 摘要： Hulun Lake, which is an important carrier of water resources in Hulunbuir Grassland and also a significant barrier in the northern ecosystems, plays a crucial role in supporting regional ecological environment, climate, and biodiversity conservation. In this paper, the application of satellite remote sensing technology in the monitoring and early warning of water dynamics, water quality and water environment, lake ice phenology, and ecosystem in Hulun Lake was studied, and high-resolution and comprehensive lake information can be obtained. It can provide strong technical support for lake supervision, maintenance and management.

 摘要： Based on the observation data of hourly precipitation and the dual polarization data of the new generation of weather radar in Yushu area from 2022 to 2023, the radar characteristics of 18 short-term heavy precipitation processes were studied through mathematical statistics and comparative analysis of cases. There were four radar detection ranges: within 50 km, within 100 km, within 150 km and beyond 150 km. The evolution laws of echo intensity, echo top height, vertically integrated liquid water (VIL), radial velocity, and dual polarization parameters at different distances were mainly analyzed. The results show that there were significant differences in the radar characteristics of short-term heavy precipitation at different detection distances. Moreover, dense flat large particles, echo parameters with specific thresholds, and appropriate movement speed were important conditions for the occurrence of short-term heavy precipitation. Meanwhile, the radar determination thresholds for short-term heavy precipitation at various detection distances were extracted to provide a scientific basis for the near-term forecast and early warning of short-term heavy precipitation in Yushu area.

 摘要： Based on the ERA-5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), the development mechanisms of explosive cyclones in the Kuroshio Current area from 2000 to 2015 were classified, and the characteristics of these explosive cyclones were analyzed by using diagnostic analysis, statistical analysis and linear fitting analysis methods. The results show that absolute vorticity advection, temperature advection, and non-adiabatic heating were the three main factors affecting the explosive development of cyclones. The development mechanisms of explosive cyclones in the Kuroshio Current area can be classified into three major categories, that is, the explosive cyclones were  dominated by a single factor, two factors, or multiple factors. The explosive cyclones dominated by a single factor were mainly weak or medium, while there were fewer strong explosive cyclones and no super explosive cyclones. Among these explosive cyclones, the explosive cyclones dominated by absolute vorticity advection were the weakest, while the strongest explosive cyclones were dominated by non-adiabatic heating. The proportion of strong and supper explosive cyclones dominated by two factors was over 60%. The combination of two factors was more likely to generate strong explosive cyclones than the single-factor dominant type and the combination of three factors, among which the impact was the greatest under the combined effect of temperature advection and non-adiabatic heating. Through statistical analysis, it is concluded that non-adiabatic heating contributed the most to the explosive development of cyclones in the Kuroshio Current area, while vorticity advection had the least impact, and temperature advection had a considerable effect. In terms of seasonal characteristics, the explosive cyclones in the Kuroshio Current area mostly appeared in spring, followed by winter, while there were basically no explosive cyclones in summer and autumn.

 摘要： From June 23 to 27, 2025, the 11th Ecosystem Services Partnership World Conference (ESP11) was held at the Darwin Convention Centre in Australia, with the theme of "From global to local ecosystem services: pathways to Nature-based Solutions inspired from Down Under". As the founder of the theory of soil and water ecology, the author was invited to attend the conference and delivered an English academic report at the B2-Healing riverscapes venue. Before and after the conference (June 19- July 5, 2025), the author also conducted soil and water ecological investigations in various locations such as Australia's Great Ocean Road, Penguin Island, Kiama Blowhole, and Kakadu National Park. The insights from the Australia investigation regarding soil and water ecology are: ① preserving the native soil and water ecology; ② protecting the culture of soil and water ecology; ③ achieving both ecological and economic benefits. The soil and water ecological insights from the International Conference on Healing Riverscapes include: ① advocating for near-natural engineering methods; ② integrating river healing techniques, methods, and philosophies with community needs; ③ emphasizing flood mitigation and disaster resilience; ④ valuing the cultural heritage of indigenous peoples in protecting the soil and water ecosystem; and ⑤ maintaining the health of river ecosystems. Theory and practice demonstrate that the theory of soil and water ecology is a theoretical distillation of nature-based solutions (NbS), serving as a common theoretical foundation in the field of ecological environment and possessing universal significance globally.

 摘要： The study of ecological water demand in rivers has been a research hotspot in recent years. In this paper, selecting the widely used research methods (Tennant method, minimum monthly flow average measurement method, monthly average flow guarantee rate method, monthly minimum flow method, 7Q10 improvement method), the ecological water demand of rivers in the Dongting Lake basin was studied. Combined with the hydrological characteristics of the basin water system, the calculation results by the above five methods were averaged. It was obtained that the ecological water demand of rivers in the basin from April to September and from October to next March was 3.876×109 and 3.425×109 m3, respectively. The annual ecological water demand was 7.301×109 m3, accounting for about 11.46% of the average annual runoff in the basin. The research results can provide a basis for regional water resource utilization planning and are of great significance for maintaining the health of river ecosystems.

