Stable Isotope Characteristics for Precipitation Events and Their Responses to Moisture and Environmental Changes During the Summer Monsoon Period in Southwestern China
Yue Hu 2
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State Key laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
College of Water Resource and Hydropower, Sichuan University, Chengdu, China
Guodong Liu   

State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, No.24 South Section 1, Yihuan Road, Chengdu , Chin, 610065, Chengdu, China
Submission date: 2019-04-06
Final revision date: 2019-06-19
Acceptance date: 2019-07-02
Online publication date: 2020-02-06
Publication date: 2020-03-31
Pol. J. Environ. Stud. 2020;29(3):2429–2445
Samples of hydrogen and oxygen stable isotopes in precipitation collected and analyzed during the summer monsoon in 2017 and 2018 in Chengdu are reported in this paper. Increasing (decreasing) trends of isotope values (δD and δ18O) occur from May to June (September to October), and the valleys occur from July to August. The correlation between δD and δ18O for both precipitation events and monthly average precipitation is significant, with high R2 values (≥0.98). The differences in regression lines may be due to the comprehensive influence of moisture sources, transport path and sub-cloud processes. Combining the d-excess values of precipitation and air mass trajectories generated by the HYSPLIT model, precipitation with a low (high) d-excess value and a more (less) negative δ18O corresponds to moisture from ocean (inland) sources. The δ18O–temperature (T) and δ18O–precipitation (P) correlations are not significant and vary greatly among different periods, which may be attributed to the mutual masking of different effects and the influence of atmospheric circulation processes. The results imply that the negative values in biological and geological proxies may be related to warmer climate, higher precipitation and a larger contribution of oceanic monsoon precipitation, but cannot indicate the changes in temperature and precipitation quantifiably.