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High Mountain Asia (HMA), with its high altitude, widely distributed snow and frozen soil, influences the climate of the northern hemisphere and even the world through thermal balance and the water vapor cycle and is also an indicator of global climate change. The influence of HMA snow cover on its surrounding areas has always been a research hotspot. Taking the Yangtze River Basin (YRB) of China as an example, this paper analyzes the relationship between winter snow depth in HMA and drought and flood in spring and summer in the YRB in the recent 40 years by using Singular Value Decomposition (SVD). The results show that the influence of snow cover on drought and flood in spring is inversely different between eastern and western parts of HMA, while the effect in summer is consistent. When the snow depth is larger (smaller) in the east and smaller (larger) in the west in winter, the YRB is drier (wetter) in spring. When the overall snow depth in HMA is larger (smaller) in winter, the northern part of the middle and lower reaches of the YRB is drier (wetter) in summer. The results provide support for understanding the impact of HMA snow cover on the surrounding climate and some important indicators for drought and flood prediction in the YRB. [ABSTRACT FROM AUTHOR]

Research on precipitation regularity in the past 120 years is an important link in analyzing the precipitation characteristics of watersheds. This paper systematically analyzes the characteristic changes of centennial precipitation data in the Haihe River basin with the help of CRU data, PCI, SPI, and the Pearson type III curve. The results show that the spatial and temporal distribution of precipitation in the Haihe River basin has a more obvious inconsistency. The temporal distribution shows the characteristics of relatively stable in the early period and increasing fluctuation in the later period, the concentration of precipitation gradually decreases, and the overall drought level decreases. The spatial distribution shows a general pattern of gradually decreasing from southwest to northeast, the overall trend of summer precipitation changes from stable to north–south extremes, and the distribution probability of extreme precipitation events in the basin decreases from southeast to northwest, while the drought-prone area transitions from the northeast to the west and southwest of the basin. Under the influence of both climate change and human activities, the seasonal distribution of precipitation tends to be average, the area affected by extreme precipitation rises, and the arid area shifts to the inland area. [ABSTRACT FROM AUTHOR]

In the context of global climate change and ecological restoration projects, significant changes have been observed in the fractional vegetation cover (FVC) in the Yellow River basin. The increased vegetation growth accelerates water consumption, exacerbating drought and water scarcity issues, thereby heightening regional water resource shortage risks. This study targets the Yellow River basin in China, employing a pixel-based model to convert NDVI into FVC datasets. We establish a pixel-wise mathematical model for annual runoff and environmental factors based on residual analysis and methods like multiple linear regression. Using climate model data from CMIP6 as independent variables, in conjunction with the statistical model, we elucidate the spatiotemporal characteristics of annual runoff in the Yellow River basin under future climate scenarios. Our results indicate that, under four different climate scenarios, the average annual runoff in the Yellow River basin is projected to increase. The increases are quantified as 0.008 mm/a, 0.065 mm/a, 0.25 mm/a, and 0.24 mm/a for SSP126, SSP245, SSP370, and SSP585 scenarios, respectively. From 2022 to 2040, the spatial distribution of the runoff change rates under the SSP245 and SSP370 scenarios show an increasing trend in upstream areas such as the Qinhe and Longmen regions, with rates ranging from 6.00 to 8.61 mm/a. During the period from 2041 to 2060, all four climate scenarios indicate minimal changes in the runoff depth in the northern part of the Yellow River basin. From 2061 to 2080, under the SSP126 and SSP245 scenarios, the spatial distribution of the runoff shows significant increases in the river source area and a decreasing trend in the middle reaches, with rates ranging from 4.52 to 11.39 mm/a. For the period from 2081 to 2100, the runoff change rates vary significantly under the four climate scenarios. These findings provide a detailed understanding of how future climate scenarios could impact water resource distribution in the Yellow River basin, offering critical insights for regional water management and policy making to mitigate potential water scarcity challenges. [ABSTRACT FROM AUTHOR]

