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Detection of Anomalies and Changes of Rainfall in the Yellow River Basin, China, through Two Graphical Methods

by Hao Wu 1,2, Xinyan Li 1,2 and Hui Qian 1,2,*
1
School of Environmental Science and Engineering, Chang’an University, Xi’an 710054, China
2
Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang’an University, Xi’an 710054, China
*
Author to whom correspondence should be addressed.
Water 2018, 10(1), 15; https://doi.org/10.3390/w10010015
Received: 20 November 2017 / Revised: 15 December 2017 / Accepted: 18 December 2017 / Published: 25 December 2017
This study aims to reveal rainfall anomalies and changes over the Yellow River Basin due to the fragile ecosystem and rainfall-related disasters. Common trend analyses relate to overall trends in mean values. Therefore, we used two graphical methods: the quantile perturbation method (QPM) was used to investigate anomalies over time in extreme rainfall, and the partial trend method (PTM) was used to analyze rainfall changes at different intensities. A nonparametric bootstrap procedure is proposed in order to identify significant PTM indices. The QPM indicated prevailing positive anomalies in extreme daily rainfall 50 years ago and in the middle reaches during the 1970s and 1980s. The PTM detected significant decreases in annual rainfall mainly in the latter half of the middle reaches, two-thirds of which occurred in high and heavy rainfall. Most stations in the middle and lower reaches showed significant decreases in rainy days. Daily rainfall intensity had a significant increase at 13 stations, where rainy days were generally decreasing. The combined effect of these opposing changes explains the prevailing absence of change in annual rainfall, and the observed decreases in annual rainfall can be attributed to the decreasing number of rainy days. The changes in rainy days and rainfall intensity were dominated by the wet season and dry season, respectively. View Full-Text
Keywords: quantile perturbation method; partial trend method; innovative trend analysis; rainfall; extreme; anomaly; the Yellow River quantile perturbation method; partial trend method; innovative trend analysis; rainfall; extreme; anomaly; the Yellow River
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MDPI and ACS Style

Wu, H.; Li, X.; Qian, H. Detection of Anomalies and Changes of Rainfall in the Yellow River Basin, China, through Two Graphical Methods. Water 2018, 10, 15.

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