Understanding the global hydrological droughts of 2003-2016 and their relationships with teleconnections

Space-based natural and human-induced water storage change quantification

Understanding water availability and its response to climate change and water extraction is crucial for sustainable water management in Australia's Murray-Darling Basin. This study introduces a space-based method that quantifies the natural and human-induced impact on changes in terrestrial water storage. It reveals an impact of 17% due to water extraction for irrigation over the past two decades, with 84% of this extraction coming from surface water and 16% from groundwater. The human-induced impact varies spatially with higher values in the southern Murray (up to 5.6%) and smaller values in the northern Darling (down to 0.2%). Data-model fusion of the satellite-based water storage changes into a hydrological model, which does not simulate water extraction, man-made reservoirs and wetlands, improved the representation of water storage variability and intensified trends in drying and wetting periods. This study adds valuable findings to better understand natural and human-induced impacts on the regional water resources under changing climate and to better represent these impacts (80% and 20% respectively) within hydrological models after data-model fusion.

Global terrestrial drought and its projected socioeconomic implications under different warming targets

Droughts are increasingly frequent as the Earth warms, presenting adaptation challenges for ecosystems and human communities worldwide. A strategic environmental assessment (SEA) and the integration of adaptation strategies into policies, plans, and programs (PPP) are two important approaches for enhancing climate resilience and fostering sustainable development. This study developed an innovative approach to strengthen the SEA of droughts by quantifying the impacts of future temperature increases. A novel method for projecting drought events was integrated into the SEA process by leveraging multiple data sources, including atmospheric reanalysis, reconstructions, satellite-based observations, and model simulations. We identified drought conditions using terrestrial water storage (TWS) anomalies and applied a random forest (RF) model for disentangling the drivers behind drought events. We then set two global warming targets (2.0 °C and 2.5 °C) and analyzed drought changes under three shared socioeconomic pathways (SSP126, SSP370, SSP585). In a 2.0 °C warming world, over 50 % of the global surface will face increased drought risk. With an additional 0.5 °C increase, >60 % of the land will be prone to further drought escalation. We utilized copulas to build the joint distribution for drought duration and severity, estimating the joint return periods (JRP) for bivariate drought hazard. In tropical and subtropical regions, JRP reductions exceeding half are projected for >33 % of the regional land surface under 2.0 °C warming and for >50 % under 2.5 °C warming. Finally, we projected the impacts of drought events on population and gross domestic product (GDP). Among the three SSPs, under SSP370, population exposure is highest and GDP exposure is minimal under 2.0 °C warming. Global GDP and population risks from drought are projected to increase by 37 % and 24 %, respectively, as warming continues. This study enhances the accuracy of SEA in addressing drought risks and vulnerabilities, supporting climate-resilient planning and adaptive strategies.

Global groundwater droughts are more severe than they appear in hydrological models: An investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model

Realistic representation of hydrological drought events is increasingly important in world facing decreased freshwater availability. Index-based drought monitoring systems are often adopted to represent the evolution and distribution of hydrological droughts, which mainly rely on hydrological model simulations to compute these indices. Recent studies, however, indicate that model derived water storage estimates might have difficulties in adequately representing reality. Here, a novel Markov Chain Monte Carlo - Data Assimilation (MCMC-DA) approach is implemented to merge global Terrestrial Water Storage (TWS) changes from the Gravity Recovery And Climate Experiment (GRACE) and its Follow On mission (GRACE-FO) with the water storage estimations derived from the W3RA water balance model. The modified MCMC-DA derived summation of deep-rooted soil and groundwater storage estimates is then used to compute 0.5∘ standardized groundwater drought indices globally to show the impact of GRACE/GRACE-FO DA on a global index-based hydrological drought monitoring system. Our numerical assessment covers the period of 2003-2021, and shows that integrating GRACE/GRACE-FO data modifies the seasonality and inter-annual trends of water storage estimations. Considerable increases in the length and severity of extreme droughts are found in basins that exhibited multi-year water storage fluctuations and those affected by climate teleconnections.

Global vegetation, moisture, thermal and climate interactions intensify compound extreme events

Compound extreme events, encompassing drought, vegetation stress, wildfire severity, and heatwave intensity (CDVWHS), pose significant threats to societal, environmental, and health systems. Understanding the intricate relationships governing CDVWHS evolution and their interaction with climate teleconnections is crucial for effective climate adaptation strategies. This study leverages remote sensing, reanalysis data, and climate models to analyze CDVWHS during historical (1982-2014), near-future (2028-2060), and far-future (2068-2100) periods under two Shared Socioeconomic Pathways (SSP; 245 and 585). Our results show that reduced vegetation health, unfavorable temperature conditions, and low moisture conditions have negligible effects on vegetation density. However, they worsen the intensity of heatwaves and increase the risk of wildfires. Wildfires can persist when thermal conditions are poor despite favorable moisture levels. For example, despite adequate moisture availability, we link the 2012 Siberian wildfire in the Ob basin to anomalous negative thermal conditions and concurrent unfavorable thermal-moisture conditions. In contrast, the Amazon experiences extreme and exceptional drought associated with unfavorable moisture conditions in the same year. A comparative analysis of Siberian and North American fires reveals distinct burned area anomalies due to variations in vegetation density and wildfire fuel. The North American fires have lower positive anomalies in burned areas because of negative anomalous vegetation density, which reduced the amount of wildfire fuel. Furthermore, we examine basin-specific variability in climate teleconnections related to compound CDVWHS, revealing the primary modes of variability and evolution of CDVWHS through climate teleconnection patterns. Moreover, a substantial increase in the magnitude of heatwave severity emerges between the near and far future under SSP 585. This study underscores the urgency for targeted actions to enhance ecosystem resilience and safeguard vulnerable communities from CDVWHS impacts. Identifying CDVWHS hotspots and comprehending their complex relationships with environmental factors are essential for developing effective adaptation strategies in a changing climate.

