Global warming has led to an increasing frequency and intensity of extreme precipitation events worldwide. The extreme precipitation of Henan Province in central China usually occurs in summer, with the climate transition from the northern subtropical to the warm temperate climate. Compared with the study of extreme precipitation events in other regions, the study of Henan Province pays less attention. In order to systematically understand the spatial and temporal characteristics of extreme precipitation in Henan Province, this study applied RClimDex model to obtain nine extreme precipitation indices based on daily precipitation data from 90 meteorological stations from 1981 to 2020. Linear propensity estimation, M-K mutation test, Morlet wavelet analysis, and geostatistical analysis were used to investigate the spatial and temporal variation characteristics of the extreme precipitation indices in the region. The results indicated that continuous dry days (CDD), number of heavy rain days (R20mm), maximum daily precipitation (Rx1day), maximum precipitation for 5 consecutive days (Rx5day), and precipitation intensity (SDII) showed an overall increasing trend, but none passed the significance test (p > 0.01). Extremely strong precipitation (R99p) and Rx5day changed abruptly in 1994, and Rx1day and SDII changed abruptly in 2004. The seven extreme precipitation indices, except CDD and continuous wet days (CWD), had a 30-year cyclical pattern. The multi-year average of extreme precipitation indices showed that the CDD gradually decreased from north to south, CWD and R20mm gradually increased from north to south. Rx1day and Rx5day gradually increased from northwest to southeast, and SDII increased from west to east. The results can contribute valuable insights to extreme precipitation trends and future climate predictions in Henan Province and provide scientific support for coping with extreme precipitation changes and disaster prevention.

Erosive rainfall is essential for initiating surface runoff and soil erosion to occur. The analysis on its temporal and spatial distribution characteristics is crucial for calculating rainfall erosivity, predicting soil erosion, and implementing soil and water conservation. This study utilized daily rainfall observation data from 90 meteorological stations in Henan from 1981 to 2020, and conducted geostatistical analysis, M-K mutation test analysis, and wavelet analysis on erosive rainfall to reveal the spatiotemporal distribution characteristics over the past 40 years. Building on this foundation, the correlation between erosive rainfall, rainfall, and rainfall erosivity were further explored. The findings indicated that the average annual rainfall in Henan Province varied between 217.66 mm and 812.78 mm, with an average yearly erosive rainfall of 549.24 mm and a standard deviation of 108.32 mm. Erosive rainfall constitutes for 77% of the average annual rainfall on average, and the analysis found that erosive rainfall is highly correlated with rainfall volume. The erosive rainfall increased from northwest to southeast, and had the same spatial distribution characteristics as the total rainfall. The number of days with erosive rainfall was 20.5 days and the annual average sub-erosive rainfall was 26.86 mm. The average annual rainfall erosivity in Henan Province ranged from 1341.81 to 6706.64 MJ·mm·ha⁻¹·h⁻¹, averaging at 3264.63 MJ·mm·ha⁻¹·h⁻¹. Both the erosive rainfall and the rainfall erosivity are influenced by the monsoon, showing a unimodal trend, with majority of the annual total attributed to rainfall erosivity from June to September, amounting to 80%. The results can provide a basis for forecasting of heavy rainfall events, soil conservation and planning, ecological treatment, and restoration.

