The co-occurrence of droughts at multiple time scales in the water source area (Upper Hanjiang River, UH) and receiving area (northern North China, NNC) of the Middle Route of the South-to-North Water Diversion project highlights the need to identify common climatic drivers for these concurrent phenomena. Using reconstructed drought/flood grade data and sunspot series from 1700 to 2023, this study analyzed the correlations of droughts/floods in the Upper Hanjiang River and northern North China with sunspots at 11-, 30- and 50-year scales. The results show that the correlation between sunspots and droughts/floods in these two areas varied in stages over time. During high sunspot periods, the frequency of extreme drought events increased in both areas. The phase change of the correlation between sunspots and droughts/floods in the Upper Hanjiang River and northern North China significantly influenced the shift in the drought-flood correspondence between the two areas. When droughts/floods in the Upper Hanjiang River and northern North China align with or oppose sunspot variations, the droughts/floods in the two areas are predominantly positively or negatively correlated. Both droughts/floods in the Upper Hanjiang River and northern North China as well as sunspots share inter-annual cycles of about 2-4 years, inter-decadal cycles of about 11-12 years, and multi-decadal cycles of about 20-30 years and 50 years. Sunspot variations may influence the droughts and floods in these two areas across multiple time scales. Additionally, when sunspots increase significantly and abruptly, the Upper Hanjiang River and northern North China tend to be more drought-prone.

Precipitation hydrogen and oxygen stable isotopes (δ²H_p and δ¹⁸O_p) can reveal the characteristics of regional climate and environmental elements. Unrevealing the variation on δ²H_p and δ¹⁸O_p of different intensity precipitation is of great significance to explore the extreme precipitation process and inherent mechanisms of regional climate change processes. Based on the measurement of δ²H_p and δ¹⁸O_p in 539 atmospheric precipitation samples collected from 6 stations in the North China region during 2020-2022, the spatiotemporal distribution of precipitation stable isotopes at different precipitation intensity was systematically analyzed, and the water vapor transport paths and source composition were explored. The results show that: (1) All precipitation events (AP), extreme precipitation events (EP) and different intensity precipitation events in the study area showed significant spatiotemporal heterogeneity. The δ²H_p and δ¹⁸O_p displayed the characteristics of depleted in summer and autumn and they were enriched in winter and spring, depleted in rainy season and enriched in non-rainy season, while the fluctuation range of precipitation stable isotopes increased from coastal to inland areas. The δ²H_p and δ¹⁸O_p were depleted with increasing precipitation intensity level. (2) Local meteoric water line (LMWL) in different regions showed obvious heterogeneity. LWML for downpour (DP) events had significant variability compared to other intensity precipitation. (3) The fluctuation of environmental elements did not show significant correlation with precipitation stable isotopes in the whole region, and the environmental effects of precipitation stable isotopes were recorded at individual sites. (4) The westerly is the main water vapor source for this region, and the dominant water vapor source shows the characteristics of alternating control between sea source and land source. Continental water vapor is an important source for regional heavy precipitation events. The results of this study will help to improve the understanding of the regional hydrologic cycle and the optimal allocation level of water resources.

Potential evapotranspiration (ET₀) plays an important role in water resource utilization and management. The uncertainty in ET₀ variation in different seasons poses challenges in accurately estimating ET₀ trends. This paper taking the Huaihe River Basin as the study area, daily meteorological data from 29 meteorological stations in the basin from 1960 to 2020 were used to calculate ET₀ using the Penman-Monteith formula. The characteristic parameters of ET₀ in different seasons (expectation Ex, entropy En, and hyperentropy He) were determined using the normal cloud model. The uncertainty characteristics of ET₀ in different seasons in the basin were analyzed from the aspects of trend, mutation, and spatial mode. The results are as follows: (1) The seasonal ordering of Ex, En, and He is the same, with the order being summer > spring > autumn > winter; (2) All characteristic parameters of ET₀ in the four seasons exhibit abrupt points, with Ex in spring showing a significant upward trend, while Ex in summer and autumn shows a significant downward trend. En in spring and autumn shows a significant upward trend, He in spring shows a significant upward trend, and He in autumn and winter shows a significant downward trend; (3) The spatial distribution of Ex, En, and He for ET₀ across the four seasons generally shows a decreasing trend from west to east.The research findings reveal the uncertainty characteristics of ET₀ in different seasons in the Huaihe River Basin, providing a scientific basis for accurately predicting the future trends of basin ET₀ and serving as a reference for uncertainty analysis of ET₀.