Spatiotemporal distribution of groundwater drought using GRACE-based satellite estimates: a case study of Lower Gangetic Basin, India

Droughts frequently occurring in India have significant societal, economic, and environmental effects. The lack of direct measurements of groundwater in location and time hinders quantitative methods to analyse the intricate nature of groundwater drought. This work used the datasets derived from the Gravity and Climate Experiment (GRACE and GRACE-FO) and Global Land Data Assimilation System (GLDAS) to extensively analyse Groundwater Storage changes in the Lower Gangetic Basin (LGB) using unique hydrological parameters between the years 2003 and 2022. The analysis highlights that the GRACE-derived terrestrial water storage anomaly in the LGB decreased significantly (-12.12 mm/yr), and the amount of Groundwater Storage Anomaly (GWSA) decreased similarly (-10.80 mm/yr), while in the GRACE-FO period, a positive trend has been noticed in TWSA (33.96 mm/yr) and GWSA (64.8 mm/yr) respectively. A drought indicator called the GRACE-derived groundwater drought index (GGDI) has been computed for the entire LGB region. A traditional drought study viz. Standardised Precipitation Index (SPI) was performed over LGB to justify the results of the GGDI. The results from GGDI study effectively matched the periods of significant drought occurrences with the 12-month SPI time series. From the GGDI, this study examined groundwater drought's spatial distribution, temporal evolution, and trend (Modified Mann Kendall trend) aspects. According to research findings, the LGB experienced three major drought periods between 2009-2010, 2019 (moderate), and 2015-2016 (severe). The study offers reliable quantitative data on the evolution of GRACE-derived groundwater drought, which may add a new perspective to additional drought research in the densely populated study area, which depends majorly on agriculture, livestock and less skilled water-intensive industries such as leather and textile industries in a sub-tropical climate. This paradigm incorporates changes in groundwater resources caused by human activities and climate change, paving the way for measuring progress towards sustainable use and water security.

GRACE-based groundwater drought in the Indochina Peninsula during 1979-2020: Changing properties and possible teleconnection mechanisms

Groundwater is very important for human productivity and daily life, hydrological cycle regulation, and ecosystem stability. However, due to the complex mechanisms of groundwater drought, the spatial and temporal variations of groundwater drought and its driving mechanisms are still not fully understood, especially in Indochina Peninsula. In this work, we used a reconstructed long-term terrestrial water storage dataset from the Gravity Recovery and Climate Experiment (GRACE) emission and a GRACE-based groundwater drought index to investigate the spatial and temporal characteristics of groundwater drought during 1979-2020 in the Indochina Peninsula. The possible teleconnection mechanisms between groundwater drought and the Indian Ocean Dipole (IOD), El Niño-Southern Oscillation (ENSO), and El Niño Modoki (ENSO_M) were also investigated using cross wavelet transform method. The results show that groundwater drought worsens significantly during 1979-2020, and becomes much more frequent and intensified after 2000 in the southern Indochina Peninsula. Both univariate and bivariate (logic 'or' and 'and') return periods for duration, severity, and peak of groundwater drought are short in the southern Indochina Peninsula, and thus the risk of groundwater drought is high. The IOD, ENSO, and ENSO_M can reduce the intensity of groundwater drought to a certain extent during the warm phases, but only ENSO_M tends to significantly exacerbate the intensity of groundwater drought during the cold phases in the southern Indochina Peninsula. The variations in groundwater drought are dominated by ENSO_M, and are also coupled influenced by the IOD and ENSO in the southern Indochina Peninsula. The results provide valuable information for the sustainable ecological environment and socioeconomic development, especially development of groundwater drought early warning and prediction models in the Indochina Peninsula.

Precipitation and vegetation transpiration variations dominate the dynamics of agricultural drought characteristics in China

Agricultural drought posing a significant threat to agricultural production is subject to the complex influence of ocean, terrestrial and meteorological multi-factors. Nevertheless, which factor dominating the dynamics of agricultural drought characteristics and their dynamic impact remain equivocal. To address this knowledge gap, we used ERA5 soil moisture to calculate the standardized soil moisture index (SSI) to characterize agricultural drought. The extreme gradient boosting model was then adopted to fully examine the influence of ocean, terrestrial and meteorological multi-factors on agricultural drought characteristics and their dynamics in China. Meanwhile, the Shapley additive explanation values were introduced to quantify the contribution of multiple drivers to drought characteristics. Our analysis reveals that the drought frequency, severity and duration in China ranged from 5-70, 2.15-35.02 and 1.76-31.20, respectively. Drought duration is increasing and drought intensity is intensifying in southeast, north and northwest China. In addition, potential evapotranspiration is the most significant driver of drought characteristics at the basin scale. Regarding the dynamic evolution of drought characteristics, the percentages of raster points for drought duration and severity with evapotranspiration as the dominant factor are 30.7 % and 32.7 %, and the percentages with precipitation are 35.3 % and 35.0 %, respectively. Precipitation in northern regions has a positive effect on decreasing drought characteristics, while in southern regions, evapotranspiration dominates the dynamics in drought characteristics due to increasing vegetation transpiration. Moreover, the drought severity is exacerbated by the Atlantic Multidecadal Oscillation in the Yangtze and Pearl River basins, while the contribution of the North Atlantic Oscillation to the drought duration evolution is increasing in the Yangtze River basin. Generally, this study sheds new insights into agricultural drought evolution and driving mechanism, which are beneficial for agricultural drought early warning and mitigation.

