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Article

Monitoring and Mapping of Soil Salinity on the Exposed Seabed of the Aral Sea, Central Asia

by
Zihao Duan
1,2,
Xiaolei Wang
1,* and
Lin Sun
1
1
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Water 2022, 14(9), 1438; https://doi.org/10.3390/w14091438
Submission received: 10 April 2022 / Revised: 24 April 2022 / Accepted: 28 April 2022 / Published: 30 April 2022
(This article belongs to the Section Soil and Water)
Browse Figures
Versions Notes

Abstract

:
The incredible drying of the Aral Sea has resulted in a large area of exposed seafloor with saline soils, which has led to catastrophic consequences. This study investigated ground-truth soil salinity data and used Landsat data to map the soil salinity distribution of the exposed seabed of the Aral Sea from 1960 onwards. The soil salinity distribution, with the depth from 0 cm to 100 cm, was analyzed. The correlation analysis was applied to find the best performance index in describing soil salinity changes. The results showed that ground-truth data of topsoil salinity (depth of 0−5 cm) exhibited a significantly strong correlation with soil salinity index 4 (SI4) among seven indices, where the Pearson correlation coefficient (r) was up to 0.92. Based on the relationship between soil salinity sampling data and SI4, a linear regression model was employed to determine the capability of evaluating the soil salinity distribution of the Aral Sea with the coefficient of determination (R2), root mean squared error (RMSE), and ratio of performance to deviation (RPD) values of 0.84 and 0.86 dS m−1 and 2.36, respectively. The SI4 performed well and was used to predict the soil salinity distribution on the exposed seabed. The distribution showed that soil salinity increased from the former to current shoreline. In the North Aral Sea, compared to 1986, the water area remained stable, accounting for 50.3% in 2020, and the soil salinization level was relatively low. However, the moderately and slightly saline areas dominated 73.8% and 7.5% of the South Aral Sea in 2020, with an increase of 53% and 6% transformed from the water area. The area of salinized soils dramatically increased. The strongly and extremely saline areas were mainly located in the northeastern part of the eastern basin and western part of Vozrozhdeniya Island, respectively, and were the main source of salt-dust storms. These results support the dynamic monitoring and distribution patterns of soil salinization in the Aral Sea.