Recent studies on China's arid and semi-arid regions, particularly the Tarim River Basin (TRB), have shown an increase in the intensity and frequency of extreme weather events. This research examines the link between meteorological droughts, as measured by the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts, as indicated by the Standardized Runoff Index (SRI) and the Standardized Terrestrial Water Storage Index (STI), over various time scales. Historical data indicate that SPEI drought frequency (DF) was 14.3–21.9%, with prevalent events in the northern oases. SRI DF ranged from 9.0% to 35.8%, concentrated around the Taklamakan and Kumtag Deserts, while STI DF varied between 4.4% and 32.7%, averaging 15% basin-wide. Future projections show an increased DF of SPEI in deserts and a decrease in oases; SRI DF decreased in deserts but increased in oases. STI changes were more moderate. The study also found a higher risk of drought progression from SPEI to SRI in the southwestern and northeastern oases, exceeding 50% probability, while central and eastern TRB had lower risks. The western TRB and inner Taklamakan Desert faced higher risks of SPEI to STI progression, with probabilities over 45%, in contrast to the lower risks in the eastern and central oases. The concurrence of SRI/STI with moderate to extreme SPEI droughts led to a higher probability and area of SRI/STI droughts, whereas consistent SPEI types showed a reduced induced probability and extent of SRI/STI droughts. This study enhances the understanding of drought propagation from meteorological to hydrological droughts in the TRB and contributes to the prevention of hydrological drought to a certain extent. [ABSTRACT FROM AUTHOR]

The intensification of the regional water cycle resulting from climate change, coupled with the influence of human activities, has brought about alterations in the frequency, scale, and intensity of droughts. In this study, based on hydrological big data and the standardized runoff drought index (SRI), the multi-scale spatiotemporal evolution of hydrological drought in China from 1948 to 2014 was analyzed using the run-length theory and gravity center model. Meanwhile, the hydrological drought hazard index was constructed to analyze the distribution of the hazard levels of drought in China. The results showed that, during 1948~2014, there was an opposite spatial distribution between the average intensity and the average coverage–duration–frequency of drought in the Yellow River Basin, Haihe River Basin and southeastern river basins. The drought situation in most river basins in China has shown an aggravating trend, among which the southeastern river basins, Haihe River Basin, Songliao River Basin and Pearl River Basin have generally shown an aggravating trend. The drought situation in China was severe in the 1950s and 1960s, gradually reduced in the 1970s, 1980s, and 1990s, and the drought situation was the mildest in the 1990s. After entering the 21st century, the drought situation began to worsen sharply. Meanwhile, from 1948 to 2014, the hazard level of drought generally presented a pattern of high in the west and north, and low in the east and south. The hazard levels of drought in the northwest and northeast were generally higher, and those in the southwest and southeast regions were generally lower. In general, the hazard levels of drought were relatively high in most areas of China. [ABSTRACT FROM AUTHOR]

Frequent droughts may have negative influences on the ecosystem (i.e., terrestrial vegetation) under a warming climate condition. In this study, the linear regression method was first used to analyze trends in vegetation change (normalized difference vegetation index (NDVI)) and drought indices (Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)). The Pearson Correlation analysis was then used to quantify drought impacts on terrestrial vegetation in the Weihe River Basin (WRB); in particular, the response time of vegetation to multiple time scales of drought (RTVD) in the WRB was also investigated. The trend analysis results indicated that 89.77% of the area of the basin showed a significant increasing trend in NDVI from 2000 to 2019. There were also significant variations in NDVI during the year, with the highest rate in June (0.01) and the lowest rate in January (0.002). From 2000 to 2019, SPI and SPEI at different time scales in the WRB showed an overall increasing trend, which indicated that the drought was alleviated. The results of correlation analysis showed that the response time of vegetation to drought in the WRB from 2000 to 2019 was significantly spatially heterogeneous. For NDVI to SPEI, the response time of 12 months was widely distributed in the north; however, the response time of 24 months was mainly distributed in the middle basin. The response time of NDVI to SPI was short and was mainly concentrated at 3 and 6 months; in detail, the response time of 3 months was mainly distributed in the east, while a response time of 6 months was widely distributed in the west. In autumn and winter, the response time of NDVI to SPEI was longer (12 and 24 months), while the response time of NDVI to SPI was shorter (3 months). From the maximum correlation coefficient, the response of grassland to drought (SPEI and SPI) at different time scales (i.e., 6, 12, and 24 months) was higher than that of cultivated land, forestland, and artificial surface. The results may help improve our understanding of the impacts of climatic changes on vegetation cover. [ABSTRACT FROM AUTHOR]