A review of recent developments on drought characterization, propagation, and influential factors

Droughts have impacted human society throughout its history. However, the occurrence of severe drought events in the last century and the concerns on the potential effects of climate change have prompted remarkable advances in drought conceptualization and modeling in recent years. This review intends to present the state-of-the-art on drought characterization and propagation, as well as providing insights on how climate dynamics and anthropogenic activities might affect this phenomenon. For this purpose, we first address the distinct concepts of droughts and their relationships. Next, we present two frequently utilized methods based on the run theory for drought characterization and explain the development and recovery stages of droughts. Then, we discuss potential drivers for drought occurrence and propagation, with focus on meteorological factors, catchments' physical characteristics and human activities. Later, we describe how droughts can affect several parameters of water quality. This review also addressed flash droughts, encompassing their definitions, commonly used indices, and potential drivers. Finally, we briefly address the roles of climate change and long-term persistence on future drought scenarios. This review may be useful for researchers and stakeholders for attaining a broader understanding on drought dynamics and impacts.

Dynamic variations of terrestrial ecological drought and propagation analysis with meteorological drought across the mainland China

Ecological drought is a complex comprehensive process in which the water conditions for normal growth and development of vegetation are changed due to insufficient water supply. In this study, based on the remotely sensed vegetation health index (VHI) and the Famine Early Warning Systems Network Land Data Assimilation System (FLDAS) datasets from 1982 to 2020 in China, the Breaks For Additive Seasons and Trend algorithm (BFAST) was used to analyze the dynamic variations of ecological drought, the standardized regression coefficient method was applied to identify the primary drivers of ecological drought, and the regression analysis was adopted to reveal the coupling effect of atmospheric circulation factors on ecological drought. The results indicated that: (1) the ecological drought showed an overall decreasing trend during 1982-2020 in China, with a negative mutation point that occurred in April 1985; (2) spring drought and summer drought were more likely to occur in the South China, and autumn drought and winter drought were more likely to appear in the Sichuan Basin; (3) the propagation time from meteorological to ecological drought was shorter in summer (2.67 months) and longer in winter (7 months), with average r values of 0.76 and 0.53, respectively; (4) the Trans Polar Index (TPI), Arctic Oscillation (AO) and El Niño-Southern Oscillation (ENSO) had important impacts on ecological drought, which can be used as input factors of drought early warning system to improve the accuracy of drought prediction.

Multivariate analysis compares and evaluates drought and flooding tolerances of maize germplasm

Drought and flooding are the two most important environmental factors limiting maize (Zea mays L.) production globally. This study aimed to investigate the physiological mechanisms and accurate evaluation indicators and methods of maize germplasm involved in drought and flooding stresses. The twice replicated pot experiments with 60 varieties, combined with the field validation experiment with 3 varieties, were conducted under well-watered, drought, and flooding conditions. Most varieties exhibited stronger tolerance to drought than flooding due to higher antioxidant enzyme activities, osmotic adjustment substances, and lower reactive oxygen species. In contrast, flooding stress resulted in higher levels of reactive oxygen species (particularly O2-), ascorbate peroxidase, catalase, peroxidase, and soluble sugars but lower levels of superoxide dismutase, proline, and soluble protein compared with well-watered conditions. Superoxide dismutase, peroxidase, catalase, ascorbate peroxidase, proline, soluble sugars, and protein contents, in addition to plant height, leaf area/plant, and stem diameter, were accurate and representative indicators for evaluating maize tolerance to drought and flooding stresses and could determine a relatively high mean forecast accuracy of 100.0% for the comprehensive evaluation value. A total of 4 principal components were extracted, in which different principal components played a vital role in resisting different water stresses. Finally, the accuracy of the 3 varieties screened by multivariate analysis was verified in the field. This study provides insights into the different physiological mechanisms and accurate evaluation methods of maize germplasm involved in drought and flooding stresses, which could be valuable for further research and breeding.

Modeling, challenges, and strategies for understanding impacts of climate extremes (droughts and floods) on water quality in Asia: A review

The increasing frequency and intensity of extreme climate events are among the most expected and recognized consequences of climate change. Prediction of water quality parameters becomes more challenging with these extremes since water quality is strongly related to hydro-meteorological conditions and is particularly sensitive to climate change. The evidence linking the influence of hydro-meteorological factors on water quality provides insights into future climatic extremes. Despite recent breakthroughs in water quality modeling and evaluations of climate change's impact on water quality, climate extreme informed water quality modeling methodologies remain restricted. This review aims to summarize the causal mechanisms across climate extremes considering water quality parameters and Asian water quality modeling methods associated with climate extremes, such as floods and droughts. In this review, we (1) identify current scientific approaches to water quality modeling and prediction in the context of flood and drought assessment, (2) discuss the challenges and impediments, and (3) propose potential solutions to these challenges to improve understanding of the impact of climate extremes on water quality and mitigate their negative impacts. This study emphasizes that one crucial step toward enhancing our aquatic ecosystems is by comprehending the connections between climate extreme events and water quality through collective efforts. The connections between the climate indices and water quality indicators were demonstrated to better understand the link between climate extremes and water quality for a selected watershed basin.

