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Global human‐induced warming has intensified water circulation in the atmospheric environment and altered the streamflow generation regime. The VIC hydrological model approach for impact assessment of climate change and human activities mainly focuses on variations in streamflow, but ignores other critical flooding characteristics induced by extreme streamflow, especially bivariate flooding characteristics. In this work, the copula functions are employed to structure the flooding risk under the shared socioeconomic pathway (SSP) across the Yellow River basin (YRB). This is based on the multi‐model ensemble (MME) and Delta downscaling outputs (Delta‐MME) of the CMIP6 global climate models (GCMs), as well as the flooding characteristics simulated by VIC hydrological model. Compared to the reference period (1995–2014), Delta‐MME reveals a significant warming and humidifying trend under three SSPs over the YRB. Despite uncertainties originating from climate variables and hydrological model, multiple findings underscore the substantial influence of climate change on the flooding generation regime in YRB. This includes: (a) an increase in the streamflow under all SSPs; (b) a larger flooding peak (Q) and volume (W) under SSP585, with Q and W at the Huayuankou hydrologic station (HYK) increasing by 52.7% and 44.8%, respectively; (c) an advancement in the bivariate flooding risk, particularly in SSP585 where flooding co‐occurrence return period at HYK may be more than 50 times earlier. This study underscores that the urgent need to enhance social resilience to climate change in the YRB. Plain Language Summary: The YRB, as the second‐longest river in China, is confronted with the threat of catastrophic flooding hazards. The CMIP6, representing the latest climate prediction products, was developed by Earth System Grid Federation. This research aims to propose a novel perspective for predicting future flooding risks along the YRB under all SSPs. The findings of this research could hold great potential for informing mitigation and adaptation policies regarding flooding hazards in the YRB. Key Points: The VIC hydrologic model is employed to simulate flooding magnitude to climate change over the Yellow River basinFlooding magnitude over the Yellow River basin become more fluctuating under three SSPsFuture return period levels for flooding peak and volume have reduced significantly from the historical period, with the co‐occurrence return period being more prominent than the joint return period [ABSTRACT FROM AUTHOR]

• We developed a modified drought severity index (MDSI) with a constrained optimization technique. • MDSI improves drought monitoring for forests and farmland. • Ecological restoration and cultivated land reclamation can help mitigate droughts, while urbanization can potentially intensify droughts. With advancement of remote sensing techniques, remote-sensing drought indices have been widely used for drought monitoring. However, the monitoring accuracy of a specific drought index regionally varies. Considering the deficiency of existing drought indices in reflecting vegetation growth, here we propose a Modified Drought Severity Index (MDSI) with local optimization method constrained by the inclusion of vegetation greenness, crop water shortage, canopy temperature, vegetation structure, and physiological status. We evaluated drought monitoring performance of MDSI across China, and detected high correlations between MDSI and soil moisture (SM), Standardized Precipitation Index at a 3-month scale (SPI-3), actual drought-affected areas (ADA), evidencing higher drought performance of MDSI when compared to 8 widely-used drought indices. Besides, MDSI performed better in monitoring agricultural drought. We found amplifying short-term drought intensity in the future. Ecological restoration and cultivated land reclamation can alleviate drought effects. However, urbanization can potentially intensify droughts. How to adapt human behavior to droughts is a challenging task. [ABSTRACT FROM AUTHOR]

Understanding historical and future drought patterns is crucial to acclimation and the mitigation of drought. The negative impact of China's droughts on the social economy has attracted attention; however, there is still no comprehensive or long-term monitoring pattern for future droughts. Here we evaluated the precipitation and temperature simulation capability of Coupled Model Intercomparison Project Phase 6 (CMIP6) and evaluated the temporal and spatial pattern of droughts during 1961–2099 across China. The results show that the multi-model ensemble mean (MME) is more representative of the observed precipitation and temperatures across China than the single climate model. China experienced an overall drying trend in the historical period. After 1991, the drought frequency (DF), drought duration (DD), and drought intensity (DI) in the northwest of the Inland River Basin and in the Yangtze River Basin increased significantly. Compared with the historical period, China will suffer more frequent drought events, although the DD and DI will be weakened under SSP1-2.6 and SSP2-4.5, while China will experience longer DD and more serious drought events under SSP3-7.0 and SSP5-8.5. The Hai River Basin and Huai River Basin are expected to have more serious drought trends in summer. Compared with historical periods, the drought trend will increase by 2.9–5.7 times and 1.1–4.2 times, respectively. The results can be used for decision making regarding future drought control. [ABSTRACT FROM AUTHOR]

