The Aral Sea Basin in Central Asia faces significant challenges in improving water utilization and treatment because of frequent transboundary river water disputes and shortages of water resources. However, the traditional water resource utilization efficiency (WRUE) assessment models generally have the defect of overvalidating evaluation results. To solve this problem, this study used the Coefficient of Variation method to constrain the self-contained weights in the traditional Data Envelopment Analysis (DEA) to construct an improved CV-DEA model, and assessed the WRUE of the Aral Sea Basin countries during 2000-2018 and compared the WRUE with that of the countries in the Mekong River Basin and Northeast Asia, then explored the factors influencing water utilization. The conclusions were drawn: since 1960, the runoff from the upper Amu Darya and Syr Darya rivers increased significantly, while the runoff from the lower Amu Darya River into the Aral Sea declined. Meanwhile, the water area of the Aral Sea shrank from 2.56 x 104 km2 to 0.70 x 104 km2 in 2000-2018, with the Northern Aral Sea remaining stable while the southern part shrinking sharply. The WRUE of the Aral Sea Basin (0.599, on average) was higher than that of the Mekong River Basin (0.547) and lower than that of Northeast Asia (0.885). Kazakhstan and Uzbekistan had the highest WRUE of 0.819 and 0.685 respectively, and the WRUE in both two countries improved from 2000 to 2018. Tajikistan (0.495) and Turkmenistan (0.402) experienced decreases in WRUEs. The high input redundancy of agricultural water consumption was the main driving force affecting WRUE in the basin.

Study region: Urumqi River headwater region in eastern Tianshan, central Asia. Study focus: Climate change is anticipated to accelerate glacier shrinkage and alter hydrological conditions, causing variations in the runoff patterns in the catchment and significantly threatening the regional water resources. However, few models exhibit adequate performance to simulate both surface alterations and glacier/snow runoff. Therefore, this study combined the glacier module with the Soil and Water Assessment Tool (SWAT) model to estimate the effect of climate change on the streamflow in the Urumqi River headwater region. The Urumqi River Headwater region is representative because of its long data series, viatal location, and local water availability, and it contains the longest-observed reference glacier (Urumqi Glacier No.1) in China, which spans the period from 1958 to the present. New hydrological insights for the region: The SWAT model performed satisfactorily for both calibration (1983-2005) and validation (2006-2016) periods with a Nash-Sutcliffe efficiency (NSE) greater than 0.80. The water balance analysis suggested that the snow/glacier melt contributed approximately 25% to the water yield. At the end of the 21st century, the temperature would increase by 2.4-3.8 degrees C while the precipitation would decrease by 1-2% under two future scenarios (ssp245 and ssp585). Thus, a 34-36% reduction in streamflow was projected due to above climate change impacts. This information would contribute to the development of adaptation strategies for sustainable water resource management.

Central Asia (CA) is one of the most severe water crisis areas on earth, which has seriously limited the achievement of sustainable development goals (SDGs) in the region. However, a multi-perspective analysis on the process and driving factors of the water crisis in CA has not been conducted. Therefore, we assess the water crisis from multiple perspectives using the water stress index (WSI), safe drinking water and water pollution indicators, and quantitatively analyze the impact of climate change, population growth, poverty, urbanization and transboundary river management on the water crisis. Results show that the water crisis in CA is intensifying. Uzbekistan and Turkmenistan belong to the "severe water stress" category, and the WSIs are increasing in both countries. Tajikistan is classified as "high water stress". Kyrgyzstan and Kazakhstan both exhibit "moderate water stress". Moreover, the proportion of the rural population with access to safe drinking water is significantly lower than that of the urban population in all the CA countries. The impact of human activities on water crisis in CA is more significant than that of climatic factors. Both cultivated land area and population are significant factors affecting the water crisis in CA (p < 0.05), with the regression coefficients of 0.62 and 1.62, respectively. Our research provides an essential reference for the sustainable management of water resources and warns that the water security situation in CA will worsen if no effective action is taken.

