012). The Landsat data have a resolution of 30 m and a revisit period of 16 days, which provides a dense time-series image that is sufficient to reflect the short-term upward and downward movement of the lake within a year and the multi-year trend. The multi-source and multi-temporal Landsat remote sensing data can be used to identify the extent of the lake and extract the area after geometric correction, geographic alignment, radiometric correction, and atmospheric correction. Specifically, surface reflectance data from Landsat-5 TM covering the period from 2002 to 2011, Landsat-7 ETM+ for 2012, and Landsat-8 OLI for 2013 to 2022 were utilized. The imagery was obtained through the Google Earth Engine (GEE) platform, which provides convenient access to pre-processed Landsat data. The data were analyzed to extract the lake area and assess the trend in lake surface change over time.

Satellite altimeter water level data products

In this study, time series water level data for Bosten Lake were obtained from several well-established global databases, including DAHITI (available: https://da-hiti.dgfi.tum.de/en/), Hydroweb (available: https://hydroweb.next.theialand.fr/), and G-REALM (available: https://ipad.fas.usda.gov/cropexplorer/global_reserve-oir/#datasets). The Inland Waters Hydrographic Time Series Database (DAHITI), developed by the German Institute of Technology (DGFI-TUM) in 2013, provides a time series of water levels in lakes, reservoirs, rivers, and wetlands measured by multi-mission satellite altimeters for hydrological applications. The Hydroweb database was developed by the Space Laboratory of Geophysics and Oceanography. To estimate the time series of lake and river water levels, a multi-mission approach using satellite altimeter data from TOPEX/Poseidon, ERS-1, ERS-2, ENVISAT, Jason-1/2/3, SARAL, and GFO was used. The Global Reservoir and Lake Monitor (G-REALM) is jointly maintained by the US Department of Agriculture's Foreign Agricultural Service (USDA/FAS) and NASA. The water level time series of lakes and reservoirs is estimated by using a single altimeter task on the target under study. The product consists of combining data from different continuous altimeter missions monitored on the same target, updated weekly, with no simultaneous altimetry for the same target during the same period. These global water level databases regularly track water level changes in large lakes and reservoirs worldwide. In this study, data from these databases were used to assess the accuracy of lake levels derived from Jason series satellite altimeter data.

Meteorological and glacier data

Meteorological data were obtained from the Resources and Environment Science and Data Center of the Chinese Academy of Sciences (available: https://www.resdc.cn/DOI/). These data, subjected to stringent quality control procedures, are suitable for supporting climate change research. Two conventional meteorological stations, Heshuo (42°15′N, 86°48′E, 1,085.4 m a.s.l) and Yanqi (42°4′N, 86°34′E, 1,055.3 m a.s.l), both located in the plains near Bosten Lake, were selected for this study. Monthly data from these stations covering the period from 2002 to 2022 were used. The meteorological variables include monthly mean air temperature, monthly mean precipitation, and monthly evaporation, which serve as essential supporting data to analyze the climatic conditions in the lake basin and to assess the response of lake level and area to climate change. In addition, glacier distribution data were derived from two key sources: the ‘GAMDAM Glacier Inventory for High Mountain Asia: Central Asia’ dataset and the second Glacier Inventory of China (available: http://www.ncdc.ac.cn) (Liu et al. 2012; Sakai 2019). These datasets provided glacier data for the Bosten Lake basin in 2000 and 2010, respectively. Furthermore, based on Landsat OLI remote sensing images from 2020, a band synthesis approach was applied to enhance the visualization of glacier surface features. Glacier distribution data were extracted using the maximum likelihood method for supervised classification, combined with visual interpretation, to improve accuracy in mapping glacier distribution in the Bosten Lake basin.

Data analysis

Lake level extraction

Lake level refers to the elevation of the free water surface of the lake, and the formula for calculating the lake level is as follows (Cnes 2017; Sun et al. 2021):
(1)
where H (m) is the lake water level elevation; Aalt is the ellipsoidal height of the altimeter; Rran is the observation distance of the altimeter; Hgeoid is the height of the geodetic datum concerning the reference ellipsoid; and ΔCcor is the observation correction for each error. Compared with the ocean, lakes are affected by tides, inverse air pressure, and extreme tidal pressure, which are relatively small and negligible. The error correction can be expressed as follows (Cai & Ke 2017):
(2)
where Wwet is the wet troposphere correction; Ddry is the dry troposphere correction; Llono is the ionosphere correction; Sset is the solid tide correction; and Ppol is the polar tide correction.
Basic Radar Altimetry Toolbox software provided by Aviso's official website was used to extract and edit the GDR data acquired from Jason series satellites. Editing criteria: the cropped data are located within the lake area; the altimeter height relative to the reference plane is valid; the height data observed by the altimeter is valid; the correction values are within the valid range; and the outliers of the output lake level were removed using the 3σ criterion (Zhang et al. 2015; Cai & Ke 2017; He et al. 2020). Thus, the time series data of Bosten Lake level were generated (Figure 3).
Figure 3

Lake-level extraction technical route.