Global analysis of the correlation and propagation among meteorological, agricultural, surface water, and groundwater droughts

Groundwater drought monitoring relies on ground observation data, which cannot be used to reflect large-scale droughts in groundwater resources. The Gravity Recovery and Climate Experiment Satellite (GRACE) improved the situation and provided a new solution for groundwater drought research. However, the propagation relationship among global different drought types has not been fully explored. We employed CRU precipitation data, MERR2 reanalysis soil moisture data, GLDAS and GRACE data to calculate SPI (Standardized precipitation index), SSI (Standardized soil moisture index), SRI (Standardized runoff index), and GDI (Groundwater drought index), characterizing meteorological, agricultural, surface water and groundwater droughts, respectively. The Pearson correlation coefficient was adopted to study the propagation time of these four types of droughts. The results showed that the average propagation times for the different drought types are meteorological drought to surface water drought (3.5 months), meteorological drought to agricultural drought (5.7 months), agricultural drought to groundwater drought (12.97 months), surface water drought to groundwater drought (13.78 months), and meteorological drought to groundwater drought (14.47 months) from longest to shortest. (2) Climate conditions had a significant impact on the propagation time of different drought types. Low temperatures in cold climates resulted in the longest drought propagation time, while dry summer climates in temperate climates reduced drought propagation time. There were weaker propagation relationships in arid climates. In tropical climates, precipitation may not be the main driving factor for drought propagation. (3) Different land cover types show significant differences in the propagation of groundwater droughts, with forests having a longer propagation time from meteorological drought to agricultural drought or surface water drought than grassland and cropland, and forests having the shortest propagation time when meteorological drought, agricultural drought, and surface water drought is propagated to groundwater drought. Woody plants have deeper root systems than herbaceous plants and can draw up deeper groundwater. Forests have greater water storage capacity and weaker groundwater recharge than grasslands and croplands, resulting in forests being more resistant to agricultural and surface water droughts and less resistant to groundwater droughts during meteorological droughts. This study can help to clarify the propagation laws among different drought types and understand the internal mechanisms that affect the development of drought during the water cycle.

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.

Hydrological drought impacts on water storage variations: a focus on the role of vegetation changes in the East Africa region. A systematic review

Drought is one of the most challenging climatic events. Recently, the drought influence in East Africa (EA) total water storage (TWS) is a serious problem, particularly in arid areas with modified natural vegetation relying on water deficit, garnered extensive research interest. Hydro-climatological and vegetation indices and remote sensing datasets derived from Gravity Recovery Climate Experiment (GRACE) mission datasets reveal good performance in analyzing hydrological drought influences in water storage. Over the last decades, studies were considered successful in monitoring the drought influence in the region TWS potential. However, several challenges remained unsolved, hindering the hydrological drought mitigation strategies. This review deals with an overview of drought impact monitoring targeted at the TWS variation with the response of vegetation change for sustainable drought mitigation. To improve the flexibility and adaptive capacities of the water deficit problem, we aim to provide an overview of drought impacts on TWS in the region to redefine the hydro-climatological and vegetation drought indices and improve the understanding of drought impact through remote sensing datasets. This review presents the challenges and prospects and offers a conclusion. Although, we hope that the review can facilitate further study regarding future hydrological drought projection in the development of several scientific research in the field.

The Influence of Climate Change on Droughts and Floods in the Yangtze River Basin from 2003 to 2020

In recent decades, extreme floods and droughts have occurred frequently around the world, which seriously threatens the social and economic development and the safety of people's lives and properties. Therefore, it is of great scientific significance to discuss the causes and characteristic quantization of extreme floods and droughts. Here, the terrestrial water storage change (TWSC) derived from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) data was used to characterize the floods and droughts in the Yangtze River basin (YRB) during 2003 and 2020. To reduce the uncertainty of TWSC results, the generalized three-cornered hat and least square methods were used to fuse TWSC results from six GRACE solutions. Then combining precipitation (PPT), evapotranspiration, soil moisture (SM), runoff, and extreme climate index data, the influence of climate change on floods and droughts in the YRB was discussed and analyzed. The results show that the fused method can effectively improve the uncertainty of TWSC results. And seven droughts and seven floods occurred in the upper of YRB (UY) and nine droughts and six floods appeared in the middle and lower of YRB (MLY) during the study period. The correlation between TWSC and PPT (0.33) is the strongest in the UY, and the response time between the two is 1 month, while TWSC and SM (0.67) are strongly correlated with no delay in the MLY. The reason for this difference is mainly due to the large-scale hydropower development in the UY. Floods and droughts in the UY and MLY are more influenced by the El Niño-Southern Oscillation (ENSO) (correlation coefficients are 0.39 and 0.50, respectively) than the Indian Ocean Dipole (IOD) (correlation coefficients are 0.19 and 0.09, respectively). The IOD event is usually accompanied by the ENSO event (the probability is 80%), and the hydrological hazards caused by independent ENSO events are less severe than those caused by these two extreme climate events in the YRB. Our results provide a reference for the study on the formation, development, and recovery mechanism of regional floods and droughts on a global scale.

Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors

Drought is a costly natural hazard with far-reaching impacts on agriculture, ecosystem, water supply, and socio-economy. While propagating through the water cycle, drought evolves into different types and affects the natural system and human society. Despite much progress made in recent decades, a synthesis of the characteristics, approaches, processes, and controlling factors of drought propagation is still lacking. We bridge this gap by reviewing the recent progress of drought propagation and discussing challenges and future directions. We first introduce drought propagation characteristics (e.g., response time scale, lag time), followed by different approaches, including statistical analysis and hydrological modeling. The recent progress in the propagation from meteorological drought to different types of drought (agricultural drought, hydrological drought, and ecological drought) is then synthesized, including the basic process, commonly used indicators, data sources, and main findings of drought propagation characteristics. Different controlling factors of drought propagations, including climate (e.g., aridity, seasonality, and anomalies of meteorological variables), catchment properties (e.g., slope, elevation, land cover, aquifer, baseflow), and human activities (e.g., reservoir operation and water diversion, irrigation, and groundwater abstraction), are then summarized. Challenges in drought propagation include the discrepancy in drought indicators (and approaches) and difficulty in characterizing the full propagation process and isolating influencing factors. Future analysis of drought propagation should shift from single indicators to multiple indicators, from individual drivers to combined drivers, from uni-directional analysis to feedbacks, from hazards to impacts, and from stationary to nonstationary assumptions. This review is expected to be useful for drought prediction and management across different regions under global warming.

