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Article

Analysis of NDVI Trends and Driving Factors in the Buffer Zone of the Aral Sea

by
Mengqi Cui
1,2,3,
Xinjun Zheng
1,2,*,
Yan Li
2,4 and
Yugang Wang
1,2
1
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2
Fukang Station of Desert Ecology, Chinese Academy of Sciences, Fukang 831505, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
4
State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China
*
Author to whom correspondence should be addressed.
Water 2023, 15(13), 2473; https://doi.org/10.3390/w15132473
Submission received: 19 April 2023 / Revised: 30 June 2023 / Accepted: 3 July 2023 / Published: 5 July 2023
(This article belongs to the Special Issue Ecohydrological Processes, Environmental Effects, and Integrated Regulation of Wetland Ecosystems, Volume II)
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Versions Notes

Abstract

:
A buffer zone can be used to analyze the influence of the lake on the surrounding spatial elements, which is of great significance for discussing the problems of lake retreat, vegetation degradation, and overall environmental deterioration in the Aral Sea. Taking the 3 km buffer zone of the Aral Sea as the research area, the spatiotemporal variation characteristics and main influencing factors of the Normalized Difference Vegetation Index (NDVI) in the Aral Sea research area were studied using remote sensing over 31 years (1987, 1997, 1992, 2007, 2010, 2014, 2015, 2017, and 2018). The results showed that the vegetation growth in the Aral Sea buffer zone deteriorates with the retreat of the lake; the vegetation of the small Aral Sea began to recover due to the stable water volume and salt content of the lake; vegetation began to grow in the west coast of the West Aral Sea; the shrinkage of the Aral Sea caused by human activities is an important factor affecting the growth of the vegetation. This study provides a reference for the restoration and reconstruction of regional vegetation.

1. Introduction

Lakes are important ecosystems providing various ecosystem services [1]. They provide habitat for a wide range of species and form essential components in hydrological, nutrient, and carbon cycles [2,3]. In arid areas with fragile ecosystems, lakes regulate climate [4], support ecological functions [5], and support human populations. Vegetation plays an important role in regulating terrestrial carbon balance and improving local environments [6,7,8]. Monitoring vegetation dynamic changes has important scientific significance and practical value [9]. A lake buffer zone generally refers to some land areas above the highest water level of lakes, reservoirs, and other water bodies, and its scope varies according to the actual situation of different water bodies [10,11]. The buffer zone is an important part of the ecosystem of a lake, and it is a crucial protective barrier for lake safety [12]. This quantitative study on the characteristics of lakeside vegetation can help us understand the range and intensity of the impact of lakes on lakeside vegetation and contribute to the knowledge useful for the restoration and reconstruction of vegetation.
Since the 1960s, contemporary long-time satellite remote sensing data have been widely used in vegetation monitoring and evaluation [13,14], providing a way to monitor the surface vegetation dynamics at different spatiotemporal scales [15,16]. Remote sensing data can be used to obtain a variety of vegetation indices, reveal the spatial pattern and heterogeneity of surface vegetation growth, and meet the needs of global and regional research. With the merits of long continuous time series, good data availability of products based on different remote sensors, and indicators of photosynthetic capacity [17], the Normalized Difference Vegetation Index (NDVI) is widely used to evaluate the growth and development of vegetation. It is an effective index to reflect the large-scale vegetation coverage and growth [7,8,9]. NDVI has various uses, including biomass estimation [18], plant productivity monitoring [19], plant stress detection [20], and leaf water potential estimation [21]. Nik et al. [22] created an NDVI time series extending to the contrasting dynamics of littoral and riparian reed stands within a wetland complex of Lake Cerknica. Li et al. [23] use the NDVI time series to find the monotonic trend of vegetation in China. Meng et al. [24] found the variation trends of NDVI in the Tibetan Plateau. NDVI values tend to increase as the plants develop, and NDVI time series data may, therefore, also be used for the monitoring of plant phenology [25,26,27]. Among the environmental impact factors, the change in NDVI can not only reflect changes in vegetation coverage but also reflect the local environmental conditions to some extent, which is of great significance to understand the ecological status of an area [28,29,30]. In arid areas, the environment is particularly fragile and the response of vegetation productivity is sensitive to lake retreat. Revealing the impacts of lake retreat on littoral vegetation productivity is of great significance for further understanding the characteristics of lake ecosystem change, the driving factors and response mechanisms of vegetation change, and the restoration of vegetation [31,32,33].
The Aral Sea is an inland lake in the arid region of Central Asia and was once the fourth-largest lake in the world [34,35]. However, due to climate change in recent decades and water resources in the lake watershed by humans, the amount of water in the lake in the Aral Sea has decreased sharply, the area has been shrinking, and the salinity has increased. This has serious negative impacts on water resources and the local ecology, causing a series of problems [36,37]. After the large-scale retreat of the Aral Sea, studying how the lakeside vegetation changes is important for ecological restoration. The present paper introduces the ecological environment crisis of the Aral Sea from the perspective of water volume, area, soil, land use, and salt dust in the area that emerged due to the retreating lake [38,39,40,41]. It focuses on the vegetation change and reconstruction in the whole Aral Sea basin and the retreat area [42,43,44]. The lake buffer zone is an important part of the lake ecosystem and a vital protective barrier. It is of great significance for ecological restoration.
This study analyzed the spatiotemporal vegetation dynamics and their response to environmental change in the buffer of the Aral Sea from 1987 to 2018. This paper focused mainly on the vegetation growing season (May to October). Analysis for spring (April to May), summer (June to August), and autumn (September to October) were also conducted to achieve a better understanding of seasonal changes in NDVI and their responses to environmental variation. We aimed (1) to investigate the NDVI of the buffer region inter-annual growing season during the past 30 years and explore facts and reasons for the NDVI trends; (2) to understand the range and intensity of the influence of the lake on vegetation on the lakeside; (3) distinguish potential drivers of NDVI changes, including the lake level and the lake area in the buffer region. The findings of this study serve as a fundamental knowledge base for projecting future vegetation growth trends, environmental changes, and ecosystem evolution in the buffer zone of the Aral Sea, all of which are necessary to assess the ecological security of the Aral Sea.

