GRACE Gravity Satellite Observations of Terrestrial Water Storage Changes for Drought Characterization in the Arid Land of Northwestern China

Comparison of groundwater storage changes over losing and gaining aquifers of China using GRACE satellites, modeling and in-situ observations

Groundwater depletion in intensively exploited aquifers of China has been widely recognized, whereas an overall examination of groundwater storage (GWS) changes over major aquifers remains challenging due to limited data and notable uncertainties. Here, we present a study to explore GWS changes over eighteen major aquifers covering an area of 1,680,000 km2 in China using data obtained from the Gravity Recovery and Climate Experiments (GRACE), global models, and in-situ groundwater level observations. The analysis aims to reveal the discrepancy in annual trends, amplitudes, and phases associated with GWS changes among different aquifers. It is found that GWS changes in the studied aquifers represent a spatial pattern of 'Wet-gets-more, Dry-gets-less'. An overall decreasing trend of -4.65 ± 0.34 km3/yr is observed by GRACE from 2005 to 2016, consisting of a significant (p < 0.05) increase of 47.28 ± 3.48 km3 in 7 aquifers and decrease of 103.56 ± 2.4 km3 (∼2.6 times the full storage capacity of the Three Gorges Reservoir) in 10 aquifers summed over the 12 years. The annual GWS normally reaches a peak in late July with an area-weighted average annual amplitude of 19 mm, showing notable discrepancy in phases and amplitudes between the losing aquifers (12 mm in middle August) in northern China and gaining aquifers (28 mm in early July) mostly in southern China. GRACE estimates are generally comparable, but can be notably different, with the results obtained from model simulations and in-situ observations at aquifer scale, with the area-weighted average correlation coefficients of 0.6 and 0.5, respectively. This study highlights different GWS changes of losing and gaining aquifers in response to coupled impacts of hydrogeology, climate and human interventions, and calls for divergent adaptions in regional groundwater management.

Using Satellite-Based Terrestrial Water Storage Data: A Review

Land water storage plays a key role for the Earth's climate, natural ecosystems, and human activities. Since the launch of the first Gravity Recovery and Climate Experiment (GRACE) mission in 2002, spaceborne observations of changes in terrestrial water storage (TWS) have provided a unique, global perspective on natural and human-induced changes in freshwater resources. Even though they have become much used within the broader Earth system science community, space-based TWS datasets still incorporate important and case-specific limitations which may not always be clear to users not familiar with the underlying processing algorithms. Here, we provide an accessible and illustrated overview of the measurement concept, of the main available data products, and of some frequently encountered technical terms and concepts. We summarize concrete recommendations on how to use TWS data in combination with other hydrological or climatological datasets, and guidance on how to avoid possible pitfalls. Finally, we provide an overview of some of the main applications of GRACE TWS data in the fields of hydrology and climate science. This review is written with the intention of supporting future research and facilitating the use of satellite-based terrestrial water storage datasets in interdisciplinary contexts.

Hydrological drought evaluation using GRACE satellite-based drought index over the lake basins, East Africa

Hydrological drought, a regular phenomenon that could heavily impact natural systems and human life, is aggravated by a water storage deficit. While Gravity Recovery and Climate Experiment (GRACE) satellite databased drought monitoring has been widely studied in East Africa (EA), drought recovery time and anthropogenic factors are still missing, which are prerequisite for drought management. Here, a water storage deficit index (WSDI) and modified WSDI are utilized for analyzing a holistic representation of drought. The results show that the drought events in recent times are well-identified and estimated using this approach over five lake basins in EA from 2002 to 2021. Although, the basin scale drought events are evaluated using the Pearson correlation coefficient (r) from 2002 to 2021. The results showed a significant correlation between WSDI, MWSDI, and the standardized precipitation-evapotranspiration index (SPEI) in all lake basins except in the Tana basin. We show that the presence of anthropogenic forcing has increased the highest peak deficits of -2.57, -3.25, -19.05, -87.2, and -99 km³ over the Tana, Abaya-Chamo, Turkana, Victoria, and Tanganyika basins, respectively. The longest deficit period of 36 months and the highest severity value of -1140 were observed in the Turkana and Victoria basins. The average drought recovery time ranges from 2.4 to 11.2 months and from 1.4 to 12.6 months as obtained by WSDI and MWSDI, respectively. Our findings highlight the importance of the calculated WSD approach to evaluating the hydrological drought characterization and estimate the drought condition at the basin scale.

