Analysis on impacts of hydro-climatic changes and human activities on available water changes in Central Asia

Spatiotemporal Evolution of the Water System's Structure and Its Relationship with Urban System Based on Fractal Dimension: A Case Study of the Huaihe River Basin, China

The formation and development of cities are inseparable from a certain scale of water resources. The information contained in the morphological structures of cities and water systems is often overlooked. Exploring the spatiotemporal evolution of water system structures (WSS) and urban system structures (USS) can reveal the "urban-water" relationship from a new perspective. The Huaihe River Basin (HRB) was selected as the case area, based on the theory of fractal dimensions, grid dimension and multifractal spectrum methods were used to depict the structural evolutionary characteristics of water systems and urban systems from different dimensions. Then, through a comparative analysis of fractal parameters and spectral lines, the characteristics and changing patterns of the "urban-water" relationship in the HRB from 1980 to 2019 were revealed. The results indicate the following: (1) The water system structure in the HRB is complex and exhibits distinct scale characteristics, showing improvement overall and at larger scales while continuously degrading at smaller scales. (2) Both the water system and urban system exhibit increasingly complex spatial development characteristics; however, the USS continues to optimize over time, while the WSS experiences degradation. (3) The development patterns of the water system and urban system are significant differences in the HRB. Urban development mainly relies on outward expansion, whereas the water system is primarily characterized by intensive enhancement. (4) Because of the rapid development of urban areas, water scarcity may occur in densely populated urban areas or larger cities in the future. The research results can serve as a scientific reference for urban planning and water resource management in the HRB.

Local surface warming assessment in response to vegetation shifts over arid lands of Central Asia (2001-2020)

The Northern Eurasia Earth Science Partnership Initiative (NEESPI) was established to address the large-scale environmental change across this region. Regardless of the increasingly insightful literature addressing vegetation change across Central Asia, the biogeophysical warming effects of vegetation shifts still need to be clarified. To contribute, the utility of robust satellite observation is explored to evaluate the surface warming effects of vegetation shifts across Central Asia, which is among NEEPSI's hotspots. We estimated an average increase of +1.9 °C in daytime local surface temperature and + 1.5 °C in the nighttime due to vegetation shift (2001-2020). Meanwhile, the mean local latent heat increased by 4.65Wm-2, following the mild reduction of emitted longwave radiation (-0.8Wm-2). We found that vegetation shifts led to local surface warming with a bright surface, noting that the average air surface temperature was revealed to have increased significantly (2001-2020). This signal was driven mainly by agricultural expansion in western Kazakhstan stretching to Tajikistan and Xinjiang, then deforestation confined in Tajikistan, southeast Kazakhstan, and the northwestern edge of Xinjiang, and finally, grassland encroachment occurred massively in the west to central Kazakhstan. These findings address the latest information on Central Asia's vegetation shifts that may be substantial in landscape change mitigation plans.

Northward shift of Indian summer monsoon and intensifying winter westerlies cause stronger precipitation seasonality over Pamirs and its downstream basins in the 21st century

Hydroclimate will change over Pamirs and its downstream basins (PDB), including Indus River, Tarim River, Amu Darya and Syr Darya Basins, in response to the variation of Indian summer monsoon (ISM) and mid-latitude westerlies. However, the precipitation variation and its mechanism over PDB in the 21st century are yet not fully understood. Here, the best models ensemble selected from 25 CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios is applied to detect the precipitation variations over PDB in the 21st century. A remarkable dipolar pattern is found in both summer and winter precipitation over PDB, particularly in the central Indus River Basin and upper Amu and Syr Darya Basins. The central Indus River Basin (upper Amu and Syr Darya Basins) will experience an increasingly wet (dry) summer in response to northward ISM and a dry (wet) winter driven by mid-latitude westerlies. The amplifying dipolar pattern of seasonal precipitation thus increases the water resource vulnerability over PDB and emphasizes the role of Pamirs in modulating the water resources over surrounding basins, especially the Amu Darya and Syr Darya Basins in the future. The findings underscore the need for prioritizing policies by considering the impacts of precipitation seasonality on social planning.