2. Materials and Methods

2.1. Study Area and Vegetation Inventory Data

The Aral Sea is an inland lake located on the territory of Kazakhstan and Uzbekistan in Central Asia (Figure 1), with a maximum length of 428 km from north to south, a width of 235 km from east to west, and a maximum area of 66,900 km2 (including 313 islands, covering an area of 23,345 km2) [45]. This region has a continental dry climate because it is located far from the ocean. Summer temperature reaches 40 °C degrees while the temperature in winter falls below −20 °C. The mean annual precipitation is 100–250 mm, and the average monthly precipitation ranges from 6 mm (in September) to 15 mm (in March) [46,47]. It used to be the world’s fourth-largest lake but has shrunk over the past few decades [48]. The water supply for the Aral Sea is dependent on the Amu Darya and Syr Darya Rivers, which are the two major tributaries of the Aral Sea Basin [37,49,50,51]. These two rivers originate from the Pamirs and Tian Shan Mountains and run through the territory of Central Asia and Afghanistan [52,53]. The Amu Darya is 2540 km long and it is geographically located in the south of the Aral Sea basin, with a coverage of the catchment area of more than 30.9 × 104 km2 [54,55,56]. The Syr Darya is approximately 3000 km, the longest river in Central Asia, and ranks second in terms of water runoff [57,58]. In the 1940s, construction began on a large scale in the Aral basin, and most of them were used for agriculture. Many sections of the channel were of poor quality, causing large amounts of water to evaporate or leak [37]. The Qaraqum, Central Asia’s largest aqueduct, is estimated to be only 30 to 70% water efficient. The canals around the Aral Sea’s two main sources of water are also leaking, with about 20 to 60 km3 of water diverted from the Amu Darya and Syr Darya rivers to the desert every year [45]. Since the 1960s, human’s high-intensity utilization of water and soil resources has led to the long-term over-exploitation of water resources in the Amu Darya and Syr Darya Rivers [59,60], and the Aral Sea has experienced a sharp reduction in water (Figure 2a,b), which has produced serious negative effects on water resources and the local ecology. The Soviet Union vigorously expanded agriculture, especially cotton cultivation, from about 4.5 million ha in 1960 to nearly 7 million ha in 1980 [35]. The local population has grown rapidly, from 14 million to about 27 million over the same period, and the total water intake has almost doubled [56]. At the same time, the destruction of the water balance in the Aral Sea basin, the overexploitation of many small tributaries, and the inefficiency of irrigation have contributed to massive waterlogging and salinity [61]. By 1990, more than 95 percent of the marshes and wetlands had become deserts, and more than 50 percent of the Delta’s lakes had dried. Salty dust is blown from the exposed lake bed to nearby farmland, degrading the soil and forcing crops to draw more river water to sustain their growth, creating a vicious cycle [61,62,63]. This phenomenon grabbed worldwide attention in the 1990s and has since been dubbed “the Aral Sea crisis” [36,37]. In 1986, the main body of the Aral Sea split into two parts—the Large Aral Sea (the South Aral Sea) and the Small Aral Sea (the North Aral Sea). In 2003, Kazakhstan built the Kok-Aral Dam between the Large Aral Sea and the Small Aral Sea to improve the environment around the Small Aral Sea and prevent water from flowing to the Large Aral Sea [64]. In 2005, the completion of the Kok-Aral Dam blocked the Syr River’s flow into the Large Aral Sea. Since then, the shrinking of the Small Aral Sea has slowed down [65]. In recent years, the water volume has increased (Figure 2a), and the salinity of the lake has begun to decline [66] (Figure 2c). In 2007, the Large Aral Sea split into two parts: the East Aral Sea and the West Aral Sea [51].
In 2019, we conducted a survey and sampling of the Aral Sea. The Aral Sea is located in the temperate zone hungriness take of Central Asia. In the western plateau area, the desert vegetation species are relatively simple, and the coverage is relatively uniform but low; the main plant types are Artemisia and Ephedra and other dwarf semi-shrubs, about 20 cm in height; there are ephemerals, such as Gramineae, with low density. The east island is high in terrain and well-covered by vegetation, mainly composed of salt-tolerant desert plants such as Haloxylon ammodendron. From Nukus to Tashkent, the desert plants are mainly clustered in Artemisia, Chenopodiaceae, and Ephedra, while there are also Gramineae such as the Poa annua. The main shrub species distributed in the delta of Amu Darya River are Suaeda physophora, Tamarix chinensis, Haloxylon ammodendron, Lycium ruthenicum, Halostachys capsica, and Calligonum mongolicum, at a farther distance from the lakeside, the vegetation distribution consists of Phragmites australis, Tamarix passerinoides, Halostachys capsica, and Suaeda physophora. The alluvial meadow of the Tugayi forest at the front of the Syr River delta decreased, and the Phragmites australis was sparse with soil drought. The formerly dense undergrowth of the central delta, such as Elaeagnus pungens, Salix babylonica, Halimodendron halodendron, and Tamarix passerinoides, has become very sparse, and the Calamagrostis epigeios and Phragmites australis have disappeared, replaced by Alhagi sparsifolia, and Salsola collina (Table 1).