Bridging the gap between GRACE and GRACE-FO using a hydrological model

Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO), two successive satellite-based missions starting in 2002, have provided an unprecedented way of measuring global terrestrial water storage anomalies (TWSA). However, a temporal gap exists between GRACE and GRACE-FO products from July 2017 to May 2018, which introduces bias and uncertainties in TWSA calculations and modeling. Previous studies have incorporated hydroclimatic factors as predictors for filling the gap, but most of them utilized artificial intelligence or pure statistical models that generally de-trended TWSA and had no physical foundation. Thus, a physically-based reconstruction is required for increasing robustness. In this study, we bridge the temporal gap by developing an empirical hydrological model. The "abcd" model, a T-based snow component, and linear correction are utilized to represent runoff generation, snow dynamics, and long-term trends. The testing results indicate that our hydrological model can successfully reconstruct TWSA in tropical, temperature, and continental climates, although further improvement is needed for arid climates. Our reconstruction for the gap achieves high accuracy and robustness as shown by the evaluations against sea-level budget and GLDAS-derived TWSA. Compared to previous studies using artificial intelligence or statistical techniques, our hydrological model performs similarly in the gap filling but does not involve de-trended or de-seasonalized transformations, which will facilitate the combination of GRACE and GRACE-FO products and improve the physical understanding of global TWSA.

Spatial–Temporal Patterns and Propagation Dynamics of Ecological Drought in the North China Plain

With the increasingly prominent ecological environmental problems, the ecological drought phenomenon will become the focus of drought research. The spatial–temporal pattern of ecological drought and its complicated propagation dynamics are still unclear in the North China Plain (NCP). In this study, the spatio–temporal patterns and gridded trend characteristics of ecological drought were investigated from 1999 to 2019 in the NCP. Subsequently, the propagation dynamics from meteorological to ecological drought were identified for the study period. The results indicated that: (1) the ecological drought showed a downward trend from 1999 to 2019 in the NCP, with a 4.2-year and 7-year period on the inter-annual scale; (2) the most serious ecological drought occurred in the year of 2002, with an average monthly vegetation condition index (VCI) ranging from 0.17 (in December) to 0.59 (in January); (3) ecological droughts were decreasing in each month and season at the grid scale; (4) the propagation time from meteorological to ecological drought was 2.67 months in winter and 1.33 months in summer, which is helpful for predicting the occurrence of ecological drought. This study sheds new viewpoints into the spatial–temporal patterns and propagation dynamics of ecological drought in the NCP, which can also be applied in Northeast China.

New Investigation and Challenge for Spatiotemporal Drought Monitoring Using Bottom-Up Precipitation Dataset (SM2RAIN-ASCAT) and NDVI in Moroccan Arid and Semi-Arid Rangelands

Remotely sensed soil moisture products showed sensitivity to vegetation cover density and soil typology at regional dryland level. In these regions, drought monitoring is significantly performed using soil moisture index and rainfall data. Recently, rainfall and soil moisture observations have increasingly become available. This has hampered scientific progress as regards characterization of land surface processes not just in meteorology. The purpose of this study was to investigate the relationship between a newly developed precipitation dataset, SM2RAIN (Advanced SCATterometer (SM2RAIN-ASCAT), and NDVI (eMODIS-TERRA) in monitoring drought events over diverse rangeland regions of Morocco. Results indicated that the highest polynomial correlation coefficient and the lowest root mean square error (RMSE) between SM2RAIN-ASCAT and NDVI were found in a 10-year period from 2007 to 2017 in all rangelands (R = 0.81; RMSE = 0.05). This relationship was strong for degraded rangeland, where there were strong positive correlation coefficients for NDVI and SM2RAIN (R = 0.99). High correlations were found for sparse and moderate correlations for shrub rangeland (R = 0.82 and 0.61, respectively). The anomalies maps showed a very good similarity between SM2RAIN and Normalized Difference Vegetation Index (NDVI) data. The results revealed that the SM2RAIN-ASCAT and NDVI product could accurately predict drought events in arid and semi-arid rangelands.

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.

What roles can water-stressed vegetation play in agricultural droughts?

Two-way feedbacks exist between water-stressed vegetation and agricultural drought. Previous studies have focused mainly on the responses of vegetation to agricultural droughts but rarely on those of agricultural droughts to vegetation. Based on a new drought index (AgDI) that incorporates dynamic climatic and vegetation information, this study evaluated the impacts of climate and vegetation variabilities on agricultural droughts in 20 catchments in southwestern China, a region frequently hit by droughts. Results showed that the drought-stressed vegetation tended to alleviate agricultural droughts, and the drought-alleviating ability of vegetation was affected by vegetation types and the magnitudes of the changes in climate. Compared to other types of vegetation, the natural forest generally has a greater ability to affect agricultural drought. Overall, the relative contribution (mean of 29.9 ± 24.6%) of changes in vegetation to agricultural drought was at least comparable to those of the changes in potential evapotranspiration (mean of 14.4 ± 12.7%). Results also showed that even though vegetation has the ability to alleviate agricultural droughts, the changes in agricultural droughts were still dominated by climate changes, especially precipitation (mean relative contribution of 55.7 ± 24.2%).

The Pantanal under Siege—On the Origin, Dynamics and Forecast of the Megadrought Severely Affecting the Largest Wetland in the World

The Pantanal is the largest wetland of the world and one of the most important biodiversity hotspots in South America. An unprecedented ongoing megadrought is severely affecting its ecological functioning, flood pulse dynamics, and fire regime. Regarding this problematic, the present study generates reliable information about the following key issues: 1—Evolution and dynamics, 2—Origin and determinants, and 3—Forecast based on identified determinants and current trends. Results show that the evolution of the megadrought has been differentiable in both, space and time. As for its origin and determinants, Climate Change was ratified as one of the most important threats to the Pantanal, and to vast areas of South America, since a strong correlation was identified between megadrought’s dynamics and the occurrence of intense marine heatwaves at Northern Hemisphere oceanic waters, and more specifically, at the Northeast Pacific. Results also show that the megadrought is expected to continue at both the Pantanal and the surrounding Highlands, at least until December 2023. Thus, an intensification of fires risk, extending now to areas historically flooded or perhumid should be expected, concomitantly to a very negative impact on non-fire-resistant vegetation cover, as well as ecosystem functioning and biodiversity, perhaps even worse than those from 2020, widely covered by the international media.