Drought characterization over Indian sub-continent using GRACE-based indices

Drought is a natural disaster affects water resources, agriculture, and social and economic development due to its long-term and frequent occurrence. It is crucial to characterize and monitor drought and its propagation to minimize the impact. However, spatiotemporal assessment of drought characteristics over India at the sub-basin scale based on terrestrial water storage is unexplored. In this study, the Terrestrial water storage anomalies (TWSA) obtained from a Gravity Recovery and Climate Experiment and precipitation data are used to characterize the propagation of drought. Combined Climatological Deviation Index (CCDI) and GRACE-Drought Severity Index (GRACE-DSI) were computed as CCDI utilizes both precipitation and TWSA data while GRACE-DSI uses only TWSA data. Our results showed that GRACE-DSI exhibits significant negative trends over most of the Indian sub-basins compared to CCDI, indicating that most of the drought events are due to depletion of TWS. While other sub-basins show changing trends for GRACE-DSI and CCDI. The number of sub-basins showing significant negative trends for GRACE-DSI is more than that for CCDI. Hence TWS is depleting for most of the subbasins in India. Our results show that Indo-Gangetic plains face many drought events during 2002–2004, 2009–2014 & 2015–2017. Maximum drought duration and drought severity obtained for the area of North Ladakh (not draining into Indus basins) by GRACE-DSI are 26 months (2002–2004) and − 44.2835, respectively. The maximum drought duration and drought severity obtained for the Shyok sub-basin by CCDI is 17 months (2013–2015) and − 13.4392, respectively. Monthly trend analysis revealed that 39 & 23 no. of sub-basins show significant negative GRACE-DSI trends for October and CCDI for November, respectively. At the same time, the seasonal trend shows that total 34 and 14 sub-basins exhibited a significant negative trend at post-monsoon Kharif season for both the GRACE-DSI & CCDI, respectively.

Oasis sustainability assessment in arid areas using GRACE satellite data

An oasis is an important habitat for humans, plants, and wildlife in arid desert areas. The sustainability of an oasis is crucial for a smooth regional ecological functioning and healthy economic development. However, the overexploitation of groundwater will result in unsustainable oasis development. Due to the lack of long-term groundwater monitoring data, the impact of groundwater level changes on the sustainability of an oasis has not been studied extensively. In the present study, we used the ground water storage anomaly (GWSA) in combination with the Gravity Recovery and Climate Experiment (GRACE) and the Global Land Data Assimilation System (GLDAS) for the rapid identification of oasis sustainability, which has been tested and evaluated in Hotan and Qira oasis located in arid areas. The results showed that (1) the GWSA is a suitable and reliable indicator for trend change analysis in small-scale oasis and, (2) additionally, M-K test results for long-term trend change of GWSA showed a positive correlation with water resource carrying capacity (WRCC). These results suggest that GWSA can be used as a reliable index for the rapid assessment of oasis sustainability status in arid areas. Moreover, the potential applicability of GRACE satellite data in evaluating the groundwater sustainability in arid areas lacking proper data has also been proved in this study. These findings have provided a foundation to evaluate the sustainability status of an oasis and set a reference point to formulate future policies for the oasis.

Analyzing the Association between ENSO and Groundwater Rise in the South Atlantic-Gulf Region in the Southeastern United States

The primary goal of this study is to comprehend the effects of El Niño Southern Oscillation (ENSO) climate pattern on groundwater storage (GWS) in the South Atlantic-Gulf Region. Groundwater issues are complex and different studies focused on groundwater depletion while few emphasized “groundwater rise”. The current research is designed to develop an outline for assessing how climate patterns can affect groundwater fluctuation, which might lead to groundwater rise. The study assessed the effect of ENSO phases on spatiotemporal variability of groundwater using Spearman Rank Correlation. A significant positive correlation between ENSO and GWS was observed. An increasing trend was detected in GWS where most grids were observed in Florida by utilizing the non-parametric Mann–Kendall test. A positive trend magnitude was also detected by utilizing Theil–Sen’s Slope method with a high magnitude in the mid-Florida region. The highest GWS anomalies were observed in the peak of El Niño events and the lowermost GWS was observed during La Niña events. Furthermore, most of the stations were above normal groundwater conditions. This study provides a better insight on the research gap among groundwater rise and ENSO.