The Tarim River, the largest inland river in China, sits in the Tarim River Basin (TRB), which is an arid area with the ecosystem primarily sustained by water from melting snow and glaciers in the headstream area. To evaluate the pressures of natural disasters in this climate‐change‐sensitive basin, this study projected flash droughts in the headstream area of the TRB. We used the variable infiltration capacity (VIC) model to describe the hydrological processes of the study area, Markov chain Monte Carlo to quantify the parameter uncertainty of the VIC model. Ten downscaled general circulation models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) were used to drive the VIC model, and the standardized evaporative stress ratio was applied to identify flash droughts. The results demonstrated that the VIC model after Bayesian parameters uncertainty analysis can efficiently describe the hydrological processes of the study area. In the future (2021–2100), compared with the plain region, the alpine region has higher flash drought frequency and intensity. Compared with the historical period (1961–2014), the frequency, duration, and intensity of flash droughts tend to increase throughout the study area, especially for the alpine area. Moreover, based on variance decomposition, CMIP6 model is the most important uncertainty source for flash drought projection, followed by the shared socioeconomic pathway of climate change scenario and VIC model parameters. Plain Language Summary: The Tarim River is the largest inland river in China, which is an arid area with the ecosystem primarily sustained by water from melting snow and glaciers in the headstream area. Compared with long‐duration drought, flash drought is more difficult to forecast and identify. We used the variable infiltration capacity model to build a hydrological model of the headstream area of the Tarim River Basin, and the model output (ET data) was used to identify flash droughts. Based on 10 representative Coupled Model Intercomparison Project Phase 6 (CMIP6) models, this study projected the future flash droughts in the study area under climate change. The findings indicated that the alpine region is likely to experience a greater frequency and intensity of flash droughts in the future (2021–2100) compared to the plain region. Compared with the historical period (1961–2014), the frequency, duration, and intensity of flash droughts tend to increase throughout the study area, especially for the alpine area. In addition, the result of uncertainty decomposition revealed that the CMIP6 model is the most important uncertainty source for flash drought projection. Key Points: The hydrological processes of study area are well described by the variable infiltration capacity model and Bayesian uncertainty analysisCompared with the plain region, the alpine region has higher flash drought frequency and intensity in the futureThe Coupled Model Intercomparison Project Phase 6 model is the most important uncertainty source for flash drought projection [ABSTRACT FROM AUTHOR]

Pressure on river water resources may increase continuously under global climate change and the increasing intensity of human activity, and the identification of river water sources is needed to maintain water resource sustainability. In this study, river water sources were studied using hydrochemical tracers (i.e. the major ions) and end‐member mixing analysis (EMMA) during two hydrological years, in the subtropical monsoon basin of the Xiangjiang River in the south‐central China. Various water types including precipitation, river water, and mountain creek water, were collected in the basin at a high frequency. The results of EMMA showed that the average contributions from the direct input of precipitation, near‐surface runoff (represented by mountain creek water), and groundwater (represented by river water sampled during the base flow period) were 28 ± 24%, 49 ± 24% and 23 ± 16%, respectively. The contributions from these water sources to the river water varied greatly within the year, which may indicate a shift in the major flow pathways from direct precipitation input and near‐surface flow pathways in the spring rainy months (e.g. from March to May), to a deeper flow pathway in the dry or rainless months (e.g. January, February, July and December). The shift of the major flow pathways may be due to the factors such as the seasonality of precipitation, evapotranspiration and soil wetness conditions. Groundwater and near‐subsurface runoff dominated the river water and the direct input of precipitation was negligible during the dry or rainless months, and consequently, the river water chemistry was less diluted and more influenced by water‐soil/rock interactions and anthropogenic pollution during these months. The creek water contribution to the river water was relatively high in summer, especially in June and July 2021, which may indicate the substantial inter‐seasonal carryover of precipitation that contributed to the river water. With the projected increased frequency of extreme weather events such as seasonal drought, streamflow in the subtropical monsoon regions may experience greater recharge by deeper flow pathways, with the enhanced role of base flow in regulating streamflow, and there may be an increased risk to the water resource security under the condition of the decreased river dilution capacity and increased anthropogenic pollution. [ABSTRACT FROM AUTHOR]

Precipitation data from 30 stations in the Huaihe River basin (HRB), a climatic transitional zone in east China, were used to investigate the spatiotemporal variability and trends of extreme precipitation on multitimescales for the period 1961–2010. Results indicated that (1) the spatial pattern of the annual precipitation, rainy days, extreme precipitation, and maximum daily precipitations shows a clear transitional change from the south (high) to the north (low) in the HR; it confirmed the conclusion that the HRB is located in the transitional zone of the 800 mm precipitation contour in China, where the 800 mm precipitation contour is considered as the geographical boundary of the south and the north. (2) Higher value of the extreme precipitation intensity mainly occurs in the middle of the east and the central part of the basin; it reveals a relatively distinct west-east spatial disparity, and this is not in line with the spatial pattern of the extreme precipitation total, the sum of the precipitation in 95th precipitation days. (3) Annual precipitation of 22 stations exhibits increasing trend, and these 22 stations are located from the central to the northern part. There is no significant trend detected for the seasonal precipitation. The summer precipitation exhibits a larger change range; this might cause the variation of the flood and drought in the HBR. However, the increasing trend in winter precipitation may be beneficial to the relief of winter agricultural drought. Rainy days in 12 stations, mostly located in and around the central northeastern part, experienced significant decreasing trend. Extreme precipitation days and precipitation intensity have increasing trends, but no station with significant change trend is detected for the maximum precipitation of the basin. (4) The spatiotemporal variability in the HRB is mainly caused by the geographic differences and is largely influenced by the interdecadal variations of East Asian Summer Monsoon in eastern China. The output of this paper could provide references for the practical decision making and integrated basin management of Huaihe River basin. [ABSTRACT FROM AUTHOR]