Figure 3

Lake-level extraction technical route.

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Lake area extraction

The water body index is widely used for water body extraction, and the method enhances the band characteristics of the water body by taking into account the reflectivity differences between electromagnetic waves of different wavelengths and the removal of the noise component (Smith 1978). In this paper, the normalized difference water index (NDWI) method proposed by McFeeters is used to extract the lake boundary (McFeeters 1996). The NDWI is represented as follows:
(3)
where Green is the green band reflectance of the Landsat TM/ETM/OLI image; NIR is the reflectance of the near-infrared band. Using NDWI to extract water body information, the interference of surface soil, vegetation, and other information characteristics can be attenuated for threshold segmentation. When the NDWI value is greater than 0.3, the feature type of the image element is water body (Wu 2019).

With millions of servers around the world and powerful cloud computing and storage capabilities, the GEE platform currently calls on a vast amount of Earth observation data and provides scientific research with an inherently parallel approach to processing massive amounts of imagery (Dong et al. 2016; Tan et al. 2019). Based on the GEE platform, this paper calls Landsat-5/7/8 images from 2002 to 2022 through JavaScript language. To ensure image quality, Landsat-5/7/8 images with less than 10% of the total cloud cover and clearly visible in the study area were used. In the GEE platform, the cloud removal process is carried out on the called image data to retain clear surface reflectivity. The water body index NDWI was added, and the water body was screened and extracted according to the set threshold value. The area of the water body is calculated using the extracted water body range, the minimum area threshold is set to 100 m2, and the small area of the water body is removed. The area data of Bosten Lake were visualized and exported. The Landsat images of Bosten Lake with a few clouds during the abundant water period of September 2002–2022 were selected for visual interpretation to calculate the area of water bodies and verify the processing results of the GEE platform.

Lake volume calculation

The water balance of inland lakes is jointly determined by the lake area and lake level (Qiao et al. 2019). Using the area and level changes of Bosten Lake, its water volume changes can be simulated. Assuming that the water volume change of the lake is approximated as a ‘platform body’, the volume change of the lake is calculated based on the ‘platform body’ volume equation, that is, the change of water quantity is calculated according to the change of lake level and area (Zheng et al. 2016). In this study, the following equation was used to estimate the volume change (Zhang et al. 2013):
(4)
where: ΔV (km3) represents the change in lake volume from lake area S1 (km2) to lake area S2 (km2) and lake elevation H1 (km) to lake elevation H2 (km). A positive value of ΔV indicates an increase in water volume and a positive equilibrium for the lake, while a negative value of ΔV indicates a decrease in water volume and a negative equilibrium for the lake. The sum of the volume changes from 2002 to 2022 is the equilibrium state of the lake throughout the study.

Grey relational analysis

Grey relational analysis is a key component of grey system theory, which is used to quantify the relationship between subsystems in a system. Through the grey relational degree analysis of each subsystem, the development trend of a system can be quantitatively measured numerically, to objectively describe the dynamic change of the system or multiple factors and calculate the similarity or difference degree of the development trend among factors. Due to the complexity of the changes in climate elements and the diversity of factors affecting lake level and area, problems such as nonlinear constraints and uncertainty factors are involved in considering the effects of changes in climate elements on lake changes, i.e., there is a wide range of greyness (Allen et al. 1998). Therefore, in this paper, grey system theory (Lin et al. 2012) is used to analyze the response of dynamic changes in lake level and area to changes in meteorological factors. The correlation degree of two sequences in the grey system is used to characterize the degree of correlation of these two sequences, and the correlation degree is calculated as
(5)
where Rij represents the degree of correlation between sequence i and sequence j. The closer the value of correlation is to 1, the better the correlation is; j represents the length of the data sequence, which is the number of data; Rij(t) represents the correlation coefficient of sequences i and j at the moment t, and its calculation formula is
(6)
where Δmin, Δmax denote the minimum and maximum of the absolute difference between the two sequences at each moment, respectively; Δij(t) denotes the absolute difference between the two sequences of data at the moment t; ρ is the resolution coefficient, ρ (0,1), which usually takes the value of 0.5 (Allen et al. 1998).

