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Jilili Abuduwaili
University of Chinese Academy of Sciences, Beijing 100049, China

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Journal article
Published: 02 August 2021 in Applied Sciences
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The burial of organic carbon in lake sediments plays an important role in the terrestrial carbon cycle. Clarifying the current status of carbon burial in the lakes of Central Asia is of great significance for the application of carbon balance assessments. With the analysis of the total organic carbon and nitrogen and the carbon isotope and organic carbon burial rate in the core sediment of the North Aral Sea, the status and influencing factors of organic carbon burial over the past 70 years can be revealed. The results showed that the main source of organic carbon was predominantly from lacustrine aquatic plants. However, the contribution of terrigenous organic carbon increased from the 1950s to the 1960s. The burial rate of organic carbon in North Aral Sea sediments was consistent with the overall change in the regional temperature. The burial rate of organic carbon showed an upward trend as a whole with an average of 28.78 g·m−2·a−1. Since 2010, the burial rate of organic carbon has stood at the highest level in nearly 70 years, with an average of 55.66 g·m−2·a−1. The protection of a lake by human beings can not only significantly improve the lake’s aquatic ecosystem but also help to increase the burial rate of the lake’s organic carbon.

ACS Style

Sen Feng; Long Ma; Jilili Abuduwaili; Wen Liu; Galymzhan Saparov; Gulnura Issanova. Organic Carbon Burial in the Aral Sea of Central Asia. Applied Sciences 2021, 11, 7135 .

AMA Style

Sen Feng, Long Ma, Jilili Abuduwaili, Wen Liu, Galymzhan Saparov, Gulnura Issanova. Organic Carbon Burial in the Aral Sea of Central Asia. Applied Sciences. 2021; 11 (15):7135.

Chicago/Turabian Style

Sen Feng; Long Ma; Jilili Abuduwaili; Wen Liu; Galymzhan Saparov; Gulnura Issanova. 2021. "Organic Carbon Burial in the Aral Sea of Central Asia." Applied Sciences 11, no. 15: 7135.

Journal article
Published: 13 June 2021 in Atmosphere
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The Aral Sea basin is the most active source of salt-dust storms in the central Asian region, while its exposed bottom is acting as a “distributer” of salts and chemicals over the adjoining areas. In this study, the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT-4) is used to identify the trajectories of air parcels from the dried bottom of the Aral Sea region (45.40° N, 61.30° E) that are potentially containing salt-dust and their probability of influencing the downwind area in the period of 2016–2020. The frequency of air parcel trajectory was mapped for six levels: 100, 300, 500, 1000, 2000, and 3000 m agl. The trajectories were categorized by k-means clustering into four clusters that are named by their direction of movement as follows: Cluster 1: E category, Cluster 2: NE category, Cluster 3: W category, and the Cluster 4: S category. The 72 h of forward trajectories showed that salt-dust storms starting from the dried bottom of the Aral Sea had the highest probability of affecting the northeastern region e.g., Siberian Plain, followed by the southern region e.g., Iran Plateau. Total number of trajectories within these two clusters (NE and S) accounts for 90% (or 413 days) of trajectories in examined days. The main area of influence of salt-dust is close to the source area. The potential transport distance of salt-dust particles increases with the height of the starting point. The surface wind, which results from the changes of the Siberian High (SH), has a major role in shaping the surface atmospheric circulation which determines the transport pathway of salt-dust particles over the Aral Sea region. The results of this study could be useful to forecast the potential occurrence of salt-dust storms in downwind affected areas and would also be helpful to understand the possible causes of salt-dust storms which can provide the scientific basis for mitigation of the negative impact of salt-dust storms on the environment and human health. Further research should be conducted by using monitoring data to confirm the deposition of dust and salt particles in those areas mapped by our study.

ACS Style

Aishajiang Aili; Jilili Abuduwaili; Hailiang Xu; Xinfeng Zhao; Xinghong Liu. A Cluster Analysis of Forward Trajectory to Identify the Transport Pathway of Salt-Dust Particles from Dried Bottom of Aral Sea, Central Asia. Atmosphere 2021, 12, 764 .

AMA Style

Aishajiang Aili, Jilili Abuduwaili, Hailiang Xu, Xinfeng Zhao, Xinghong Liu. A Cluster Analysis of Forward Trajectory to Identify the Transport Pathway of Salt-Dust Particles from Dried Bottom of Aral Sea, Central Asia. Atmosphere. 2021; 12 (6):764.

Chicago/Turabian Style

Aishajiang Aili; Jilili Abuduwaili; Hailiang Xu; Xinfeng Zhao; Xinghong Liu. 2021. "A Cluster Analysis of Forward Trajectory to Identify the Transport Pathway of Salt-Dust Particles from Dried Bottom of Aral Sea, Central Asia." Atmosphere 12, no. 6: 764.

Article
Published: 04 January 2021 in Journal of Arid Land
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In this study, we analyzed the hydrological and meteorological data from the Syr Darya River Basin during the period of 1930–2015 to investigate variations in river runoff and the impacts of climate change and human activities on river runoff. The Syr Darya River, which is supplied by snow and glacier meltwater upstream, is an important freshwater source for Central Asia, as nearly half of the population is concentrated in this area. River runoff in this arid region is sensitive to climate change and human activities. Therefore, estimation of the climatic and hydrological changes and the quantification of the impacts of climate change and human activities on river runoff are of great concern and important for regional water resources management. The long-term trends of hydrological time series from the selected 11 hydrological stations in the Syr Darya River Basin were examined by non-parametric methods, including the Pettitt change point test and Mann-Kendall trend tests. It was found that 8 out of 11 hydrological stations showed significant downward trends in river runoff. Change of river runoff variations occurred in the year around 1960. Moreover, during the study period (1930–2015), annual mean temperature, annual precipitation, and annual potential evapotranspiration in the river basin increased substantially. We employed hydrological sensitivity method to evaluate the impacts of climate change and human activities on river runoff based on precipitation and potential evapotranspiration. It was estimated that human activities accounted for over 82.6%–98.7% of the reduction in river runoff, mainly owing to water withdrawal for irrigation purpose. The observed variations in river runoff can subsequently lead to adverse ecological consequences from an ecological and regional water resources management perspective.