Two Severe Prolonged Hydrological Droughts Analysis over Mainland Australia Using GRACE Satellite Data

In recent years, many droughts have happened over mainland Australia, especially the two severe prolonged droughts, from 2006 to 2009 and 2018 to 2020, resulting in serious water scarcity. Therefore, using the Total Storage Deficit Index (TSDI) from the Gravity Recovery and Climate Experiment (GRACE), we analyzed the two severe prolonged droughts from the perspective of the affected area, spatial evolution, frequency, severity and drought driving factors. The results show that the affected area of Drought 2006–2009 ranged from 57% to 95%, and that of Drought 2018–2020 ranged from 45% to 95%. Drought 2006–2009 took its rise in southeastern Australia and gradually spread to the central part. Drought 2018–2020 originated in the southwest corner of the Northern Territory and northern New South Wales, and gradually expanded to Western Australia and the whole New South Wales respectively. During Drought 2006–2009, Victoria suffered drought all months, including 59% mild drought and 41% moderate drought, North Territory had the highest drought severity of 44.26 and Victoria ranked the second high with the severity of 35.51 (cm months). For Drought 2018–2020, Northern Territory was also dominated by drought all months, including 92% mild drought and 8% moderate drought, the drought severities were in North Territory and Western Australia with 52.19 and 31.44 (cm months), respectively. Finally, the correlation coefficients between the two droughts and Indo-Pacific climate variability including El Niño-Southern Oscillation and Indian Ocean Dipole (IOD) are computed. By comparing the correlation coefficients of Drought 2018–2020 with Drought 2006–2009, we find that the impact of the El Niño on the hydrological drought becomes weaker while IOD is stronger, and the role of Southern Oscillation on droughts is diverse with the quite different spatial patterns. The results from Fourier analysis confirm that the two hydrological droughts are all related to Indo-Pacific climate variability but with slightly different driving mechanisms.

Monthly and Seasonal Drought Characterization Using GRACE-Based Groundwater Drought Index and Its Link to Teleconnections across South Indian River Basins

Traditional drought monitoring is based on observed data from both meteorological and hydrological stations. Due to the scarcity of station observation data, it is difficult to obtain accurate drought distribution characteristics, and also tedious to replicate the large-scale information of drought. Thus, Gravity Recovery and Climate Experiment (GRACE) data are utilized in monitoring and characterizing regional droughts where ground station data is limited. In this study, we analyzed and assessed the drought characteristics utilizing the GRACE Groundwater Drought Index (GGDI) over four major river basins in India during the period of 2003–2016. The spatial distribution, temporal evolution of drought, and trend characteristics were analyzed using GGDI. Then, the relationship between GGDI and climate factors were evaluated by the method of wavelet coherence. The results indicate the following points: GRACE’s quantitative results were consistent and robust for drought assessment; out of the four basins, severe drought was noticed in the Cauvery river basin between 2012 and 2015, with severity of −27 and duration of 42 months; other than Godavari river basin, the remaining three basins displayed significant negative trends at monthly and seasonal scales; the wavelet coherence method revealed that climate factors had a substantial effect on GGDI, and the impact of Southern Oscillation Index (SOI) on drought was significantly high, followed by Sea Surface Temperature (SST) Index (namely, NINO3.4) and Multivariate El Niño–Southern Oscillation Index (MEI) in all the basins. This study provides reliable and robust quantitative result of GRACE water storage variations that shares new insights for further drought investigation.