Characteristics of changes in lake level

Various geophysical corrections were proceeded to calculate the elevation database on the Jason series of satellite altimeters, and the lake level series anomalies were removed from the data, which led to the inconsistency of the time interval of the data series. In this study, the time series interval was resampled to 30 days, and the missing data were linearly interpolated during the resampling process to generate a continuous monthly average lake level time series of Bosten Lake in the period of 2002–2022. Three water level products (DAHITI, Hydroweb, G-REALM) in Bosten Lake from 2002 to 2022 were selected with a 30 day interval. To verify the accuracy and reliability of the satellite altimetry data, the correlation between Jason altimetry time series lake level data and the other three lake level data were analyzed, the accuracy results are shown (Table S1), and the comparison graphs of lake levels (Figure 4) are shown as follows. As can be seen from the table, the Jason altimetry water level data from this study correlate well with all three global water level databases, with smaller differences in mean water level values (−0.01 to 0.51), higher R2 (0.84–0.89), and smaller Root Mean Square Error (RMSE) and Relative Error (RE) (0.39–0.46, and 0.03%–0.04%), respectively. This large RMSE between comparative data and Jason in this study was attributed to insufficient completeness of data from DAHITI, Hydroweb, and G-REALM (Wang et al. 2023). It can be seen from Figure 4 that the lake level time series of the three products are basically consistent with the trend of the Jason satellite altimetry lake level time series. The results show the feasibility of utilizing Jason satellite altimetry data to monitor the level changes in the long-time series of Lake Bosten.
Figure 4

Comparison of lake level changes of different products.

Figure 4

Comparison of lake level changes of different products.

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The figure clearly shows that the level of Lake Bosten presents an overall decreasing trend from 2002 to 2022, at a rate of −0.076 m/a. During this period there are three phases of change, ‘falling-rising-falling again’, bounded by the years 2013 and 2020, respectively. The inter-annual variation of lake level is dramatic (Figure 5). The highest lake level in 2002 was 1,050.48 m, the lowest lake level in 2013 was 1,044.62 m, and the difference between the highest and lowest lake levels was as high as 5.86 m. Taking 2013 as the turning point of lake level change and 2002–2013 as the period of lake level decline, lake level decreased from 1,049.12 to 1,045.43 m, it decreased by 3.69 m in 12 years, and the annual change rate was about −0.308 m/a. From 2013 to 2020, the Bosten Lake level was in an increasing trend, continuously rising from 1,045.43 to 1,048.30 m, with a total increase of 2.87 m, and the annual change rate of lake level was about 0.359 m/a. During 2020–2022, the Bosten Lake level decreased slightly, from 1,048.30 to 1,047.51 m, and the annual change rate of lake level was about −0.261 m/a. To further monitor the intra-annual dynamic changes in the level of Bosten Lake, this paper analyzed the lake level of each month during the study period (Figure 6). The Bosten Lake level is the highest from March to May in spring, with an average lake level of 1,047.17 m. In March, the highest lake level of the year was 1,047.24 m. The lake level is relatively high from June to August in summer, with an average lake level of 1,046.99 m. Since September, the level of Lake Bosten has been relatively stable. During this period, the average is maintained at approximately 1,046.87 m.
Figure 5

Water level time series of Bosten Lake based on Jason satellite altimetry.

Figure 5

Water level time series of Bosten Lake based on Jason satellite altimetry.

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Figure 6

Change in monthly mean water level of Bosten Lake during the year from 2002 to 2022.

Figure 6

Change in monthly mean water level of Bosten Lake during the year from 2002 to 2022.

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Characteristics of changes in lake area

Based on the Landsat-5/7/8 images from 2002 to 2022 invoked by GEE, the lake area with 30 m resolution in Bosten Lake in the past 20 years was extracted by the water index threshold method, and its area varied from 1,096.05 to 890.93 km2, with a relatively large variation range. In order to verify the extraction accuracy of this study, Landsat-5/7/8 images with no or few clouds in the study area in September from 2002 to 2022 were selected for visual interpretation of the lake. Based on the visual interpretation results, the lake area data obtained were edited again. The difference between the visual interpretation area value and the area obtained in GEE based on the Landsat series was distributed in the range of 0.17–39.77 km2 (Figure 7), with an average value of 2.86 km2. The coefficient of determination R2 is about 0.944 (Figure S1), and the relative error is 0.8%. The results show that it is feasible to extract lake area by using the water index algorithm in the GEE platform, and the accuracy is good.
Figure 7

Comparison of visual interpretation and Landsat extraction results.

