Snowmelt water in spring is an important source of soil water, which is critical to supporting crop growth. Quantifying the contribution of snowmelt water to soil water and its dynamic changes is essential for evaluating soil moisture and allocating agricultural water resources. In this paper, through controlled outdoor experiments, different snow depths and soil depth gradients were set; and snow, precipitation, and soil samples were collected regularly. To analyze the contribution of snowmelt water to soil water and its dynamic changes, the MAT-253 stable isotope ratio mass spectrometer was adopted for hydrogen and oxygen isotope analyses. The results showed that the snowmelt water for snow depths of 10 cm, 30 cm, and 50 cm all contributed to the 0–30 cm soil layer. The contribution increased with soil depth, contributing 8.13%, 8.55%, and 11.24%, respectively. The contribution of the snow cover at the same depth to the soil moisture at different depths also varied, i.e., the contribution increased with increasing soil depth. The snowmelt water retention time at depths of 10 cm, 30 cm, and 50 cm was inconsistent, i.e., it was the longest at 0–10 cm (average of 69 days), followed by 20–30 cm (average of 59 days), and the shortest at 10–20 cm (average of 54 days). The greater the snow depth, the shorter the retention time of the snowmelt water in the different soil layers. For surface soil, the contribution of the snowmelt water at greater depths was significantly different; while for deep soil, the contribution was more sensitive to the snow depth. Regardless of snow depth, soil contributions at different depths were significantly different. Precipitation also affected the contribution of the snowmelt water to the soil water, exhibiting different effects at different depths.

In this study, on the basis of the temperature data collected at 612 meteorological stations in China from 1961 to 2019, cold regions were defined using three indicators: an average temperature of <−3.0 °C during the coldest month; less than five months with an average temperature of >10 °C; and an annual average temperature of ≤5 °C. Spatial interpolation, spatial superposition, a trend analysis, and a spatial similarity analysis were used to obtain the spatial distribution of the cold regions in China from 1961 to 2019. Then, the areas of the cold regions and the spatial change characteristics were analyzed. The results reveal that the average area of the cold regions in China from 1961 to 2019 was about 427.70 × 10⁴ km², accounting for about 44.5% of the total land area. The rate of change of the area of the cold regions from 1961 to 2019 was −14.272 × 10⁴ km²/10 a, exhibiting a very significant decreasing trend. On the basis of the changes between 1991–2019 and 1961–1990, the area of China’s cold regions decreased by 49.32 × 10⁴ km². The findings of this study provide references for studying changes in the natural environment due to climate change, as well as for studying changes on a global scale.

Peanut growth in Shandong Province, a major peanut-producing area in China, is greatly affected by drought. The present study uses hierarchical analysis, weighted comprehensive evaluation, and ArcGIS spatial analysis to conduct spatial zoning of peanut drought risk in Shandong Province based on daily precipitation data for the province acquired from 1991 to 2020, the per capita GDP, and the peanut planting area of Shandong Province, so as to quantify the disaster risk of peanut drought and formulate disaster prevention and resilience planning accordingly. The results show the high-drought-risk zone was mainly distributed in the northwestern part of Shandong Province and on the Jiaodong Peninsula, covering 32.4% of the province. Drought risk was concentrated on the Jiaodong Peninsula, covering 20.7% of the province. The high-vulnerability zone was mainly distributed in the cities of Yantai, Weihai, Linyi, and Rizhao, accounting for 26.8% of the total area. The low-disaster-prevention and low-mitigation-capacity zone was mainly distributed in the western part of Shandong Province, covering 38.7% of the province. Medium- and high-risk areas for drought affecting peanuts were widely distributed, while the overall comprehensive risk index was high, covering 76.2% of the province. Spatial analysis to conduct risk zoning and assessment of peanut drought in Shandong Province, so as to provide a basis for peanut drought disaster prevention and safe peanut production in Shandong Province.

As a major agricultural province of China, Shandong province has long ranked first in agricultural growth value among all of the provinces; at the same time, it is also the province that is most affected by dry-hot wind. Therefore, it is of great significance to study the spatial zoning of the risks of dry-hot wind in this province. Based on meteorological, slope, and altitude data, and the principle of disaster risk assessment, this study uses a weighted comprehensive evaluation method, analytic hierarchy process, and ARC-GIS spatial analysis to study the spatial zoning of the risks of dry-hot wind in Shandong province. The results show that the high-risk regions of dry-hot wind are concentrated in the north-central portion of the province, the medium-risk regions are in the peripheral areas, and the low-risk regions are located mainly in the west, southwest, and east. Exposure of disaster-bearing bodies is high in the south and low in the north, while vulnerability to disaster-bearing bodies is high in the west and low in the east. The more developed areas in the east show high disaster prevention and mitigation capability, whereas this is weak in the west. In summary, dry-hot wind risk in Shandong province varies significantly by area. The medium- and high-risk areas are mainly in the west and central portions of the province.