Tracking seasonal and monthly drought with GRACE-based terrestrial water storage assessments over major river basins in South India

Drought is a complex natural hazard that affects ecosystems and society in several ways and it is important to quantify drought at the river basin scale. Assessment of drought requires both hydrological observations and simulation models as the data are generally scarce. Therefore, we use remote sensing products to help understand drought conditions in four basins in South India. This study analysed the correlation among five drought indices for four seasons: gravity recovery and climate experiment - drought severity index (GRACE-DSI), standardized precipitation index (SPI), self-calibrated palmer drought severity index (sc_PDSI), standardized precipitation-evapotranspiration index (SPEI), and combined climatologic deviation index (CCDI) with GRACE terrestrial water storage anomalies (TWSA) using the Pearson correlation coefficient (r) from 2002 to 2016 over the Godavari, Krishna, Pennar, and Cauvery river basins. Basin scale drought events are evaluated using CCDI, GRACEDSI, sc_PDSI, SPI12, and SPEI12 at seasonal and monthly time scale. Characteristics of drought event analysis are calculated for CCDI monthly. The results showed that GRACE TWS is highly correlated with GRACE-DSI, CCDI, and sc_PDSI. Seasonally, high spatial correlations between CCDI and GRACE-DSI with GRACE TWS are evident for all the river basins. Additionally, correlation is found to exist between sc_PDSI and GRACE TWS as soil moisture content is an operating variable between them. The 12-month SPI and SPEI correlated better with GRACE TWS than the 3 and 6-month periods. Among the four basins, droughts in the Krishna Basin lasted 29 months, longer than in the rest of the basins between 2003 and 2005. Overall, CCDI and GRACE-DSI indices are found to be effective for examining and evaluating the drought conditions at the basin scale.

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

Water resources in Central Asia are very scarce due to natural and anthropogenic impacts. Water shortages have been a major factor hampering the socio-economic development of Central Asia. Exploring internal interactions among climate change, human activities and terrestrial hydrological cycles will help to improve the management of water resources in Central Asia. In this paper, hydro-climatic and anthropogenic data for the period 2003-2016 from the Gravity Recovery and Climate Experiment (GRACE), the Global Land Data Assimilation System (GLDAS), the Climatic Research Unit (CRU) and the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to analyze the influence of natural factors and human activities on changes of available water (AWC). The terrestrial water storage derived from GRACE and GLDAS remarkably declined in 2008, due to a serious drought, but increased thereafter. The AWC positively responded to the vegetation index, evapotranspiration, potential evapotranspiration and air temperature at a lag of 0-1 month, but to precipitation at a lag of 2-3 months. Results of correlation analysis with a spatial square moving window indicated that forests, grasses, croplands and water areas presented significantly positive correlations with AWC, while barren areas and urban areas were negatively correlated with AWC. According to the Boruta algorithm and the Random Forest model, natural factors, namely precipitation, evapotranspiration and potential evapotranspiration, were major factors for AWC in the whole Central Asia. Human activities had direct and indirect impacts on AWC. With the development of society and economy, croplands and urban areas gradually increased, resulting in a rising demand for water withdrawals for agriculture irrigation and industry. The unreasonable utilization and exploitation of water resources led to vegetation degradation and ecosystem deterioration, which would worsen the shortage of water resources in arid regions of Central Asia.

Using GRACE satellite observations for separating meteorological variability from anthropogenic impacts on water availability

Gravity Recovery and Climate Experiment (GRACE) observations provide information on Total Water Storage Anomaly (TWSA) which is a key variable for drought monitoring and assessment. The so-called Total Water Storage Deficit Index (TWSDI) based on GRACE data has been widely used for characterizing drought events. Here we show that the commonly used TWSDI approach often exhibits significant inconsistencies with meteorological conditions, primarily upon presence of a trend in observations due to anthropogenic water use. In this study, we propose a modified version of TWSDI (termed, MTWSDI) that decomposes the anthropogenic and climatic-driven components of GRACE observations. We applied our approach for drought monitoring over the Ganges–Brahmaputra in India and Markazi basins in Iran. Results show that the newly developed MTWSDI exhibits consistency with meteorological drought indices in both basins. We also propose a deficit-based method for drought monitoring and recovery assessment using GRACE observations, providing useful information about volume of deficit, and minimum and average time for drought recovery. According to the deficit thresholds, water deficits caused by anthropogenic impacts every year in the Ganges–Brahmaputra basin and Markazi basins is almost equal to an abnormally dry condition and a moderate drought condition, receptively. It indicates that unsustainable human water use have led to a form of perpetual and accelerated anthropogenic drought in these basins. Continuation of this trend would deplete the basin and cause significant socio-economic challenges.