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.

Propagation of meteorological to hydrological drought for different climate regions in China

Drought can lead to considerable agricultural, ecological, and societal damage. Improving our understanding of the propagation relationship between meteorological and hydrological drought is necessary to lessen drought impacts. The different drought responses and underlying mechanisms among different climate types are not yet sufficiently understood. By applying the standardized precipitation index and standardized runoff index, we investigated the propagation relationship between meteorological and hydrological drought. Because of short-term response between meteorological and hydrological droughts, the propagation time was considered among time scales of 1-12 months. Wavelet analysis was employed to examine the two types of drought from 1902 to 2014. Our results showed that arid environments had a weaker propagation relationship than moist environments. There was a stronger relationship between the two types of drought in summer and autumn than in spring and winter. The climate was not the only factor impacting drought propagation; land (cover and topographic feature) may also impact propagation time and intensity from meteorological to hydrological drought. This study analyzed and highlighted that the most susceptible regions in China and global scale, respectively. The most susceptible regions were tropical and subtropical Chinese southern zones in China and equatorial and warm temperate climate zones in global; however, arid climate zones showed little interaction between the two kinds of drought. Other factors that impact drought propagation, such as land cover, landforms, and human activity, should be considered in future research.

Exploring groundwater and soil water storage changes across the CONUS at 12.5 km resolution by a Bayesian integration of GRACE data into W3RA

Climate variability and change along with anthropogenic water use have affected the (re)distribution of water storage and fluxes across the Contiguous United States (CONUS). Available hydrological models, however, do not represent recent changes in the water cycle. Therefore, in this study, a novel Bayesian Markov Chain Monte Carlo-based Data Assimilation (MCMC-DA) approach is formulated to integrate Terrestrial Water Storage changes (TWSC) from the Gravity Recovery and Climate Experiment (GRACE) satellite mission into the W3RA water balance model. The benefit of this integration is its dynamic solution that uses GRACE TWSC to update W3RA's individual water storage estimates while rigorously accounting for uncertainties. It also down-scales GRACE data and provides groundwater and soil water storage changes at ~12.5 km resolution across the CONUS covering 2003-2017. Independent validations are performed against in-situ groundwater data (from USGS) and Climate Change Initiative (CCI) soil moisture products from the European Space Agency (ESA). Our results indicate that MCMC-DA introduces trends, which exist in GRACE TWSC, mostly to the groundwater storage and to a lesser extent to the soil water storage. Higher similarity is found between groundwater estimation of MCMC-DA and those of USGS in the southeastern CONUS. We also show a stronger linear trend in MCMC-DA soil water storage across the CONUS, compared to W3RA (changing from ±0.5 mm/yr to ±2 mm/yr), which is closer to independent estimates from the ESA CCI. MCMC-DA also improves the estimation of soil water storage in regions with high forest intensity, where ESA CCI and hydrological models have difficulties in capturing the soil-vegetation-atmosphere continuum. The representation of El Niño Southern Oscillation (ENSO)-related variability in groundwater and soil water storage are found to be considerably improved after integrating GRACE TWSC with W3RA. This new hybrid approach shows promise for understanding the links between climate and the water balance over broad regions.

Drought Monitoring Based on Remote Sensing in a Grain-Producing Region in the Cerrado–Amazon Transition, Brazil

Drought is a natural disaster that affects a country’s economy and food security. The monitoring of droughts assists in planning assertive actions to mitigate the resulting environmental and economic impacts. This work aimed to evaluate the performance of the standardized precipitation index (SPI) using rainfall data estimated by orbital remote sensing in the monitoring of meteorological drought in the Cerrado–Amazon transition region, Brazil. Historical series from 34 rain gauge stations, in addition to indirect measurements of monthly precipitation obtained by remote sensing using the products CHIRPS-2.0, PERSIANN-CDR, PERSIANN-CCS, PERSIANN, GPM-3IMERGMv6, and GPM-3IMERGDLv6, were used in this study. Drought events detected by SPI were related to a reduction in soybean production. The SPI calculated from the historical rain series estimated by remote sensing allowed monitoring droughts, enabling a high detailing of the spatial variability of droughts in the region, mainly during the soybean development cycle. Indirect precipitation measures associated with SPI that have adequate performance for detecting droughts in the study region were PERSIANN-CCS (January), CHIRPS-2.0 (February and November), and GPM-3IMERGMv6 (March, September, and December). The SPI and the use of precipitation data estimated by remote sensing are effective for characterizing and monitoring meteorological drought in the study region.

More frequent and widespread persistent compound drought and heat event observed in China

Compound drought and heat event (CDHE) causes severe impacts on agriculture, ecosystem, and human health. Based on daily maximum surface air temperature and meteorological drought composite index data in China, changing features of CDHEs in warm season from 1961 to 2018 is explored at a daily time scale based on a strict and objective definition in this study. Results reveal that CDHEs have occurred more frequently and widely in China, especially since the late 1990s. Notably, such changes are more obvious in Southwest China, eastern Northwest China, northern North China, and the coastal area of southeastern China. A prominent feature is that persistent CDHEs on a daily scale have increased significantly. To better understand climate change of compound extreme events, further studies on the physical mechanism, especially attribution analyses at a regional scale, are urgently needed.