ACS Style

SaniM Bissenbayeva; Jilili Abuduwaili; Assel Saparova; Toqeer Ahmed. Long-term variations in runoff of the Syr Darya River Basin under climate change and human activities. Journal of Arid Land 2021, 13, 56 -70.

AMA Style

SaniM Bissenbayeva, Jilili Abuduwaili, Assel Saparova, Toqeer Ahmed. Long-term variations in runoff of the Syr Darya River Basin under climate change and human activities. Journal of Arid Land. 2021; 13 (1):56-70.

Chicago/Turabian Style

SaniM Bissenbayeva; Jilili Abuduwaili; Assel Saparova; Toqeer Ahmed. 2021. "Long-term variations in runoff of the Syr Darya River Basin under climate change and human activities." Journal of Arid Land 13, no. 1: 56-70.

Journal article
Published: 04 January 2021 in Water
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This study investigated the temporal patterns of annual and seasonal river runoff data at 13 hydrological stations in the Lake Issyk-Kul basin, Central Asia. The temporal trends were analyzed using the innovative trend analysis (ITA) method with significance testing. The ITA method results were compared with the Mann-Kendall (MK) trend test at a 95% confidence level. The comparison results revealed that the ITA method could effectively identify the trends detected by the MK trend test. Specifically, the MK test found that the time series percentage decreased from 46.15% in the north to 25.64% in the south, while the ITA method revealed a similar rate of decrease, from 39.2% to 29.4%. According to the temporal distribution of the MK test, significantly increasing (decreasing) trends were observed in 5 (0), 6 (2), 4 (3), 8 (0), and 8 (1) time series in annual, spring, summer, autumn, and winter river runoff data. At the same time, the ITA method detected significant trends in 7 (1), 9 (3), 6(3), 9 (3), and 8 (2) time series in the study area. As for the ITA method, the “peak” values of 24 time series (26.97%) exhibited increasing patterns, 25 time series (28.09%) displayed increasing patterns for “low” values, and 40 time series (44.94%) showed increasing patterns for “medium” values. According to the “low”, “medium”, and “peak” values, five time series (33.33%), seven time series (46.67%), and three time series (20%) manifested decreasing trends, respectively. These results detailed the patterns of annual and seasonal river runoff data series by evaluating “low”, “medium”, and “peak” values.

ACS Style

Yilinuer Alifujiang; Jilili Abuduwaili; Yongxiao Ge. Trend Analysis of Annual and Seasonal River Runoff by Using Innovative Trend Analysis with Significant Test. Water 2021, 13, 95 .

AMA Style

Yilinuer Alifujiang, Jilili Abuduwaili, Yongxiao Ge. Trend Analysis of Annual and Seasonal River Runoff by Using Innovative Trend Analysis with Significant Test. Water. 2021; 13 (1):95.

Chicago/Turabian Style

Yilinuer Alifujiang; Jilili Abuduwaili; Yongxiao Ge. 2021. "Trend Analysis of Annual and Seasonal River Runoff by Using Innovative Trend Analysis with Significant Test." Water 13, no. 1: 95.

Journal article
Published: 09 December 2020 in Journal of Arid Environments
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Spatiotemporal variability in the land surface energy flux is largely and comprehensively affected by many factors, including land surface temperature (LST), land coverage, soil characteristics, terrain conditions, etc. In contrast with other climatic zones, arid and semiarid lands have fragile ecological environments that are more sensitive to land surface energy flux changes. In this study, we used MODerate Resolution Imaging Spectroradiometer (MODIS) LST products (2001–2015) for air temperature comparisons. Then, we investigated the spatiotemporal variation in LSTs in the Syr Darya Basin (SDB) during 2001–2015. More specifically, a new statistical model known as GeoDetector was adopted to analyze the driving factors controlling the spatiotemporal variation in LSTs. The result shows that the MODIS LST can provide a good estimation of air temperature, especially at night. The LST change rate can be considered as an important indicator of climate change (rapid warming at high altitudes) and human activities (increased water consumption of crop). Based on the GeoDetector model, we determined that the elevation explained more of the LST distribution (84–90%) and spatiotemporal variation (22–26%) than any other land surface parameters. The combination of albedo and the other explanatory variables can significantly increase the explanatory power of each single factor, especially with elevation.

ACS Style

Wei Wang; Alim Samat; Jilili Abuduwaili; Yongxiao Ge. Quantifying the influences of land surface parameters on LST variations based on GeoDetector model in Syr Darya Basin, Central Asia. Journal of Arid Environments 2020, 186, 104415 .

AMA Style

Wei Wang, Alim Samat, Jilili Abuduwaili, Yongxiao Ge. Quantifying the influences of land surface parameters on LST variations based on GeoDetector model in Syr Darya Basin, Central Asia. Journal of Arid Environments. 2020; 186 ():104415.

Chicago/Turabian Style

Wei Wang; Alim Samat; Jilili Abuduwaili; Yongxiao Ge. 2020. "Quantifying the influences of land surface parameters on LST variations based on GeoDetector model in Syr Darya Basin, Central Asia." Journal of Arid Environments 186, no. : 104415.

