This study investigated the temporal and spatial variations of precipitation duration and intensity in Jiangsu Province from 1960 to 2020 using the IDW spatial interpolation method and Kendall’s tau trend test, based on daily precipitation data collected from 22 meteorological stations. Additionally, a Pearson correlation analysis was conducted to examine the correlations between the occurrence rate and contribution rate of precipitation with different durations and grades, as well as five large-scale climate indices. The results indicated the following trends: (1) An increase in the precipitation duration corresponded to a decrease in the occurrence rates, while the contribution rates initially increased and then decreased. The province was predominantly characterized by 1–3 days of light rainfall, with a higher probability of short-duration heavy rainfall in northern Jiangsu. (2) From 1960 to 2020, most stations experienced decreasing trends in the precipitation duration occurrence and contribution rates, but heavy rainfall increased, suggesting a shift to short-duration heavy precipitation. (3) The Arctic Oscillation (AO) notably negatively correlates with the 9-day occurrence rate of precipitation (9dOR), while it positively correlates significantly with the occurrence rate of moderate rainfall (MROR). The North Atlantic Oscillation (NAO) exhibits a significant positive correlation with the 2-day occurrence rate of precipitation (2dOR) and a notable negative correlation with the 9-day occurrence rate of precipitation (9dOR). The PDO (Pacific Decadal Oscillation) has shown significant positive correlations with the 2-day precipitation occurrence rate (2dOR) and contribution rate (2dCR), a negative correlation with the light rainfall occurrence rate (LROR), and significant positive correlations with both the moderate and heavy rainfall occurrence rates (MROR and HROR, respectively). The AO, NAO, and PDO are potential climate factors that influence changes in the precipitation structure in Jiangsu Province. These research findings offer valuable insights for regional water resource management, flood risk assessment, and predicting future precipitation trends under climate change scenarios.

Hill fires have the potential to influence dissolved organic matter (DOM) in water bodies, yet fewer studies have investigated the effects of hill fires on DOM within watersheds in karst areas. In this study, we employed the three-dimensional fluorescence-parallel factor analysis (EEM-PARAFAC) method to analyze the DOM fluorescence peaks, component compositions, fluorescence indices, and sources within the water body of the Yuanteng River sub-basin, which was impacted by the hill fire, serving as our primary research focus. The results indicate the presence of three primary fluorescent fractions in the water body of the Yuanteng River: C1, resembling humic acid (fulvic acid); C2, consisting of biopolymers and microbial by-products; and C3, containing proteins such as tyrosine and tryptophan. The Yuanteng River exhibited elevated levels of humus-like substances, diminished concentrations of protein-like substances, and demonstrated higher biogenic, freshness, and humification indices compared to unaffected water samples, reflecting the impact of the hill fire. Elevated levels of exogenous humic acid-like inputs into the waters of the Yuanteng River, along with exogenous inputs of DOM, were primarily influenced by stable, high-molecular-weight organic matter. Additionally, agricultural effluent, domestic sewage, and anthropogenic activities contributed to these inputs to a lesser degree. The impacts of endogenous inputs are mainly related to the restoration of ecosystems. The occurrence of hill fires has significantly influenced the composition of dissolved organic matter in the waters of the Yuanteng River. A comprehensive analysis of the impacts of hill fires on dissolved organic matter in water bodies can serve as a valuable reference for characterizing DOM in the water bodies of the Yuanteng River. Furthermore, it can inform strategies for environmental protection, facilitate the traceability of pollutants in water bodies, and contribute to environmental and ecological restoration efforts following hill fires in the region.

Due to its unique hydrogeological conditions, the Southwest Karst Area (SKA) in China experiences droughts far more frequently than non-karst regions. Exploring the distribution patterns and driving factors of different drought types is crucial for enhancing the region’s disaster prevention and mitigation capabilities and effectively addressing climate change risks. Using meteorological data from 1979 to 2023 in the SKA—including precipitation, temperature, humidity, potential evapotranspiration, and soil moisture—this study employed Copula theory to construct the Standardized Temperature Deficit Index (SDTI), the Standardized Humidity–Temperature Deficit Index (SDHTI), and the Standardized Atmosphere–Soil Index (SASI). Based on these indices and run theory, this study revealed the spatial distribution characteristics of different drought types (general, atmospheric, and composite) in terms of intensity, frequency, severity, and duration. Furthermore, the Mann–Kendall test and random forest analysis were applied to investigate drought trends and primary driving factors. The results indicate that droughts in the SKA exhibit significant regional characteristics and an overall worsening trend. Among them, droughts in karst-developed regions are generally more severe, though their manifestations vary across areas: compound droughts are particularly severe on the western Sichuan Plateau but relatively mild in Guangxi. In contrast, atmospheric droughts are more pronounced in Guangxi. Regarding trends, the rate of drought intensification was relatively moderate in Guangxi and the western Sichuan Plateau but more pronounced in other regions, with the maximum increase reaching 0.59. However, this upward trend is not statistically significant. Additionally, drought in karst areas was characterized by high frequency and intensity but shorter duration and lower severity, whereas the opposite was true in non-karst areas. Random forest analysis revealed that temperature is the primary driver of SDTI (2.60), while relative humidity and temperature have significant impacts on SDHTI (3.21 and 2.42, respectively). Soil moisture and temperature contribute most significantly to SASI (2.08 and 1.48, respectively). These findings provide important insights to guide the rational allocation of regional water resources and optimize agricultural management strategies.