Although evidence of the hydrological response of watersheds to climate change is abundant, reliable assessments of water yield (WY) over mountainous regions, such as the Upper Brahmaputra River (UBR) basin, remain unclear. Here, we examine long-term WY changes during 1982–2013 in the UBR basin, based on multi-station runoff observations. We find that there are significant shifts in hydrological regimes in the late 1990s; WY increases in the range of ∼10 % to ∼80 %, while the directions reverse from increasing to decreasing. Additionally, the double mass curve (DMC) technique is used to assess the effects of climate, vegetation, and cryosphere on WY changes. Results show that cryosphere and climate together contribute to over 80 % of the increase in WY across the entire UBR basin, while the role of vegetation is negligible. The combined effects, however, are either offsetting or additive, thus leading to slight or substantial magnitude increases, respectively. The downward WY trend has primarily been regulated by decreased precipitation in recent years. However, we find that meltwater may alleviate the resulting water shortage in some basins. Therefore, the combined effects of climate and cryosphere on WY should be considered in future water resources management over mountainous basins, particularly involving co-benefits between upstream and downstream regions.

Central Asia, located in the hinterland of the Eurasian continent, is characterized with sparse rainfall, frequent droughts and low water use efficiency. Limited water resources have become a key factor restricting the sustainable development of this region. Accurately assessing the efficiency of water resources utilization is the first step to achieve the UN Sustainable Development Goals (SDGs) in Central Asia. However, since the collapse of the Soviet Union, the evaluation of water use efficiency is difficult due to low data availability and poor consistency. To fill this gap, this paper developed a Water Use Efficiency dataset (WUE) based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Gross Primary Production (GPP) data and the MODIS evapotranspiration (ET) data. The WUE dataset ranges from 2000 to 2019 with a spatial resolution of 500 m. The agricultural WUE was then extracted based on the Global map of irrigated areas and MODIS land use map. As a complementary, the water use amount per GDP was estimated for each country. The present dataset could reflect changes in water use efficiency of agriculture and other sectors. The published data are available at http://www.dx.doi.org/10.11922/sciencedb.j00076.00012.

Abstract. Although evidence of hydrological responses to climate is abundant, changes in water yield (WY) in mountainous regions due to climate change and intensified cryospheric melt remain unclear, mainly because of limited observations and large uncertainties in cryosphere-hydrological modeling. In this study, we used annual runoff observations and a high-resolution precipitation dataset to examine the long-term changes in WY in the Upper Brahmaputra River (UBR) basin, as represented by six sub-basins from the stream head to downstream. We found that WY generally increased during 1982–2013, but regime shifts were detected in the late 1990s. Moreover, the direction of the changes in WY reversed from increasing to decreasing in recent years despite the magnitude of the changes continually increasing from less than 10 % to 80.5 %. Furthermore, we used the double mass curve technique to assess the effects of climate, vegetation, and the cryosphere on WY. The results showed that the climate and cryosphere together contributed to over 80 % of the magnitude increases in WY over the entire UBR basin. However, the combined effects were either offsetting or additive, further leading to slight or substantial magnitude increases, respectively, in which the role of vegetation was nearly negligible. Nevertheless, we found that meltwater from the cryosphere had the potential to alleviate the loss of water availability, which mainly resulted from reduced effective precipitation in most regions. Therefore, the combined effects of climate and cryosphere changes should be considered in ecological restoration and water resources management, particularly involving co-benefits for upstream and downstream regions.

Satellite-driven and site observational data show that global warming has greatly enhanced vegetation activity (greening), with a broad upward trend in vegetation indices (VIs). However, the biophysical impact of vegetation on land surface temperature (T-s) is widely unknown, particularly in High Mountain Asia (HMA). In this study, we assessed vegetation dynamics in HMA from 2000 to 2020 and used intrinsic biophysical mechanism (IBM) models to quantify the biophysical feedback effects of vegetation on T-s. The results illustrate that, during the study period, HMA has undergone greening at a rate of 0.505 x 10(-3) W m(-2) mu m(-1) sr(-1) yr(-1) (solar-induced chlorophyll fluorescence: SIF) and 1.7 x 10(-3) yr(-1) (normalized vegetation index: NDVI), accounting for 52.75% and 47.24% of the total number of pixels, respectively. However, vegetation browning has occurred in areas such as the central Tien Shan and southeastern Tibet. Meanwhile, 64.22% (SIF) and 53.68% (NDVI) of the vegetation area in HMA showed a negative sensitivity of T-s to vegetation activity, particularly herbaceous and scrub vegetation in Inner Tibet and eastern Kun Lun. Additionally, the Bovine ratio and aerodynamic drag (r(a)) exhibited a negative sensitivity to vegetation activity. Most importantly, the vegetation activity-induced temperature changes were -0.278 K (Delta T-NDVIC(IBM)), -0.538 K (Delta T-SIFC(IBM)), 0.028 K (Delta T-NDVIS(IBM)), and 0.024 K (Delta T-SIFS(IBM)). Moreover, in the sensitivity method (Delta T-VegS(IBM)), vegetation cooling was detected in more than half of the pixels in HMA and was even more pronounced with SIF, accounting for 64.22% compared to 53.68% with NDVI. Enhanced vegetation activity alters the original balance of latent and sensible heat fluxes (Le, H) and increases the turbulent heat transfer between land and atmosphere, particularly Le. Our findings have important implications for understanding the response and feedback of vegetation dynamics to climate change in arid alpine regions.