Journal article
Published: 10 November 2020 in CATENA
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An attribute study of the runoff changes due to climate change and anthropogenic activities is of great value to determining the best response to runoff changes. This study investigates the evolution of the intra-annual runoff and evaluates the effects of changes in climate and anthropogenic activities on runoff variations in the Lake Issyk-Kul Basin (LIKB). The monotonic trend test and wavelet transform analysis were used to characterize the trends and periods of the hydro-meteorological variables in the LIKB. In addition, the periodicity-trend superposition model and double-mass curves were used to assess the contributions of climate change and anthropogenic activities to runoff variations. The analyses were conducted using regional climate data combined with runoff data derived from 13 different river stations in the LIKB for the period between 1943 and 2012. The results indicate the following. (1) The monthly runoff trends in the three groups of tributaries (northern, southeastern, and southern tributaries) exhibit distinct differences, and the percentage of the data sets with no pattern gradually increased (from 26% to 38%) from north to south. There is a positive trend, with a similar decrease (from 50% to 24%) from north to south. (2) The air temperature, precipitation, and runoff in the LIKB increased throughout the low and high flow periods. The statistical index of the runoff concentration degree (RCD) decreased at most stations (Chong-Koi-Suu, Chong-Ak-Suu, Chong-Urykty, Pzhergalan, Ak-Sai, Tossor, Ton, Chong-Kyzyl-Suu, Tamga, and Karakol), except for the Cholpon-Ata, Ak-Suu, and Dzhuuku stations. (3) In addition, the periodic characteristics of the RCD show that the RCD has a 12-year significant period over the low flow period, which is similar to that for precipitation but varies from that for air temperature. (4) Climate variability and anthropogenic activities are two different contributors to runoff reduction in the LIKB. The respective contributions of anthropogenic activities to the runoff determined using the two methods were 35.3% and 18%, whereas the climate change contributions were 64.7% and 82%, respectively. Climate change was the main reason for the runoff variations. These results provide a basis for the scientific management and sustainable allocation of water resources in the LIKB.

ACS Style

Yilinuer Alifujiang; Jilili Abuduwaili; Michael Groll; Gulnura Issanova; Balati Maihemuti. Changes in intra-annual runoff and its response to climate variability and anthropogenic activity in the Lake Issyk-Kul Basin, Kyrgyzstan. CATENA 2020, 198, 104974 .

AMA Style

Yilinuer Alifujiang, Jilili Abuduwaili, Michael Groll, Gulnura Issanova, Balati Maihemuti. Changes in intra-annual runoff and its response to climate variability and anthropogenic activity in the Lake Issyk-Kul Basin, Kyrgyzstan. CATENA. 2020; 198 ():104974.

Chicago/Turabian Style

Yilinuer Alifujiang; Jilili Abuduwaili; Michael Groll; Gulnura Issanova; Balati Maihemuti. 2020. "Changes in intra-annual runoff and its response to climate variability and anthropogenic activity in the Lake Issyk-Kul Basin, Kyrgyzstan." CATENA 198, no. : 104974.

Journal article
Published: 19 October 2020 in Remote Sensing
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A lack of long-term soil wind erosion data impedes sustainable land management in developing regions, especially in Central Asia (CA). Compared with large-scale field measurements, wind erosion modeling based on geospatial data is an efficient and effective method for quantitative soil wind erosion mapping. However, conventional local-based wind erosion modeling is time-consuming and labor-intensive, especially when processing large amounts of geospatial data. To address this issue, we developed a Google Earth Engine-based Revised Wind Erosion Equation (RWEQ) model, named GEE-RWEQ, to delineate the Soil Wind Erosion Potential (SWEP). Based on the GEE-RWEQ model, terabytes of Remote Sensing (RS) data, climate assimilation data, and some other geospatial data were applied to produce monthly SWEP with a high spatial resolution (500 m) across CA between 2000 and 2019. The results show that the mean SWEP is in good agreement with the ground observation-based dust storm index (DSI), satellite-based Aerosol Optical Depth (AOD), and Absorbing Aerosol Index (AAI), confirming that GEE-RWEQ is a robust wind erosion prediction model. Wind speed factors primarily determined the wind erosion in CA (r = 0.7, p < 0.001), and the SWEP has significantly increased since 2011 because of the reversal of global terrestrial stilling in recent years. The Aral Sea Dry Lakebed (ASDLB), formed by shrinkage of the Aral Sea, is the most severe wind erosion area in CA (47.29 kg/m2/y). Temporally, the wind erosion dominated by wind speed has the largest spatial extent of wind erosion in Spring (MAM). Meanwhile, affected by the spatial difference of the snowmelt period in CA, the wind erosion hazard center moved from the southwest (Karakum Desert) to the middle of CA (Kyzylkum Desert and Muyunkum Desert) during spring. According to the impacts of land cover change on the spatial dynamic of wind erosion, the SWEP of bareland was the highest, while that of forestland was the lowest.

ACS Style

Wei Wang; Alim Samat; Yongxiao Ge; Long Ma; Abula Tuheti; Shan Zou; Jilili Abuduwaili. Quantitative Soil Wind Erosion Potential Mapping for Central Asia Using the Google Earth Engine Platform. Remote Sensing 2020, 12, 3430 .

AMA Style

Wei Wang, Alim Samat, Yongxiao Ge, Long Ma, Abula Tuheti, Shan Zou, Jilili Abuduwaili. Quantitative Soil Wind Erosion Potential Mapping for Central Asia Using the Google Earth Engine Platform. Remote Sensing. 2020; 12 (20):3430.

Chicago/Turabian Style

Wei Wang; Alim Samat; Yongxiao Ge; Long Ma; Abula Tuheti; Shan Zou; Jilili Abuduwaili. 2020. "Quantitative Soil Wind Erosion Potential Mapping for Central Asia Using the Google Earth Engine Platform." Remote Sensing 12, no. 20: 3430.

Journal article
Published: 15 October 2020 in THE BULLETIN
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Desertification and land degradation are common processes in arid and semi-arid regions of Kazakhstan, especially southern parts, where areas are covered by a great variety of desert types. In deserts, soil-forming processes take place in conditions of severe water shortage, and high level of soil degradation and desertification. The main natural factors for these processes are a flat terrain, a high degree of arid climate, soil salinity, carbonate content, a lack of structure and low natural soil fertility. However, the anthropogenic factors of desertification and soil degradation became dominant last decades. The study considers the actual problems of natural and anthropogenic factors of desertification and land degradation within Kazakhstan. The desertification of huge territories is accompanied by soil contamination, waterlogging by surface water and groundwater, soil salinization, erosion (water, wind), degradation of vegetation cover, dehumidification and a decrease in general regional biological capacity. Analysis of the current status of the soil cover has shown intensive land degradation 43 % of the territory of Kazakhstan is subjected to degradation in significant degree; over 14 % of pastures have reached an extreme degree of degradation or are completely degradated. The Aral Sea region, Northern Caspian Sea and Southern Balkhash deserts can be observed as areas of intensive soil desertification, salinization and deflation processes. As well as the desertification process are progressing in the irrigated soils of the deltas of Syrdarya, Shu, Ile and Karatal rivers.

