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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 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]

Global climate change is projected to increase the probability of occurrence and severity of droughts. Increased CO2 concentration drives partial closure of plant stomata and reduces evapotranspiration. However, the impact of reduced evapotranspiration due to CO2 on future droughts characteristics in China is unclear. In this study, we have used the Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model simulations (GCMs) under historical period, and four shared socioeconomic pathway scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5) to estimate drought. We used a widely applicable drought index (i.e., the self‐calibrating Palmer Drought Severity Index [scPDSI]) to evaluate the historical and future drought conditions, using the Penman–Monteith formula with and without the CO2 concentrations. The results show that the increasing trend of scPDSI slows down when the CO2 effect is considered in all scenarios, especially in Heilongjiang, northern Xinjiang, and the Qinghai–Tibet Plateau. The divergence in the slowdown trend among the different scenarios becomes greater after 2030, with higher emission scenarios implying a greater slowdown in the increasing trend of scPDSI. After considering CO2, drought characteristics such as the drought frequency, intensity, and drought area decrease. Increased CO2 concentration on vegetation physiological processes could mitigate future drought. Therefore, the effects of CO2 on plant physiology should be considered in studies of future drought trends to develop more realistic response and adaptation policies to future drought changes. [ABSTRACT FROM AUTHOR]

Under global warming, according to results obtained from offline drought indices driven by projections of general circulation models (GCMs), future droughts in China will worsen but the results are not consistent. We analyzed changes in droughts covering the entire hydrologic cycle using outputs of GCMs of the 6th Coupled Model Intercomparison Project (CMIP6) for SSP2-4.5 and SSP5-8.5 climate scenarios, and compared the results with that of popular, offline drought indices [the self-calibrating Palmer Drought Severity Index (scPDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Actual Evapotranspiration Index (SPAEI)]. Among meteorological, agricultural, and hydrological drought indices tested under both SSP scenarios, the results obtained from SPAEI and scPDSI agree better with univariate drought indices than SPEI. scPDSI generally agrees well with agricultural droughts (Standardized Soil Moisture Index with the surface soil moisture content; SSIS). Future droughts estimated using soil moisture analysis are more widespread than that from precipitation and runoff analysis in humid regions of South China by the end of the twenty-first century. In arid northwestern China and Inner Mongolia, drought areas and severity based on scPDSI and SSIS forced with the SSP scenarios show obvious decreasing trends, in contrast to increasing trends projected in South China. Trends projected using SPEI contradict those projected by other drought indices in non-humid regions. Therefore, selecting appropriate drought indices is crucial in project representative future droughts and provides meaningful information needed to achieve effective regional drought mitigation strategies under climate warming impact. [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]

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]