Monitoring and Predicting Drought Based on Multiple Indicators in an Arid Area, China

Droughts are one of the costliest natural disasters. Reliable drought monitoring and prediction are valuable for drought relief management. This study monitors and predicts droughts in Xinjiang, an arid area in China, based on the three drought indicators, i.e., the Standardized Precipitation Index (SPI), the Standardized Soil Moisture Index (SSMI) and the Multivariate Standardized Drought Index (MSDI). Results indicate that although these three indicators could capture severe historical drought events in the study area, the spatial coverage, persistence and severity of the droughts would vary regarding different indicators. The MSDI could best describe the overall drought conditions by incorporating the characteristics of the SPI and SSMI. For the drought prediction, the predictive skill of all indicators gradually decayed with the increasing lead time. Specifically, the SPI only showed the predictive skill at a 1-month lead time, the MSDI performed best in capturing droughts at 1- to 2-month lead times and the SSMI was accurate up to a 3-month lead time owing to its high persistence. These findings might provide scientific support for the local drought management.

Monitoring and Analysis of Drought Using Gravity Recovery and Climate Experiment (GRACE)

Drought monitoring needs comprehensive and integrated meteorological and hydrologic data. However, such data are generally not available in extensive catchments. The present study aimed to analyze drought in the central plateau catchment of Iran using the terrestrial water storage deficit index (TSDI). In this arid catchment, the meteorological and hydrologic observed data are scarce. First, the time series of terrestrial water storage changes (TWSC) obtained from the gravity recovery and climate experiment (GRACE) was calculated and validated by the water budget output. Then, the studied area was divided into semi-arid, arid, and hyper-arid zones and the common drought indices of SPI and RDIe within a timescale of 3, 6, and 12 months were calculated to compare the results obtained from the TSDI by using the meteorological data of 105 synoptic stations. Based on the results, the study area experienced a drought with extreme severity and expansion during 2007–2008. The drought spatial distribution map obtained from three indices indicated good conformity. Based on the maps, the severity, duration, and frequency of drought in the semi-arid zone were greater than that in other zones, while no significant drought occurred in the hyper-arid zone. Furthermore, the temporal distribution of drought in all three zones indicated that the TSDI could detect all short- and long-term droughts. The study results showed that the TSDI is a reliable, integrated, and comprehensive index. Using this index in arid areas with little field data led to some valuable results for planning and water resource management.

Drought Assessment using GRACE Terrestrial Water Storage Deficit in Mongolia from 2002 to 2017

Climate warming can result in increases in the frequency and magnitude of drought events, leading to water shortages and socioeconomic losses. Gravity Recovery and Climate Experiment (GRACE) satellite data have been used to monitor and estimate drought events. However, there is little information on detecting the characteristics of droughts in Mongolia due to sparse observations. In this study, we estimate the drought conditions in Mongolia using GRACE terrestrial water storage data during 2002–2017. Water storage deficit (WSD) is used to identify the drought event and calculate the water storage deficit index (WSDI). The WSDI was compared with the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). The results showed that there were two turning points of WSD in 2007 and 2012. Eight drought events were identified and the most severe drought occurred in 2007–2009 lasting for 38 months with a WSDI of −0.98 and a total WSD of −290.8 mm. Overall, the WSD and WSDI were effective in analyzing and assessing the drought severity in a region where hydrological observations are lacking.

