Characteristics of spatio temporal variations of surface aridity index and its response to meteorological factors in the upper reaches of the Yangtze River
The upper reaches of the Yangtze River is an important water resources area in china, revealing the evolution of its surface aridity under the background of global warming is of great significance to the prevention and control of flood and drought disasters in the basin, the protection of ecological environment and rational development and utilization of water resources. Based on the monthly meteorological data from 67 weather stations in the upper reaches of the Yangtze River from 1961 to 2019, the Penman-Monteith model was adopted to calculate the potential evapotranspiration, and then the surface aridity index (AI), climate tendency rate, accumulative anomaly method, sliding t test, Mann-Kendall test and Morlet wavelet method were combined to analyze the characteristics of AI spatio temporal changes, and the climate sensitivity coefficient method was used to assess the sensitivity of AI to the major meteorological factors, by which the contribution rate of each meteorological factor to AI changes was quantified. The results show that the annual average precipitation in the upper reaches of the Yangtze River decreased significantly at a rate of 0.809 mm/10a (P＜0.05), the potential evapotranspiration increased significantly at a rate of 0.946 mm/10a (P＜0.05), and the average AI decreased at a rate of 0.014/10a, with a main cycle of about 23 a and an abrupt change in 1998. Seasonal changes of AI were significant, resulting in dry winters and springs, and relatively humid summers and autumns. The distribution of multi year average AI of the basin generally increased from southeast to northwest. The area of semi arid and semi humid regions accounted for 47.8% and 40.7% respectively. The number of sunshine hours and average temperature were the main influencing factors of AI changes in the northwestern part of the study area, whereas wind speed and relative humidity were the main influencing factors of AI changes in the southeast.