1. Introduction

Soil salinization is a major type of land degradation and has been a critical issue over the past few decades [1,2]. It is a threat to the sustainable development in arid and semi-arid areas. Approximately 1 billion hectares of soil globally is salt-affected, most of which can be found in arid and semi-arid regions [3]. More than 1.5 billion people face harsh challenges relating to food production as a result of soil degradation [4,5]. Soil salinity is one of the effective evaluation indicators of soil salinization [6,7]. This implies that accurate and efficient monitoring of local soil salinity dynamics is particularly important for assessing sustainable land resource management in arid regions.
Soil electrical conductivity (EC) measurements are the usual methods for the measurement of soil salinity; however, they are cost-prohibitive and are limited in time and space [8]. Remote sensing is widely used owing to its advantages in monitoring large spatial areas and long recording periods as well as its good spatial distribution [9]. Many studies have assessed soil salinity using remote sensing [10,11,12,13,14]. First, the soil salinity can be checked by the spectral characteristics of the soil surface from satellite data. For example, Rao et al. [9] studied the spectral characteristics of several typical salt-affected soils in the Ganges alluvial plain in India. Salinized soil exhibited high reflectance values in the visible and near-infrared spectra. In addition, soil salinity can be detected using the characteristics of vegetation; for instance, Scudiero et al. [13] explored and assessed soil salinity via vegetation indices in the western San Joaquin Valley, USA, which showed good performance. Different methods have been employed to evaluate soil salinity distribution in an attempt to obtain higher accuracy [14]. Notably, more studies have used a combination of an in situ salinity dataset and multi-bands with regression analysis and have effectively monitored and mapped the soil salinity distribution [15,16,17,18]. However, appropriate indices for soil salinity should be determined with care due to differences in methods and regions.
The water salt content increased dramatically with a decline in the Aral Sea. Subsequently, the salt in the seawater remained in the soil, resulting in high salinity of the exposed seabed. The dried bottom of the South Aral Sea has become a source of salt-dust storms, which can be transmitted to the Siberian plain and Iranian plateau [19,20,21]. Consequently, this has caused great harm to the ecological environment (e.g., air pollution, degradation of land and vegetation) [22,23] and caused health issues for residents (e.g., respiratory and reproductive diseases as well as cancers) [24,25,26]. Determining the soil salinity distribution of the exposed seabed after the water level drops has become the basis for solving ecological problems. Some studies have evaluated the global soil salinity distribution [3,4,27,28] and salt-affected coastline [29], which is helpful for improving the understanding of soil salinity changes and distribution in large-scale spatiotemporal variations. Unfortunately, the dried bottom of the Aral Sea since 1960 has not been included in these studies. Some studies have collected and analyzed soil samples from the dried seafloor in the northeast of the South Aral Sea [30] and investigated the distribution of salinity indices in this region [31]; however, the time scale, regional distribution, and accuracy are limited. There is a lack of comprehensive assessment of the spatial patterns of soil salinity and change processes on the dry seafloor.
Although it is well-known that soil salinization is severe in the retreat area of the Aral Sea [30,31], there have been few studies on the distribution of and changes in soil salinity. Thus, to provide strategies for ecological restoration in retreat areas, analyzing the temporal and spatial distribution patterns of soil salinity is necessary. This is a key issue in halting salinization and boosting soil productivity.
The salinity changes in the exposed seabed since 1960 were explored in this study. Specifically, the aims of this study were to (1) analyze soil salinity vertical distribution based on sampling soil data from 2019; (2) analyze the relationship between soil salinity indices derived from Landsat data and sampling soil salinity data and validate their capabilities in monitoring the soil salinity dynamic; (3) determine the appropriate salinity index to derive soil salinity maps of the Aral Sea; (4) evaluate the distribution of topsoil salinity on the exposed seabed of the Aral Sea; and (5) determine changes in topsoil salinity on the exposed seafloor from 1986 to 2020.

2. Materials and Methods

2.1. Study Region

The Aral Sea is the terminal lake of Amu Darya and Syr Darya in Central Asia (Figure 1). It is the fourth largest inland water body in the world, covering an area of 67,500 km2 [25]. The Karakum Desert is located to the southwest, and the Kyzylkum Desert is located to the northeast. The average annual precipitation is less than 250 mm during the period of 1960–2020, and the potential annual evaporation varies from 800 to 1300 mm [31,32]. The average temperature ranges from −6.60 °C to 17.98 °C [33]. In the South Aral, the water salinity increased to 220.2 g/L in the eastern basin in 2008 and 193.5 g/L in the western basin in 2019 [34,35]. However, the salinity decreased to 5.8 g/L in 2019 in the North Aral Sea with the water recovery [36].
The Aral Sea water level has declined sharply since the 1960s, which is attributable to a remarkable reduction in inflow from Amu Darya and Syr Darya [35]. The long-term negative water balance has resulted in extensive retreat of the lake. In the early 1990s, a dam was built in the Berg Strait between the South and North Aral seas. Subsequently, the lake level in the north has recovered to approximately 42 m since 2005. Nonetheless, the water level in the south has been decreasing. Compared with 1960, the exposed playa surface area in 2020 is 89% of its original area.