Hydro-climatic changes and their impacts on vegetation in Xinjiang, Central Asia

Central Asia is one of the most arid regions in the world. Xinjiang is the core area of the arid region in Central Asia. Climate warming and hydrological changes might affect the vegetation dynamics in the region; however there has been no systematic evaluation of the hydro-climatic changes and their impacts on vegetation in Xinjiang. In this study, the vegetation growth and its response to hydro-climatic changes from 2003 to 2013 were analyzed based on multiple satellite observations. It was found that precipitation increased, with fluctuations, at a rate of 12.07 mm/decade, and evapotranspiration decreased, also with fluctuations, at a rate of -14.79 mm/decade. The change in total water storage, derived from the Gravity Recovery and Climate Experiment satellite, displayed an increasing trend, with a rate of increase of 112.91 mm/decade. The changes in the Global Land Data Assimilation System-derived soil moisture and groundwater estimated by the water budget presented a slight increasing trend from 2003 to 2013. The total water storage, soil moisture, and groundwater all significantly increased after 2008, and the increases in soil moisture and groundwater had positive effects on the increasing total water storage in Xinjiang. There were more obvious time lags in the response of changes in total water storage to precipitation than for the changes in soil moisture. The changes in the normalized difference vegetation index from 2003 to 2013 indicated a slight greening, and the accumulated normalized difference vegetation index anomalies also increased sharply after 2008. There were significant increases in the Tianshan Mountains, Altay Mountains, and around the Tarim Basin, especially along the Tarim River. The results suggested that the changes in total water storage and soil moisture were regarded as better indicators of the vegetation dynamics than other hydro-climatic variables in Xinjiang. Climate warming has led to accelerated glacier shrinkage and snow melt, and the increased runoff is likely to lead to more infiltration of surface water into the soil and ground, resulting in increased total water storage.

Identification of Drought Events and Correlations with Large-Scale Ocean–Atmospheric Patterns of Variability: A Case Study in Xinjiang, China

This research analyzed the spatiotemporal patterns of drought in Xinjiang (northwestern China) between 1961 and 2015 using the standardized precipitation evapotranspiration index (SPEI). Furthermore, the correlations between Atlantic Multidecadal Oscillation (AMO)/El Niño–Southern Oscillation (ENSO) events and drought were explored. The results suggested an obvious trend toward aggravated drought, with a significant inflection point in 1997, after which the frequency of drought increased sharply. Spatially, the increase in drought occurred largely in southern and eastern Xinjiang, where occurrences of moderate and extreme drought have become more frequent during the last two decades, whereas northwestern Xinjiang and the Pamir Plateau showed wetting trends. Empirical orthogonal function analysis (EOF) of drought patterns showed a north–south antiphase and an east–west antiphase distribution. The positive (negative) phase of the AMO was related to increased (decreased) drought in Xinjiang, particularly after 1997. During a warm phase (El Niño), major droughts occurred over northern Xinjiang, but they lagged by 12 months. However, not all El Niño and La Niña events were responsible for drought events in northern Xinjiang during this period, and other drivers remain to be identified. This study suggests the possibility of AMO and ENSO links to drought in Xinjiang, but further analysis is needed to better understand such mechanisms.

Detection of hydrological variations and their impacts on vegetation from multiple satellite observations in the Three-River Source Region of the Tibetan Plateau

The Three-River Source Region (TRSR) of the Tibetan Plateau (TP) is regarded as the "Chinese water tower". Climate warming and the associated degradation of permafrost might change the water cycle and affect the alpine vegetation growth in the TRSR. However, the quantitative changes in the water budget and their impacts on the vegetation in the TRSR are poorly understood. In this study, the spatial-temporal changes in the hydrological variables and the normalized difference vegetation index (NDVI) during 2003-2014 were investigated using multiple satellite data and a remote sensing energy balance model. The results indicated that precipitation showed an increasing trend at a rate of 14.0 mm 10 a^-1, and evapotranspiration (ET) showed a slight decreasing trend. The GRACE-derived total water storage (TWS) change presented a significant increasing trend at a rate of 35.1 mm a^-1. The change in groundwater (GW) which showed an increasing trend at a rate of 18.5 mm a^-1, was estimated by water budget. The time lag of the GRACE-TWS that was influenced by precipitation was more obviously than was the GLDAS-SM (Soil Moisture) change. The vegetation in the TRSR was greening during the study period, and the accumulation of the NDVI increased rapidly after 2008. The effect of total TWS and GLDAS-SM on vegetation was considerably more than that the effects of other factors in this region. It was concluded that the hydrological cycle had obviously changed and that more soil water was transferred into the GW since the aquiclude changed due to climate warming. The increasing area and number of lakes and the thickening of the active layer in the permafrost area led to the greater infiltration of surface water into the groundwater, which resulted in increased water storage.