2.2. Data Sources

The Landsat products were downloaded from the United States Geological Survey (USGS) online web portal. The scenes in 1987, 1997, 1992, 2007, and 2010 were first-level spectral data products from Landsat4 and Landsat5 Thematic Mapper (TM), with a spatial resolution of 30 m and a temporal resolution of 16 d. The scenes in 2014, 2015, 2017, and 2018 were first-level multispectral data products from Landsat8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) with a spatial resolution of 30 m and a temporal resolution of 16d (Table 2).
ENVI5.3 and ArcGIS10.2.2 were used for radiometric calibration and band fusion of the original remote sensing image. According to the shoreline of the Aral Sea in different years, the scope of the lakeside was determined and formed the contours of the study area in different periods (Figure 3). The NDVI tool in ENVI 5.3 Toolbox was used to calculate the band of images and the NDVI value from May to October was obtained. A maximum value composite (MVC) method was applied to obtain the annual NDVI data by reducing the atmospheric effects of clouds and aerosols [69,70]. The average NDVI for the growing season, spring, summer, and autumn was calculated for analysis. Pixels location with NDVI values of a month in the growing season not greater than zero were also masked and excluded from the study to decrease the effects of snow cover and water.
Data on the Aral Sea’s water surface area and water level were obtained from the Portal of Knowledge for Water and Environmental Issues in Central Asia. The meteorological data are based on the time series (TS) high resolution (0.5 × 0.5°) monthly variation grid data provided by the Grid Climatic Research Unit (CRU) of the University of East Anglia. The data version is 4.04. The temperature and precipitation data from 1960 to 2018 are used.

2.3. Analysis Methods

2.3.1. Normalized Difference Vegetation Index (NDVI) and Maximum Value Composite (MVC)

The Normalized Difference Vegetation Index (NDVI) shows light absorbance and reflectance. For each pixel, we then calculated the NDVI using the following equation [22]:
N D V I = N I R − R e d / N I R + R e d  
where NIR represents the reflectance in the near-infrared region of the electromagnetic spectrum and Red represents the reflectance in the red region of the electromagnetic spectrum.
To study the overall changes in vegetation in space, monthly NDVI and annual NDVI values were obtained by the Maximum Value Composite (MVC), which can effectively reduce the influence of atmospheric aerosols, cloud shadows, solar altitude angles, and other factors [71]. The formula is as follows:
M a x N D V I i = M a x N D V I 1 , N D V I 2 , N D V I 3 , N D V I 4
where MaxNDVIi indicates the maximum monthly NDVI; i indicates the month, and the value ranges from 5 to 10. NDVI1–NDVI4 represent the preprocessed NDVI values of the original images in corresponding months.