2.2. Soil Sampling and Analysis

Measurements of soil salinity were taken in the retreat area of the South Aral Sea in January 2019. These plots were distributed in different elevations, and as many as possible were investigated. They represent the typical environment without vegetation. Sampling locations of each plot were separated by a minimum of 2–3 km. Meanwhile, these sampling sites were easy to access. The size of each plot was 1 × 1 m2. Soil samples were collected 3 times at each plot. A hand auger was used to collect the soil at the following vertical depth intervals: 0–5, 5–15, 15–40, 40–70, and 70–100 cm. Each soil sample was collected one time from each level. The 150 soil samples were obtained from 10 plots (Figure 1). The location of each sample was recorded using GPS (Trimble RTX, accuracy <0.05 m). The soil samples were placed in sealed plastic bags, numbered, and returned to the laboratory. Then, the stones and plant residues were removed through the use of a 2 mm sieve, and the big soil blocks were smashed with a wooden mallet to create final soil particles. Finally, the soil samples were dried and stored in the laboratory for data extraction and analysis, and the soil salinity (EC) was obtained. More details about the process of obtaining EC data in the laboratory can be found in Wang et al. [7]. Additionally, the total salt content of 0–100 cm depth of soil in each plot was obtained by adding the salinity values of the five levels for the whole profile. According to the Food and Agriculture Organization (FAO) classification [3], soil salinity was classified into five levels based on EC, as shown in Table 1.
Furthermore, these site samples were divided into different elevations within 1 m intervals according to their locations. If there was more than one plot within a 1 m elevation, the mean value of these samples was calculated as the representative value for this elevation interval. Finally, the soil salinity at different elevations was presented. The elevation data of site samples can be obtained from the digital elevation model (DEM). It is based on a 1:500,000 topographic map of the Aral Sea bottom [37]. The DEM used the same projection systems as the Landsat images and was gridded to 30 m. Additionally, the locations of the soil samples were same in 1986 and 2020, when the soil salinity distribution was evaluated.

2.3. Soil Salinity Indices

It is important to use spectral properties to describe the characteristics of soil salinity using remote sensing [38,39]. The soil salinity index was adjusted according to the different responses of the salinized soil to different spectral bands to detect salt minerals in the soil. The salinity indices have different performance in different regions. In order to find the most suitable soil salinity index to characterize soil salinity changes of the exposed lakebed of the Aral Sea, the correlations were analyzed between the topsoil salinity of soil samples and different potential salinity indices at the corresponding locations and times. Table 2 summarizes the different soil salinity indices.
Soil salinity indices were calculated using Landsat images from 1986 to 2020 to derive a soil salinity map. The remote sensing images had 16 day temporal resolution and a 30 m spatial resolution. Landsat datasets were archived on the Google Earth Engine platform. The dataset was subjected to noise removal, radiometric correction, geometric precision correction, cloud removal, and image stitching processes, which were performed using the JavaScript programming language on the Google Earth Engine platform (https://earthengine.google.com/, 15 December 2021).
Soil salinity indices were derived from January to December. The median value was used as the representative value for each year. The topsoil salinity in depth of 0–5 cm was employed to explore the relationship between ground-truth salinity data and soil salinity indices to map the soil salinity distribution. Additionally, the retreat area was defined as the exposed lakebed of the Aral Sea since 1960.

2.4. Water Salinity

The water salt content dataset in the Aral Sea was derived from relevant studies [35,45,46].

2.5. Correlation Analysis Method

The Pearson correlation coefficient (r) was applied to evaluate the correlation between the ground-truth data of topsoil salinity and soil salinity indices; details of the method can be found in [7,47].

3. Results and Discussion

3.1. Soil Salinity Vertical Distribution

The ground soil salinity data distribution with depth at different elevations were analyzed, as shown in Figure 2. The soil salinity decreased with increasing depth, which indicated the salinity accumulation at the dried bottom to the topsoil layer. In addition, active capillary rise of saline groundwater by evaporative processes caused salt accumulation in the topsoil [48]. It is worth noting that the maximum salinity did not appear in the top layer of the soil, but in the lower layer of 5–15 cm, which was attributable to natural leaching action. Meanwhile, as the elevation decreased, the total salinity at 100 cm showed an increasing trend. It exhibited a significant positive correlation between the total salt content of the 0–100 cm soils and water salinity when the water level dropped in the corresponding location, as shown in Figure 3. R2 = 0.87 and r = 0.93 at a significance level of 0.01. This agrees well with the result that water salinity increases dramatically with decreasing water levels. With the recession of the saline lake, salt in the water body remained in the exposed soil. Consequently, the lower the water level, the higher the exposed soil salinity. This also implies that the soil salinity is higher in the lower position of the exposed lakebed.