Responses of vegetation cover to hydro-climatic variations in Bosten Lake Watershed, NW China

Amidst the backdrop of global climate change, it is imperative to comprehend the intricate connections among surface water, vegetation, and climatic shifts within watersheds, especially in fragile, arid ecosystems. However, these relationships across various timescales remain unclear. We employed the Ensemble Empirical Mode Decomposition (EEMD) method to analyze the multifaceted dynamics of surface water and vegetation in the Bosten Lake Watershed across multiple temporal scales. This analysis has shed light on how these elements interact with climate change, revealing significant insights. From March to October, approximately 14.9-16.8% of the areas with permanent water were susceptible to receding and drying up. Both the annual and monthly values of Bosten Lake's level and area exhibited a trend of initial decline followed by an increase, reaching their lowest point in 2013 (1,045.0 m and 906.6 km2, respectively). Approximately 7.7% of vegetated areas showed a significant increase in the Normalized Difference Vegetation Index (NDVI). NDVI volatility was observed in 23.4% of vegetated areas, primarily concentrated in the southern part of the study area and near Lake Bosten. Regarding the annual components (6 < T < 24 months), temperature, 3-month cumulative NDVI, and 3-month-leading precipitation exhibited the strongest correlation with changes in water level and surface area. For the interannual components (T≥ 24 months), NDVI, 3-month cumulative precipitation, and 3-month-leading temperature displayed the most robust correlation with alterations in water level and surface area. In both components, NDVI had a negative impact on Bosten Lake's water level and surface area, while temperature and precipitation exerted positive effects. Through comparative analysis, this study reveals the importance of temporal periodicity in developing adaptive strategies for achieving Sustainable Development Goals in dryland watersheds. This study introduces a robust methodology for dissecting trends within scale components of lake level and surface area and links these trends to climate variations and NDVI changes across different temporal scales. The inherent correlations uncovered in this research can serve as valuable guidance for future investigations into surface water dynamics in arid regions.

The climatic and river runoff trends in Central Asia: The case of Zhetysu Alatau region, the south-eastern part of Kazakhstan

This study analyses, compares and correlates historical hydrometeorological data for the Zhetysu Alatau region and its main rivers (Lepsy, Sarykan, Koktal, Byzhy) to document characteristics and evidence of changes in climate change (temperature and precipitation) and its impact on annual and monthly river runoff. This study applies Andreyanov method for computation of runoff data and Mann-Kendall statistic method for assessing statistically significant or weak trends. The study reveals that the pattern of temperature for period of 1960-2020 and runoff for period of 1930-2019 has changed in the region. Mann-Kendall test result indicates a statistically significant increase in temperature at all meteorological stations (p<0.01), while the fluctuations in precipitation trends are not meaningful (p>0.05). Andreyanov method shows significant changes in intra-annual runoff trends, e.g., calculations for the period of 1965-2019 show a decrease of 5.3% in summer runoff in the Sarykan river, and the increase in runoff in the remaining months was 6.4% higher compared to the period of 1930-1965. Furthermore, the Mann-Kendall test confirms a significant positive trend in the change of seasonal runoff for the Sarykan, Byzhy, and Koktal rivers (p<0.02). The precipitation is one of the main factors influencing river runoff and the correlation coefficient between river runoff and precipitation for Lepsy river is r=0.81; for Byzhy river is r=0.70; for Koktal river is r=0.62; for Sarykan river is r=0.60.

A comprehensive assessment of runoff dynamics in response to climate change and human activities in a typical karst watershed, southwest China

The Chengbi River Basin is a typical karst watershed in Southwest China. Understanding the effects of climate change (CC) and human activities (HAs) on hydrological process is important for regional water resources management and water security. However, a comprehensive assessment of the effects of CC and HAs on runoff dynamics at different time scales in the Chengbi River Basin is still lacking. To address these needs, we used Budyko Mezentsev-Choudhurdy-Yang and Slope change ratio of accumulative quantity methods to assess the contribution of the changing environment to annual and intra-annual runoff changes in the Chengbi River Basin. The results indicated that annual runoff time series was divided into the base phase Ta (1980-1996) and the change phase Tb (1997-2019). Compared to the natural status in Ta, the relative contributions of CC and HAs to the runoff increase in Tb were 154.86% and -54.86%. In addition, the shift in intra-annual runoff occurred in 2007 and was mainly caused by HAs, with a contribution rate of 76.22%. The increase in annual runoff in Tb could be attributed to the positive contribution of rainfall. Changes in rainfall and reservoir construction altered the original state of intra-annual runoff. Furthermore, the high degree of heterogeneity in the surface karst zone increased the runoff coefficient. The spatial unsaturation of the subsurface water-bearing media and rainfall patterns caused a significant lag effect in the response of surface runoff to rainfall. This study can help researchers and policy makers to better understand the response of karst runoff to changing environment and provide insights for future water resources management and flood control measures.