Hydrological drought is a highly complex and extreme natural disaster, which has increased in deficit, areal extent, and frequency with the penetration of climate change impact. For better anticipating hydrological droughts, it is crucial to evaluate hydrological drought and its teleconnections with large-scale climate indices (LSCI) effectively. This study estimated the dynamics and patterns of hydrological drought in the near-real river networks by virtue of the standardized runoff index (SRI) based on VIC and large-scale routing model in the Xijiang River basin, and revealed their teleconnections with the climate indices. Results show that model simulation can reasonably reveal the hydrological drought evolutions in near-real river networks and effectively expose the drought downward spread along main channels. The drought spread distances in Hongshuihe and Yujiang Rivers are farther under the comprehensive influence of climate, topography, and watershed shape. Hydrological drought evolutions in the upper reaches are mainly manifested as three patterns, including S12 (simultaneous significant changes in drought intensity, concentration degree, and frequency), S7(simultaneous significant changes in drought intensity and frequency), and S1(single significant change in drought intensity). These drought dynamic patterns are majority affected by climate variation patterns M1 (warm and cold AMO), M3 (cold PDO), and M7 (warm AMO/AO). For decision-makers, this work is beneficial for understanding and anticipating hydrological droughts in the river networks, and further selecting management strategies for water resources. Highlights: The quantitative results of model simulation are reliable for drought evaluation. Drought concentration period delays and drought risk increases significantly. Dynamic evolutions of drought mainly manifest as three combinations patterns. Upstream drought is mainly affected by AMO, PDO, and AMO/AO. [ABSTRACT FROM AUTHOR]

The Yellow River Basin is an important economic belt and key ecological reservation area in China. In the context of global warming, it is of great significance to project the drought disaster risk for ensuring water security and improving water resources management measures in practice. Based on the five Global Climate Models (GCMs) projections under three scenarios of the Shared Socioeconomic Pathways (SSP) (SSP126, SSP245, SSP585) released in the Sixth Coupled Model Intercomparison Project (CMIP6), this study analyzed the characteristics of meteorological drought in the Yellow River Basin in combination with SPEI indicators over 2015–2100. The result indicated that: (1) The GCMs from CMIP6 after bias correction performed better in reproducing the spatial and temporal variation of precipitation. The precipitation in the Yellow River Basin may exhibit increase trends from 2015 to 2100, especially under the SSP585 scenario. (2) The characteristics of meteorological drought in the Yellow River Basin varied from different combination scenarios. Under the SSP126 scenario, the meteorological drought will gradually intensify from 2040 to 2099, while the drought intensity under SSP245 and SSP585 scenarios will likely be higher than SSP126. (3) The spatial variation of meteorological drought in the Yellow River Basin is heterogeneous and uncertain in different combination scenarios and periods. The drought tendency in the Loess Plateau will increase significantly in the future, and the drought frequency and duration in the main water conservation areas of the Yellow River Basin was projected to increase. [ABSTRACT FROM AUTHOR]

Drought is a severe natural hazard all over the world, resulting in enormous losses in many aspects, especially in agriculture. It is essential to analyze the spatio-temporal variation of drought and its relationships with the El Niño-Southern Oscillation under a background of global climate change for better drought prevention. The Songhua River Basin (SHRB), which is an important food base in northeastern China that suffered a severe drought in 2020, was chosen as the research site. The standardized precipitation evapotranspiration index (SPEI) was chosen as the drought index to analyze the spatio-temporal variation of droughts in the SHRB by linear regression analysis and T-test using the meteorological data from 1960 to 2019. The cross-wavelet analysis was adopted to reveal the relationship between the SPEI and El Niño-Southern Oscillation indexes (the Niño 1+2 SST Index (SST1), Niño 3 SST Index (SST2), Niño 3.4 SST Index (SST3), Niño 4 SST Index (SST4), and Southern Oscillation Index (SOI)). The results reveal that the changing trends of yearly, spring, summer, autumn, and winter precipitation were 0.56, 1.47 (p < 0.05), 0.13, 0.04, and 0.16 (p < 0.05) mm/a, respectively; the precipitations were higher in the southeastern regions and lower in the western regions, with extreme values of 831.62 mm and 381.69 mm, respectively. The SPEI was significantly increased (p < 0.05) with a gradient of 0.01/a on a yearly scale and were increased in all seasons (significant in winter (p < 0.05)). The drought probability on a yearly scale was dominated by summer and autumn. The SPEI was positively correlated with SST1, SST2, SST3, and SST4 in a different period with a different resonant period and was negatively correlated with the SOI with a short-term period for 3–4 years from 1986 to 1990 and a long-term period for 9–12 years from 1992 to 2010. These results could provide a scientific guide for drought prevention in the SHRB. [ABSTRACT FROM AUTHOR]