 摘要： Based on MODIS NDVI data and sunshine hours data from 2000 to 2019, using mathematical statistical methods, the monthly variations in vegetation and sunshine hours in the Beijiang River basin were primarily analyzed, as well as the response relationship between the two. The results showed that: ① the annual average NDVI of the basin was 0.58. In terms of intra-annual distribution, the lowest value was recorded in February (0.41), and it gradually increased from February to September, reaching the highest value in September (0.72). Then, it gradually decreased from September to next February. The overall NDVI of the basin showed a fluctuating upward trend. From an intra-annual perspective, it increased rapidly in the second half of the year (July to December). Areas with low vegetation coverage were mainly distributed in the southern part of the basin and the valley plains in the central and northern parts. ② The average annual sunshine hours was 1 595.80 h, but there were significant variations between years, and the overall trend of annual sunshine hours was a decline. NDVI and sunshine hours were primarily positively correlated, with a stronger correlation from January to June.

 摘要： Based on the data of the national station in Wengyuan County from 1975 to 2024, the tourism climate comfort of Wengyuan County was analyzed and evaluated by using temperature-humidity index, wind chill index, holiday climate index, and linear trend analysis. The results show that in Wengyuan County, people felt most comfortable in April, May, October, and November, and the holiday climate index in each month was over 63, reaching or exceeding the "suitable" level, and there were no "acceptable" or lower levels. Spring and autumn were the best time for people to visit Wengyuan. The temperature-humidity index in Wengyuan County rose significantly at a tendency rate of 0.19/10 a, while wind chill index dropped significantly at a tendency rate of 2.9/10 a. The annual average number of comfortable days in Wengyuan was up to 164 d, accounting for over 44.9% of the total number in the whole year. It tended to decline at a tendency rate of -3.9/10 a. The annual average number of uncomfortable cold days and uncomfortable hot days showed an upward trend at a tendency rate of 1.5/10 a and 1.7/10 a, respectively. HCL and the number of days with unfavorable climate tended to decline slowly at a tendency rate of -0.236/10 a and -0.248/10 a, respectively. The number of days with suitable climate showed an upward trend at a tendency rate of 1.2/10 a, while the number of days with general and acceptable climate showed a slow downward trend at a tendency rate of -1.96/10 a.

 摘要： Vegetation not only plays a critical role in regulating regional climate, hydrological cycles, carbon sequestration, and oxygen release, but also is directly linked to ecosystem stability and regional sustainable development. In this study, based on the data of kNDVI in Jiangsu Province (an economically developed coastal region in eastern China) from 2002 to 2022, the spatial and temporal dynamics of vegetation in the province were systematically analyzed by using the Theil- Sen slope estimation and Mann – Kendall trend test methods. The results indicate that vegetation coverage in Jiangsu Province generally followed a trend of “fluctuation in the early period and improvement in the later period” from 2002 to 2022. Spatially, kNDVI changes exhibited clear heterogeneity, with an overall pattern of “decline in the south, increase in the north, and stability in the central region”. Based on the 21-year mean of kNDVI, it is found that  vegetation conditions were relatively better in northern and central Jiangsu, while lower mean of kNDVI was observed in southern Jiangsu (e.g., Suzhou, Wuxi, and Changzhou), reflecting the pressure of accelerating urbanization on green space coverage. Further investigation into the driving factors of changes in vegetation reveals that social factors had the strongest influence, with a path coefficient of −0.86, followed by topographic and climatic factors. This spatial differentiation pattern and the identified driving factors highlight ongoing conflicts between the economic development and ecological conservation in Jiangsu Province. In the future, land use structure should be optimized based on local conditions, and coordinated development between ecological restoration and urban expansion should be strengthened.

 摘要： With the rapid development of artificial intelligence technology, the education sector is gradually exploring how AI tools to empower subject teaching. In this paper, the first lesson of Japan published by People's Education Press in the second semester of seventh grade is taken as an example, focusing on the feasibility of using AI tools for lesson preparation. Through the Meta Sota AI special topic, Kimi, deepseek, and Baidu AI images, lesson preparation is completed. Using Coze intelligent agents, interactive learning scenarios are developed to complete teaching design. Research has shown that AI technology can effectively improve the efficiency and quality of lesson preparation, and can assist in the implementation of core competencies in geography. This paper can provide a reference for the operability of AI empowering educational and teaching activities.

 摘要： Prediction of wind speed at high plateau airports can not only provide certain theoretical basis for the safe and efficient operation of the airports, but also save cost and time for their flight scheduling. In this paper, based on the data of average wind speed and related meteorological factors at the meteorological station of Lhasa Gonggar airport from 1964 to 2019, a prediction model of wind speed was constructed based on the support vector regression (SVR) algorithm. After the analysis of correlations between various meteorological features, significant features were selected by the random forest algorithm, thereby further improving the prediction performance of the model. The results indicate that both visibility and temperature having high correlations with wind speed are key features determining the final accuracy of the prediction model. Meanwhile, compared with other machine learning algorithms, the SVR algorithm represents more highlighted prediction performance for small sample data.