Junqiang Yao

Dr. Junqiang Yao

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2018 in Science of The Total Environment
Verified
Journal Article
Closed access
JYJunqiang Yao
Junqiang Yao
YZYong Zhao
Yong Zhao
Ya-ning ChenYa-ning Chen
Ya-ning Chen
XYXiaojing Yu
Xiaojing Yu
Ruibo ZhangRuibo Zhang
Ruibo Zhang

1 June 2020 in Journal of Hydrology
Verified
Journal Article
Closed access
JYJunqiang Yao
Junqiang Yao
YCYaning Chen
Yaning Chen
YZYong Zhao
Yong Zhao
XGXuefeng Guan
Xuefeng Guan
WMWeiyi Mao
Weiyi Mao
LYLianmei Yang
Lianmei Yang

1 April 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
JYJunqiang Yao
Junqiang Yao
WHWenfeng Hu
Wenfeng Hu
Ya-ning ChenYa-ning Chen
Ya-ning Chen
WHWen Huo
Wen Huo
YZYong Zhao
Yong Zhao
QYQing Yang
Qing Yang

1 August 2016 in Global and Planetary Change
Verified
Journal Article
Closed access
JYJunqiang Yao
Junqiang Yao
QYQing Yang
Qing Yang
WMWeiyi Mao
Weiyi Mao
YZYong Zhao
Yong Zhao
XXXinbing Xu
Xinbing Xu

31 August 2021 in Journal of Geographical Sciences
Verified
Journal Article
Closed access
PDF file
JYJunqiang Yao
Junqiang Yao
WMWeiyi Mao
Weiyi Mao
JCJing Chen
Jing Chen
TDTuoliewubieke Dilinuer
Tuoliewubieke Dilinuer

25 January 2021 in PeerJ
Verified
Journal Article
Open access
PDF file
WHWenfeng Hu
Wenfeng Hu
JYJunqiang Yao
Junqiang Yao
HQHe Qing
He Qing
JCJing Chen
Jing Chen
Xinjiang is a major part of China’s arid region and its water resource is extremely scarcity. The change in precipitation amounts and extremes is of significant importance for the reliable management of regional water resources in this region. Thus, this study explored the spatiotemporal changes in extreme precipitation using the Mann–Kendall (M–K) trend analysis, mutation test, and probability distribution functions, based on the observed daily precipitation data from 89 weather stations in Xinjiang, China during 1961–2018. We also examined the correlations between extreme precipitation and climate indices using the cross-wavelet analysis. The results indicated that the climate in Xinjiang is becoming wetter and the intensity and frequency of extreme precipitation has begun to strengthen, with these trends being more obvious after the 1990s. Extreme precipitation trends displayed spatial heterogeneity in Xinjiang. Extreme precipitation was mainly concentrated in mountainous areas, northern Xinjiang, and western Xinjiang. The significant increasing trend of extreme precipitation was also concentrated in the Tianshan Mountains and in northern Xinjiang. In addition, the climate indices, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Multivariate ENSO Index and Indian Ocean Dipole Index had obvious relationships with extreme precipitation in Xinjiang. The relationships between the extreme precipitation and climate indices were not clearly positive or negative, with many correlations advanced or delayed in phase. At the same time, extreme precipitation displayed periodic changes, with a frequency of approximately 1–3 or 4–7 years. These periodic changes were more obvious after the 1990s; however, the exact mechanisms involved in this require further study.