3.2. Distribution of Topsoil Salinity

To map the distribution of topsoil salinity at the depth of 0−5 cm on the exposed seabed of the Aral Sea, the relationships between the topsoil salinity (EC) and potential salinity indices were built, as shown in Figure 4. The correlation coefficients are shown in Table 3. Soil salinity was significantly positively correlated with salinity indices SI4 and NDSI (r = 0.92, 0.69), whereas it had a significant negative correlation with NDVI (r = −0.69). Notably, SI4 was most sensitive to changes in soil salinity, which can be used to characterize the soil salinity in this region. Other salinity indices (BI, SI1, SI2, and SI3) had weak negative correlations with soil salinity (r = −0.44, −0.2, −0.46, and −0.26, respectively). Additionally, the negative relationship with NDVI indicated that vegetation decreases with increasing soil salinity levels [16].
According to previous studies [31,49], there were strong spectral reflections of the salinized soil on the red and near-infrared bands, which suggests a good performance on the dried seafloor of the Aral Sea. Considering the correlation between soil salinity and indices, SI4 was employed to evaluate the capability of monitoring the distribution of soil salinity. Thus, the relationship between EC and SI4 was established, as shown in Equation (1), with R2 = 0.84 and r = 0.92 at a significance level of 0.01:
EC = 21.84 × (SI4) − 0.11
Soil salinity (EC) was calculated using Equation (1), and the measured and estimated soil salinity changes are shown in Figure 5, indicating a good distribution along the 1:1 line. Based on recent studies [7,50], the model was the most effective with reliable prediction when the ratio of performance to deviation (RPD) was more than 2.00. The RPD was 2.36, and the R2 was 0.84 with a low root mean square error (RMSE) of 0.86 in this model, suggesting that the model had high estimation performance.
Therefore, soil salinity can be mapped by applying SI4 using remote sensing data, as shown in Figure 6. The soil salinity was relatively low around the northern and southern parts (delta areas) of the Aral Sea. Affected by the Kokaral Dam, freshwater from Syr Darya flowed into the north and water salinity remained relatively low (5.8 g/L) in 2019, which led to low soil salinity. However, soil salinity presented an increasing trend from the coastline in 1960 to the current shoreline in the South Aral Sea. High salinity areas were mainly distributed in the western part of Vozrozhdeniya Island and the eastern part of the south. The dramatic shrinkage of the water surface caused a large area of seafloor to be exposed, and the salinity of the water remained in the soil. The Aralkum Desert developed in the eastern region of the south. These areas (dash cycles) became the main source of salt-dust storms, and measures are necessary to reduce the damage resulting from this disaster [20,21,25].
Notably, the soil salinity around the water surface was relatively low, particularly around the South Aral Sea. Fluctuations in water level push the lake water to nearby coastal areas and submerge the surface soil. These factors play an important role in soil leaching. As a result, the soil salinity decreases.