• An observation-based natural and human-impacted catchment comparison method is proposed. • Human influence are quantified based on gridded socio-economic and land use data. • Climatic and anthropogenic influences on drought propagation are investigated. • Climate change accelerates the response of hydrological drought to meteorological drought. • Human activities delay the propagation from meteorological to hydrological drought. It is crucial to investigate how a precipitation deficit is transformed into hydrological drought and how climate change and human activities affect this transformation process, which is helpful to gain a deep understanding of drought propagation process in this changing environment. This study proposed an observation-based natural and human-impacted catchment comparison method to assess the impacts of climate change and human activities on propagation from meteorological drought to hydrological drought. The method mainly consists of the following three steps: (1) selection of natural catchments through analysis of trends and change points of hydro-meteorological data, as well as statistics analysis of human influence based on land use and socio-economic indicators data sets; (2) calculation of drought propagation characteristics (e.g., drought severity, duration, and propagation time) based on run theory and the Pearson correlation coefficient; and (3) comparison of drought propagation characteristics of natural catchments between undisturbed and disturbed periods to identify the impacts of climate change on drought propagation, and comparison of the propagation characteristics between natural and human-impacted catchments during the disturbed period to investigate human influence on drought propagation. The Laohahe basin (with eleven sub-catchments), located in northern China, was evaluated via the proposed procedure, and standardized precipitation index (SPI) and standardized runoff index (SRI) were used to characterize meteorological and hydrological droughts, respectively. The results demonstrate that the proposed method is suitable tool for distinguishing natural and human-impacted catchments, and separating the impacts of climate change and human activities on drought propagation. Furthermore, the comparison results of different schemes show that climate change accelerates the propagation from meteorological drought to hydrological drought in the Laohahe basin, shortening it by approximately 3 months. Human activities, however, disturb and then delay the natural propagation from meteorological drought to hydrological drought, retarding it by 11–12 months. Although the Laohahe basin was selected as a case study in this paper, the proposed method can be applied in other regions as well to improve drought prediction and water resources management. [ABSTRACT FROM AUTHOR]

Both climate and land-use changes can influence drought in different ways. Thus, to predict future drought conditions, hydrological simulations, as an ideal means, can be used to account for both projected climate change and projected land-use change. In this study, projected climate and land-use changes were integrated with the Soil and Water Assessment Tool (SWAT) model to estimate the combined impact of climate and land-use projections on hydrological droughts in the Lutheran River basin. We showed that the measured runoff and the remote sensing inversion of soil water content were simultaneously used to validate the model to ensure the reliability of the model parameters. Following calibration and validation, the SWAT model was forced with downscaled precipitation and temperature outputs from a suite of nine global climate models (GCMs) based on CMIP5, corresponding to three different representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5) for three distinct time periods: 2011–2040, 2041–2070 and 2071–2100, referred to as early century, mid-century and late-century, respectively, and the land use predicted by the CA–Markov model in the same future periods. Hydrological droughts were quantified using the standardized runoff index (SRI). Compared to the baseline scenario (1961–1990), mild drought occurred more frequently during the next three periods (except for the 2080s under the RCP2.6 emissions scenario). Under the RCP8.5 emissions scenario, the probability of severe drought or above occurring in the 2080s increased, the duration was prolonged, and the severity increased. Under the RCP2.6 scenario, the upper central region of the Luanhe River in the 2020s and upper reaches of the Luanhe River in the 2080s were more likely to experience extreme drought events. Under the RCP8.5 scenario, the middle and lower Luanhe River in the 2080s was more likely to experience these conditions. [ABSTRACT FROM AUTHOR]