Introduction: The Yuanjiang dry–hot valley area of China serves as a vital ecological functional zone and a typical ecologically fragile area, where drought constitutes a significant factor affecting both the ecological environment and agricultural production. Conducting an in–depth analysis of drought variation trends across spatiotemporal scales and exploring its primary driving factors in this region will provide a scientific reference for regional drought monitoring and warning, drought prevention and disaster reduction efforts.Methods: By analyzing the Temperature Vegetation Dryness Index (TVDI) constructed from the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) from 2000 to 2020, combined with Theil–Sen trend analysis method, M–K trend test, stability analysis, Hurst index, and geographic detector, the characteristics, future evolution trends, and influencing factors of drought spatiotemporal changes in the Yuanjiang dry–hot valley area were analyzed from a spatiotemporal perspective.Results: The results indicated that (1) the average TVDI in the Yuanjiang dry–hot valley area from 2000 to 2020 was 0.67, showing a moderately dry state as a whole, and it was slowly decreasing at a rate of 0.0011 per year, indicating that the drought situation has eased. (2) The TVDI showed a trend of a slow increase in the northwest and a slow decrease in the southeast area, with a relatively high stability. In the future, the TVDI in the northwest of the study area will weakly and continuously increase, while the TVDI in the southeast will weakly and continuously decrease. The future changes are also relatively stable. (3) In the Yuanjiang dry–hot valley area, potential evapotranspiration, precipitation, and temperature are key factors influencing TVDI. Among these, potential evapotranspiration is the most significant factor, with a q value of 0.3768. The interaction effects between factors exceed the influence of any single factor, particularly the interaction between potential evapotranspiration and GDP, which shows the strongest effect (q value is 0.490).Discussion: The results in the study indicated that the future trend of drought changes was highly uncertain. The future changes in drought conditions still require continuous attention. Cultivated land and woodland exhibited the highest contribution rate to TVDI. Natural factors exert a strong influence on drought conditions, while the impact of human factors remains less pronounced.

To control soil erosion, the intensity, area, and distribution of regional soil erosion must be determined to accurately plan and implement corresponding soil conservation measures. Therefore, regional soil erosion assessment has received extensive attention worldwide. At present, a sampling survey approach and full-coverage grid-based calculation are mainly applied in regional soil erosion assessment. The quantitative evaluation of the entire region depends on the quality of the data source. Furthermore, owing to the greatness of the evaluation object, the difficulty of data acquisition, the high cost, and poor usability, the present approach is bound to be at the expense of data accuracy, spatial resolution, time resolution, etc. The sampling survey approach can obtain high-precision data of soil erosion factors. Therefore, it can accurately quantify soil erosion in a field investigation unit. However, the sampling method, sampling density, and extrapolation methods have a significant impact on regional soil erosion assessments. This study considers the case of Baiquan County in the rolling hills of Northeast China as an example. Regional soil erosion evaluation using sampling survey and grid computing were compared. The impact of the data source accuracy on the soil erosion assessment was also quantitatively evaluated. The results of grid method showed a phenomenon of large rates of soil erosion and the ratio of the soil erosion area (the share of areas above the mild level), which were overestimated by 20% and 6%, respectively. A digital elevation model (DEM) with a resolution of 30 m can be used for soil erosion evaluation in plain areas, but that with the same resolution in hilly areas has insufficient calculation accuracy and provides large errors. The grid method can be adopted when land use and soil conservation measures are accurate. Otherwise, the sampling method is recommended. Interpolation of the ratio of the soil erosion area in the survey unit based on land use can better evaluate regional soil erosion.

China’s North-South Transition Zone is a critical ecological transition region, marked by complex environments, climatic sensitivity, and transitional characteristics. To investigate the effects of individual rainfall events on runoff generation and sediment yield across different slopes and land uses within this zone, the study collected data from slope runoff plots (20 m in length and 5 m in width, measured as horizontal projection) at three monitoring stations (Luoshan, Lushan, Shanzhou) between 2014 and 2023. Rainfall events were classified via K-means clustering. Regression and correlation analyses were applied to reveal the effects of rainfall characteristics, slope gradient and land use type (grass land, dry land, forest land, bare land and natural vegetation) on runoff and sediment. The results indicate that: (1) The most frequent rainstorms were Type C (short, low-intensity, low-volume, low-erosivity events). (2) The runoff depth of bare land is 3.6, 2.3, and 2 times that of forest land, dry land, and natural vegetation, respectively. Similarly, its sediment concentration is 134, 13, and 16 times higher, respectively. Grassland, however, showed markedly lower levels of both runoff and sediment. (3) Rainfall intensity was significantly correlated with runoff and sediment across slopes. Runoff depth depended mainly on rainfall amount. While Type A (prolonged, high-intensity) caused peak runoff, Type D (moderate but intense and erosive) yielded the highest sediment. (4) Sediment reduction efficiency (sediment reduction compared to bare land under identical conditions) consistently surpassed runoff reduction across all land types, with grassland showing the highest efficiency for both. For soil and water conservation, grass-planting was the most effective measure on 10° and 15° slopes, whereas both afforestation and grass-planting were optimal on the 25° slopes.