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Spatiotemporal variation in extreme precipitation in Beijiang River Basin, Southern Coastal China, from 1959 to 2018

Liu, Z., Yang, H. ORCID: https://orcid.org/0000-0001-9940-8273, Wei, X. and Liang, Z. (2023) Spatiotemporal variation in extreme precipitation in Beijiang River Basin, Southern Coastal China, from 1959 to 2018. Journal of Marine Science and Engineering, 11 (1). 73. ISSN 2077-1312

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To link to this item DOI: 10.3390/jmse11010073

Abstract/Summary

Extreme precipitation events have caused serious impacts on natural ecosystem and human society and have attracted increasing attention in recent years. IPCC AR6 WG I report highlighted a lack of conclusive consensus on the change trend of extreme precipitation in some basins and variation (increase or decrease) between regions. Based on seven precipitation indexes defined by ETCCDI, using daily precipitation data observed by 18 national reference meteorological stations in China during 1959–2018, this study analysed spatiotemporal variation trend of extreme precipitation in the Beijiang River Basin, Southern Coastal China, in recent 60 years, using Mann–Kendall (M-K) trend test, coefficient of variation, and continuous wavelet transformation. M-K test results showed that there were mutations in all seven precipitation indexes, and mutation points were mainly concentrated in two periods (1986–1991 and 2005–2010). The change range of each index after mutation was generally greater than that before mutation. Continuous wavelet transformation showed that each indicator had a significant oscillation period of 2–4 year in most time domains. The southeastern part of the basin (Fogang and Qingyuan) was the center of extremely heavy precipitation, and most precipitation indexes decreased from this area to the surrounding area. As far as the basin as a whole was concerned, consecutive wet days (CWD) declined significantly (passing 0.05 of confidence test), and there was a significantly positive correlation between annual distribution of R95ds and monthly precipitation (p < 0.001). The research results expand our understanding of regional water cycle and extreme climate change, guide the allocation and management of water resources related to regional industrial and agricultural activities, and provide reference for disaster prevention and mitigation.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
ID Code:109768
Publisher:MDPI

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