Compound droughts and heat waves have garnered increasing attentions due to their disastrous impacts on the structure and function of ecosystems and societies. A drought is generally characterized by a precipitation deficit, and its negative impact can be amplified by the simultaneous occurrence of a heat wave. More recent studies have highlighted the multicharacteristics of compound droughts and heat waves, which may call for improved efforts on assessing the impact of compound extremes. In this study, a compound drought and heat wave magnitude index (CDHMI) is built to characterize the severity of compound extremes in the Huai River basin (HRB) during 1961–2017. The CDHMI considers the impact of both drought/extreme heat conditions and the duration of drought/extreme heat. In addition, the magnitude index has been graded according to the degree of severity to detect the most drastic extreme compound events. The results show that from 1961 to 2017, mild and moderate events occurred more often than severe events. A significant increase in all compound events was observed from 2003 to 2017. Compound drought and heat wave events, especially in drought status, have increased significantly with the global climate warming in recent decades. The assessment of the impact for compound drought and heat wave events over the HRB needs to be improved in the context of global climate changing. Therefore, the CDHMI can be used to accurately assess the risk of compound droughts and heat waves. [ABSTRACT FROM AUTHOR]

Objective evaluation of the relationships among different types of droughts remains a challenging task due to the combined impacts of climate change and land surface modification caused by human activities. Based on the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) at the 3- and 6-month timescales, this study presents a systematic analysis of the relationships between the severity (S) and duration (D) of meteorological (MD) and hydrological droughts (HD) in the three catchments of the upper Huai River Basin in China. The relation between SPI and SRI is explored by the maximal information coefficient and the mutual entropy. The spatial propagation mechanism of MD is identified by the centroid trajectory, and the response of HD to MD is quantified by the model averaging method. The results indicate a drying (wetting) trend in the upstream (downstream) area, while the centroid trajectory of MD is found in the midstream area, but not associated with the large (or small) S and D simultaneously. There is a strong correlation (determination coefficient > 0.55) between SPI and SRI in all three subareas, particularly at the 6-month timescale. The increasing influences of human activities (e.g., regulation of water conservancy facilities) from upstream to downstream lead to a weaker correlation between SPI and SRI as well as a decreasing threshold of D for MD to trigger HD in downstream. By contrast, the drier climatic conditions are the main reason for the increasing threshold of S for MD to trigger HD from upstream to downstream. [ABSTRACT FROM AUTHOR]

In this paper, future drought characteristics (frequency, duration and intensity) over China are analysed by using four climate models from CMIP6 under the seven SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, SSP370, and SSP585) for three defined periods of 2021–2040 (near-term), 2041–2060 (mid-term) and 2081–2100 (long-term). The corresponding four climate models output from CMIP5 are also used to conduct a comparison analysis between CMIP5 and CMIP6 to address the improvements added to CMIP6 in terms of drought identification. The drought characteristics are identified by applying the standardized precipitation-evapotranspiration index (SPEI) at a 12-month timescale and run theory. The results show that CMIP6 has a robust capability to capture historical (1986–2005) drought characteristics. For the future period of 2021–2040, the decrease in precipitation and increase in potential evapotranspiration will lead to continuous dry conditions in the upper and middle Yangtze River basin and eastern Pearl River basin. Relative to the reference period, drought events will be more frequent and severe with longer durations in the Northwest River basins and middle Yangtze River basin. Furthermore, higher emissions signify a greater increase in drought frequency and intensity in the long-term period. Except for the SSP585 scenario, the lower emission scenario corresponds to the higher drought duration soon and in the mid-21st century (2021–2060). This finding is regarded as a "strange phenomenon", which cannot be detected by the previous CMIP5-based emission scenarios (RCP2.6, RCP4.5 and the unlikely pathway RCP8.5). Therefore, additional "possible future"-based scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, and SSP370) should be included in extreme climate studies, especially for the near future and mid-21st century. Notably, compared with CMIP5, the reduced biases in drought characteristics are more likely associated with improvements in the representation of physical processes in climate models from CMIP6. The results of this study could provide a basis for the development of drought adaptation measures over China. • Latest CMIP6 climate models and seven SSP-RCP scenarios are used to analyze the possible changes in droughts over China. • More robust projections will be presented by CMIP6 than CMIP5, due to the better representations in physical processes. • The higher emission signifies shorter drought duration, lower precipitation and PET in mid-21st century over China. [ABSTRACT FROM AUTHOR]

As an extremely important region for the socioeconomic development of China, the Yangtze River Basin (YRB) is vulnerable to climate change and natural disasters. In recent decades, hydrological droughts have jeopardized regional water supply, local ecosystem services, and economic development in this region. This study simulates the characteristics of hydrological droughts in the YRB using the PCR-GLOBWB v2.0 model and the variable threshold method. High-spatial-resolution (about 10 km) PCR-GLOBWB v2.0 simulations considering the effects of human activities closely match the observed hydrological data for the YRB. Thus, the results indicate that human activities directly influence the tempo-spatial characteristics of hydrological droughts in the YRB. Reservoir operation decreases the multi-year monthly discharge but increases low flow in the severe drought years in the middle and lower subbasins of the YRB. These findings highlight the uneven effects of human activities on hydrological droughts in the YRB. In conclusion, anthropogenic activities must be considered when developing future mitigation and adaptation strategies for the YRB. [ABSTRACT FROM AUTHOR]