Figure 7

Comparison of visual interpretation and Landsat extraction results.

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Figure 8 shows the long-term variation of lake area data for the period 2002–2022. Correspondingly, the lake area also shows an overall decreasing trend at a rate of −3.616 km2/a, where the same trend as that of the water level also has three phases of change with 2013 and 2020 as the nodes, respectively. The annual variation of the water area of Bosten Lake showed a significant downward trend during 2002–2013, with a total reduction of 177.299 km2 and an average annual reduction of 14.775 km2, as shown in the image data (Figure 9). The boundary of the water body shrinks inward, and the north-western lakeside wetland area, the narrow strip of water in the southern edge and the eastern edge shrink to a greater extent. After 2013, the lake area has increased, and by 2020, the lake area has increased by 115.390 km2, with an average annual increase of 14.424 km2. Figure 9 shows the overall expansion of the lake boundary, in which a large area of water near the lakeside wetland in the northwest corner of the lake and the narrow strip of water on its east side recover. The water body in the southeast corner of the lake has a certain area of expansion to the surrounding sandbank. By 2020, the water bodies reduced from 2002 to 2013 have been restored to a large extent. However, from 2020 to 2022, the lake area has a small downward trend again, from 1,019.922 to 1,005.897 km2, with an annual change rate of −4.675 km2/a. Bosten Lake exhibits significant seasonal variations in the area over the course of a year (Figure 10). Spring (March–May) shows the highest average area of approximately 983.921 km2. Particularly, in April, the lake achieves its peak area for the year, measuring 984.374 km2. The summer months (June–August) see a relatively higher average area of around 982.260 km2. Subsequently, from September onwards, the lake's area stabilizes, maintaining about 975.341 km2.
Figure 8

Change characteristics of Bosten Lake area in long-time series.

Figure 8

Change characteristics of Bosten Lake area in long-time series.

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Figure 9

Expansion-contraction of Bosten Lake area.

Figure 9

Expansion-contraction of Bosten Lake area.

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Figure 10

Changes in the average monthly area of Bosten Lake.

Figure 10

Changes in the average monthly area of Bosten Lake.

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Correlation analysis of lake elevation and area change and lake water balance

Figure S2 shows the relationship between the level and area of Bosten Lake, indicating a high correlation (R2 = 0.8472). In this paper, the observed lake level and area values of the same period were used to calculate the changes in water quantity of Bosten Lake in different observation periods from 2002 to 2022 according to the water balance formula (Figure S3). The water quantity of the lake fluctuates greatly and changes frequently. Table 2 shows that the water volume of Bosten Lake will decrease by 2.715 km3 during 2002–2022. From 2002 to 2013, the lake water volume decreased significantly, and the total water volume decreased by 3.993 km3. From 2013 to 2020, the amount of lake water increased by 2.473 km3. In 2020–2022, the lake shrank again, and the water volume decreased by 1.175 km3, showing a downward trend. In conclusion, the variation in lake water volume is consistent with the variation trend of lake level and area.

Table 2

Change of water volume in Bosten Lake

Time periodInitial elevation (m)Final elevation (m)Change in elevation (m)Initial area (km2)Final area (km2)Change in area (km2)Water balance (km3)
2002–2013 1,049.62 1,045.24 −4.38 1,077.19 907.35 −169.84 −3.993 
2013–2020 1,045.59 1,047.97 2.38 909.66 1,006.22 96.56 2.473 
2020–2022 1,048.17 1,047.00 −1.17 1,013.66 995.80 −17.86 −1.175 
2002–2022 1,049.62 1,047.00 −2.62 1,077.19 995.80 −81.39 2.715 
Time periodInitial elevation (m)Final elevation (m)Change in elevation (m)Initial area (km2)Final area (km2)Change in area (km2)Water balance (km3)
2002–2013 1,049.62 1,045.24 −4.38 1,077.19 907.35 −169.84 −3.993 
2013–2020 1,045.59 1,047.97 2.38 909.66 1,006.22 96.56 2.473 
2020–2022 1,048.17 1,047.00 −1.17 1,013.66 995.80 −17.86 −1.175 
2002–2022 1,049.62 1,047.00 −2.62 1,077.19 995.80 −81.39 2.715 