ACS Style

G. Issanova; A. Saduakhas; J. Abuduwaili; K. Tynybayeva; S. Tanirbergenov. DESERTIFICATION AND LAND DEGRADATION IN KAZAKHSTAN. THE BULLETIN 2020, 5, 95 -102.

AMA Style

G. Issanova, A. Saduakhas, J. Abuduwaili, K. Tynybayeva, S. Tanirbergenov. DESERTIFICATION AND LAND DEGRADATION IN KAZAKHSTAN. THE BULLETIN. 2020; 5 (387):95-102.

Chicago/Turabian Style

G. Issanova; A. Saduakhas; J. Abuduwaili; K. Tynybayeva; S. Tanirbergenov. 2020. "DESERTIFICATION AND LAND DEGRADATION IN KAZAKHSTAN." THE BULLETIN 5, no. 387: 95-102.

Journal article
Published: 14 October 2020 in Water
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As one of the important water sources of the desert ecosystem in the Tarim Basin, the largest fishery base in Xinjiang, and the former largest inland and freshwater lake of China, the water quality of Bosten Lake is worthy of government and public attention. To determine the water’s hydrochemical composition and the water quality of Bosten Lake, analyses of the spatial distribution, water pollution status and irrigation suitability were conducted with statistical methods, including redundancy and factor analyses, inverse distance weighted interpolation, and water quality assessment and saturation index simulation of minerals in the water from a survey done in 2018. The results suggested that the average total dissolved solids (TDS) of Bosten Lake in 2018 was 1.32 g/L, and the lake is alkaline with a pH of 8.47. The strength of the water exchange capacity affected the spatial distribution of TDS. The spatial distribution of TDS and its value can be significantly changed by restoring the water supply of seasonal rivers in the northwest. The water of Bosten Lake contains sulfate and sodium groups, which are mainly affected by lake evaporation. As the pH increases, the content of carbonate ions increases, while the content of bicarbonate ions decreases. The spatial distributions of other major ions are consistent with that of the TDS. The spatial distribution of potentially toxic elements is more complicated than that of major ions. In general, the spatial distribution of Cu and As is more consistent with the spatial distribution of electrical conductivity or TDS. The spatial distributions of the Zn, Se and pH values are more consistent with respect to other variables. Although the water of Bosten Lake is still at a permissible level for water irrigation, the lake is moderately polluted, and the local site almost has a highly polluted status. The research results are of great significance for lake environmental protection and management as well as watershed ecological restoration.

ACS Style

Wen Liu; Long Ma; Jilili Abuduwaili; Lin Lin. Distributions, Relationship and Assessment of Major Ions and Potentially Toxic Elements in Waters of Bosten Lake, the Former Largest Inland and Freshwater Lake of China. Water 2020, 12, 2859 .

AMA Style

Wen Liu, Long Ma, Jilili Abuduwaili, Lin Lin. Distributions, Relationship and Assessment of Major Ions and Potentially Toxic Elements in Waters of Bosten Lake, the Former Largest Inland and Freshwater Lake of China. Water. 2020; 12 (10):2859.

Chicago/Turabian Style

Wen Liu; Long Ma; Jilili Abuduwaili; Lin Lin. 2020. "Distributions, Relationship and Assessment of Major Ions and Potentially Toxic Elements in Waters of Bosten Lake, the Former Largest Inland and Freshwater Lake of China." Water 12, no. 10: 2859.

Journal article
Published: 28 September 2020 in Applied Sciences
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The Tianshan Mountain is the largest mountain range in Central Asia, and the source area of many river systems. Changes in precipitation result in significant alterations to regional hydrological processes. Lake sediment from the Tian Shan representative of the last 90 years was chosen as the object of this research study. The grain-size data were used in conjunction with instrumental data to provide a method for determining changes in paleoprecipitation. The results showed the three-point moving average curve of the silty fraction content with a size of 16 to 32 μm to be significantly consistent with the curve of total precipitation from April to September since 1950. The total content of clay and fine-silty fraction (0–16 μm) was clearly consistent with the monthly precipitation in July. The total precipitation from April to September showed a significant downward trend from 1930 to 1975, and then an overall increasing trend beginning in 1975, which may have been influenced by the North Atlantic Oscillation. The change in precipitation reconstructed by the grain size of lake sediments was significantly different from the high-resolution gridded datasets (Climatic Research Unit Time-Series version 4.04) because of the lack of data from meteorological stations in China before 1950. The conclusions of this study are significant for evaluating the validity of climatic research unit (CRU) data in arid areas of Western China. In addition, the results of this study serve as a bridge between modern instrumental records and long time-scale paleoclimate research and provide important reference values for future reconstructions of long time-scale paleoclimate.

ACS Style

Long Ma; Jilili Abuduwaili; Wen Liu; Zhenjie He. Variations in Sediment Grain Size from a Lake in the Tianshan Mountain of Central Asia: Implications for Paleoprecipitation Reconstruction. Applied Sciences 2020, 10, 6793 .

AMA Style

Long Ma, Jilili Abuduwaili, Wen Liu, Zhenjie He. Variations in Sediment Grain Size from a Lake in the Tianshan Mountain of Central Asia: Implications for Paleoprecipitation Reconstruction. Applied Sciences. 2020; 10 (19):6793.

Chicago/Turabian Style

Long Ma; Jilili Abuduwaili; Wen Liu; Zhenjie He. 2020. "Variations in Sediment Grain Size from a Lake in the Tianshan Mountain of Central Asia: Implications for Paleoprecipitation Reconstruction." Applied Sciences 10, no. 19: 6793.

