Characteristics of climate change in Pangduo Reservoir in Tibet and its impact analysis
This study aims to further explore the impact of the construction and operation of the Pangduo Reservoir on the local climate of the reservoir area and its surrounding areas,and to provide a reference for decision-making on the ecological environmental impact assessment of the construction of large-scale water conservancy facilities on the plateau.Based on the basic data of daily mean temperature,precipitation,relative humidity and maximum wind speed from 2018 to 2022,the linear tendency estimation method in climatology statistics is used in this study,the change trend of climate factors and its influence in the past 5 years after the reservoir was built and operated were analyzed.The results show that the annual average temperature of Pangduo Reservoir shows an upward trend with an annual increase range of 0.13℃.The annual average temperature difference between the near and far reservoir areas shows an obvious downward trend,After the completion and operation of the reservoir,the local temperature of the surrounding area will be increased;The annual decrease was 47.5 mm.The ratio of annual average precipitation in the near and far reservoir areas shows an obvious decreasing trend,and the local precipitation has a decreasing trend after the construction and operation of the reservoir,while the annual average relative humidity of the Pangduo Reservoir shows a decreasing trend,and the annual decrease is 0.9%.The annual average relative humidity ratio in the near and far reservoir areas shows an increasing trend,and the local average relative humidity tends to increase after the operation of the reservoir.The annual average maximum wind speed of Pangduo Reservoir shows an increasing trend year by year,with an annual increasing range of 0.3 m/s.The results show that the local temperature rises,precipitation and relative humidity decreases after the construction and operation of Pangduo Reservoir,and the climate of Pangduo Reservoir shows a warm and dry trend.
NETL
NSTL
万方数据
