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The timely and effective early warning of sudden drought events is of great importance for reducing disaster losses and drought risk. Satellite microwave remote sensing with the advanced microwave scanning radiometer (AMSR) has enabled the global monitoring of multiple components of water, such as soil moisture (SM), vapour pressure deficit (VPD), and open water fraction (OWF), on a daily scale since 2002. In this study, the applicability of the AMSR surface wetness index (ASWI) and drought features in Central Asia were studied from 2002 to 2017 based on AMSR data. This study concluded that (1) the spatial and temporal differences in the various water components and coefficient of variation of the Central Asia land–atmosphere interface were large, which led to large spatial and temporal differences under both dry and wet conditions in Central Asia; (2) although the ASWI was not significantly correlated with other drought indices (i.e., gravity recovery and climate experiment (GRACE) combined climatological deviation index (CCDI) and GRACE drought severity index (DSI)) over Central Asia, the maximum Pearson correlation coefficient (CC) between the ASWI and Palmer drought severity index (PDSI) in the Irtysh River Basin was 0.824 (p < 0.05), corresponding to a moving average window of 11 months. The CCs of ASWI and Standardized Precipitation Evapotranspiration Index on a 6‐month scale (SPEI‐6) in Central Asia were generally more than 0.8 (p < 0.05), indicating that the ASWI was effective for retrieving drought conditions in Central Asia. In addition, these four drought indices (ASWI, PDSI, GRACE‐DSI, and GRACE‐CCDI) revealed that drought occurred continuously after 2003 in Central Asia; (3) the spatial and temporal distribution of dry and wet conditions in Central Asia is closely related to the teleconnection indices (i.e., MEI, SOI, and PDO). Thus, AMSR data are critical for understanding drought events and their evolution in regions influenced by climate change. [ABSTRACT FROM AUTHOR]

Understanding temporal and spatial changes in precipitation has far-reaching implications for watershed development and risk assessment under global climate change. In our study, temporal and spatial variability in precipitation concentration (PC) in Central Asia (CA) from 1980 to 2017, measured with the precipitation concentration index (PCI) and Gini Coefficient (GC), was analyzed using interpolated precipitation from the Climate Prediction Center (CPC) and National Centers for Environmental Prediction (NCEP). The results showed that: (1) interpolated precipitation increased significantly, with significant mutations (P <.5) mainly concentrated between 2000 and 2010; (2) the spatial distribution of the CPC PCI was opposite to that of the NCEP PCI, and fluctuations in CPC GC were larger than that of the NCEP, which indicated that the precipitation data from NCEP was more uniform over the year; (3) for two of three interpolation methods, CPC PC displayed significant mutations in southern CA between 1985 and 2005, while significant (P <.05) mutations in NCEP PC were relatively concentrated in southern CA between 1987 and 2005; (4) although the El Niño Modoki Index (EMI), Pacific Decadal Oscillation (PDO), Nino 3.4, and Southern Oscillation Index (SOI) displayed resonance relationships with CPC PCI, there were no significant abrupt changes in the resonance correlation. In the NCEP data, EMI, PDO, Nino 3.4, and North Atlantic Oscillation (NAO) led to mutations in the resonance relationship with PCI. Our research proved that the change in PC in CA had closely relationship with some teleconnection indices. • The characteristics from different product were different over Central Asia. • The mutations for different interpolated precipitation were different. • Precipitation concentration had a gradual trend in space over Central Asia. • More than one teleconnection index impacted on the precipitation concentration. [ABSTRACT FROM AUTHOR]

Under climate change, droughts are causing increasingly larger damages around the world, attracting the attention of governments and researchers. In this study, the terrestrial water storage anomalies (TWSA) obtained from a Gravity Recovery and Climate Experiment (GRACE) were coupled with precipitation, creating a Combined Climatological Deviation Index (CCDI). This index was used to analyze the drought events that occurred in the major basins of Central Asia between April 2002–June 2017. The main conclusions are as follows: (1) the certain but not significant (i.e., p >.05) impacts of precipitation were detected on the total water storage anomalies (TWSA) of three basins (i.e., Irtysh River Basin (IRB), Syr Darya Basin (SDB), and Amu Darya Basin (ADB)) that originate from the Tienshan Mountains based on the correlation coefficient between precipitation and terrestrial water storage (TWS); (2) the Drought Severity Index (DSI), the Palmer Drought Severity Index (PDSI), and the Standardized Precipitation Index over a 12-month scale (SPI12) were related to the CCDI in the major basins of Central Asia, suggesting that the CCDI can be applied effectively to assess the drought characteristics of these basins; (3) the most severe drought events detected by the CCDI in the IRB, SDB, and ADB occurred in 2012, 2014, and 2014, respectively. A humidification trend was observed for the IRB, while a drought trend was observed in the SDB and ADB. Therefore, it appears that the CCDI can be effectively applied to determine the severity of droughts, increase water-saving awareness, and avoid the effects of droughts. • Precipitation has little effect on TWS in Central Asia. • CCDI can character the drought events in Central Asia well. • The drought severity from CCDI was more severe than that from other traditional drought indices. • All the drought indices were discovered the obvious drought events in Central Asia during 2008–2009. [ABSTRACT FROM AUTHOR]