Water, energy, food, and ecology play significant roles in poverty reduction, human well-being, and regional sustainable development. With the increasing demand for energy and food, environmental degradation, and increasing pressure on regional finite water resources, water-energy-food-ecology (WEFE) systems have been facing serious challenges in Central Asia. To address these challenges, it is necessary to understand and manage the WEFE nexus; thus, we explore the relationship between cross-sectoral pressures in this study. Based on the projection pursuit model and the virtual water trade concept, we comprehensively assess the WEFE system pressure and reveal the transmission of pressure. Finally, we develop a coordination mechanism to achieve the sustainable development of WEFE systems. The main results are as follows: (1) During 1992-2014, the comprehensive pressure level of the WEFE system showed a slightly upward trend, but there were significant differences between countries; (2) the pressures of cross-sectors are not only closely related but also transmittable. Unreasonable sectoral structure (crop planting, power generation and food import and export), spatial mismatch of resources and virtual water trade (especially for food trade) are important reasons for the pressure transfer within and across countries. And, (3) the proposed coordination mechanism optimizes the system structure, makes trade-offs and synergies for the interests of the sectors, and is more targeted. The integration of policies and regions is key to ensuring the smooth operation of the mechanism. This research can serve as a reference to achieve the coordinated development of WEFE systems in Central Asia.

As the “Water Tower of Asia” and “The Third Pole” of the world, the Qinghai–Tibet Plateau (QTP) shows great sensitivity to global climate change, and the change in its terrestrial water storage has become a focus of attention globally. Differences in multi-source data and different calculation methods have caused great uncertainty in the accurate estimation of terrestrial water storage. In this study, the Yarlung Zangbo River Basin (YZRB), located in the southeast of the QTP, was selected as the study area, with the aim of investigating the spatio-temporal variation characteristics of terrestrial water storage change (TWSC). Gravity Recovery and Climate Experiment (GRACE) data from 2003 to 2017, combined with the fifth-generation reanalysis product of the European Centre for Medium-Range Weather Forecasts (ERA5) data and Global Land Data Assimilation System (GLDAS) data, were adopted for the performance evaluation of TWSC estimation. Based on ERA5 and GLDAS, the terrestrial water balance method (PER) and the summation method (SS) were used to estimate terrestrial water storage, obtaining four sets of TWSC, which were compared with TWSC derived from GRACE. The results show that the TWSC estimated by the SS method based on GLDAS is most consistent with the results of GRACE. The time-lag effect was identified in the TWSC estimated by the PER method based on ERA5 and GLDAS, respectively, with 2-month and 3-month lags. Therefore, based on the GLDAS, the SS method was used to further explore the long-term temporal and spatial evolution of TWSC in the YZRB. During the period of 1948–2017, TWSC showed a significantly increasing trend; however, an abrupt change in TWSC was detected around 2002. That is, TWSC showed a significantly increasing trend before 2002 (slope = 0.0236 mm/month, p < 0.01) but a significantly decreasing trend (slope = −0.397 mm/month, p < 0.01) after 2002. Additional attribution analysis on the abrupt change in TWSC before and after 2002 was conducted, indicating that, compared with the snow water equivalent, the soil moisture dominated the long-term variation of TWSC. In terms of spatial distribution, TWSC showed a large spatial heterogeneity, mainly in the middle reaches with a high intensity of human activities and the Parlung Zangbo River Basin, distributed with great glaciers. The results obtained in this study can provide reliable data support and technical means for exploring the spatio-temporal evolution mechanism of terrestrial water storage in data-scarce alpine regions.