Annual and inter-annual variations of climate elements

The annual average air temperature, annual cumulative precipitation, and annual evaporation of Yanqi meteorological station and Heshuo meteorological station from 2002 to 2022, as well as the annual average monthly air temperature, monthly precipitation, and monthly evaporation, are shown in Figure 11. The two meteorological stations showed similar trends. From 2002 to 2022, the annual precipitation of Yanqi and Heshuo meteorological stations fluctuated between 22.2–154.5 mm and 37.1–195.3 mm, respectively, with a large annual variation. Among them, the precipitation in 2003 (124.9 and 161.3 mm), 2008 (139.8 and 146.2 mm), 2016 (154.5 and 195.3 mm), and 2021 (133.6 and 117.2 mm) was significantly higher than that in previous years. The average monthly precipitation from May to August in a year is very abundant, but there is a valley value in June, which is about 8.2 mm in Yanqi and 11.8 mm in Heshuo. Due to the lack of partial evaporation data from Heshuo meteorological station, we only analyzed its evaporation from 2002 to 2013. During this period, both Yanqi and Heshuo meteorological stations showed a trend of significant increase in evaporation, and the same valley value occurred in 2003 (1,089.9 and 1,636.4 mm). Three peaks of evaporation occurred at Yanqi meteorological station in 2008 (1,414.6 mm), 2013 (1,419.6 mm), and 2018 (1,409 mm). The evaporation of the two meteorological stations rose first and then declined in a year, with the strongest evaporation in summer. The average annual air temperature in Yanqi and Heshuo meteorological stations showed a rising trend from 2002 to 2022, and the changing rates were 0.0354 °C/a and 0.0124 °C/a, respectively. The valley value was found in 2003 (8.3 and 8 °C) and 2014 (8.3 and 8.1 °C), and the peak value was found in 2017 (10.3 and 9.6 °C). The average monthly temperature is the highest in July (23.9 and 23.7 °C) and the lowest in January (−11 and −11.2 °C).
Figure 11

(a) Annual climate change in Yanqi meteorological station. (b) Annual climate change in Heshuo meteorological station. (c) Monthly climate change in Yanqi meteorological station. (d) Monthly climate change in Heshuo meteorological station.

Figure 11

(a) Annual climate change in Yanqi meteorological station. (b) Annual climate change in Heshuo meteorological station. (c) Monthly climate change in Yanqi meteorological station. (d) Monthly climate change in Heshuo meteorological station.

Close modal

The decreasing precipitation at the Heshuo meteorological station and the continuously rising air temperatures at both stations are closely related to the overall decreasing trend in the lake level and area. In 2016, for instance, while precipitation sharply increased, the lake also expanded. In the three stages of lake change, from 2002 to 2013, the data from the Yanqi and Heshuo meteorological stations showed an increase in evaporation (18.029 and 9.367 mm/a), while precipitation exhibited a decreasing trend (−3.061, and −4.121 mm/a), leading to a shrinking trend in the lake during this period. From 2013 to 2020, the evaporation at the Yanqi meteorological station showed a rapid decrease (−32.036 mm/a), while precipitation continued to increase, resulting in an expanding trend for the lake. After 2020, there was a slight increase in evaporation and a decrease in precipitation, leading to another period of lake shrinking. Regarding seasonal changes in the lake, the water volume of the lake rapidly increases from March onwards due to warming air temperatures and the supply of meltwater from ice and snow. Precipitation increases rapidly from March to May, followed by a rapid increase in the lake level and area. Despite sufficient water supply to the lake, the summer, being the period of strongest evaporation, results in relatively low lake levels and areas. This indicates a close relationship between climate factors and the expansion and contraction of the lake.