In the context of global warming, relevant studies have shown that China will experience the largest temperature rise in the Qinghai–Tibet Plateau and northwestern regions in the future. Based on MOD10A2 and MYD10A2 snow products and snow depth data, this study analyzes the temporal and spatial evolution characteristics of the snow cover fraction, snow depth, and snow cover days in the three stable snow cover areas in China, and combines 15 modes in CMIP6 snow cover data in four different scenarios with three kinds of variables, predicting the spatiotemporal evolution pattern of snow cover in China's three stable snow cover areas in the future. The results show that (1) the mean snow cover fraction, snow depth, and snow cover days in the snow cover area of Northern Xinjiang are all the highest. Seasonal changes in the snow cover areas of the Qinghai–Tibet Plateau are the most stable. The snow cover fraction, snow depth, and snow cover days of the three stable snow cover areas are consistent in spatial distribution. The high values are mainly distributed in the southeast and west of the Qinghai–Tibet Plateau, the south and northeast of Northern Xinjiang, and the north of the snow cover area of Northeast China. (2) The future snow changes in the three stable snow cover areas will continue to decline with the increase in development imbalance. Snow cover fraction and snow depth decrease most significantly in the Qinghai–Tibet Plateau and the snow cover days in Northern Xinjiang decrease most significantly under the SSPs585 scenario. In the future, the southeast of the Qinghai–Tibet Plateau, the northwest of Northern Xinjiang, and the north of Northeast China will be the center of snow cover reduction. (3) Under the four different scenarios, the snow cover changes in the Qinghai–Tibet Plateau and Northern Xinjiang are the most significant. Under the SSPs126 and SSPs245 scenarios, the Qinghai–Tibet Plateau snow cover has the most significant change in response. Under the SSPs370 and SSPs585 scenarios, the snow cover in Northern Xinjiang has the most significant change. [ABSTRACT FROM AUTHOR]

Simultaneous/sequential occurrence of multiple extreme climate events has the tendency to inflict greater damage compared to isolated extreme climate events. The exploration of simultaneous or continuous extreme events holds profound implications for disaster risk prevention. Therefore, we identified the compound heatwaves and extreme precipitation events (CHP, extreme precipitation events following heatwaves) in China based on ERA5 data. Then, the individual extreme events and compound events were undertaken through event coincidence analysis. Furthermore, the atmospheric background of individual extreme events and compound extreme events was further investigated. The results show that the CHP events with an increasing trend mainly occurred in northern China and northeastern the Qinghai-Tibet Plateau (QTP). Notably, after the year 2000, the time interval of extreme precipitation in CHP events was significantly shortened. In July and August, the trigger coincidence rate of extreme precipitations by heatwaves occurred higher and extreme precipitation events following heatwaves accounted for 40%. Moreover, Extreme precipitation is more likely to occur after a longer duration and higher intensity heatwave in the QTP. Convective effective potential energy (CAPE) and relative humidity manifest a considerable increase during the heatwave duration, greatly augmenting the risk of extreme precipitation events. In addition, the frequency of CHP events is higher in northern and northeastern China during El Niño years. While it predominantly concentrates in the northeast region in La Niña years. • The time interval of extreme precipitation after the heatwave in the compound events became shorter after 2000. • Extreme precipitation is more likely to occur after a longer duration and higher intensity heatwave in the QTP. • Significantly increased CAPE and relative humidity during heatwave enhance the risk of extreme precipitation events. [ABSTRACT FROM AUTHOR]

• There is high consistency in the extent of land degradation. • There are consistent hydrothermal change characteristics in the land degradation hotspots area. Land degradation is a major impediment to achieving sustainable development. However, there is currently no harmonized global map of land degradation status and hotspots. This paper aims to obtain the status and hotspots map of global land degradation by multiple methods and indicators to give essential references for land degradation neutrality. The results show that there are significant differences in the distribution and degree of land degradation between the different methods and indicators. Validation through observation points reveals that most of the methods and indicators can reflect land degradation in arid and semi-arid areas, while there are suitable methods or indicators in tropical and high-latitude areas. The degree of degradation has a large difference after overlay analysis, which shows that there are shortcomings of different methods and indicators for monitoring the degree of land degradation. However, the overlay of land degradation extent displays a high consistency, reflecting the current state of global land degradation to a certain extent. These areas with high overlay value can be recognized as hotspots of land degradation. It is also found there are consistent water-energy change characteristics in the hotspot area, such as increased land surface temperature and air temperature and decreased soil moisture and precipitation. These results conclude that studies on the degree of land degradation need to be considered in an integrated manner about the regional background. The combination of multiple methods and indicators is recommended for land degradation extent studies in large areas. Comparison of different methods and indicators is important guidance for global land degradation research. Accelerating ecological monitoring and restoration of land degradation hotspots is the first step towards land degradation neutrality. [ABSTRACT FROM AUTHOR]