2.3.2. Buffer Analysis

Buffer analysis is a common spatial geometric relationship analysis tool in ArcGIS for analyzing spatial proximity. The buffer zone is a band-shaped buffer area with a specific distance established around the spatial objects of different geometric types to represent the specific influence range or service range of the spatial target. It is used to analyze the influence of the geographical object on the surrounding spatial elements [72,73]. From the perspective of GIS technology, the buffer zone refers to a buffer polygon area with a specified width generated by setting a buffer radius of a specific value around geographic elements such as points, lines, and areas. Because of the different geometries of spatial objects, the construction mode of the buffer is also different. From a mathematical point of view, a buffer is a set of spaces that meet certain conditions, and the mathematical expression is:
B i = x : d x i , O i ≤ R
where Oi is the object, R is the neighborhood radius, d is the minimum Euclidean distance, and Bi is a set of all points whose distance from Oi is less than or equal to R.
As an independent data layer for overlay analysis, the buffer zone can be applied to spatial analysis such as roads, rivers, and residential areas [74]. Hu et al. [10] determined that the width of the Lake Taihu buffer zone is 2 km based on literature research, domestic and foreign river lake buffer zone research, and field investigations. In this study, the buffer zone of the Aral Sea is initially set as 3 km, and 3 km away from the present lake shoreline is taken as the research area. The use of buffer area analysis to establish the Aral Sea as the center of the circle, the search distance is 3 km, and the interval is 0.25 km.

2.3.3. Trend Analysis

We used linear regression to analyze the variation and intensity of NDVI in the growing season of vegetation [73]. The regression analysis was used to analyze the change in the maximum NDVI in the buffer zone from 1987 to 2018. The trend of NDVI in each grid of remote sensing images from 1987 to 2018 was fitted pixel by pixel to obtain the trend of NDVI in the study period, and the linear regression relationship between variable NDVIi and time t was established. The slope represents the rate of change of variable xi. When slope > 0, this means that the growing season NDVI is increasing during the study period. When slope = 0, it indicates that this variable does not change [75,76]. The greater the absolute value of slope, the greater the change in variable xi.
s l o p e = n ∑ i = 1 n N D V I i t i − ∑ i = 1 n N D V I i ∑ i = 1 n t i n ∑ i = 1 n t i 2 − ∑ i = 1 n t i 2
where n is the number of years in the monitoring period (n = 9); NDVIi is the maximum value of NDVI in the growing season of different years.

2.3.4. Correlation Analysis between Vegetation Dynamics and Lake Hydrology

NDVI can be fitted by Unitary Linear Regression (ULR) analysis in this study to represent the influence of lake hydrology, including the area and the level of the lake. Correlation coefficients were used [77]:
r x y = ∑ i = 1 n x i − x ¯ y i − y ¯ ∑ i = 1 n x i − x ¯ 2 ∑ i = 1 n y i − y ¯ 2
where x ¯ and y ¯ represent the average values of the sample values of the two elements; rxy is the correlation coefficient between x and y, indicating the correlation between the two elements with a value between [−1, 1].

3. Results

3.1. Temporal Variation Trends of NDVImax

3.1.1. Temporal Variation in the Aral Sea

The area-weighted average of the NDVImax of the Aral Sea buffer zone during the growing season from 1987 to 2018 ranges from 0.09 to 0.19, and the trend is −0.173 × 10−2 a−1 (p < 0.005)—a fluctuating downward trend over time (Figure 4a). NDVI had a downward trend from 1987 to 1992, a slow rise from 1992 to 2007, and a decline again from 2007 to 2017. NDVI reached its lowest point in 2017, and slightly increased in 2018.

3.1.2. Temporal Variation in the Small Aral Sea

From 1987 to 2018, the area-weighted average of the NDVImax of the growing season in the buffer zone of the Small Aral Sea decreased over time (Figure 4b), ranged from 0.12–0.25, and the trend was −0.186 × 10−2 a−1 (p < 0.005); from 1987 to 2014, the area-weighted average of the NDVImax decreased, and the trend was 0.29 × 10−2 a−1 (p < 0.005); from 2015 to 2018, the NDVImax during the growing season increased with the trend 0.84 × 10−2 a−1 (p = 0.003).

3.1.3. Temporal Variation in the West Bank of the Western Aral

The area-weighted average of the NDVImax of the growing season in the buffer zone of the west bank of the Western Aral from 1987 to 2018 ranged from 0.10–0.19 and decreased over time (Figure 4c). The trend was −0.114 × 10−2 a−1 (p < 0.005). NDVI decreased from 1987 to 1997, increased from 1997 to 2010, and decreased again from 2010 to 2014. NDVI reached its lowest point in 2014 and slightly increased from 2014 to 2018.

3.1.4. Temporal Variation in the East Bank of the Eastern Aral

The area-weighted average of the NDVImax of the growing season in the buffer zone of the east bank of the Eastern Aral from 1987 to 2018 ranged from 0.03–0.18 and decreased over time (Figure 4d). The trend was −0.124 × 10−2 a−1 (p < 0.005). NDVI decreased from 1987 to 1997, increased from 1997 to 2010, and decreased again from 2010 to 2015. NDVI reached its lowest point in 2015 and slightly increased from 2015 to 2018.