An Iterative ICA-Based Reconstruction Method to Produce Consistent Time-Variable Total Water Storage Fields Using GRACE and Swarm Satellite Data

Observing global terrestrial water storage changes (TWSCs) from (inter-)seasonal to (multi-)decade time-scales is very important to understand the Earth as a system under natural and anthropogenic climate change. The primary goal of the Gravity Recovery And Climate Experiment (GRACE) satellite mission (2002–2017) and its follow-on mission (GRACE-FO, 2018–onward) is to provide time-variable gravity fields, which can be converted to TWSCs with ∼ 300 km spatial resolution; however, the one year data gap between GRACE and GRACE-FO represents a critical discontinuity, which cannot be replaced by alternative data or model with the same quality. To fill this gap, we applied time-variable gravity fields (2013–onward) from the Swarm Earth explorer mission with low spatial resolution of ∼ 1500 km. A novel iterative reconstruction approach was formulated based on the independent component analysis (ICA) that combines the GRACE and Swarm fields. The reconstructed TWSC fields of 2003–2018 were compared with a commonly applied reconstruction technique and GRACE-FO TWSC fields, whose results indicate a considerable noise reduction and long-term consistency improvement of the iterative ICA reconstruction technique. They were applied to evaluate trends and seasonal mass changes (of 2003–2018) within the world’s 33 largest river basins.

A Non-stationary Standardized Streamflow Index for hydrological drought using climate and human-induced indices as covariates

The aim of this paper is to propose a new non-stationarity hydrological drought index, which incorporates the climate-driven and human-induced non-stationarities in streamflow. For this purpose, significant teleconnection indices have been selected by correlation analysis to represent large-scale climate variability, and human-induced indices have been calculated using the Soil and Water Assessment Tool (SWAT) to indicate varying anthropogenic forcing. Whereafter, a non-stationary probability model fitted to streamflow series has been developed using the climate-driven and human-induced indices as covariates. Base on the non-stationary model, we present a variation of the classical Standardized Streamflow Index (SSI), named Non-stationary Standardized Streamflow Index (NSSI). Focusing on the streamflow records of Luanhe River basin from 1958 to 2011, a comparison of performance between NSSI and SSI has been conducted to demonstrate the capability of the NSSI. Finally temporal-spatial patterns of drought during the last 40 years over the basin have been estimated by using the NSSI. The results show that the non-stationary model describes the variability of streamflow better than a stationary one, and the covariates selected with Akaike information criterion (AIC) provide insights into non-stationary behaviors. Since the NSSI effectively accounts for the non-stationarities of streamflow associated with climate changes and human activities, it provides more reasonable and satisfactory results than the SSI. Additionally, it is indicated that serious long-term droughts generally appeared more frequently in the southeast of Luanhe River basin, and an obvious aggravating tendency of drought was observed in this area during 1971-2011. The presented NSSI enables hydrological droughts to be better characterized in a non-stationary context, thus providing valuable references for the improvement of drought index and the drought related policy-making.

Exceptional Drought across Southeastern Australia Caused by Extreme Lack of Precipitation and Its Impacts on NDVI and SIF in 2018

Increased drought frequency in Australia is a pressing concern for scholars. In 2018, a severe drought in eastern Australia was recorded by the Emergency Events Database (EM-DAT). To investigate the main causes and impacts of this drought across southeastern Australia, this work presents an overview of the drought mechanism and depicts its evolutionary process. The Standardized Precipitation Evapotranspiration Index (SPEI) from the Global Drought Monitor was used to identify the drought event and characterize its spatiotemporal distribution. The Normalized Difference Vegetation Index (NDVI) and the sun-induced chlorophyll fluorescence (SIF) were used to investigate the drought impacts on vegetation growth. In addition, the effects of drought response measures on Sustainable Development Goals (SDGs) were analyzed. Our results showed that the exceptional drought occurred across southeastern Australia from April to December, and it was most severe in July, owing to an extreme lack of precipitation and increase in temperature. Moreover, we identified profound and long-lasting impacts of the drought on NDVI and SIF levels, especially for cropland. Furthermore, we also found that SIF was superior to NDVI in detecting drought impacts. This study advised on how to formulate timely and effective drought-response measures and supports sustainable socioeconomic development in Australia.

Hydrologic alteration and possible underlying causes in the Wuding River, China

Understanding hydrological alteration of rivers and the potential driving factors are crucial for water resources management in the watershed. This study analyzed the daily runoff time series at six gauging stations during 1960-2016 in Wuding River basin, northwestern China. The Mann-Kendall test and Lee-Heghinian method were employed to detect the temporal trends and abrupt changes in annual streamflow. The flow duration curve (FDC) and the index of hydrologic alteration (IHA)/Range of Variability Approach (RVA) were applied to assess the daily streamflow and degree of hydrologic alteration (DHA). In addition, we analyzed the changes of index of hydrological connectivity (IC) and reservoirs/dams (RI) in 1990, 1995, 2000 and 2015 in the basin. The relationship between IC, RI and DHA were assessed to investigate the potential influences of land use changes and constructions of reservoirs/dams on hydrological alteration. The results indicated that annual streamflow at five stations showed significant downward trends (p < 0.01) from 1960 to 2016, and an abrupt changing point appeared in the beginning of 1970s in Wuding River basin. Exception is Qingyangcha station without significant changes, and Hanjiamao station with changing point in 1967. FDC analysis indicated that both high and low flow indices reduced greatly. The integral DHA were higher than 70% at all the stations in the Wuding River basin, suggesting great variation in the magnitude, duration, frequency, timing and rate of change of daily streamflow. Both IC value and RI had close relationship with DHA, implying that DHA was highly affected by land use changes and dams/reservoirs constructions, and was more sensitive to the land use change (p < 0.01). This study provides good insight to understand the effects of soil and water conservation measures on hydrological regime.