Figures 12 and 13 show the average annual and monthly changes in the difference between precipitation and evaporation in the Bosten Lake basin. The difference between precipitation and evaporation is exceptionally large, reflecting the water consumption in the basin. It is shown from Figure 12 that the change of EP is divided into three stages of ‘rising, falling and rising’ with the nodes of 2013 and 2020, which correspond to the nodes of lake level and area change. The higher the EP, the lower the lake change. The lower the EP, the reverse of the lake change. As shown from Figure 13, EP peaked in June, showed an upward trend from January to June, and gradually dropped to the lowest point from June to December. Combined with the precipitation (sudden increase of precipitation in March) and air temperature (rise above 0 °C in March) in the basin, the level and area of Bosten Lake reached a peak from March to April, mainly due to snowmelt water volume increasing from rising spring air temperatures. The EP value is particularly high from June to August, indicating that evaporation is extraordinarily strong at this time, and the lake water level and area value are not the highest in the whole year when there is precipitation and glacial meltwater recharge in summer.
Figure 12

Average annual change of precipitation–evaporation.

Figure 12

Average annual change of precipitation–evaporation.

Close modal
Figure 13

Monthly mean change of precipitation–evaporation.

Figure 13

Monthly mean change of precipitation–evaporation.

Close modal

Responses of lake dynamics to climate change

Before grey system analysis, the correlation analysis of climate factors with annual and monthly mean lake levels and area is carried out. Figure 14 shows the correlation between the climatic factors of Heshuo and Yanqi meteorological stations and the dynamic changes of Bosten Lake. Both the annual and monthly correlations of the variables indicate that evaporation may be the main factor affecting the change in the lake. The correlation between the annual lake level and area with the annual variation in evaporation at the Yanqi meteorological station is significant at the 0.05 level. The correlation between the monthly average lake area and the monthly variation in evaporation at both meteorological stations is significant at the 0.01 level. In addition, there was a significant correlation between the monthly mean area and the meteorological elements of temperature and precipitation (p < 0.05).
Figure 14

(a) Pearson correlation coefficient heatmap of annual mean lake level and area with climate factors; (b) Spearman correlation coefficient heatmap of annual mean lake level and area with climate factors; (c) Kendall correlation coefficient heatmap of annual mean lake level and area with climate factors; (d) Pearson correlation coefficient heatmap of monthly mean lake level and area with climate factors; (e) Spearman correlation coefficient heatmap of monthly mean lake level and area with climate factors; and (f) Kendall correlation coefficient heatmap of monthly mean lake level and area with climate factors. * p < = 0.05, ** p < = 0.01.

Figure 14

(a) Pearson correlation coefficient heatmap of annual mean lake level and area with climate factors; (b) Spearman correlation coefficient heatmap of annual mean lake level and area with climate factors; (c) Kendall correlation coefficient heatmap of annual mean lake level and area with climate factors; (d) Pearson correlation coefficient heatmap of monthly mean lake level and area with climate factors; (e) Spearman correlation coefficient heatmap of monthly mean lake level and area with climate factors; and (f) Kendall correlation coefficient heatmap of monthly mean lake level and area with climate factors. * p < = 0.05, ** p < = 0.01.

Close modal

According to grey system theory, the correlation between temperature, precipitation, and evaporation from the Heshuo and Yanqi meteorological stations and the level and area changes of Bosten Lake is determined by Equations (5) and (6). As shown in Table 3(a), the annual evaporation from the Heshuo meteorological station exhibits the highest correlation with the annual average lake area (0.83). Additionally, Table 3(b) demonstrates that the evaporation from the Heshuo meteorological station also shows the highest correlation with the lake's area in terms of monthly average variation (0.66).

Table 3

Correlation degree of meteorological elements with (a) annual mean lake level and area, (b) monthly mean lake level and area

Yanqi
Heshuo
TemperaturePrecipitationEvaporationTemperaturePrecipitationEvaporation
(a) Annual mean lake level and area 
Lake level 0.7108 0.6558 0.5485 0.6607 0.6413 0.6893 
Lake area 0.6614 0.7743 0.5765 0.6665 0.6607 0.8282 
(b) Monthly mean lake level and area 
Lake level 0.5795 0.5470 0.6139 0.5622 0.5727 0.6550 
Lake area 0.5847 0.5461 0.6090 0.5672 0.5723 0.6614 
Yanqi
Heshuo
TemperaturePrecipitationEvaporationTemperaturePrecipitationEvaporation
(a) Annual mean lake level and area 
Lake level 0.7108 0.6558 0.5485 0.6607 0.6413 0.6893 
Lake area 0.6614 0.7743 0.5765 0.6665 0.6607 0.8282 
(b) Monthly mean lake level and area 
Lake level 0.5795 0.5470 0.6139 0.5622 0.5727 0.6550 
Lake area 0.5847 0.5461 0.6090 0.5672 0.5723 0.6614 