基于雅鲁藏布江流域奴下水文站1961-2015年逐月径流量资料，采用启发式分割算法识别径流突变年份，继而采用Mann-Kendall非参数检验分析径流的长期变化趋势，应用集中度和集中期研究径流的年内变化规律。结果表明：（1）年径流量呈现先减少后增加的变化趋势，且转折点为1992年，即年径流量在转折点前以2.715 mm/a的速率呈现显著的下降趋势，但在转折点后呈现不显著的上升趋势；（2）湿润季径流量占全年径流量的71.6%±4.4%，主导着雅鲁藏布江流域的年径流量变化过程，而在转折点后干旱季径流的变化是年径流呈现增加趋势的另一个重要原因；（3）雅鲁藏布江流域的径流年内分配规律呈"坦化现象"，即径流量最大值出现时间推迟且年内分配更加均匀，这可能归因于该地区植被覆盖状况的恢复和改善。研究结果可以进一步识别气候变化和下垫面在径流变化过程中的作用奠定良好的基础，为区域生态环境可持续发展提供建议和指导。

Estimating Terrestrial Water Storage (TWS) not only helps to provide a comprehensive insight into water resource variability and the hydrological cycle but also for better water resource management. In the current research, Gravity Recovery And Climate Experiment (GRACE) data are combined with the available hydrological data to reconstruct a longer record of Terrestrial Water Storage Anomalies (TWSA) prior to 2003 of the Tarim River Basin (TRB), based on a Long Short-Term Memory (LSTM) model. We found that the TWSA generated by LSTM using soil moisture, evapotranspiration, precipitation, and temperature best matches the GRACE-derived TWSA, with a high correlation coefficient (r) of 0.922 and a Normalized Root Mean Square Error (NRMSE) of 0.107 during the period 2003–2012. These results show that the LSTM model is an available and feasible method to generate TWSA. Further, the TWSA reveals a significant fluctuating downward trend (p < 0.001), with an average decline rate of 0.03 mm/month during the period 1982–2016 in the TRB. Moreover, the TWSA amount in the north of the TRB was less than that in the south of the basin. Overall, our findings unveiled that the LSTM model and GRACE data can be combined effectively to analyze the long-term TWSA in large-scale basins with limited hydrological data.

The growing water crisis in Central Asia (CA) and the complex water politics over the region's transboundary rivers have attracted considerable attention; however, they are yet to be studied in depth. Here, we used the Gini coefficient, water political events, and social network analysis to assess the matching degree between water and socio-economic elements and analyze the dynamics of water politics in the transboundary river basins of CA. Results indicate that the mismatch between water and land resources is a precondition for conflict, with the average Gini coefficient between water and population, gross domestic product (GDP), and cropland measuring 0.19 (highly matched), 0.47 (relatively mismatched), and 0.61 (highly mismatched), respectively. Moreover, the Gini coefficient between water and cropland increased by 0.07 from 1997 to 2016, indicating an increasing mismatch. In general, a total of 591 water political events occurred in CA, with cooperation accounting for 89 % of all events. Water events have increased slightly over the past 70 years and shown three distinct stages, namely a stable period (1951–1991), a rapid increase and decline period (1991–2001), and a second stable period (2001–2018). Overall, water conflicts mainly occurred in summer and winter. Among the region's transboundary river basins, the Aral Sea basin experienced the strongest conflicts due to the competitive utilization of the Syr and Amu Darya rivers. Following the collapse of the former Soviet Union, the density of water conflictive and cooperative networks in CA increased by 0.18 and 0.36, respectively. Uzbekistan has the highest degree centrality in the conflictive network (6), while Kazakhstan has the highest degree centrality in the cooperative network (15), indicating that these two countries are the most interconnected with other countries. Our findings suggest that improving the water and land allocation systems and strengthening the water cooperative networks among countries will contribute to the elimination of conflicts and promotion of cooperation in CA.

为准确识别高寒缺资料地区长序列陆地水储量变化特征及归因,该研究选取青藏高原东南部的雅鲁藏布江流域为研究区,基于2003—2017年的GRACE(Gravity Recovery and Climate Experiment)重力卫星数据,结合欧洲中期天气预报中心的第五代产品ERA5(the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts)再分析资料和GLDAS(Global Land Data Assimilation System)陆面同化数据,开展青藏高原东南部地区陆地水储量变化研究.分别使用ERA5和GLDAS两套数据集,采用水量平衡法和组分相加法两种方法,将反演的4套陆地水储量结果与GRACE反演的陆地水储量变化(Terrestrial Water Storage Change,TWSC)进行对比分析.结果表明:基于GLDAS的组分相加法反演的陆地水储量变化与GRACE反演的结果最为一致.因此,基于GLDAS数据集,采用组分相加法进一步探究雅鲁藏布江流域长序列(1948—2017年)陆地水储量的时空演变规律.在1948—2017年期间,TWSC呈现显著增加的趋势,但是在2002年左右发生了突变,即2002年之前呈现极显著增加的趋势(0.024 mm/月,P<0.01),2002年之后呈现极显著减少的趋势(-0.397 mm/月,P<0.01).进一步归因分析表明,2002年前后土壤含水量和雪水当量的变化趋势与陆地水储量变化的趋势一致.然而,2002年前后土壤含水量的变化对陆地水储量变化的贡献率分别为61％和99％,对陆地水储量变化起主导作用.在空间分布上,TWSC呈现出较大的空间异质性,主要体现在人类活动强度较高的"一江两河"地区和冰川分布集中的帕隆藏布地区.研究结果可为探究气候变化背景下青藏高原水储量时空演变机理提供可靠的参考方法和数据支持.