Drought has become one of the most serious meteorological disasters for agricultural production in many areas around the world, and the situation could be worse under the impact of climate change. To facilitate better adaptation planning, this study proposed a drought assessment framework integrating downscaling method, drought index, copula technique, and bivariate frequency analysis, and applied it to investigate the change of the drought characteristics and drought risks from the past to the future in Huang-Huai-Hai River basin (HRB), North China. Drought was firstly defined by standardized precipitation evapotranspiration index (SPEI) based on 1497 observed grid data from 1979 to 2004. Then, we constructed the joint distribution of drought duration and severity based on copulas to detect and quantify the drought risks. To address the effect of climate change, similar calculation process was applied to the future climate data, which was downscaled using delta change method from representative concentration pathway (RCP 8.5) of 12 general circulation models (GCMs). The study results suggested that, under climate change condition, most irrigation districts over HRB would generally experience lower frequency of drought events but with extended duration; some districts would have more serious drought, but majority would experience similar or even lower level of severity. In light of the mean joint occurrence probability, the irrigation district at the south part of Huai River basin would likely experience the highest increase of drought risks in near future (by 0.86%) and distant future (by 0.76%), while most of other districts over HRB would face low risk of serious drought risks. The obtained results offer useful information to agricultural managers or water resources authorities who are interested in the development of effective long-term adaptation strategies for drought management. [ABSTRACT FROM AUTHOR]

Drought projection is of critical significance for designing long-term drought adaptation strategies to cope with changing climate. This study presents an application of multi-class models for characterizing future droughts in the Yellow River basin (YRB). Using meteorological observations and simulations of three CMIP5 climatic models as input into VIC hydrologic model, the standardized Palmer drought index-based joint drought index (SPDI-JDI) is calculated to investigate spatiotemporal patterns and possible changes of future drought in the YRB, through an approach of bivariate modeling and analysis. It is concluded that moderate drought will be alleviated with decreased duration and severity, but extreme drought risk is likely to increase for future climate scenarios (2021–2050) relative to baseline period (1961–2000). From the perspective of bivariate analyses, the concurrence probability of drought events with extreme duration and severity might rise in the future, while increasing variability and heterogeneity of duration, severity and bivariate joint/concurrent return period would also increase the stochastic occurrence of extreme drought over time and space. These findings can provide insights into projection of climate change impacts on drought trends for the next 30 years, and help to preparations for strict control of socio-economic water consumption as well as eco-environmental protection and restoration in the YRB. [ABSTRACT FROM AUTHOR]

Climate change and human activities are two major driving forces affecting the hydrologic cycle, which further influence the stationarity of the hydrologic regime. Hydrological drought is a substantial negative deviation from the normal hydrologic conditions affected by these two phenomena. In this study, we propose a framework for quantifying the effects of climate change and human activities on hydrological drought. First, trend analysis and change‐point test are performed to determine variations of hydrological variables. After that, the fixed runoff threshold level method (TLM) and the standardized runoff index (SRI) are used to verify whether the traditional assessment methods for hydrological drought are applicable in a changing environment. Finally, two improved drought assessment methods, the variable TLM and the SRI based on parameter transplantation are employed to quantify the impacts of climate change and human activities on hydrological drought based on the reconstructed natural runoff series obtained using the variable infiltration capacity hydrologic model. The results of a case study on the typical semiarid Laohahe basin in North China show that the stationarity of the hydrological processes in the basin is destroyed by human activities (an obvious change‐point for runoff series is identified in 1979). The traditional hydrological drought assessment methods can no longer be applied to the period of 1980–2015. In contrast, the proposed separation framework is able to quantify the contributions of climate change and human activities to hydrological drought during the above period. Their ranges of contributions to hydrological drought calculated by the variable TLM method are 20.6–41.2% and 58.8–79.4%, and the results determined by the SRI based on parameter transplantation method are 15.3–45.3% and 54.7–84.7%, respectively. It is concluded that human activities have a dominant effect on hydrological drought in the study region. The novelty of the study is twofold. First, the proposed method is demonstrated to be efficient in quantifying the effects of climate change and human activities on hydrological drought. Second, the findings of this study can be used for hydrological drought assessment and water resource management in water‐stressed regions under nonstationary conditions. [ABSTRACT FROM AUTHOR]