Attribution Analysis of Hydrological Drought Risk Under Climate Change and Human Activities: A Case Study on Kuye River Basin in China

This study conducted quantitative diagnosis on the impact of climate change and human activities on drought risk. Taking the Kuye river basin (KRB) in China as the research area, we used variation point diagnosis, simulation of precipitation and runoff, drought risk assessment, and attribution quantification. The results show that: (1) the annual runoff sequence of KRB changed significantly after 1979, which was consistent with the introduction of large-scale coal mining; (2) under the same drought recurrence period, the drought duration and severity in the human activity stage were significantly worse than in the natural and simulation stages, indicating that human activities changed the drought risk in this area; and (3) human activities had little impact on drought severity in the short duration and low recurrence period, but had a greater impact in the long duration and high recurrence period. These results provide scientific guidance for the management, prevention, and resistance of drought; and guarantee sustainable economic and social development in the KRB.

Performance Assessment of SM2RAIN-CCI and SM2RAIN-ASCAT Precipitation Products over Pakistan

Accurate estimation of precipitation from satellite precipitation products (PPs) over the complex topography and diverse climate of Pakistan with limited rain gauges (RGs) is an arduous task. In the current study, we assessed the performance of two PPs estimated from soil moisture (SM) using the SM2RAIN algorithm, SM2RAIN-CCI and SM2RAIN-ASCAT, on the daily scale across Pakistan during the periods 2000–2015 and 2007–2015, respectively. Several statistical metrics, i.e., Bias, unbiased root mean square error (ubRMSE), Theil’s U, and the modified Kling–Gupta efficiency (KGE) score, and four categorical metrics, i.e., probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), and Bias score, were used to evaluate these two PPs against 102 RGs observations across four distinct climate regions, i.e., glacial, humid, arid and hyper-arid regions. Total mean square error (MSE) is decomposed into systematic (MSEs) and random (MSEr) error components. Moreover, the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TRMM TMPA 3B42v7) was used to assess the performance of SM2RAIN-based products at 0.25° scale during 2007–2015. Results shows that SM2RAIN-based product highly underestimated precipitation in north-east and hydraulically developed areas of the humid region. Maximum underestimation for SM2RAIN-CCI and SM2RIAN-ASCAT were 58.04% and 42.36%, respectively. Precipitation was also underestimated in mountainous areas of glacial and humid regions with maximum underestimations of 43.16% and 34.60% for SM2RAIN-CCI. Precipitation was overestimated along the coast of Arabian Sea in the hyper-arid region with maximum overestimations for SM2RAIN-CCI (SM2RAIN-ASCAT) of 59.59% (52.35%). Higher ubRMSE was observed in the vicinity of hydraulically developed areas. Theil’s U depicted higher accuracy in the arid region with values of 0.23 (SM2RAIN-CCI) and 0.15 (SM2RAIN-ASCAT). Systematic error components have larger contribution than random error components. Overall, SM2RAIN-ASCAT dominates SM2RAIN-CCI across all climate regions, with average percentage improvements in bias (27.01% in humid, 5.94% in arid, and 6.05% in hyper-arid), ubRMSE (19.61% in humid, 20.16% in arid, and 25.56% in hyper-arid), Theil’s U (9.80% in humid, 28.80% in arid, and 26.83% in hyper-arid), MSEs (24.55% in humid, 13.83% in arid, and 8.22% in hyper-arid), MSEr (19.41% in humid, 29.20% in arid, and 24.14% in hyper-arid) and KGE score (5.26% in humid, 28.12% in arid, and 24.72% in hyper-arid). Higher uncertainties were depicted in heavy and intense precipitation seasons, i.e., monsoon and pre-monsoon. Average values of statistical metrics during monsoon season for SM2RAIN-CCI (SM2RAIN-ASCAT) were 20.90% (17.82%), 10.52 mm/day (8.61 mm/day), 0.47 (0.43), and 0.47 (0.55) for bias, ubRMSE, Theil’s U, and KGE score, respectively. TMPA outperformed SM2RAIN-based products across all climate regions. SM2RAIN-based datasets are recommended for agricultural water management, irrigation scheduling, flood simulation and early flood warning system (EFWS), drought monitoring, groundwater modeling, and rainwater harvesting, and vegetation and crop monitoring in plain areas of the arid region.

Multi-scale assessment of eco-hydrological resilience to drought in China over the last three decades

Understanding to what extent can terrestrial ecosystems maintain their structure and functions and recover after being hit by drought is critical for sustainable ecosystem management and drought mitigation practices. This study assesses multi-scale (i.e., at grid, climate type, land use, basin, province scales) eco-hydrological resilience to drought over China during the period of 1982-2015, based on Standard Evapotranspiration Deficit Index as well as satellite-retrieved evapotranspiration (ET) and net primary production (NPP). Over the last three decades, the ecosystem water use efficiency (eWUE) increased in most regions of China (especially in Northeast China and North China Plain) in the context of climate change. The western China showed a significant wetting trend with ascending ET, GPP and eWUE. The SEDI and ET showed significantly increasing tendencies but the ecosystem GPP and eWUE did not exhibit obvious responses to regional wetting in the middle and lower reaches of Yangtze River basin. Most terrestrial ecosystems in China were found overall resilient to drought except for mild temperature-fully humid-warm summer at the climate type scale, water type at the land use scale, Northwest Rivers at the basin scale as well as Ningxia, Qinghai, Shanghai and Hong Kong at the province scale. These findings would facilitate the identification of most drought-vulnerable regions for ecosystem management and taking reasonable adaptation measures (e.g., use of alternative water resources or reuse water, water conservation and smart irrigation) to ensure the sustainability of terrestrial ecosystems during the drought periods over China.