Changes in glaciers

The change of the lake is not only affected by evaporation and precipitation but also closely related to the change of glaciers. Figure 15, the glacier area in the basin shows a decreasing trend. From 2000 to 2010, the area of glaciers decreased from 415.163 to 388.129 km2, and the number of glaciers decreased by 239; from 2010 to 2020, the area and number of glaciers decreased by 36.350 km2 and 175 glaciers, respectively. Glacier melting is also one of the important ways to recharge lake water. Usually, the glaciers on the mountain are partially melted by high air temperatures in the summer, bringing water supplies to rivers and lakes downstream, so Bosten Lake remains relatively high in level and area during the season of high evaporation.
Figure 15

Change of glacier area in Bosten Lake basin.

Figure 15

Change of glacier area in Bosten Lake basin.

Close modal

Analysis of anthropogenic driving factors of lake change

The water resources system of the Bosten Lake basin in the arid region is fragile, and the uncertainty of the unstable water resources is aggravated by the frequent extreme climate. However, the influence of man-made water use factors on Bosten Lake is also especially important. At present, although human activities are still smaller than the impact of climate change on the lake level change, the impact on the water level change of Bosten Lake shows an increasing trend, which is mainly reflected in the main runoff consumption area of the plain and basin below the alluvial fan where human activities are frequent.

Hydropower is one of the main indicators of economic development in the Bosten Lake basin. The Kaidu River, the largest river in the Yanqi Basin, flows through Dashankou Hydropower Station and empties into Bosten Lake. Dashankou Hydropower Station is the largest hydropower station on the Kaidu River, which is mainly used for power generation and flood control during flood season. The project provides energy applications and brings significant economic benefits to the Yanqi Basin, but also changes the natural runoff injected into Bosten Lake, which plays an important role in the water control of the lake. In addition, with the growth of population and the development of the agricultural economy in the surrounding areas, the change of cultivated land has played a positive role in promoting the change of cultivated land. The cultivated land area of Yanqi Basin has been expanding continuously, from about 42% in 2000 to more than half of the total area of the basin in 2012 (Ghalip et al. 2015). The increase in cultivated land area also means the increase in irrigation area, and the agricultural irrigation water mainly comes from surface water diversion in different reaches of the Kaidu River and groundwater extraction in different irrigation areas. Therefore, the water diversion and consumption of agricultural irrigation increased year by year, increasing the water pressure of the runoff of Bosten Lake Basin and accelerating the continuous reduction of the water volume of Bosten Lake to a certain extent (Wang et al. 2008). On the other hand, the state began to implement the western development strategy in 2000. The western development requires it to take comprehensive measures, adhere to comprehensive management, and achieve sustainable development. In the process of treatment and conditioning, Bosten Lake undertook the task of emergency water transmission to the green ecological corridor of the lower reaches of the Tarim River, and the west pumping station was always running at full capacity. By November 2011, 11 ecological water transfers had been completed from Bosten Lake to the lower reaches of the Tarim River, with a total ecological water transfer volume of about 30 × 108 m3 (Zou et al. 2021), which affects the distribution and utilization of lake water resources. Such changes in water resource allocation and utilization patterns put the water volume of Bosten Lake in a continuous downward trend, resulting in the continuous shrinking of the water body of Bosten Lake.

Statistics show that since 2010, 13 central investment projects have been implemented in Bazhou to improve the ecological environment of rivers and lakes. These include ecological protection projects, pollution prevention and control projects of industrial enterprises, pollution source control projects, and environmental monitoring and supervision capacity building. Major measures include the implementation of an ecological water replenishment project in Bosten Lake. Since 2018, the Bayingoleng Management Bureau of the Tarim River Basin has organized the implementation of the ‘Diversion of the Kaidu River and the Huangshui Ditch’ project, focusing on the Huangshui Ditch. By 2022, the total amount of ecological water replenishment to Bosten Lake will reach 7.26 × 108 m3 (Zhao 2017). In 2010, Xinjiang Bohu Reed Industry Co., Ltd built a natural wetland conservation and ecological restoration technology research demonstration area in the Tianhe Reed Area (a small lake area southwest of Bosten Lake) to promote the restoration of water bodies here. Strengthening the unified management of water resources and developing water-saving agriculture, the state government has imposed a quota water supply target for the Kaidu-Peacock River Basin, and since 2016, it has been vigorously developing highly efficient water conservation in agriculture and conventional water conservation. To manage the ecological environment, Bazhou has stepped up efforts to manage the ecological environment of the source of the Kaidu River and the Bayinbuluk Grassland and to enhance its ability to conserve water (Yaermaimaiti et al. 2024). Since 2021, the water conservancy department of the government has implemented the ‘lake chief system’ of rivers. In the face of increasing ecological risks such as continuous discharge, water intercepting, and water transfer downstream of Bosten Lake, multiple measures have been implemented in parallel to continuously strengthen ecological construction, and the artesian flow from Bosten Lake to Peacock River has been realized for the first time in more than two decades.