3.2. Spatial Variation of Annual NDVImax

3.2.1. Spatial Variation in the Aral Sea

From 1987 to 2018, the annual NDVImax in the growing season of the Aral Sea decreased with increasing distance from the lake within the 3 km buffer zone (Figure 5a). In other years, it is relatively stable, showing a downward trend within 0.25–1.25 km from the lake surface, and almost no change after 1.25 km. During the study period, the variation in annual NDVImax in the growing season of the 3 km buffer zone ranged from 0.09 to 0.2, with the minimum and maximum values appearing in 2017 and 1987, respectively. This indicates that within a range of 3 km lakeside, the NDVImax decreased with the distance from the lake; it tended to be stable after 1.25 km.

3.2.2. Spatial Variation in the Small Aral Sea

The annual NDVImax the growing season of the Small Aral Sea 1987–2018 decreased with increasing distance from the lake within the 3 km buffer zone (Figure 5b), and the value ranged from 0.12 to 0.3. In 1987, the annual NDVImax in the buffer zone fluctuated slightly within the study area, decreasing first and then stabilizing. Within 0.25–0.75 km from the lake, the annual NDVImax barely changed, it declined beyond 0.75 km and leveled off at about 1.5 km. After the 1990s, the annual NDVImax becomes stable, and the variation is similar each year. The annual NDVImax decreases within 1.0 km from the lake surface, and there is almost no change after 1.25 km, i.e., the buffer distance at which the annual NDVImax becomes stable is 1.25 km.

3.2.3. Spatial Variation in the Western Aral Sea

From 1987 to 2018, the annual NDVImax in the growing season of the west bank of the Western Aral first increased with increasing distance from the lake to 3 km and then tended to be stable (Figure 5c), with a range of 0.05–0.2. In 1987, the annual NDVImax increased within 3 km from the lake surface, with no obvious regularity. This was because the lakeside retreat of the west bank of the Western Aral Sea was small from 1987 to 1997, and most of it was cliff within 3 km. In 2007 and 2010, the annual NDVImax increased within 1 km from the lake surface and then decreased. Farther than 1.75 km from the lake’s surface, the annual NDVImax increased again. After 2010, it rapidly increased within 1.25 km from the lake surface and tended to be stable after 1.25 km, i.e., the buffer distance at which the annual NDVImax becomes stable is 1.25 km.
From 1987 to 2018, the annual NDVImax in the growing season of the east bank of the Western Aral Sea first decreased with increasing distance from the lake within 3 km and then tended to be stable (Figure 5d), with a range of 0.04–0.15 and the variation of each year similar. The annual NDVImax first decreased within 1.0 km from the lake. Farther than 1.25 km, there is almost no change, i.e., the buffer distance when the annual NDVImax reaches a stable value is 1.25 km. This indicates that the annual NDVImax after 1.25 km is little affected by lake water.

3.2.4. Spatial Variation in the Eastern Aral Sea

From 1987 to 2018, the annual NDVImax in the growing season of the west bank of the Eastern Aral barely changed within the range of 3 km (Figure 5e), and the value ranged from 0 to 0.1, indicating mostly bare land. The east bank of the Western Aral is a newly exposed lake basin after the retreat of the Aral Sea and the vegetation is not established. This indicates that the annual NDVImax is not affected by lake water.
From 1987 to 2018, the annual NDVImax in the growing season of the east bank of the Eastern Aral decreased slightly with increasing distance from the lake within 3 km of the lakeside and showed a steady trend with the range of 0.04–0.2 (Figure 5f). The annual NDVImax in 2007 was the largest, and the vegetation growth was better. In 1987, the annual NDVImax fluctuated with increasing distance, but the change was not large. The other years showed a decreasing trend, but the change was small.

3.3. Driving Forces of Vegetation Change

3.3.1. Driving Forces of Vegetation Change in the Aral Sea

The growth of vegetation is inseparable from water. The NDVImax in the study area has a significant positive correlation with the water level of the Aral Sea and the lake area (Figure 6a,b). With the increase in the water level of the Aral Sea and the increase in the lake area, the NDVImax of the vegetation increases significantly. Among them, the correlation with water level is more significant.
Since the 1960s, the annual precipitation in the Aral Sea research area changed slightly (Figure 7a), while the average temperature in the growing season increased (Figure 7b). There is no significant correlation between the NDVImax and the average temperature of the growing season and the annual precipitation in the study area. In particular, there is a weak negative correlation between NDVImax and the temperature (Figure 6c,d), which decreases with the increase in the average temperature of the growing season. There is no correlation with annual precipitation.