Understanding linkages between global climate indices and terrestrial water storage changes over Africa using GRACE products

Africa, a continent endowed with huge water resources that sustain its agricultural activities is increasingly coming under threat from impacts of climate extremes (droughts and floods), which puts the very precious water resource into jeopardy. Understanding the relationship between climate variability and water storage over the continent, therefore, is paramount in order to inform future water management strategies. This study employs Gravity Recovery And Climate Experiment (GRACE) satellite data and the higher order (fourth order cumulant) statistical independent component analysis (ICA) method to study the relationship between terrestrial water storage (TWS) changes and five global climate-teleconnection indices; El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Madden-Julian Oscillation (MJO), Quasi-Biennial Oscillation (QBO) and the Indian Ocean Dipole (IOD) over Africa for the period 2003-2014. Pearson correlation analysis is applied to extract the connections between these climate indices (CIs) and TWS, from which some known strong CI-rainfall relationships (e.g., over equatorial eastern Africa) are found. Results indicate unique linear-relationships and regions that exhibit strong linkages between CIs and TWS. Moreover, unique regions having strong CI-TWS connections that are completely different from the typical ENSO-rainfall connections over eastern and southern Africa are also identified. Furthermore, the results indicate that the first dominant independent components (IC) of the CIs are linked to NAO, and are characterized by significant reductions of TWS over southern Africa. The second dominant ICs are associated with IOD and are characterized by significant increases in TWS over equatorial eastern Africa, while the combined ENSO and MJO are apparently linked to the third ICs, which are also associated with significant increase in TWS changes over both southern Africa, as well as equatorial eastern Africa.

Retrieving Groundwater Depletion and Drought in the Tigris-Euphrates Basin Between 2003 and 2015

Quantitative estimates of the groundwater depletion and droughts in the Tigris-Euphrates Basin (TEB) can be useful for sustainably managing its water resources. Here, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to infer the monthly changes in the total water storage of the TEB from January 2003 to December 2015. Additionally, the data of altimetry and output from land surface models are used to remove the contributions from lake water changes and other hydrological factors to obtain the total groundwater depletion (TGWD), human-driven groundwater depletion (HGWD), and climate-driven groundwater depletion. We conclude that an alarming rate of decrease in the total water storage and the loss of TGWD have an "accelerating" trend, as the trend during 2007 to 2015 was 3.6 times that during 2003 to 2006. Moreover, the HGWD is 116.09 Gt, which accounts for 98% of the TGWD. Finally, the total storage deficit index (TSDI) is derived from the GRACE data to characterize the drought of the TEB. The results show that TSDI agrees well with the actual drought rather than the Palmer drought severity index (PDSI) and that the TEB has been undergoing a severe drought since September 2007 according to both the TSDI and PDSI. The research in this study provides an effective and unique method for understanding the hydrological processes and sustainable use of water resources in regions or countries with little data, which is essential for more efficient, sustainable, and cross-boundary cooperative water resource management.

Drought evaluation using the GRACE terrestrial water storage deficit over the Yangtze River Basin, China

Droughts are some of the worst natural disasters that bring significant water shortages, economic losses, and adverse social consequences. Gravity Recovery and Climate Experiment (GRACE) satellite data are widely used to characterize and evaluate droughts. In this work, we evaluate drought situations in the Yangtze River Basin (YRB) using the GRACE Texas Center for Space Research (CSR) mascon (mass concentration) data from 2003 to 2015. Drought events are identified by water storage deficits (WSDs) derived from GRACE data, while the drought severity evaluation is based on the water storage deficit index (WSDI), standardized WSD time series, and total water storage deficit (TWSD). The WSDI is subsequently compared with the Palmer drought severity index (PDSI), standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and standardized runoff index (SRI). The results indicate the YRB experienced increased wetness during the study period, with WSD values increasing at a rate of 5.20mm/year. Eight drought events are identified, and three major droughts occurred in 2004, 2006, and 2011, with WSDIs of -2.05, -2.38, and -1.30 and TWSDs of -620.96mm, -616.81mm, and -192.44mm, respectively. Our findings suggest that GRACE CSR mascon data can be used effectively to assess drought features in the YRB and that the WSDI facilitates robust and reliable characterization of droughts over large-scale areas.