The utilization of water resources and water security in Central Asia are critical to the stability of the region. This paper assesses the water security of the five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) by using the projection pursuit model based on particle swarm optimization (PSO-PEE). The results show that the average annual water consumption in Central Asia is about 1255.57 x 10(8) m(3), and the proportion of agricultural water consumption decreased due in large part to the changes of crop planting structure. For the ecological security, Kazakhstan, Tajikistan and Kyrgyzstan have improved their status, but Turkmenistan is getting worse. For the quantity security of water resources, Tajikistan and Kyrgyzstan are relatively safe, whereas Uzbekistan is at risk. For the socio-economic conditions, Kazakhstan scored the highest, while Tajikistan and Uzbekistan scored the lowest, water consumption per 10,000 dollars of GDP across all five countries is relatively high but shows a significant decreasing trend. For the water supply and demand security, the status of Kazakhstan, Kyrgyzstan and Tajikistan are better than that of Turkmenistan and Uzbekistan. Kazakhstan has achieved a relatively safe level (level II) and the degree of water security is high. Kyrgyzstan, Tajikistan and Turkmenistan are only in the basically safe level (level III). Uzbekistan is under significant pressure with regard to water security (level IV), which indicates that the country needs to strictly control population growth and strengthen the comprehensive management of water resources.

定量评估水资源开发潜力对掌握区域水资源开发现状、提高水资源利用率具有重要意义.通过选取水资源利用率、灌溉率、地表水控制率、人均占有水量、重复利用率、生活用水定额、供水量模数、生态环境用水率等8个重要指标,借助模糊综合评价模型对中亚五国水资源开发潜力进行定量分析.结果 表明:中亚地区整体水资源开发利用处于中级阶段,开发潜力综合评分值为0.502 7,表明开发潜力较大.其中,哈萨克斯坦水资源综合评分值最高,为0.712 4,有很大的开发潜力,但要注意摒弃不合理的水资源利用方式;吉尔吉斯斯坦和塔吉克斯坦综合评分值分别为0.591 1、0.488 7,有较大的开发潜力,但应注意由广度开发逐渐向深度开发转变.下游国家土库曼斯坦和乌兹别克斯坦处于开发利用的高级阶段,综合评分值分别为0.352 6、0.315 0,水资源开发潜力较小.今后应注意发展节水型经济,注重水资源综合管理.

The destruction of the Aral Sea area constitutes one of the world's most infamous ecological disaster. However, the retreat of the Aral Sea has slowed down in recent years and the underlying reasons are not reported. In this work, based on the extreme-point symmetric mode decomposition (ESMD) method and the multiple linear regression model, we analyzed the changing of the Aral Sea from 1960 to 2018, and detected the time for slowdown of retreat, then explored the driving forces. The results show that the Aral Sea retreated rapidly from 1960 to 2004, and the shrinking rates of water surface area, water volume and water level were 1087.00 km(2)/year, 25.07 km(3)/year, and 0.56 m/year, respectively; the retreat has slowed since 2005, with the shrinking rates being 760.00 km(2)/year, 2.86 km(3)/year, and 0.38 m/year, respectively. At the same time, the area of water bodies surrounding the Aral Sea increased due to the agricultural drainage water. The oscillation periods of water level in the Aral Sea are 2.1a, 7.6a and 29.5a, of which 29.5a is the main period of oscillation. The trend residual RES indicates that water level shows a non-linear downward trend, and the degree of fluctuation has decreased significantly after 2005. The impact of human activities on the Aral Sea is more significant than that of climate change. Overall, the increased upstream runoff, reduced water withdrawal, and rise in water delivery to the Aral Sea has led to a slowing down of the sea's notorious shrinkage. The findings provide a scientific reference for the management and protection of the Aral Sea.