Trade-offs and synergistic relationships of ecosystem services under land use change in Xinjiang from 1990 to 2020: A Bayesian network analysis

Ecosystem service value (ESV) refers to the value of benefits provided by the ecosystem to people, and can reflect the quality of regional ecological environment. There have been few studies on ESV in arid regions experiencing dramatic land use changes. Also, many past ESV studies have obtained distorted results by using a simple linear function to examine the trade-offs between driving factors. This study quantified ESV in Xinjiang from 1990 to 2020 based on value equivalent method. Differences in ESV among ecosystem services in Xinjiang under different scenarios were simulated using a Bayesian network model. The results demonstrated land use changes in Xinjiang from 1990 to 2020, with construction land expanding the most significantly (dynamic index: 224.63 %), whereas grassland area decreased (dynamic index: -1.31 %) due to transformation to unused and cultivated land. ESV in Xinjiang presented an N-shaped variation trend from 1990 to 2020 and decreased by 309.6 × 10⁸ CNY, with a variation rate of -20.35 %. The rank of the four categories of ecological services from 1990 to 2020 in terms of ESV was: regulating services > support services > cultural services > supply services. There was a gradual reduction in ESV in Xinjiang from 1990 to 2020. The rank of the different regions in terms of the reduction in ESV was: Northern Xinjiang (295.24 × 10⁸ CNY) > Southern Xinjiang (280.94 × 10⁸ CNY) > Eastern Xinjiang (109.76 × 10⁸ CNY). Land use change was a direct driver of changes in ESV, whereas natural and social factors, such as precipitation, temperature, population, and policy factors, were indirect drivers. This study can act as a reference for sustainable management of ecosystem services in arid regions.

Nitrogen and Phosphorus Retention Risk Assessment in a Drinking Water Source Area under Anthropogenic Activities

Excessive nitrogen (N) and phosphorus (P) input resulting from anthropogenic activities seriously threatens the supply security of drinking water sources. Assessing nutrient input and export as well as retention risks is critical to ensuring the quality and safety of drinking water sources. Conventional balance methods for nutrient estimation rely on statistical data and a huge number of estimation coefficients, which introduces uncertainty into the model results. This study aimed to propose a convenient, reliable, and accurate nutrient prediction model to evaluate the potential nutrient retention risks of drinking water sources and reduce the uncertainty inherent in the traditional balance model. The spatial distribution of pollutants was characterized using time-series satellite images. By embedding human activity indicators, machine learning models, such as Random Forest (RF), Support Vector Machine (SVM), and Multiple Linear Regression (MLR), were constructed to estimate the input and export of nutrients. We demonstrated the proposed model’s potential using a case study in the Yanghe Reservoir Basin in the North China Plain. The results indicate that the area information concerning pollution source types was effectively established based on a multi-temporal fusion method and the RF classification algorithm, and the overall classification low-end accuracy was 92%. The SVM model was found to be the best in terms of predicting nutrient input and export. The determination coefficient (R2) and Root Mean Square Error (RMSE) of N input, P input, N export, and P export were 0.95, 0.94, 0.91, and 0.93, respectively, and 32.75, 5.18, 1.45, and 0.18, respectively. The low export ratios (2.8–3.0% and 1.1–2.2%) of N and P, the ratio of export to input, further confirmed that more than 97% and 98% of N and P, respectively, were retained in the watershed, which poses a pollution risk to the soil and the quality of drinking water sources. This nutrient prediction model is able to improve the accuracy of non-point source pollution risk assessment and provide useful information for water environment management in drinking water source regions.

