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Drought seriously restricts people's lives and social–economic development. An accurate understanding of the evolution of drought characteristics and future changes in cultivated land exposure can reduce the risk of drought. There is evidence that increased CO2 concentrations alter the physiological properties of vegetation and, thus, affect drought evolution. In this study, both changes and differences in drought (i.e., characteristics and cropland exposure) with and without the CO2 effect over the arid region of China are investigated, using seven CMIP6 outputs and land-use under seven shared-socioeconomic-pathway (SSP)-based scenarios. The results show that: (1) drier conditions will be more severe in 2015–2100 under SSP5-8.5, especially if the CO2 effect is neglected. Moreover, the CO2 effect will increase with increasing emission concentrations; (2) drought intensity will be greater than in the baseline period (1995–2014, approximately −1.45) but weaker than that without the CO2 effect under all scenarios; (3) drought frequency will decrease, and will generally decline faster if the CO2 effect is not considered; (4) drought duration will increase and the difference between the presence and absence of the CO2 effect will always be smallest under SSP1-1.9 and largest under SSP5-8.5; (5) drought acreage will also increase, and neglecting the CO2 effect is always higher than that considering CO2. The difference between the two algorithms will increase with time; and (6) cropland exposure to drought will increase, and can even reach 669,000 km2 and 524,000 km2 considering and ignoring the CO2 effect, respectively. Our findings suggest that ignoring CO2 in drought evaluations will result in significant overestimations of drought projections. [ABSTRACT FROM AUTHOR]

Landslides result in severe casualties every year in China. An increase in extreme precipitation in China has been found, and the areas experiencing unusually extreme precipitation are also expanding due to climate changes. This leads to a change of landslide occurrence due to climate change. We try to assess the future change of landslide occurrence in China under different climate change scenarios based on a fatal landslide event inventory with 1950 non-seismically triggered landslides, the observed daily rainfall data and the Global Daily Downscaled Projections (NEX-GDDP) dataset derived from 21 General Circulation Models (GCMs) for RCP 4.5 and RCP 8.5. Firstly, the CTRL-T algorithm is used to extract the rainfall events and their corresponding rainfall duration and cumulative event rainfall for observed precipitation data and the GCM dataset including the historical and future data. Then, the relationship between the extracted rainfall events from the observation data and the fatal landslide events is analyzed to establish the cumulative event rainfall (E) and rainfall duration (D) threshold. Appropriate GCM models are selected based on the comparison of the GCM historical rainfall event and the E-D threshold. The characteristics of past and future GCM rainfall events at locations where landslide susceptibility is above a certain value are analyzed and the frequencies are determined i.e. the possible landslide occurrence that exceeds the E-D threshold. Finally, we assess the impact of climate change on landslides in China by comparing the historical and future frequency of landslide occurrence under different climate scenarios. This research will help to better understand the future changes in landslide hazard in the context of climate change. [ABSTRACT FROM AUTHOR]