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DEVIATIONS IN GRIDDED FIELD MEASUREMENTS OF GROUND TEMPERATURE AND ACTIVE LAYER THICKNESS IN WUDAOLIANG BASIN, QINGHAI-TIBET PLATEAU

Session: Permafrost Degradation I / Dégradation du pergélisol I

guoan YIN, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences (China)
Fujun Niu, State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences (China)
Jing Luo, State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences (China)
Zhanju Lin, State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences (China)
Bingzhuo Yang, Lanzhou University (China)
Minghao Liu, State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences (China)
Anyuan Li, State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences (China)

Ground temperatures were measured with 60 boreholes at four study sites (1, 2, 3, and 4). Under the similar climate condition, the ground surface temperatures in the same site from 15 boreholes were not similar. There is a maximum difference of 2.4°C at site 1 (alpine meadow with rock grids), 2.6 °C at site 2 (alpine meadow), 3.0 °C at site 3 (transitional area), and 3.1 °C at site 3 (alpine grassland), respectively. The active layer thickness measured from 15 boreholes is also have a maximum deviation of 118.0 cm at site 1, 78.5 cm at site 2, 64.0 cm site 3 and 65.0 cm site 4. The climate changing, soil moisture content loss and the environmental variables (thermokarst, strong sand wind, and vegetation degeneration) may be the main reason for these deviations, which should be better evaluated when mapping the permafrost spatial distribution and assessing local factors influence