3.3.2. Driving Forces of Vegetation Change in the Small Aral Sea and the West Bank of the Western Aral

As the Aral Sea recedes, the salt content of different parts varies. During the study period, the salt content of the Small Aral Sea changed little, with a maximum value of 26.35 g/L. The NDVImax was positively correlated with the salt content of the lake water (Figure 8a), and the NDVImax increased with the increase in the salt content of the Aral Sea. The salt content of the Western Aral increased rapidly as the retreat intensified, with a maximum value of 265.455 g/L. The NDVImax in the study area on the west bank of the Western Aral showed a weak negative correlation with the salt content in the lake (Figure 8a) and the NDVImax decreased with the increase in salt content in the Western Aral.
The lake area and water level of the Small Aral Sea did not change significantly during the study period and the NDVImax in the study area was not significantly correlated with the lake level (Figure 8b) but was negatively correlated with the lake area (Figure 8d). The lake area and water level of the Western Aral decreased rapidly, and NDVImax of the study area of the Western Aral showed a significant positive correlation with the lake level (Figure 8c) and a weak positive correlation with the lake area (Figure 8e).
There was no significant correlation between the NDVImax in the study area of the Small Aral Sea and the west bank of the Western Aral with the annual precipitation and the mean temperature of the growing season (Figure 8f–i).

4. Discussion

The vegetation changes in dry lake bed [46,78], lakeside wetland [79], and river delta are related to wetland changes [80] caused by lake changes. In nearly 60 years since 1960, the structure, function, and spatial pattern of the vegetation ecosystem have continuously evolved. Groundwater depth is an important driving force for the change in spatial and temporal patterns of ecosystems [81]. In arid desert environments, the water required by woody plants cannot be satisfied solely by natural precipitation, so vegetation formed by woody plants with stronger soil and water conservation function is strongly affected and controlled by groundwater depth, river, wetland, and lake distribution [82,83]. The retreat of the Aral Sea has been shown to affect the environment in some studies [36,37], and the loss of vegetation is one of them. Li et al. [23,24] use the NDVI time series to find the monotonic trend of vegetation, in the present study, the results showed that the area-weighted average of the NDVImax in the growing season of the Aral Sea was between 0.09 and 0.19, showing a decreasing trend. Whereas the vegetation along the lakeshore of the Small Aral Sea deteriorated after the sea is destroyed, the completion of the Kok-Aral Dam provided a better environment for its growth and development and the vegetation begins to recover [66]. Between 2005 and 2014, the water level fluctuated with drought and flood years; however, in general, the water level and area of the Small Aral Sea tended to be stable, providing a basis for the germination and growth of lakeside vegetation. The NDVImax in the lakeside growing season of the Small Aral Sea decreased before 2014 and increased after 2014. The completion of the Kok-Aral Dam was a death sentence for the Large Aral Sea. Water flowing from the Syr River into the desert basin only flows into the Small Aral Sea, and the Large Aral Sea has undergone drastic changes. The environment of the Large Aral Sea has undergone great changes with the retreat of the lake surface, and the vegetation was severely damaged. The vegetation growth of the different shores of the East and West Aral Sea varies, but the vegetation growth of the whole is relatively poor, especially the East Aral Sea with almost no vegetation growth and thus just a large area of bare land. The west bank of the Western Aral is a cliff, and with the retreat of the lake, the lake bed is exposed, which provides more space for the growth of vegetation. The water available to vegetation on the west coast also became a key factor affecting its growth and development, and the lake level showed a significant positive correlation with NDVImax. Since 1987, the newly exposed lake basin on the west coast of the West Aral Sea is about 2 km, and the exposed lake basin provides space for the settlement of lakeside vegetation. The vegetation growth dynamics beyond 2 km were not analyzed. NDVI can reflect changes in vegetation coverage, but there is no characterization of the types of vegetation that grows or how the vegetation community changed.
Through field investigation, in the environmental deterioration of the Aral Sea, the soil of the lake bed exposed at different periods from the far shore to the lakeside showed obvious plant species gradients. We found there was obvious spatial heterogeneity in the growth of lakeside vegetation. Within a range of 3 km lakeside, the NDVImax decreased and was higher with the distance from the lake; it tended to be stable after 1.25 km. Within the lakeside buffer, with the increase in the distance from the lakeside, the lake provides less water for vegetation, and there is a difference in vegetation growth. Within 1.25 km from the lakeside, the farther the distance from the lakeside, the soil and influence of the lake will be weaker on vegetation.
Yang et al. [40] found that human activities (especially irrigation and damming) are the dominant factors influencing the long-term variations of the Aral Sea. Similarly, Micklin [48] believed that irrigated water withdrawal was the dominant factor causing the recession of the Aral Sea from 1911 to 2010. Nik et al. [22] proved that more constant and moderate conditions at the riparian site benefited the growth and productivity of the common reed, we also found the annual in the lakeside area of the Aral Sea was significantly affected by the water level and lake surface area, showing a significant positive correlation. Therefore, the shrinkage of the Aral Sea caused by human factors is an important factor affecting the growth of Aral Sea vegetation.
Due to the decrease in the water level of the Aral Sea, the water is gradually concentrated and the water quality changes [84], the salt gradually increased and began to form a hard salt crust along the shore of the lake. With the further decrease in the water level, the salt crust gradually evolved into salty soil under a series of physical effects such as drying and weathering; under wind erosion, the salt soil further evolves into other types of bare land [34]. This is the biggest obstacle preventing ecological restoration and environmental improvement of the Aral Sea region. However, halophytes have strong salt tolerance. Halophytic vegetation has a certain resistance to salt concentration, and a certain concentration of salt can promote germination. Therefore, with the increase in salt in the Aral Sea, there is still some vegetation growth, and vegetation types have changed from shrubs to more salt-tolerant herbs. The salinity of the Small Aral Sea was stable (~30 g/L), which has little influence on the growth of halophytic vegetation. With natural succession, vegetation began to grow and settle, and NDVImax increased but showed a positive correlation with salt. Halophytic vegetation of the Large Aral Sea adapts to the harsh growth environment and begins to grow, but salt is still an important factor restricting its growth and development, and NDVImax is negatively correlated with salt. Within 2 km, the salt of the West Aral Sea increased with time. The closer the lake is to the shore, the higher the salt concentration is, which is more unfavorable to the growth of vegetation. On the contrary, with the increase in the distance from the lake shore, the soil salinity decreased and the halophytic vegetation could grow in the adapted environment. The NDVImax increased with increasing the distance from the lake shore at 1.25 km.

