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Gaining a comprehensive understanding of the characteristics and propagation of precipitation-based meteorological drought to terrestrial water storage (TWS)-derived hydrological drought is of the utmost importance. This study aims to disentangle the frequency–time relationship between precipitation-derived meteorological and TWS-based hydrological drought from June 2002 to June 2017 based on the Standardized Precipitation Index (SPI) and Standardized Terrestrial Water Storage Index (STI) by employing wavelet coherence rather than a traditional correlation coefficient. The possible influencing factors on drought propagation in 28 regions across the world are examined. The results show that the number of drought months detected by the STI is higher than that detected by the SPI worldwide, especially for slight and moderate drought. Generally, TWS-derived hydrological drought is triggered by and occurs later than precipitation-based meteorological drought. The propagation characteristics between meteorological and hydrological droughts vary by region across the globe. Apparent intra-annual and interannual scales are detected by wavelet analysis in most regions, but not in the polar climate region. Drought propagation differs in phase lags in different regions. The phase lag between hydrological and meteorological drought ranges from 0.5 to 4 months on the intra-annual scale and from 1 to 16 months on the interannual scale. Drought propagation is influenced by multiple factors, among which the El Niño–Southern Oscillation, North Atlantic Oscillation, and potential evapotranspiration are the most influential when considering one, two, or three factors, respectively. The findings of this study improve scientific understanding of drought propagation mechanisms over a global scale and provide support for water management in different subregions. [ABSTRACT FROM AUTHOR]

Terrestrial water storage (TWS) is an essential element of the water cycle and a key state variable for land surface–atmosphere interaction. This study investigates the changes of TWS in Xinjiang of China in response to climate change, using Gravity Recovery and Climate Experiment (GRACE)-derived data and ground hydrological/meteorological observations in 2003–2015. The results show that the TWS has an overall significant decreasing trend of −2.8 mm per year. TWS is in a state of surplus in the first half year (from February to July), while it is in a state of deficit in the second half year (from August to next January). The change rates in TWS exhibit strong regional disparities, with profound decreasing trends in Tianshan Mountains and increasing in Kunlun Mountains. Further analyses suggest that the spatial-temporal change of TWS was closely related to the variations in seasonal snow melt and glacier retreat due to temperature and precipitation changes. [ABSTRACT FROM AUTHOR]

Under climate change and increasing water demands, groundwater depletion has become regional and global threats for water security, which is an indispensable target to achieving sustainable developments of human society and ecosystems, especially in arid and semiarid regions where groundwater is a major water source. In this study, groundwater depletion of 2003–2016 over Xinjiang in China, a typical arid region of Central Asia, is assessed using the gravity recovery and climate experiment (GRACE) satellite and the global land data assimilation system (GLDAS) datasets. In the transition of a warm-dry to a warm-wet climate in Xinjiang, increases in precipitation, soil moisture and snow water equivalent are detected, while GRACE-based groundwater storage anomalies (GWSA) exhibit significant decreasing trends with rates between-3.61 ± 0.85 mm/a of CSR-GWSA and −3.10 ± 0.91 mm/a of JPL-GWSA. Groundwater depletion is more severe in autumn and winter. The decreases in GRACE-based GWSA are in a good agreement with the groundwater statistics collected from local authorities. However, at the same time, groundwater abstraction in Xinjiang doubled, and the water supplies get more dependent on groundwater. The magnitude of groundwater depletion is about that of annual groundwater abstraction, suggesting that scientific exploitation of groundwater is the key to ensure the sustainability of freshwater withdrawals and supplies. Furthermore, GWSA changes can be well estimated by the partial least square regression (PLSR) method based on inputs of climate data. Therefore, GRACE observations provide a feasible approach for local policy makers to monitor and forecast groundwater changes to control groundwater depletion. [ABSTRACT FROM AUTHOR]

• Significantly decreasing trend of GRACE is observed which indicates the serious terrestrial water depletion. • Soil moisture and runoff have significant decreasing linear trends in Aral Sea Basin. • Precipitation is the major climate factor positively impacting on the terrestrial water cycle components. Assessments of the regional terrestrial water variabilities are important for improving our knowledges of the complex hydroclimate system and providing scientific information in regional water resource management under a changing environment due to climate change and intensified human activities. The Aral Sea Basin has experienced a serious ecological crisis which is majorly caused by the water resources due to the excessive water utilization. Therefore, in this study, we examine the long-term linear trend and variability of the terrestrial water cycle components based on multiple datasets over the Aral Sea Basin during 2003–2016. The terrestrial water cycle components include precipitation, evapotranspiration (ET), terrestrial water storage anomaly (TWSA), terrestrial water storage change (TWSC), runoff (R), soil moisture (SM) and groundwater. Major results show that increased trends of the annual precipitation and ET are observed during 2003–2016. For TWSA, Gravity Recovery and Climate Experiment (GRACE) derived datasets have significantly decreased trends with the values from −0.47 mm/mon to −0.29 mm/mon which reveal the serious terrestrial water depletion. Runoff, soil moisture and groundwater have the decreasing linear trends derived from multiple datasets. For the impacts of the climate factors on TWSA and TWSC, precipitation is the main climate factor with the significantly positive impacts. These results help us to have a better understanding of the complex hydrological process over the Aral Sea Basin, and provide a reliable scientific basic for police maker in the water resource management to achieve a sustainable development goal over the regions of the One Belt and One Road. [ABSTRACT FROM AUTHOR]