Natural- and Human-Induced Influences on Terrestrial Water Storage Change in Sichuan, Southwest China from 2003 to 2020

A quantitative understanding of changes in water resources is crucial for local governments to enable timely decision-making to maintain water security. Here, we quantified natural-and human-induced influences on the terrestrial water storage change (TWSC) in Sichuan, Southwest China, with intensive water consumption and climate variability, based on the data from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-on (GRACE-FO) during 2003–2020. We combined the TWSC estimates derived from six GRACE/GRACE-FO solutions based on the uncertainties of each solution estimated from the generalized three-cornered hat method. Metrics of correlation coefficient and contribution rate (CR) were used to evaluate the influence of precipitation, evapotranspiration, runoff, reservoir storage, and total water consumption on TWSC in the entire region and its five economic regions. The results showed that a significant improvement in the fused TWSC was found compared to those derived from a single model. The increase in regional water storage with a rate of 3.83 ± 0.54 mm/a was more influenced by natural factors (CR was 53.17%) compared to human influence (CR was 46.83%). Among the factors, the contribution of reservoir storage was the largest (CR was 42.32%) due to the rapid increase in hydropower stations, followed by precipitation (CR was 35.16%), evapotranspiration (CR was 15.86%), total water consumption (CR was 4.51%), and runoff (CR was 2.15%). Among the five economic regions, natural influence on Chengdu Plain was the highest (CR was 48.21%), while human influence in Northwest Sichuan was the largest (CR was 61.37%). The highest CR of reservoir storage to TWSC was in Northwest Sichuan (61.11%), while the highest CRs of precipitation (35.16%) and evapotranspiration (15.86%) were both in PanXi region. The results suggest that TWSC in Sichuan is affected by natural factors and intense human activities, in particular, the effect of reservoir storage on TWSC is very significant. Our study results can provide beneficial help for the management and assessment of regional water resources.

The divergence between potential and actual evapotranspiration: An insight from climate, water, and vegetation change

Recently, unprecedented extreme drought has appeared around the world. As the most direct signal of drought, evapotranspiration deserves a more systematic and comprehensive study. Further depicting their divergence of potential (ET_p) and actual evapotranspiration (ET_a) will help to explore the limitation of evapotranspiration. In this paper, the multi-source remote sensing datasets from the Climate Research Unit (CRU), Gravity Recovery and Climate Experiment (GRACE) and its follow-on experiment (GRACE-FO), the Global Land Data Assimilation System (GLDAS), and the Moderate Resolution Imaging Spectroradiometer (MODIS) during 2002 to 2020 were employed to explore the influence of meteorological, hydrological and botanical factors on ET_p, ET_a and their divergence - reduction of evapotranspiration (E_r) which represents regional vegetation and water limitations. According to the Pearson correlation analysis and the Boruta Algorithm based on Random Forest, the temperature is the first decisive promoter of evapotranspiration in the most area while the sparse vegetation is the primary or second determinant limiting the evapotranspiration in 61.84% of the world. In addition, the Coupled Model Intercomparison Project (CMIP6) data from 2030 to 2090 and the support vector machine regression (SVMR) model were applied to predict the future global ET_p, ET_a and E_r on the pixel scale. Predicted results of the model considering the water change not only can highly improve the model performance (with higher R²), but also can simulate the drought in Europe and the more intense ET_a in Africa. Thus, E_r proposed in this study provide a good reference for regional ET_a except for ET_p. The future evapotranspiration value derived by introducing the water storage changes into the machine learning model in this study is also valuable for climate change adaptation and drought warning.

Identification of conservation priorities in the major basins of Central Asia: Using an integrated GIS-based ordered weighted averaging approach

Ecosystem services (ESs) provided by the major basins of Central Asia are critical to human well-being and have attracted the attention of the international community. The identification of conservation priorities is of great significance for the maintenance and protection of key ESs. In this study, we quantified the spatiotemporal changes of net primary productivity (NPP), soil conservation (SC), water yield (WY) and habitat quality (HQ) in the major basins of Central Asia from 1995 to 2015. In addition, a GIS-based ordered weighted averaging (OWA) multi-criterion valuation method was adopted to identify potential conservation areas under 11 scenarios. Conservation priorities were determined by comparing the conservation efficiency under each scenario. Then, a broad range of indicators were considered to distinguish the driving factors affecting ESs in conservation priorities. The results show that the average conservation efficiency in the Issyk-Kul Basin was the highest, followed by the Am Darya Basin, Ili-Balkhash Basin and Syr Darya Basin. We observed that the conservation efficiency of the four ESs declined continuously in the Ili-Balkhash Basin from 1995 to 2015, while it changed steadily in the other three basins. Correlation analysis indicated that natural factors (e.g., precipitation and topography) were the main driving factors of WY, SR and NPP in conservation priorities, while HQ was more affected by socio-economic factors (e.g., population density and both cropland and urban percentages). The identification of conservation priorities and their driving factors plays an important role in ensuring the ecological security of the lower reaches, regulating the regional water balance and stabilizing the climate pattern.