3.3. Changes in Topsoil Salinization Levels

To further identify changes in soil salinity levels from 1986 to 2020, the EC distribution was mapped based on Equation (1), as shown in Figure 7. Then, the proportion of different soil salinity classes in the area was investigated, as shown in Table 4. Combined with the dynamics of the water surface of the Aral Sea, it was found that, in the North Aral Sea, the proportions of water area and soils classified as non-saline, slightly saline, moderately saline, strongly saline, and extremely saline were 50.3%, 0.2%, 1.0%, 42.1%, 6.0%, and 0.3% in 1986, and 50.3%, 0.8%, 2.3%, 45.6%, 0.7%, and 0.2% in 2020, respectively. For the South Aral Sea, the proportions of water area and soils classified as non-saline, slightly saline, moderately saline, strongly saline, and extremely saline were 76.1%, 0.1%, 1.5%, 21.2%, 0.8%, and 0.2% in 1986, and 15%, 0.4%, 7.5%, 73.8%, 2.1%, and 1.2% in 2020, respectively. Overall, the moderately saline soil was predominant in the exposed lakebed. As seen from the salinity distribution in Figure 8, a large area of seabed was exposed from 1960 to 2020, and the strongly and extremely saline soils were mainly distributed in the west of Vozrozhdeniya Island and the centre of the eastern basin in 2020, because of the drying of the saline lake. This reveals that the sea shrinkage led to the high salt seafloor being exposed, where salt storms have prevailed in the last 20 years (dish cycle area in Figure 7b). The degree of salinization in the South Aral Sea is higher than that in the North Aral Sea. Additionally, compared to the South, the degree of soil salinization experienced fewer changes from 1986 to 2020 in the North Aral Sea.
In order to find more information about soil salinity level changes from 1986 to 2020, Sankey diagrams were employed to display the degree of soil salinity change in the North and South Aral Sea, as shown in Figure 8 and Figure 9. The Sankey diagram uses the comparative flow between different periods to show changes in soil salinity levels [7,51,52]. By using the Sankey diagram, the transition of different soil salinity levels from 1986 to 2020 can be found at the pixel scale. The soil salinity level changes are displayed from 1986 to 2020 in the same location. Specifically, the diagram indicates that the soil salinity class flows “begin” (1986) and “end” (2020) at each node, and the transition lines between the paired salinity class categories are applied to show these flows. In addition, the stacked bar indicates the proportion of each soil salinity class, and the width of the direction line is directly proportional to the magnitude of the flow changes.
As seen in Figure 8, although there were some conversions between the water surface and different soil salinity levels, the water area of the North Aral Sea was relatively stable from 1986 to 2020. Notably, the slightly (2–4 dS m−1) and moderately saline (4–8 dS m−1) areas increased by 1.3% and 3.5%, whereas the strongly saline (8–16 dS m−1) area decreased by 5.3%. The increase in moderately salinized soil in 2020 was mainly caused by the conversion of strongly salinized soil. The increase in slightly salinized soil in 2020 was mainly caused by the conversion of the water as well as moderately, strongly, and extremely salinized soils (>16 dS m−1).
Unfortunately, the water surface experienced severe recession for 35 years, decreasing by 61.1% in the South Aral Sea. The water area was primarily converted into moderately, slightly, and strongly saline soils from 1986 to 2020, as shown in Figure 9. Specifically, the slightly and moderately saline areas increased significantly by 6% and 52.6%, respectively. Most of the exposed lakebed became moderately saline soil from 1986. While the area of slightly saline soil increased in 2020, part of the slightly saline soil area in 1986 was converted into water as well as moderately and strongly saline soils in 2020. These soil salinity level changes suggest a dynamic process.
The soil salinity in the retreat area is not only affected by lake water salinity but also by soil texture, groundwater, and precipitation [7,53]. During precipitation leaching, the salt moved to the subsoil layer, and the topsoil salinity decreased. Spatially, the soil particle size decreased from the former to the present shoreline. The soil texture changed from sandy to clayey soil, and the capillary action was stronger. Simultaneously, the groundwater depth gradually increased. Under strong evaporation, salt accumulated in the surface layer. Subsequently, the loose salty sand was blown up by strong winds and developed a salt-dust storm. This caused great damage to both crops and human health around the Aral Sea. Eventually, the ecological environment of the Aral Sea deteriorated.
Recently, effective measures to prevent further salinization in slightly and moderately salinized areas to restore the ecological environment in arid and semi-arid areas have attracted the attention of researchers and governments. Increasing the inflow into the sea through the allocation of water resources in the Amu Darya and Syr Darya and improving irrigation efficiency will be a fast and effective solution. As the water area has expanded, the dried bottom with large areas of loose salinized sediment has been submerged, and the salt-dust storm in the playa has been inhibited to a certain extent. To this end, it is imperative to establish a unified coordination mechanism for water allocation among Central Asian countries. Additionally, artificial plants will also be an effective method for reducing soil salinization and improving the local ecological environment, although it may take 14–20 years for soil improvement [30,54]. However, this topic is beyond the scope of this study and will be discussed in the future.
The present study had some limitations. It may be argued that more field soil surveys are needed to build a more robust model to map soil salinity distribution on the exposed seabed. Unfortunately, the current ground-truth salinity data available are too scarce to further improve the accuracy of the soil salinity distribution. Thus, future studies should conduct more field surveys on soil salinity to improve the accuracy of the soil salinity model.