Journal article
Published: 22 September 2020 in Toxics
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Aiming at the pollution and ecological hazards of the lake sediments of Bosten Lake, once China’s largest inland lake, the spatial distribution and influencing factors of the potentially-toxic elements in its surface sediments were studied with the methods of spatial autocorrelation, two-way cluster analysis, and redundancy analysis. Finally, based on the background value of potentially-toxic elements extracted from a sediment core, a comprehensive evaluation of the risk of these potentially-toxic elements was conducted with the potential-ecological-risk index and the pollution-load index. With data on the grain size, bulk-rock composition, and organic matter content, this comprehensive analysis suggested that with the enrichment of authigenic carbonate minerals, the content of potentially-toxic elements exhibited distinctive characteristics representative of arid regions with lower values than those in humid region. All potentially-toxic elements revealed a significant spatial autocorrelation, and high-value areas mainly occurred in the middle and southwest. The content of potentially-toxic elements is related to Al2O3, K2O, Fe2O3, TiO2, MgO, and MnO, and the storage medium of potentially-toxic elements mainly consists of small particles with a grain size <16 μm. The pollution load index (PLI) for the whole lake due to the potentially-toxic elements was 1.31, and the surface area with a PLI higher than 1 and a moderate pollution level accounted for 87.2% of the total lake area. The research conclusions have an important scientific value for future lake ecological quality assessment and lake environment governance.

ACS Style

Long Ma; Jilili Abuduwaili; Wen Liu. Spatial Distribution and Ecological Risks of the Potentially-Toxic Elements in the Surface Sediments of Lake Bosten, China. Toxics 2020, 8, 77 .

AMA Style

Long Ma, Jilili Abuduwaili, Wen Liu. Spatial Distribution and Ecological Risks of the Potentially-Toxic Elements in the Surface Sediments of Lake Bosten, China. Toxics. 2020; 8 (3):77.

Chicago/Turabian Style

Long Ma; Jilili Abuduwaili; Wen Liu. 2020. "Spatial Distribution and Ecological Risks of the Potentially-Toxic Elements in the Surface Sediments of Lake Bosten, China." Toxics 8, no. 3: 77.

Journal article
Published: 13 August 2020 in Applied Sciences
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The Aral Sea has received worldwide attention for the deterioration of its biological and chemical status. The accumulation of potentially toxic elements (PTEs) in the lake sediments reflects changes in the surrounding watershed and represents a potential hazard for the lake ecosystem. In conjunction with existing environmental records from the Aral Sea basin, sedimentary records of PTEs in North Aral Sea covering a short time scale, anno Domini (AD) 1950–2018, were used to reveal historical changes in PTE concentrations and potential risks to lake functioning. The results suggested that the levels of PTEs in lake sediments from North Aral Sea changed abruptly around 1970 AD, which is concurrent with the intensification of human activities within the basin. After 1970 AD, with the exception of As, which remained at unpolluted-to-moderately polluted levels, the geo-accumulation indices of the remaining PTEs studied (V, Cr, Zn, Co, Pb, Ni, Cu and Cd) inferred a moderately polluted status. Before 1970 AD, the total ecological risk was low, but since 1970, the total ecological risk index has exceeded 150, indicating moderate risk. Historical changes in PTE levels of lake sediments from North Aral Sea and their potential ecological risks are reported for the first time. The conclusions provide an important reference for the protection of lake ecosystems and will provide data for regional/global comparisons of environmental change during the Anthropocene.

ACS Style

Wen Liu; Long Ma; Jilili Abuduwaili. Historical Change and Ecological Risk of Potentially Toxic Elements in the Lake Sediments from North Aral Sea, Central Asia. Applied Sciences 2020, 10, 5623 .

AMA Style

Wen Liu, Long Ma, Jilili Abuduwaili. Historical Change and Ecological Risk of Potentially Toxic Elements in the Lake Sediments from North Aral Sea, Central Asia. Applied Sciences. 2020; 10 (16):5623.

Chicago/Turabian Style

Wen Liu; Long Ma; Jilili Abuduwaili. 2020. "Historical Change and Ecological Risk of Potentially Toxic Elements in the Lake Sediments from North Aral Sea, Central Asia." Applied Sciences 10, no. 16: 5623.

Journal article
Published: 19 June 2020 in Remote Sensing
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To investigate the performance of extreme gradient boosting (XGBoost) in remote sensing image classification tasks, XGBoost was first introduced and comparatively investigated for the spectral-spatial classification of hyperspectral imagery using the extended maximally stable extreme-region-guided morphological profiles (EMSER_MPs) proposed in this study. To overcome the potential issues of XGBoost, meta-XGBoost was proposed as an ensemble XGBoost method with classification and regression tree (CART), dropout-introduced multiple additive regression tree (DART), elastic net regression and parallel coordinate descent-based linear regression (linear) and random forest (RaF) boosters. Moreover, to evaluate the performance of the introduced XGBoost approach with different boosters, meta-XGBoost and EMSER_MPs, well-known and widely accepted classifiers, including support vector machine (SVM), bagging, adaptive boosting (AdaBoost), multi class AdaBoost (MultiBoost), extremely randomized decision trees (ExtraTrees), RaF, classification via random forest regression (CVRFR) and ensemble of nested dichotomies with extremely randomized decision tree (END-ERDT) methods, were considered in terms of the classification accuracy and computational efficiency. The experimental results based on two benchmark hyperspectral data sets confirm the superior performance of EMSER_MPs and EMSER_MPs with mean pixel values within region (EMSER_MPsM) compared to that for morphological profiles (MPs), morphological profile with partial reconstruction (MPPR), extended MPs (EMPs), extended MPPR (EMPPR), maximally stable extreme-region-guided morphological profiles (MSER_MPs) and MSER_MPs with mean pixel values within region (MSER_MPsM) features. The proposed meta-XGBoost algorithm is capable of obtaining better results than XGBoost with the CART, DART, linear and RaF boosters, and it could be an alternative to the other considered classifiers in terms of the classification of hyperspectral images using advanced spectral-spatial features, especially from generalized classification accuracy and model training efficiency perspectives.