Drought and Flood Monitoring of the Liao River Basin in Northeast China Using Extended GRACE Data

In recent years, alternating periods of floods and droughts, possibly related to climate change and/or human activity, have occurred in the Liao River Basin of China. To monitor and gain a deep understanding of the frequency and severity of the hydro-meteorological extreme events in the Liao River Basin in the past 30 years, the total storage deficit index (TSDI) is established by the Gravity Recovery and Climate Experiment (GRACE)-based terrestrial water storage anomalies (TWSAs) and the general regression neural network (GRNN)-predicted TWSA. Results indicate that the GRNN model trained with GRACE-based TWSA, model-simulated soil moisture, and precipitation observations was optimal, and the correlation coefficient and the root mean square error (RMSE) of the predicted TWSA and GRACE TWSA for the testing period equal 0.90 and 18 mm, respectively. The drought and flood conditions monitored by the TSDI were consistent with those of previous studies and records. The extreme climate events could indirectly reflect the status of the regional hydrological cycle. By monitoring the extreme climate events in the study area with TSDI, which was based on the TWSA of GRACE and GRNN, the decision of water resource management in the Liao River Basin could be made reasonably.

Spatial-temporal variation and impacts of drought in Xinjiang (Northwest China) during 1961-2015

Observations indicate that temperature and precipitation patterns changed dramatically in Xinjiang, northwestern China, between 1961 and 2015. Dramatic changes in climatic conditions can bring about adverse effects. Specifically, meteorological drought severity based on the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI) showed a decreasing trend in Xinjiang prior to 1997, after which the trend reversed. SPEI-based drought severity shows a much stronger change during 1997-2015 than the SPI, which is independent of the effect of evaporative demand. Meteorological drought severity has been aggravated by a significant rise in temperature (1.1 °C) over the last two decades that has not been accompanied by a corresponding increase in precipitation. As a result, the evaporative demand in Xinjiang has risen. An examination of a large spatio-temporal extent has made the aggravated drought conditions more evident. Our results indicate that increased meteorological drought severity has had a direct effect on the normalized difference vegetation index (NDVI) and river discharge. The NDVI exhibited a significant decrease during the period 1998-2013 compared to 1982-1997, a decrease that was found to be caused by increased soil moisture loss. A positive relationship was recorded between evaporative demand and the runoff coefficients of the 68 inland river catchments in northwestern China. In the future, meteorological drought severity will likely increase in arid and semiarid regions as global warming continues.

Hydrogeological characterisation of groundwater over Brazil using remotely sensed and model products

For Brazil, a country frequented by droughts and whose rural inhabitants largely depend on groundwater, reliance on isotope for its monitoring, though accurate, is expensive and limited in spatial coverage. We exploit total water storage (TWS) derived from Gravity Recovery and Climate Experiment (GRACE) satellites to analyse spatial-temporal groundwater changes in relation to geological characteristics. Large-scale groundwater changes are estimated using GRACE-derived TWS and altimetry observations in addition to GLDAS and WGHM model outputs. Additionally, TRMM precipitation data are used to infer impacts of climate variability on groundwater fluctuations. The results indicate that climate variability mainly controls groundwater change trends while geological properties control change rates, spatial distribution, and storage capacity. Granular rocks in the Amazon and Guarani aquifers are found to influence larger storage capability, higher permeability (>10^-4 m/s) and faster response to rainfall (1 to 3months' lag) compared to fractured rocks (permeability <10^-7 m/s and lags > 3months) found only in Bambui aquifer. Groundwater in the Amazon region is found to rely not only on precipitation but also on inflow from other regions. Areas beyond the northern and southern Amazon basin depict a 'dam-like' pattern, with high inflow and slow outflow rates (recharge slope > 0.75, discharge slope < 0.45). This is due to two impermeable rock layer-like 'walls' (permeability <10^-8 m/s) along the northern and southern Alter do Chão aquifer that help retain groundwater. The largest groundwater storage capacity in Brazil is the Amazon aquifer (with annual amplitudes of > 30cm). Amazon's groundwater declined between 2002 and 2008 due to below normal precipitation (wet seasons lasted for about 36 to 47% of the time). The Guarani aquifer and adjacent coastline areas rank second in terms of storage capacity, while the northeast and southeast coastal regions indicate the smallest storage capacity due to lack of rainfall (annual average is rainfall <10cm).