• A multiscalar standardized terrestrial water storage index (STI) based on GRACE TWS is proposed to assess droughts. • The short-term STI has higher correlation with long-term SPI and SPEI in the aspect of spatial distributions and temporal correlations. • The index is a robust multiscalar hydrological drought indicator with less noise. • STI has higher correlations with NDVI variations compared to other drought indices. A multiscalar standardized terrestrial water storage index (STI) is proposed to assess global hydrological droughts in this study. STI is defined as the standardized statistical deviation of terrestrial water storage (TWS) measured by GRACE to the climatology at multiple time scales. Because of the statistical nature of its definition, the proposed index is comparable to other standardized drought indices in different time scales, e.g., standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI) across different regions at multiple time scales. Our comparisons of STI with multiscalar drought indices (i.e. SPI and SPEI) and uni-scalar indices (i.e. self-calibrating palmer drought severity index [scPDSI], standardized soil moisture index [SM-Z], standardized runoff index [R-Z], and GRACE-based drought severity index [DSI]) show that STI can capture drought events with less noise than other indicators in persistent drought events. As a hydrological drought index based on TWS (which includes groundwater, soil moisture, etc.), STI at short-term time scales (e.g. 3 and 6 months) have higher correlations (mostly > 0.7) with SPI/SPEI at long-term scales (e.g. 18 and 24 months). Since the TWS measured by GRACE incorporates the impacts of the accumulated changes in meteorological variables, hydrological processes, and human activities as well as the advantage of multiscale, STI better represents vegetation growth reflected by Normalized Difference Vegetation Index (NDVI) than uni-scalar drought indices including the GRACE-based DSI, suggesting STI is a robust indicator for hydrological droughts and vegetation changes. [ABSTRACT FROM AUTHOR]

Hydrological droughts bring about great losses in agriculture, ecosystem and socioeconomics, so it is important to establish hydrological models or indicators to describe the occurrence, severity and duration of drought. But it remains challenging to obtain the whole relevant hydrological variables (e.g.., surface water, soil moisture, and groundwater) on the appropriate temporal and spatial scales. Now the Gravity Recovery and Climate Experiment (GRACE) satellite observations can provide realistic spatiotemporal variations of vertically integrated measurement of water storage (groundwater, glacier ice, soil moisture, surface water, snow water equivalent, permafrost, etc.) at large research area. Here we present a new GRACE-derived index (GNSI) to investigate drought conditions and evaluate its applicability. We obtain the Release-05 GRACE terrestrial water storage data from the University of Texas Center for Space Research and precipitation data in the high spatial resolution from the version 4.02 of the gridded Climatic Research Unit Time-series dataset from March 2002 to December 2016. We choose July 2010 in which drought occurred in many countries as an example to evaluate the performances of the drought indices. The GNSI and Standardized Precipitation Index (SPI) reach good agreement in the spatial distribution of drought conditions in south China, northern India, western Russia, middle Europe, west side of South America and Western Australia. However, the intensities among the two indices in some regions are different, such as in the middle of China, United States and Greenland. In the middle of China, the GNSI detects more normal area while SPI captures some dry conditions. In the northern part of the United States, the GNSI reveals two obvious drought regions whereas the SPI does not. Furthermore, GNSI is compared with SPI at different time scales. The GNSI shows time lag about three months compared with SPI. [ABSTRACT FROM AUTHOR]

• Declining water storage trends in the GRACE and GHMs were observed over Central Asia. • TWSA can be well simulated and predicted by climate variables. • Potential strategies are provided to address the SDGs of water resource over Central Asia. Arid regions of Central Asia have sensitive ecosystems that rely heavily on terrestrial water storage which is composed of surface water storage, soil moisture storage and groundwater storage. Therefore, we employed three Gravity Recovery and Climate Experiment (GRACE) satellite datasets and five global hydrological models (GHMs) to explore the terrestrial water storage (TWS) changes over arid regions of Central Asia from 2003 to 2014. We observed significantly decreasing water storage trends in the GRACE data, which were underestimated by the GHMs. After averaging the three GRACE satellite datasets, we found that the water storage was decreasing at a rate of −4.74 mm/year. Contrary to the prevailing declining water storage trends, northeastern Kazakhstan (KAZ), and southern Xinjiang increased their water storage over the same period. The GRACE data showed that Turkmenistan (TKM), Uzbekistan (UZB) and KAZ experienced the most severe water depletions, while Tajikistan (TJK) and northwest China (NW) experienced the least significant depletions. With respect to the major river and lake basins, the Aral Sea Basin exhibited the most serious water loss (-0.60 mm/month to −0.38 mm/month). The water storage positively correlates with the precipitation; and negatively correlates, with a three-month lag, with temperature and potential evapotranspiration (PET). Partial least square regression (PLSR) had the high capability in simulating and predicting the TWS. These results provide scientific evidence and guidance for local policy makers working toward sustainable water resource management, and the resolution of international water resource disputes among Central Asian countries. [ABSTRACT FROM AUTHOR]