ACS Style

Alim Samat; Erzhu Li; Wei Wang; Sicong Liu; Cong Lin; Jilili Abuduwaili. Meta-XGBoost for Hyperspectral Image Classification Using Extended MSER-Guided Morphological Profiles. Remote Sensing 2020, 12, 1973 .

AMA Style

Alim Samat, Erzhu Li, Wei Wang, Sicong Liu, Cong Lin, Jilili Abuduwaili. Meta-XGBoost for Hyperspectral Image Classification Using Extended MSER-Guided Morphological Profiles. Remote Sensing. 2020; 12 (12):1973.

Chicago/Turabian Style

Alim Samat; Erzhu Li; Wei Wang; Sicong Liu; Cong Lin; Jilili Abuduwaili. 2020. "Meta-XGBoost for Hyperspectral Image Classification Using Extended MSER-Guided Morphological Profiles." Remote Sensing 12, no. 12: 1973.

Journal article
Published: 09 June 2020 in Sustainability
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Over the past century, the impacts of human activities on the natural environment have continued to increase. Historic evolution of the environment under anthropogenic influences is an important reference for sustainable social development. Based on the geochemical analyses of a short sediment core of 49 cm from Lake Balkhash, the largest lake in Central Asia, potential factors historically influencing geochemical variation were revealed, and influences of human activity on regional environmental change were reconstructed over the past 150 years. The results showed that the dominant factor inducing changes in potentially toxic elements (V, Cr, Co, Ni, Zn, Cu, Cd, and Pb) is the physical weathering of the terrestrial materials. The variation in Ca content was influenced by the formation of authigenic carbonate. Since 1930, potentially toxic elements (Cr, Co, Ni, Zn, Cu, Cd, and Pb) in the lake sediments have obviously been affected by human activities, but the impact of human activities has not exceeded that of natural terrestrial weathering. In particular, the enrichment factors (EFs) for Cd and Pb reached 1.5. The average ecological risks of Cd were higher than the criterion of 30, suggesting a moderate risk to the local ecosystem in recent years. Total risk indices indicated moderate potential ecological risk for the lake ecology. The results will provide support for the environmental protection and better management practices of the Lake Balkhash watershed.

ACS Style

Kun Huang; Long Ma; Jilili Abuduwaili; Wen Liu; Gulnura Issanova; Galymzhan Saparov; Lin Lin. Human-Induced Enrichment of Potentially Toxic Elements in a Sediment Core of Lake Balkhash, the Largest Lake in Central Asia. Sustainability 2020, 12, 4717 .

AMA Style

Kun Huang, Long Ma, Jilili Abuduwaili, Wen Liu, Gulnura Issanova, Galymzhan Saparov, Lin Lin. Human-Induced Enrichment of Potentially Toxic Elements in a Sediment Core of Lake Balkhash, the Largest Lake in Central Asia. Sustainability. 2020; 12 (11):4717.

Chicago/Turabian Style

Kun Huang; Long Ma; Jilili Abuduwaili; Wen Liu; Gulnura Issanova; Galymzhan Saparov; Lin Lin. 2020. "Human-Induced Enrichment of Potentially Toxic Elements in a Sediment Core of Lake Balkhash, the Largest Lake in Central Asia." Sustainability 12, no. 11: 4717.

Journal article
Published: 17 May 2020 in International Journal of Environmental Research and Public Health
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The water resources of Central Asia play an important role in maintaining the fragile balance of ecosystems and the sustainable development of human society. However, the lack of research on the heavy metals in river waters has a far−reaching influence on public health and the sustainable development in Central Asia. In order to reveal the possible sources of the heavy metals and to assess the associated human health risks, thirty−eight water samples were collected from the rivers of the Issyk−Kul Basin during the period with low river flow (May) and the period with high river flow (July and August), and the hydrochemical compositions and major ions of heavy metals were analyzed. No changes in hydrochemical facies were observed between the two periods and the river water type was calcium bicarbonate. Carbonate dissolution and silicate weathering controlled the variation of cations and anions in river waters from the Issyk−Kul Basin. There were some differences in the sources of heavy metals in water bodies between the two periods. During the period with low river flow, heavy metals (Cr) were closely clustered with major ions, indicating that they were mainly affected by water–rock interactions. During the period with high river flow, all heavy metals studied in this paper had different sources of major ions, and the heavy metals maybe influenced by human activities. From the human health risk assessment, the hazard quotients for all samples were less than 1, reflecting that there was no noncarcinogenic risk in the river waters of the Issyk−Kul Basin during the two sampling periods. However, the water samples with carcinogenic risk of arsenic exceeding the threshold (10−4) accounted for 21.1% of the total, indicating that there were some certain carcinogenic hazards for human health via water drinking with direct oral ingestion. The results are of certain significance for the utilization and protection of water resources in the basin as well as the protection of public health.

ACS Style

Wen Liu; Long Ma; Yaoming Li; Jilili Abuduwaili; Salamat Abdyzhapar Uulu. Heavy Metals and Related Human Health Risk Assessment for River Waters in the Issyk−Kul Basin, Kyrgyzstan, Central Asia. International Journal of Environmental Research and Public Health 2020, 17, 3506 .

AMA Style

Wen Liu, Long Ma, Yaoming Li, Jilili Abuduwaili, Salamat Abdyzhapar Uulu. Heavy Metals and Related Human Health Risk Assessment for River Waters in the Issyk−Kul Basin, Kyrgyzstan, Central Asia. International Journal of Environmental Research and Public Health. 2020; 17 (10):3506.

Chicago/Turabian Style

Wen Liu; Long Ma; Yaoming Li; Jilili Abuduwaili; Salamat Abdyzhapar Uulu. 2020. "Heavy Metals and Related Human Health Risk Assessment for River Waters in the Issyk−Kul Basin, Kyrgyzstan, Central Asia." International Journal of Environmental Research and Public Health 17, no. 10: 3506.