4. Conclusions

In this study, the soil salinity distribution and salinization level were evaluated using remote-sensing salinity indices. The seven potential salinity indices were tested, and the SI4 [ R × N I R ] had the best performance in retrieving the soil salinity of the Aral Sea. Based on the relationship between SI4 and in situ measurement data, a model of the soil salinity distribution was established for the exposed seabed. The estimation model performed well, with R2, RMSE, and RPD values of 0.83, 0.78, and 2.25, respectively. The soil salinity map showed an increasing trend from the former to the current shoreline during 2016–2020. Meanwhile, the salinization levels of the exposed topsoil were derived from SI4, which revealed that moderately saline soil dominated the areas. In 1986 and 2020, the water surface of the North Aral Sea was stable, which accounted for 50.3% of its total area. The moderately saline soil area was 45.6% of the total area in 1986, and the moderately saline area increased by 3.5% in 2020. In the South Aral Sea, the area of salinized soil expanded rapidly from 1986 to 2020. The water surface area decreased by 61.1% in 2020 and was mainly converted to moderately and slightly saline areas. The moderately saline area accounted for 73.8%, which was the main soil salinization type. Strong and extremely saline conditions dominated the western part of the island and the northeastern part of the south in 2020, which developed into a source of dust and salt storms. It is essential to pay attention to these areas to solve ecological environmental issues in the future. Our study provides a basis for the dynamic monitoring of soil salinization and patterns of soil salinity distribution in the Aral Sea and provides guidance for ecological restoration in different areas.

Author Contributions

Conceptualization, writing—original draft preparation, Z.D.; methodology, writing—review and editing, X.W. and L.S.; supervision, X.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences, Pan-Third Pole Environment Study for a Green Silk Road (grant number XDA20060301) and the National Natural Science Foundation of China (grant number 42171032).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available from the corresponding authors upon request.