Danxia landforms are unique land surface morphologies formed by long-term natural weathering and erosion of Tertiary red sandstone. An in-depth study of the spatio-temporal distribution characteristics of their surface thermal environment exhibits significant practical importance. This study quantitatively analyzes the micro-geomorphological characteristics of Danxia Mountain and their interplay with the spatio-temporal differentiation of land surface temperature (LST), integrating multi-source remote sensing imageries from the Sustainable Development Goals Science Satellite 1 (SDGSAT-1), Sentinel-2A/2B, and SPOT6 spanning 2022-2023. Firstly, the LSTs with a 30-m spatial resolution are retrieved for day and night across all four seasons using the three-channel split-window algorithm. The geomorphons (GM) terrain classification method is then applied for the finer GM classification of Danxia Mountain. Finally, the study analyzes the spatial and temporal differentiation characteristics of LST. Furthermore, we elucidate the impact of different micro-topographies of Danxia Mountain on the spatial and temporal variations of LST. The research reveals that Danxia Mountain comprises seven typical GM terrestrial landscapes, including peak, ridge, spur, slope, hollow, pit, and valley. These GM terrestrial landscapes are found to exert a significant impact on the seasonal and diurnal fluctuations of LST. Specifically, in the lower-lying areas of pits and valleys, the average daytime LST is relatively high, exhibiting the characteristic of "geomorphologic ravine thermal effect"; whereas in high-altitude peaks and ridges, the average nighttime LST is relatively high, leading to a "geomorphologic hilltop thermal effect". In spring, daytime LST and Normalized Difference Vegetation Index (NDVI) show a negative correlation across different GM terrestrial landscapes. However, this negative relationship reverses in autumn, where a positive correlation between daytime LST and NDVI is observed, particularly evident on straight back slopes and convex back slopes. There exists a positive correlation between nighttime LST and the Digital Elevation Model (DEM), which is more pronounced in spring and winter. The results further reveal the spatial and temporal differentiation characteristics of LST under the micro-topographical conditions of Danxia Mountain in Guangdong's subtropical region. This provides important insights into the spatial and temporal variations of LST, offering valuable information for ecological environment research, biodiversity conservation, and climate change adaptation in regions where Danxia landforms are distributed.

Global change has significantly increased the frequency and intensity of extreme climate events, impacting the structure and function of terrestrial ecosystems. While climate warming has prolonged the growing season and increased carbon sequestration in temperate forests, the effects of extreme seasonal climate events on forest phenology and productivity remain unclear, which hinders a comprehensive understanding of the terrestrial carbon cycle. Based on the vegetation autumn phenology dataset extracted from the GIMMS NDVI3g data, this study assessed the impacts of extreme drought, extreme precipitation, high temperatures, and low temperatures on autumn phenology and gross primary productivity in temperate forests in China from 1982 to 2015 using partial correlation analysis. The results show that the mean end dates of the growing season occurred in 281-345 days with a delay rate of 0.5 days per year, and mean gross primary productivity occurred in 276-1367 g C m^-2 with an increase rate of 0.4 g C m^-2 per year on temperate forests in China. Increased drought severity and extreme high-temperature days during the growing season advanced autumn phenology and decreased productivity. In contrast, more drought and moderate high-temperature days delayed autumn phenology and increased productivity. Seasonal differences in phenology responses to extreme climate events were also observed. Spring and summer extreme high temperatures and drought advanced autumn phenology and reduced productivity, while autumn extreme high temperature and drought have the opposite effect. This phenomenon likely stems from elevated summer temperatures exacerbating heat stress and drought conditions, which collectively deplete soil moisture, and induce plant water stress, ultimately resulting in advanced autumn phenology and suppressed photosynthetic activity. However, cooler autumns make high-temperature events more conducive to forest growth, delaying autumn phenology and enhancing productivity. The study reveals seasonal differences of extreme climate events on autumn phenology and forest growth, suggesting that the timing of extreme events is crucial for understanding their effects on vegetation phenology and the terrestrial carbon cycle, which is essential to comprehend the carbon cycle of terrestrial ecosystems and their responses to climate change in the future.

Flash floods pose a significant threat to life and property, as well as to the stable social and economic development in mountainous regions. Understanding the driving factors and spatio-temporal heterogeneity of flash floods is crucial for their prevention and mitigation. Geomorphic features are key determinants in the occurrence and development of flash floods across different scales. Therefore, this paper integrates geomorphic regions defined by three-level terrain and geomorphic type based formative processes to investigate the spatio-temporal variations, driving factors and heterogeneity of flash floods in China from 1985 to 2015, considering seasonal, interannual and multi-year scales. The findings reveal that the geomorphic regions based on the three-level terrain effectively capture the spatio-temporal heterogeneity of flash floods. Notably, interannual variation of flash floods occurrences differ significantly across six geomorphic regions. The most pronounced increasing trends are observed in the Southwestern Mountain region, the Southeastern Hilly Mountain region, and the Tibetan Plateau region. Seasonally, flash floods are most frequent in summer, followed by spring and autumn. Geomorphic types based on formative processes provide insights into the driving factors of flash floods. In erosional mountainous and hilly areas, key drivers include temperature, vegetation coverage, soil texture type, and land use. In karst landform areas, temperature, precipitation, land use, and soil texture type are the primary factors. In plains and terraces, the driving factors include soil texture type, precipitation and land use. This study enhances the understanding of the historical development of flash floods and provides a foundation for further exploring the mechanisms underlying their occurrence and evolution under different geomorphic conditions. Additionally, it offers valuable insights for flash flood planning and prevention strategies in the context of climate change.