• The drought events in Central Asia retrieved by ASWI are consistent with the records of actual situation. • The drought centroid of Central Asia hardly occurs in the southeast. • Central Asia has experienced drought in the past two decades, followed by gradual wetting. • The water vapor flux, precipitation, and temperature have obvious influence on the occurrence of drought in Central Asia. Under warm climates, the more complex and malleable relationship between water and heat and the changes in the water components at the land–atmosphere interface pose greater challenges to understanding hydro-meteorological processes. However, the emergence of the advanced microwave scanning radiometer (AMSR) has facilitated the precise monitoring of these changes. Therefore, this study investigated and analyzed the spatiotemporal transformation characteristics of drought–wetness and its driving mechanisms in Central Asia from July 2002 to December 2018 based on the AMSR surface wetness index (ASWI) coupled with multiple water components. Three major conclusions were drawn from this investigation. First, the spatiotemporal differences in multiple water components in Central Asia caused substantial spatiotemporal differences in the extent of changes in drought–wetness. For example, arid areas were mainly concentrated in the lower reaches of the Amu Darya and Syr Darya river basins, where the dominant drought periods were 2007 and 2018. Second, the centroids of the largest drought patches were mainly located in the northeast, northwest, and southwest regions of Central Asia. Central Asia experienced a continuous drought from 2002 to 2005, and then a gradual wetting from 2008 to 2017. Third, the drought–wetness variation can be attributed to the variation of water vapor flux in the typical barometric layer as well as the variation of precipitation and temperature. The ASWI may play an essential role in drought monitoring and tracking prediction, particularly for drought risk mitigation and aversion. [ABSTRACT FROM AUTHOR]

As most of the runoff resulting from snow-ice melt is related to climate change factors in the arid region of northwest China, the risk to water resource systems threatens the socio-economic and ecological environment and is becoming increasingly prevalent. Therefore, we explored the risks of water resource shortages for different periods (2010, 2020, and 2030) in the Aksu River basin (ARB) in the northwest arid region of China by reconstructing a risk model based on the framework proposed by the Intergovernmental Panel on Climate Change (IPCC) with an improved vulnerability (V) module and a more suitable hazard probability in the cost module. The major conclusions are as follows: (1) the simulation of the Community Land Model-Distributed Time Variant Gain Model (CLM-DTVGM) and the Vegetation Interface Processes model (VIP) was suitable for the eco-hydrological processes in the ARB under climate change (i.e., R2 ≥ 0.583; Nash coefficient ≥0.371; and relative mean standard ≤155.727 for CLM-DTVGM; R2 = 0.798 for VIP); (2) the vulnerability of the water resource system in the ARB was medium in 2010, and dropped to a medium-low to non-vulnerable level in 2020 before increasing in 2030 under different Representative Concentration Pathways (RCP) (RCP2.6, RCP4.5, and RCP8.5); and (3) there was a medium-low risk of water resource shortages in the ARB in 2010 (i.e., 0.246), and although the risk of water resource shortages decreased in 2020 due to the increasing water supply from mountainous areas, the risk predicted to increase significantly in 2030, to a medium-high risk level. This study is critical for accurately predicting and understanding the impact of climate change on water resource systems as well as on the drought risk in arid regions. [Display omitted] • Climate change and human activities have a significant impact on the risk of water shortage in the Aksu River Basin. • VIP and CLM-DTVGM can simulate the hydrological process in the Aksu River Basin well. • The cost of drought disaster was well integrated into the risk assessment model of water resource system. • The resilience of the water resource system in the ARB weakened, but the cost and exposure, and vulnerability increased. • The water resource system of Aksu River Basin will also suffer from great risks in the future. [ABSTRACT FROM AUTHOR]