Acknowledgments

We are grateful to the anonymous reviewers for helping to significantly improve the quality of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Location of the Aral Sea in Central Asia and its digital elevation model: (a) the location of the study area and soil sampling sites; (b,c) pictures of two of ten sampling sites.
Figure 1. Location of the Aral Sea in Central Asia and its digital elevation model: (a) the location of the study area and soil sampling sites; (b,c) pictures of two of ten sampling sites.
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Figure 2. The soil salinity distribution with depth at different elevations of the South Aral Sea (E is the elevation).
Figure 2. The soil salinity distribution with depth at different elevations of the South Aral Sea (E is the elevation).
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Figure 3. The relationship the total salt content of the 0–100 cm soils and water salt content.
Figure 3. The relationship the total salt content of the 0–100 cm soils and water salt content.
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Figure 4. Scatterplots of EC and salinity indices derived from Landsat data, including BI, SI1, SI2, SI3, SI4, NDSI, and NDVI.
Figure 4. Scatterplots of EC and salinity indices derived from Landsat data, including BI, SI1, SI2, SI3, SI4, NDSI, and NDVI.
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Figure 5. The scatterplots of measured EC derived from field survey versus estimated EC derived from modeling data.
Figure 5. The scatterplots of measured EC derived from field survey versus estimated EC derived from modeling data.
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Figure 6. The distribution of soil salinity on the exposed seabed during 2016–2020.
Figure 6. The distribution of soil salinity on the exposed seabed during 2016–2020.
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Figure 7. The distribution of soil salinity (EC) on the exposed seafloor in 1986 (a) and 2020 (b).
Figure 7. The distribution of soil salinity (EC) on the exposed seafloor in 1986 (a) and 2020 (b).
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Figure 8. Changes in soil salinity types from 1986 to 2020 in the North Aral Sea.
Figure 8. Changes in soil salinity types from 1986 to 2020 in the North Aral Sea.
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Figure 9. Changes in soil salinity type from 1986 to 2020 in the South Aral Sea.
Figure 9. Changes in soil salinity type from 1986 to 2020 in the South Aral Sea.
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Table
Table 1. Soil salinity classes [3].
Table 1. Soil salinity classes [3].
ClassificationNon-SalineSlightly SalineModerately SalineStrongly SalineExtremely Saline
EC/dS m−10–22–44–88–16>16
Table
Table 2. Reference salinity indices used in this study.
Table 2. Reference salinity indices used in this study.
Index NameSpectral FunctionReferences
Brightness index (BI) B I = R 2 + N I R 2 (Khan et al. [40])
Salinity index 1 (SI1) S I 1 = B / R (Khan et al. [40])
Salinity index 2 (SI2) S I 2 = R × N I R / G (Douaoui et al. [41])
Salinity index 3 (SI3) S I 3 = R × B (Abbas et al. [42])
Salinity index 4 (SI4) S I 4 = R × N I R (Kim et al. [31])
Normalized difference salinity index (NDSI) N D S I = R − N I R / R + N I R (Farahmand and Sadeghi [43])
Normalized difference vegetation index (NDVI) N D V I = N I R − R / N I R + R (Bannari et al. [44])
B, Blue band; G, green band; R, red band; NIR, near-infrared band.
Table
Table 3. Correlation coefficients between the soil salinity (EC) and seven potential salinity indices.
Table 3. Correlation coefficients between the soil salinity (EC) and seven potential salinity indices.
BISI1SI2 SI3SI4NDSINDVI
EC−0.44−0.20−0.46−0.260.92 **0.69 *−0.69 *
** Indicates significance level of 0.01, and * indicates significance level of 0.05.
Table
Table 4. The area percentage of salinization type transformation from 1986 to 2020.
Table 4. The area percentage of salinization type transformation from 1986 to 2020.
ClassificationNorth Aral Sea (%)South Aral Sea (%)
1986202019862020
Water50.350.376.115.0
Non-saline0.20.80.10.4
Slightly saline1.02.31.57.5
Moderately saline42.145.621.273.8
Strongly saline6.00.70.82.1
Extremely saline0.30.20.21.2
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Duan, Z.; Wang, X.; Sun, L. Monitoring and Mapping of Soil Salinity on the Exposed Seabed of the Aral Sea, Central Asia. Water 2022, 14, 1438. https://doi.org/10.3390/w14091438

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Duan Z, Wang X, Sun L. Monitoring and Mapping of Soil Salinity on the Exposed Seabed of the Aral Sea, Central Asia. Water. 2022; 14(9):1438. https://doi.org/10.3390/w14091438

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Duan, Zihao, Xiaolei Wang, and Lin Sun. 2022. "Monitoring and Mapping of Soil Salinity on the Exposed Seabed of the Aral Sea, Central Asia" Water 14, no. 9: 1438. https://doi.org/10.3390/w14091438

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