5. Conclusions

Based on buffer zone analysis and trend analysis, we analyzed trends of lakeside vegetation in the Aral Sea with the retreat of the lake and discussed the driving factors of the change in the Aral Sea vegetation. The results showed that the area-weighted average of the NDVImax in the growing season of the Aral Sea was between 0.09 and 0.19, showing a decreasing trend; the NDVImax in the lakeside growing season of the Small Aral Sea decreased before 2014 and increased after 2014; the NDVImax in the growing season for the East Aral Sea and West Aral Sea showed a fluctuating decline. There was obvious spatial heterogeneity in the growth of lakeside vegetation. Within a range of 3 km lakeside, the NDVImax decreased and was higher with the distance from the lake; it tended to be stable after 1.25 km.
The impact of human activities on the growth of vegetation in the buffer zone of the Aral Sea is crucial and overrides the impacts of climate change. The annual NDVImax in the lakeside area of the Aral Sea was significantly affected by the water level and lake surface area, showing a significant positive correlation. This had little to do with changes in temperature and precipitation. There was a positive correlation between the annual NDVImax and the salt content of the lake in the Small Aral Sea area. On the west bank of the Western Aral, the annual NDVImax was negatively correlated with the salt content of the lake, and significantly positively correlated with the lake level. The effects of annual precipitation and the average temperature of the growing season on the annual NDVImax in the study area of the Small Aral Sea and the west bank of the Western Aral were not significant. Therefore, the shrinkage of the Aral Sea caused by human factors is an important factor affecting the growth of Aral Sea vegetation.

Author Contributions

Conceptualization, Y.W.; methodology, collected and processed the data, writing—original draft preparation, M.C.; supervision, review and editing X.Z. and Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Strategic Priority Research Program of Chinese Academy of Sciences (no. XDA2006030102); and the “Western Light” program of the Chinese Academy of Sciences (2019-XBQNXZ-B-003).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors also thank the anonymous reviewers for their helpful comments and suggestions.

Conflicts of Interest

The authors declare that they have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper.