Journal article
Published: 15 April 2020 in REPORTS
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Desertification is a land degradation in arid, semi-arid and dry sub-humid areas as a result of various factors, including climate change and human activities. The Aral Sea is called the once large, and now almost dry, salt lake, which today looks like a large salt desert. Its drying is considered one of the greatest environmental disasters of our time, because only 50 years ago it was one of the four largest lakes on our planet. In the 1990s, the western world learned about the environmental disaster of what used to be the fourth largest lake in the world - The Aral Sea. The abrupt drying of the Aral Sea led to the intensive development of desertification processes in the region and the formation of the new man-made Aralkum desert. The main method for determining the soil degradation of the Aralkum desert is the calculation of indices. The selected methods are widely known and repeatedly applied in world practice methods for processing satellite images. So, all of the listed spectral indices are universal. The uniqueness of this technique lies in the determination of the exact ranges of values for each of the spectral indices in the identification of various indicators of desertification.

ACS Style

G.Y. Saduova; G.T. Issanova; Y.Kh. Kakimzhanov; J. Abuduwaili. STUDY AND MAPPING OF DEGRADATION OF THE ARALKUM DESERT. REPORTS 2020, 2, 49 -57.

AMA Style

G.Y. Saduova, G.T. Issanova, Y.Kh. Kakimzhanov, J. Abuduwaili. STUDY AND MAPPING OF DEGRADATION OF THE ARALKUM DESERT. REPORTS. 2020; 2 (330):49-57.

Chicago/Turabian Style

G.Y. Saduova; G.T. Issanova; Y.Kh. Kakimzhanov; J. Abuduwaili. 2020. "STUDY AND MAPPING OF DEGRADATION OF THE ARALKUM DESERT." REPORTS 2, no. 330: 49-57.

Journal article
Published: 15 April 2020 in REPORTS
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Desertification and degradation provide a clear picture of global environmental and socio-economic issues. Most of Kazakhstan is located in a desert region, including the suburbs of South Balkhash. The reason is that desertification of the region has a strong influence on natural and anthropogenic factors. To consider the geomorphological state of the region and the problem of desertification of the territory, it is necessary to determine the importance of the process of relief of geological structure and relief of tectonics. In recent years, the environmental situation in Balkhash has deteriorated sharply not only as a result of river flow regulation, but also as a result of non-commercial economic activities. Therefore, it is very important to assess the situation of desertification and degradation in the Balkhash region. Desert vegetation has been identified, since information in the spectral range is often insufficient to describe the state of plants, plant indices often develop by combining two or more spectral bands. Land cover index is the percentage of vegetation over a given surface area. Remote sensing information was used to detect the entire land cover. Remote sensing with time and space limitations is widely used to classify vegetation cover. In this work, the proportion of vegetation was estimated by NDVI. The proportion of land cover is based on the relationship between NDVI (NDVIS) and NDVI (NDVIV) in the soil. Using the NDVI index, land cover zones were determined based on satellite images of 2006 and Landsat-5 from 2011. TCT (Tasseled Cap Transformation) coefficients are used in the widest range of problems solved using Earth remote sensing data: from recognition of the coastline of water bodies to determination of forest disturbances. Stressful vegetation may be an indirect sign of the presence of salt in soils. Saline soils are usually characterized by poorly planted areas. A normalized differential salinity index (NDSI) was also determined.

ACS Style

A.G. Gabdykadyr; G.T. Issanova; Y.Kh. Kakimzhanov; Long Ma. ANALYSIS OF SOIL DEGRADATION AND DESERTIFICATION IN SOUTHERN BALKASH DESERT BASED ON GIS. REPORTS 2020, 2, 41 -48.

AMA Style

A.G. Gabdykadyr, G.T. Issanova, Y.Kh. Kakimzhanov, Long Ma. ANALYSIS OF SOIL DEGRADATION AND DESERTIFICATION IN SOUTHERN BALKASH DESERT BASED ON GIS. REPORTS. 2020; 2 (330):41-48.

Chicago/Turabian Style

A.G. Gabdykadyr; G.T. Issanova; Y.Kh. Kakimzhanov; Long Ma. 2020. "ANALYSIS OF SOIL DEGRADATION AND DESERTIFICATION IN SOUTHERN BALKASH DESERT BASED ON GIS." REPORTS 2, no. 330: 41-48.

Journal article
Published: 29 March 2020 in Atmosphere
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The analysis of various characteristics and trends of precipitation is an essential task to improve the utilization of water resources. Lake Issyk-Kul basin is an upper alpine catchment, which is more susceptible to the effects of climate variability, and identifying rainfall variations has vital importance for water resource planning and management in the lake basin. The well-known approaches linear regression, Şen’s slope, Spearman’s rho, and Mann-Kendall trend tests are applied frequently to try to identify trend variations, especially in rainfall, in most literature around the world. Recently, a newly developed method of Şen-innovative trend analysis (ITA) provides some advantages of visual-graphical illustrations and the identification of trends, which is one of the main focuses in this article. This study obtained the monthly precipitation data (between 1951 and 2012) from three meteorological stations (Balykchy, Cholpon-Ata, and Kyzyl-Suu) surrounding the Lake Issyk-Kul, and investigated the trends of precipitation variability by applying the ITA method. For comparison purposes, the traditional Mann–Kendall trend test also used the same time series. The main results of this study include the following. (1) According to the Mann-Kendall trend test, the precipitation of all months at the Balykchy station showed a positive trend (except in January (Zc = −0.784) and July (Zc = 0.079)). At the Cholpon-Ata and Kyzyl-Suu stations, monthly precipitation (with the same month of multiple years averaged) indicated a decreasing trend in January, June, August, and November. At the monthly scale, significant increasing trends (Zc > Z0.10 = 1.645) were detected in February and October for three stations. (2) The ITA method indicated that the rising trends were seen in 16 out of 36 months at the three stations, while six months showed decreasing patterns for “high” monthly precipitation. According to the “low” monthly precipitations, 14 months had an increasing trend, and four months showed a decreasing trend. Through the application of the ITA method (January, March, and August at Balykchy; December at Cholpon-Ata; and July and December at Kyzyl-Suu), there were some significant increasing trends, but the Mann-Kendall test found no significant trends. The significant trend occupies 19.4% in the Mann-Kendall test and 36.1% in the ITA method, which indicates that the ITA method displays more positive significant trends than Mann–Kendall Zc. (3) Compared with the classical Mann-Kendall trend results, the ITA method has some advantages. This approach allows more detailed interpretations about trend detection, which has benefits for identifying hidden variation trends of precipitation and the graphical illustration of the trend variability of extreme events, such as “high” and “low” values of monthly precipitation. In contrast, these cannot be discovered by applying traditional methods.

