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Investigation of extreme precipitation events in arid and semiarid regions, especially for occurrence time and the associated circulation mechanisms, is vital to support the forecasting of and the advanced response to resultant disasters. In this study, the spatiotemporal pattern of occurrence time of extreme precipitation and atmospheric circulation mechanisms in the Arid Region of Northwest China (ARNC) were analyzed using two indicators (precipitation concentration degree and period) and the climate diagnosis method. Results showed that the significant scattered pattern of extreme precipitation occurrence time (EPOT) in Northern Xinjiang and the postponed pattern of maximum extreme precipitation occurrence (MEPO) from southern to northern Xinjiang are consistent with the input pathway of the Arctic air mass. During the anomaly dispersion year of EPOT and the anomaly delay year of MEPO, the Arctic air mass carried sufficient water vapor is transported to ARNC for triggering extreme precipitation events. Meanwhile, the pattern of concentration–dispersion–concentration in eastern ARNC demonstrates interaction between the westerlies and the summer monsoon. Sufficient water vapor is transported to southwestern ARNC by the southwest monsoon during the anomaly delay year of MEPO and the anomaly concentration year of EPOT. The findings of this study suggest that invasion of the Arctic air mass and the summer monsoon could influence extreme precipitation in ARNC.

Drought-induced risk has attracted the attention of many scholars, but the risk of combined events caused by drought and high-temperature heat waves still needs further study. Based on MODIS products and meteorological data, the spatiotemporal variation characteristics of summer drought and high-temperature heat waves in the North China Plain from 2000 to 2018 were analyzed by the standardized precipitation evapotranspiration index (SPEI), crop water stress index (CWSI) and high-temperature threshold, and their combined-events risk was evaluated. The results showed that (1) from 2000 to 2018, summer drought in the North China Plain became more severe. Especially in Henan, Anhui and Jiangsu Provinces, drought increased significantly. (2) From 2000 to 2018, the frequency and intensity of high-temperature heat wave events in the North China Plain gradually increased at rates of 0.28 times/10 year and 1.6 °C/10 year, respectively. (3) The slightly high risk and high risk caused by summer drought were mainly distributed in Hebei Province and Tianjin Municipality in the north, and the risk change was characterized by a decrease in the north and an increase in the south. (4) The combined-events risk of summer drought and high-temperature heat waves did not increase significantly, with an increase rate of approximately 0.01/10 year. Among them, the increase rate of combined-events risk in Henan Province was the largest (0.14/10 year), followed by the obvious increase in northern Anhui, Jiangsu and southern Shandong, while the risk in Beijing showed a decreasing trend. The research results have scientific guiding significance for formulating disaster prevention and reduction strategies.

Much attention has recently been devoted to the qualitative relationship between climate factors and drought; however, the influences of climate variability, land-use/cover changes (LUCC), and other human activities on drought have rarely been quantitatively assessed. Based on the Soil and Water Assessment Tool (SWAT) model and the Palmer drought severity index (PDSI), this study presents a framework to quantify drought changes in an attribution study, and quantifies the effects of climate factors, LUCC, and other human activities on drought in a typical basin (Yihe River) in eastern China from 1980 to 2019. (1) The SWAT–PDSI results revealed a slight decreasing trend from 1980 to 2019, indicating that the degree of drought increased—especially in the middle of the basin. (2) The precipitation in the basin exhibited a downward trend (−2.7 mm/10 a), while the temperature exhibited a significant increasing trend (0.13 °C/10 a, p < 0.05). Over the past 40 years, LUCC in the Yihe River Basin was mainly characterized by a reduction in the dryland area (149 km2) and an increase in the built-up area (135 km2), which changed by −1.77% and 18.96%, respectively. (3) Climate fluctuation was the main driving factor of drought change, with a contribution rate ranging from 68 to 84%, and the contribution to drought gradually increased. Among the various factors, the contribution of temperature exceeded that of precipitation from 2010 to 2019, suggesting that temperature has become the most important climate factor affecting drought. The contribution rates of LUCC to drought changes over the periods 1990–1999, 2000–2009, and 2010–2019 were 7.8%, 18%, and 12.6%, respectively. This indicates that the relative contributions of other human activities to drought changes gradually decreased. This study refines the drought attribution framework, which could provide scientific support for the quantitative attribution of drought and the formulation of disaster prevention and reduction strategies.

Global Satellite Mapping of Precipitation (GSMaP), Climate Hazards Group InfraRed Preconception with Station data (CHIRPS), Tropical Rain Measurement Mission Multisatellite Precipitation Analysis (TRMM 3B42 V7) and Rainfall Estimation from Soil Moisture Observations (SM2RAIN) are satellite precipitation products with high applicability, but their applicability in hydrological research in arid mountainous areas is not clear. Based on precipitation and runoff data, this study evaluated the applicability of each product to hydrological research in a typical mountainous basin (the Qaraqash River basin) in an arid region by using two methods: a statistical index and a hydrological model (Soil and Water Assessment Tool, SWAT). Simulation results were evaluated by Nash efficiency coefficient (NS), relative error (PBIAS) and determination coefficient (R2). The results show that: (1) The spatial distributions of precipitation estimated by these four products in the Qaraqash River basin are significantly different, and the multi-year average annual precipitation of GSMaP is 97.11 mm, which is the closest to the weather station interpolation results. (2) On the annual and monthly scales, GSMaP has the highest correlation (R ≥ 0.82) with the observed precipitation and the smallest relative error (BIAS < 6%). On the seasonal scale, the inversion accuracy of GSMaP in spring, summer and autumn is significantly higher than other products. In winter, all four sets of products perform poorly in estimating the actual precipitation. (3) Monthly runoff simulations based on SM2RAIN and GSMaP show good fitting (R2 > 0.6). In daily runoff simulation, GSMaP has the greatest ability to reproduce runoff changes. The study provides a reference for the optimization of precipitation image data and hydrological simulation in data-scarce areas.