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Water 15 02473 g001 550
Figure 1. Location of the Aral Sea.
Figure 1. Location of the Aral Sea.
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Figure 2. Changes in water level and area of the Aral Sea since the 1950s: (a) water surface area; (b) level; (c) salt. Source: [67].
Figure 2. Changes in water level and area of the Aral Sea since the 1950s: (a) water surface area; (b) level; (c) salt. Source: [67].
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Figure 3. Remote sensing images and contours of the Aral Sea: (a) 1987; (b) 1992; (c)1997; (d) 2007; (e) 2010; (f) 2014; (g) 2015; (h) 2017, and (i) 2018.
Figure 3. Remote sensing images and contours of the Aral Sea: (a) 1987; (b) 1992; (c)1997; (d) 2007; (e) 2010; (f) 2014; (g) 2015; (h) 2017, and (i) 2018.
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Figure 4. Changes in NDVImax during growing season in the study area from 1987 to 2018. (a): temporal variation of NDVImax in the Aral Sea; (b): temporal variation of NDVImax in the Small Aral Sea; (c): temporal variation of NDVImax in the west bank of the Western Aral; (d): temporal variation of NDVImax in the east bank of the Western Aral.
Figure 4. Changes in NDVImax during growing season in the study area from 1987 to 2018. (a): temporal variation of NDVImax in the Aral Sea; (b): temporal variation of NDVImax in the Small Aral Sea; (c): temporal variation of NDVImax in the west bank of the Western Aral; (d): temporal variation of NDVImax in the east bank of the Western Aral.
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Figure 5. Variation of NDVImax in Aral Sea buffer zone from 1987 to 2018.
Figure 5. Variation of NDVImax in Aral Sea buffer zone from 1987 to 2018.
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Figure 6. The relationship between NDVImax and driving factors in the study area from 1987 to 2018. (a): water level; (b): lake surface area; (c): temperature; (d): precipitation.
Figure 6. The relationship between NDVImax and driving factors in the study area from 1987 to 2018. (a): water level; (b): lake surface area; (c): temperature; (d): precipitation.
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Figure 7. Variation of precipitation and growing season temperature in the Aral Sea during 1960–2018. (a): Precipitation; (b): growing season temperature.
Figure 7. Variation of precipitation and growing season temperature in the Aral Sea during 1960–2018. (a): Precipitation; (b): growing season temperature.
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Water 15 02473 g008a 550Water 15 02473 g008b 550
Figure 8. The relationship between NDVImax and driving factors in the study area from 1987 to 2018. (a): the salt of the Small Aral Sea and the Western Aral; (b): the level of the Small Aral Sea; (c): the level of the west bank of the Western Aral (d): the surface area of the Small Aral Sea; (e): the surface area of the west bank of the Western Aral (f): the precipitation of the Small Aral Sea; (g): the precipitation of the west bank of the Western Aral (h): the temperature of the Small Aral Sea (i): the temperature of the west bank of the Western Aral.
Figure 8. The relationship between NDVImax and driving factors in the study area from 1987 to 2018. (a): the salt of the Small Aral Sea and the Western Aral; (b): the level of the Small Aral Sea; (c): the level of the west bank of the Western Aral (d): the surface area of the Small Aral Sea; (e): the surface area of the west bank of the Western Aral (f): the precipitation of the Small Aral Sea; (g): the precipitation of the west bank of the Western Aral (h): the temperature of the Small Aral Sea (i): the temperature of the west bank of the Western Aral.
Water 15 02473 g008aWater 15 02473 g008b
Table
Table 1. List of lake ecosystem vegetation survey 2019 in Large Aral Sea.
Table 1. List of lake ecosystem vegetation survey 2019 in Large Aral Sea.
Latin NamesFamilies
Phragmites australis (Cav.) Trin. ex Steud.Gramineae
Haloxylon ammodendron (C. A. Mey.) Bunge.Chenopodiaceae
Tamarix chinensis Lour.Tamaricaceae
Calamagrostis epigeios (L.) Roth. Gramineae
Seriphidium santolinum (Schrenk) Poljak. Compositae
Alhagi sparsifolia Shap. Leguminosae
Halostachys caspica C. A. Mey. ex Schrenk. Chenopodiaceae
Halimodendron halodendron (Pall.) Voss. Leguminosae
Lycium ruthenicum Murray. Solanaceae
Suaeda physophora Pall. Chenopodiaceae
Calligonum caput-medusae Schrenk.Polygonaceae
Salsola collina Pall.Chenopodiaceae
Table
Table 2. Remote sensing data sources. Source: [68].
Table 2. Remote sensing data sources. Source: [68].
Data SourcesTimePath/RowSpatial Resolution (m)Temporal Resolution (d)
Landsat 5 TM1987p160/r28-303016
1992p161/r27-30
1997p162/r28-30
2007
2010
Landsat 8 OLI2014p160/r28-303016
2015p161/r27-30
2017p162/r28-30
2018
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Cui, M.; Zheng, X.; Li, Y.; Wang, Y. Analysis of NDVI Trends and Driving Factors in the Buffer Zone of the Aral Sea. Water 2023, 15, 2473. https://doi.org/10.3390/w15132473

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Cui M, Zheng X, Li Y, Wang Y. Analysis of NDVI Trends and Driving Factors in the Buffer Zone of the Aral Sea. Water. 2023; 15(13):2473. https://doi.org/10.3390/w15132473

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Cui, Mengqi, Xinjun Zheng, Yan Li, and Yugang Wang. 2023. "Analysis of NDVI Trends and Driving Factors in the Buffer Zone of the Aral Sea" Water 15, no. 13: 2473. https://doi.org/10.3390/w15132473

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