ACS Style

Yilinuer Alifujiang; Jilili Abuduwaili; Balati Maihemuti; Bilal Emin; Michael Groll. Innovative Trend Analysis of Precipitation in the Lake Issyk-Kul Basin, Kyrgyzstan. Atmosphere 2020, 11, 332 .

AMA Style

Yilinuer Alifujiang, Jilili Abuduwaili, Balati Maihemuti, Bilal Emin, Michael Groll. Innovative Trend Analysis of Precipitation in the Lake Issyk-Kul Basin, Kyrgyzstan. Atmosphere. 2020; 11 (4):332.

Chicago/Turabian Style

Yilinuer Alifujiang; Jilili Abuduwaili; Balati Maihemuti; Bilal Emin; Michael Groll. 2020. "Innovative Trend Analysis of Precipitation in the Lake Issyk-Kul Basin, Kyrgyzstan." Atmosphere 11, no. 4: 332.

Journal article
Published: 24 March 2020 in International Journal of Environmental Research and Public Health
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With the aggravation of air pollution in recent years, a great deal of research on haze episodes is mainly concentrated on the east-central China. However, fine particulate matter (PM2.5) pollution in northwest China has rarely been discussed. To fill this gap, based on the standard deviational ellipse analysis and spatial autocorrelation statistics method, we explored the spatio-temporal variation and aggregation characteristics of PM2.5 concentrations in Xinjiang from 2001 to 2016. The result showed that annual average PM2.5 concentration was high both in the north slope of Tianshan Mountain and the western Tarim Basin. Furthermore, PM2.5 concentrations on the northern slope of the Tianshan Mountain increased significantly, while showing an obviously decrease in the western Tarim Basin during the period of 2001–2016. Based on the result of the geographical detector method (GDM), population density was the most dominant factor of the spatial distribution of PM2.5 concentrations (q = 0.550), followed by road network density (q = 0.423) and GDP density (q = 0.413). During the study period (2001–2016), the driving force of population density on the distribution of PM2.5 concentrations showed a gradual downward trend. However, other determinants, like DEM (Digital elevation model), NSL (Nighttime stable light), LCT (Land cover type), and NDVI (Normalized Difference Vegetation Index), show significant increased trends. Therefore, further effort is required to reveal the role of landform and vegetation in the spatio-temporal variations of PM2.5 concentrations. Moreover, the local government should take effective measures to control urban sprawl while accelerating economic development.

ACS Style

Wei Wang; Alim Samat; Jilili Abuduwaili; Yongxiao Ge. Spatio-Temporal Variations of Satellite-Based PM2.5 Concentrations and Its Determinants in Xinjiang, Northwest of China. International Journal of Environmental Research and Public Health 2020, 17, 2157 .

AMA Style

Wei Wang, Alim Samat, Jilili Abuduwaili, Yongxiao Ge. Spatio-Temporal Variations of Satellite-Based PM2.5 Concentrations and Its Determinants in Xinjiang, Northwest of China. International Journal of Environmental Research and Public Health. 2020; 17 (6):2157.

Chicago/Turabian Style

Wei Wang; Alim Samat; Jilili Abuduwaili; Yongxiao Ge. 2020. "Spatio-Temporal Variations of Satellite-Based PM2.5 Concentrations and Its Determinants in Xinjiang, Northwest of China." International Journal of Environmental Research and Public Health 17, no. 6: 2157.

Original article
Published: 29 January 2020 in Environmental Earth Sciences
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Water balance is considered as an important tool to assess the amount of water and its availability in a region. The Small Aral Sea is a salt lake in the territory of the Kyzylorda region of Kazakhstan, the Northern part of the shrinking Aral Sea, receiving water from the Syr Darya, as a result of lowering of the water horizon of the Aral Sea and with the onset of 40–40.2 m in 1987, when the Berg Strait was formed. In this study, water balance assessment in the Small Aral Sea has been done from 1987 to 2014. The water balance of the Small Aral Sea during the observation period is mainly determined by river runoff, precipitation and evaporation. The general tendency of precipitation decreased slightly, while the general tendency for evaporation increase is high. The annual inflow of the river into the Small Aral Sea increased from 1 km3 in 1987 to 5 km3 in 2014 while its water balance increased from − 1.4 to 2.44 km3. As the result, the water volume of the Small Aral Sea increased by 6% and the water surface area by 4% during the analyzed period.

ACS Style

Assiya Massakbayeva; Jilili Abuduwaili; SaniM Bissenbayeva; Botagoz Issina; Zhassulan Smanov. Water balance of the Small Aral Sea. Environmental Earth Sciences 2020, 79, 75 .

AMA Style

Assiya Massakbayeva, Jilili Abuduwaili, SaniM Bissenbayeva, Botagoz Issina, Zhassulan Smanov. Water balance of the Small Aral Sea. Environmental Earth Sciences. 2020; 79 (3):75.

Chicago/Turabian Style

Assiya Massakbayeva; Jilili Abuduwaili; SaniM Bissenbayeva; Botagoz Issina; Zhassulan Smanov. 2020. "Water balance of the Small Aral Sea." Environmental Earth Sciences 79, no. 3: 75.