The assessment of future climate changes on drought and water scarcity is extremely important for water resources management. A modeling system is developed to study the potential status of hydrological drought and water scarcity in the future, and this modeling system is applied to the Jinghe River Basin (JRB) of China. Driven by high-resolution climate projections from the Regional Climate Modeling System (RegCM), the Variable Infiltration Capacity model is employed to produce future streamflow projections (2020–2099) under two Representative Concentration Pathway (RCP) scenarios. The copula-based method is applied to identify the correlation between drought variables (i.e., duration and severity), and to further quantify their joint risks. Based on a variety of hypothetical water use scenarios in the future, the water scarcity conditions including extreme cases are estimated through the Water Exploitation Index Plus (WEI+) indicator. The results indicate that the joint risks of drought variables at different return periods would decrease. In detail, the severity of future drought events would become less serious under different RCP scenarios when compared with that in the historical period. However, considering the increase in water consumption in the future, the water scarcity in JRB may not be alleviated in the future, and thus drought assessment alone may underestimate the severity of future water shortage. The results obtained from the modeling system can help policy makers to develop reasonable future water-saving planning schemes, as well as drought mitigation measures. [ABSTRACT FROM AUTHOR]

Extreme hydrometeorological events have far-reaching impacts on our daily life and may occur more frequently with rising global temperatures. The probability of the concurrence of these extreme events in the upper reaches of the river network is of particular importance for the lower reaches, which is referred to as the encounter probability of extreme events, and may have even stronger socio-economic impacts. In this study, the Rao River basin in China is selected as an example to explore the encounter probability and risk of future flood and drought based on the encounter probability model. The reference period was 1971–2000, and the future prediction periods were 2020–2049 and 2070–2099. The calibrated and validated statistical downscaling model (SDSM) was used to generate future daily precipitation and daily mean temperature. The calibrated and validated Xin'anjiang model was used to predict future daily mean streamflow in the basin. In addition, the encounter probability model was established using the joint distribution of occurrence dates and magnitudes of daily mean streamflow to investigate the encounter probabilities of flood and drought under future climate change. Results show that, for flood occurrence dates, the encounter probability during the flood season would decrease in the two future periods while the dates would generally be earlier. For flood magnitudes, the encounter probability of the two tributaries' floods and the probability of flood at each tributary would decrease (e.g., the encounter probability with the same-frequency of 100-years would reduce by 53% to 95%), which indicates reduced risk of future major floods in the study area. For drought occurrence dates, the encounter probability during the non-flood season would decrease. For drought magnitudes, the encounter probability would decrease (e.g., the encounter probability with the same-frequency of 100-years would reduce by 18% to 33%), even though the probability of future drought at each tributary would increase. Such analyses provide important probabilistic information to help us prepare for the upcoming extreme events. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Drought is one of the most widespread and threatening natural disasters in the world, which has terrible impacts on agricultural irrigation and production, ecological environment, and socioeconomic development. As a critical ecologically fragile area located in southwest China, the Yarlung Zangbo River (YZR) basin is sensitive and vulnerable to climate change and human activities. Hence, this study focused on the YZR basin and attempted to investigate the spatiotemporal variations of drought and associated multi-scale response to climate change based on the scPDSI (self-calibrating Palmer drought severity index) and CRU (climate research unit) data. Results showed that: (1) The YZR basin has experienced an overall wetting process from 1956 to 2015, while a distinct transition period in the mid 1990s (from wet to dry) was detected by multiple statistical methods. (2) Considering the spatial variation of the scPDSI, areas showing the significantly wetting process with increasing scPDSI values were mostly located in the arid upstream and midstream regions, which accounted for over 48% area of the YZR basin, while areas exhibiting the drying tendency with decreasing scPDSI values were mainly concentrated in the humid southern part of the YZR basin, dominating the transition period from wet to dry, to which more attention should be paid. (3) By using the EEMD (ensemble empirical mode decomposition) method, the scPDSI over the YZR basin showed quasi-3-year and quasi-9-year cycles at the inter-annual scale, while quasi-15-year and quasi-56-year cycles were detected at the inter-decadal scale. The reconstructed inter-annual scale showed a better capability to represent the abrupt change characteristic of drought, which was also more influential to the original time series with a variance contribution of 55.3%, while the inter-decadal scale could be used to portray the long-term drought variation process with a relative lower variance contribution of 29.1%. (4) The multi-scale response of drought to climate change indicated that changes of precipitation (PRE) and diurnal temperature range (DTR) were the major driving factors in the drought variation at different time scales. Compared with potential evapotranspiration (PET), DTR was a much more important climate factor associated with drought variations by altering the energy balance, which is more obvious over the YZR basin distributed with extensive snow cover and glaciers. These findings could provide important implications for ecological environment protection and sustainable socioeconomic development in the YZR basin and other high mountain regions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]