Rapidly declining surface and terrestrial water resources in Central Asia driven by socio-economic and climatic changes

A systematic understanding of the dynamics of surface water resources and terrestrial water storage (TWS) is extremely important for human survival in Central Asia (CA) and maintaining the balance of regional ecosystems. Although several remote sensing products have been used to map surface water, the spatial resolution of some of them (hundreds of meters) is not sufficient to identify small surface water bodies, with monitoring data only being available for a few years or less. Thus, long-term continuous monitoring of surface water dynamics has not yet been achieved. To address this, we used all available Landsat images and the adjacent-years interpolation method to describe the dynamics of surface water in CA with a 30-m spatial resolution during 1990-2019. Subsequently, based on the multiple stepwise regression model, the climatic changes and human activity drivers affecting the surface water were systematically assessed. The permanent surface water areas (PSWA) of downstream countries with water scarcity decreased over time. The PSWA of Kazakhstan continues to decline at a maximum rate of 1189 km²/a. Additionally, human activities represented by population and reservoir areas are the dominant drivers affecting surface water resources in CA. The relationship between TWS and PSWA in CA and the constraints on social and economic development provided by the available water resources are discussed. The findings demonstrate that more than one-third of the croplands in CA are suffering from declining SWAs and TWS. The water crisis in CA has intensified, and the spatial mismatch between water and land resources is expected to remain one of the biggest challenges for future social and economic development in CA. Our dataset and findings provide high-precision surface water dynamics data that could be valuable for mitigating the water crisis in CA and provide a current scientific reference for achieving the United Nations' Sustainable Development Goals.

Impacts of Human Activities on the Variations in Terrestrial Water Storage of the Aral Sea Basin

Assessing the impacts of human activities on the variations in terrestrial water storage (TWS) is essential for water resource management, particularly in regions like the Aral Sea Basin which suffers from severe water scarcity. In this study, the variations in TWS anomalies (TWSA) of the Aral Sea Basin during the period of April 2002 to June 2017 were analyzed using Gravity Recovery and Climate Experiment (GRACE) data and the Global Land Data Assimilation System (GLDAS) Noah model outputs. The impacts of human activities on TWS variations were further quantified through the variations in TWS components and the comparison of TWS obtained from GRACE and GLDAS. The results indicate that TWSA of the entire Aral Sea Basin derived from GRACE experienced a significant decreasing trend of 4.12 ± 1.79 mm/year (7.07 ± 3.07 km3/year) from 2002 to 2017. Trends in individual TWS components indicate that the reduction in TWS of the Aral Sea Basin was primarily attributed to surface water loss, followed by groundwater depletion, which account for ~53.16% and 11.65 ± 45.39 to 42.48 ± 54.61% of the total loss of TWS, respectively. Precipitation (P) and evapotranspiration (ET) both exhibited increasing trends, indicating that ET played a dominant role in TWS depletion from the perspective of water balance. The variations in ET and TWS induced by human activities contributed ~45.54% and ~75.24% to those in total ET and TWS of the Aral Sea Basin, respectively.

The Energy Situation in Central Asia: A Comprehensive Energy Review Focusing on Rural Areas

The northern part of the globe is dominated by industrialisation and is well-developed. For many years, the southern part of the world (South Asia, Africa etc.) has been a target of research concentrating on access to energy (mainly electricity) in rural regions. However, the Central Asian region has not been a focus of energy research compared to South East Asia and Africa. Despite plentiful domestically available energy resources, the energy supply in Central Asia is very unevenly distributed between urban and rural areas. Almost half of the total population of Central Asia lives in rural areas and there is a lack of access to modern energy services to meet primary needs. To analyse the energy situation (i.e., electricity, heating, hot water consumption, cooking, etc.) in rural Central Asia, this paper reviews residential energy consumption trends in rural Central Asian regions as compared to urban areas. Furthermore, the paper illustrates the potential of renewable energies in Central Asia. To perform the study, a qualitative comparative analysis was conducted based on a literature review, data, and statistical information. In summary, the presented article discusses the rural energy situation analytically and provides in-depth insights of Central Asian energy infrastructure.