Spatiotemporal Trend Analysis of Precipitation Extremes in Ho Chi Minh City, Vietnam During 1980–2017

Nguyen Trong Quan , Dao Nguyen Khoi , Nguyen Xuan Hoan , Nguyen Ky Phung , Thanh Duc Dang

International Journal of Disaster Risk Science ›› 2021, Vol. 12 ›› Issue (1) : 131 -146.

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International Journal of Disaster Risk Science ›› 2021, Vol. 12 ›› Issue (1) : 131 -146. DOI: 10.1007/s13753-020-00311-9
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Spatiotemporal Trend Analysis of Precipitation Extremes in Ho Chi Minh City, Vietnam During 1980–2017

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Abstract

In this study, the spatiotemporal variability of trends in extreme precipitation events in Ho Chi Minh City during the period 1980–2017 was analyzed based on several core extreme precipitation indices (Rx1day, Rx5day, CDD, CWD, R20mm, R25mm, R95p, and SDII). The non-parametric Mann–Kendall and Sen’s slope methods were used to compute the statistical strength, stability, and magnitude of trends in annual rainfall, as well as the extreme precipitation indices. We found that 64% of the stations had statistically significant upward trends in yearly rainfall, with high magnitudes frequently observed in the northern and southern regions of the city. For the extreme precipitation indices, only SDII and R25mm showed dominantly significant trends. Additionally, there were increasing trends in the frequency and duration at the southern and central regions of the city during the study period. Furthermore, El Niño-Southern Oscillation and Pacific Decadal Oscillation positively correlated with the duration and negatively correlated with the intensity and frequency of extreme precipitation. Thus, water management plans should be adjusted appropriately to reduce the severe impacts of precipitation extremes on communities and ecosystems.

Keywords

Spatiotemporal trend / Extreme precipitation / Extreme precipitation indices / Ho Chi Minh City

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Nguyen Trong Quan, Dao Nguyen Khoi, Nguyen Xuan Hoan, Nguyen Ky Phung, Thanh Duc Dang. Spatiotemporal Trend Analysis of Precipitation Extremes in Ho Chi Minh City, Vietnam During 1980–2017. International Journal of Disaster Risk Science, 2021, 12(1): 131-146 DOI:10.1007/s13753-020-00311-9

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