This paper qualitatively discusses the driving effect of various factors on the dynamic changes of Bosten Lake in different periods and reveals the complexity of the hydrological changes of the lake. Although the study focused on the local area of Bosten Lake, the multi-source remote sensing monitoring method used has broad applicability and can be extended to the long-term water resources management of inland lakes in other arid regions. The research results not only provide a basis for the in-depth understanding of the changes in Bosten Lake but also have important implications for water resources regulation in arid areas around the world, especially in coping with hydrological instability caused by climate change. Certainly, we plan to perform a quantitative analysis in the future. This will involve utilizing the cutting-edge cryosphere – hydrology lake – dam model as described by Wang et al. (2022). By employing model-based numerical simulations, the hydrological processes of the lake-river network will be reproduced. Simultaneously, spatial information such as Digital Elevation Model (DEM), soil type, and land cover will be integrated to quantify the factors influencing lake changes.

Lakes are monitors of climate and ecological change in arid/semi-arid regions and are important links in the water cycle of the basin. In this paper, Bosten Lake, a lake in the arid region of central Asia, which is a sensitive region of global climate change, is selected as the research object. (1) Using Jason-1/2/3 data, a time series of lake water levels in Bosten Lake from 2002 to 2022 is constructed. Through comparative analysis with DAHITI, Hydroweb, and G-REALM lake water level products, it is proved that the lake level time series extracted in this study is long, highly precise, and reliable. The research results show that the level of Bosten Lake in 2013 and 2020 as nodes presents three change processes of rising and then falling. The decrease of lake level from 2002 to 2013 and the rise of lake level from 2013 to 2020 are consistent with the results of previous studies. The annual level of the lake shows a certain seasonal change. Lake levels are highest in the spring and relatively high in the summer. (2) Using Geographic Information System (GIS) and Remote Sensing (RS) technology, the GEE platform, and comprehensive utilization of Landsat-5/7/8 images from 2002 to 2022, the changing trend of the Bosten Lake area in the past two decades was obtained. The general trend of the area is in good agreement with that of the lake level. (3) Based on the time series data of lake level and area, the lake water balance formula was used to estimate the change in lake water volume from 2002 to 2022. In the past 20 years, the lake water volume decreased by 2.715 km3, which showed a decreasing trend from 2002 to 2013, an increasing trend from 2013 to 2020, and a decrease again from 2020 to 2022. (4) According to the above results, the driving mechanism behind the dynamic change of Bosten Lake is discussed by using the climate data of meteorological stations, glacial data, and human activity factors. During the study period, the dynamic changes of Bosten Lake were jointly affected by climate change and human activities, among which the main factors were evaporation, glacier melting, industrial and agricultural water use in human activities, and ecological regulation of water resources in the region, among which the effects of human activities became more and more significant in the process of lake change. Indeed, the future water security of Lake Bosten may depend heavily on the impact of human activities.

The above research conclusions have important reference significance for Bosten Lake wetland ecological environment protection, rational ecological water transfer, comprehensive utilization and development of water resources, local people's life stability and socially sustainable development, and can provide scientific basis and data support for future policy formulation of Bosten Lake water resources comprehensive development and utilization. At the same time, the results of this study show that Bosten Lake will show a certain shrinking trend after 2020. Therefore, the focus of the next step is to continue to track and study the temporal and spatial dynamic changes of Bosten Lake and explore the optimal water control interval of the lake to achieve the maximum optimization of the interests of all parties in the region, and ensure the stable and healthy development of the ecosystem of Bosten Lake while delivering water to the downstream ecology.

The Jason altimeter data used in the study came from AVISO, and the Landsat image data came from NASA. We would like to express our sincere thanks!

The manuscript was funded by The Major Science and Technology Project of the Qinghai Provincial Science and Technology Department (No. 2021-SF-A6). The funder supported this research primarily in the following aspects: Data collection and analysis and general research funding.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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