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您选择的条件: LI Lanhai(3)
  • Projection of hydrothermal condition in Central Asia under four SSP-RCP scenarios

    分类: 地球科学 >> 地理学 提交时间: 2022-05-30 合作期刊: 《干旱区科学》

    摘要:

    Abstract: Hydrothermal condition is mismatched in arid and semi-arid regions, particularly in Central Asia (including Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, and Turkmenistan), resulting many environmental limitations. In this study, we projected hydrothermal condition in Central Asia based on bias-corrected multi-model ensembles (MMEs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios (SSP126 (SSP1-RCP2.6), SSP245 (SSP2-RCP4.5), SSP460 (SSP4-RCP6.0), and SSP585 (SSP5-RCP8.5)) during 2015–2100. The bias correction and spatial disaggregation, water-thermal product index, and sensitivity analysis were used in this study. The results showed that the hydrothermal condition is mismatched in the central and southern deserts, whereas the region of Pamir Mountains and Tianshan Mountains as well as the northern plains of Kazakhstan showed a matched hydrothermal condition. Compared with the historical period, the matched degree of hydrothermal condition improves during 2046–2075, but degenerates during 2015–2044 and 2076–2100. The change of hydrothermal condition is sensitive to precipitation in the northern regions and the maximum temperatures in the southern regions. The result suggests that the optimal scenario in Central Asia is SSP126 scenario, while SSP585 scenario brings further hydrothermal contradictions. This study provides scientific information for the development and sustainable utilization of hydrothermal resources in arid and semi-arid regions under climate change.

  • Characteristics and hazards of different snow avalanche types in a continental snow climate region in the Central Tianshan Mountains

    分类: 地球科学 >> 地理学 提交时间: 2021-04-30 合作期刊: 《干旱区科学》

    摘要:Snow avalanches are a common natural hazard in many countries with seasonally snow-covered mountains. The avalanche hazard varies with snow avalanche type in different snow climate regions and at different times. The ability to understand the characteristics of avalanche activity and hazards of different snow avalanche types is a prerequisite for improving avalanche disaster management in the mid-altitude region of the Central Tianshan Mountains. In this study, we collected data related to avalanche, snowpack, and meteorology during four snow seasons (from 2015 to 2019), and analysed the characteristics and hazards of different types of avalanches. The snow climate of the mid-altitude region of the Central Tianshan Mountains was examined using a snow climate classification scheme, and the results showed that the mountain range has a continental snow climate. To quantify the hazards of different types of avalanches and describe their situation over time in the continental snow climate region, this study used the avalanche hazard degree to assess the hazards of four types of avalanches, i.e., full-depth dry snow avalanches, full-depth wet snow avalanches, surface-layer dry snow avalanches, and surface-layer wet snow avalanches. The results indicated that surface-layer dry snow avalanches were characterized by large sizes and high release frequencies, which made them having the highest avalanche hazard degree in the Central Tianshan Mountains with a continental snow climate. The overall avalanche hazard showed a single peak pattern over time during the snow season, and the greatest hazard occurred in the second half of February when the snowpack was deep and the temperature increased. This study can help the disaster and emergency management departments rationally arrange avalanche relief resources and develop avalanche prevention strategies.

  • Environmental factors influencing snowfall and snowfall prediction in the Tianshan Mountains, Northwest China

    分类: 地球科学 >> 地理学 提交时间: 2019-01-17 合作期刊: 《干旱区科学》

    摘要: Snowfall is one of the dominant water resources in the mountainous regions and is closely related to the development of the local ecosystem and economy. Snowfall predication plays a critical role in understanding hydrological processes and forecasting natural disasters in the Tianshan Mountains, where meteorological stations are limited. Based on climatic, geographical and topographic variables at 27 meteorological stations during the cold season (October to April) from 1980 to 2015 in the Tianshan Mountains located in Xinjiang of Northwest China, we explored the potential influence of these variables on snowfall and predicted snowfall using two methods: multiple linear regression (MLR) model (a conventional measuring method) and random forest (RF) model (a non-parametric and non-linear machine learning algorithm). We identified the primary influencing factors of snowfall by ranking the importance of eight selected predictor variables based on the relative contribution of each variable in the two models. Model simulations were compared using different performance indices and the results showed that the RF model performed better than the MLR model, with a much higher R2 value (R2=0.74; R2, coefficient of determination) and a lower bias error (RSR=0.51; RSR, the ratio of root mean square error to standard deviation of observed dataset). This indicates that the non-linear trend is more applicable for explaining the relationship between the selected predictor variables and snowfall. Relative humidity, temperature and longitude were identified as three of the most important variables influencing snowfall and snowfall prediction in both models, while elevation, aspect and latitude were of secondary importance, followed by slope and wind speed. These results will be beneficial to understand hydrological modeling and improve management and prediction of water resources in the Tianshan Mountains.