globalchange  > 气候变化与战略
DOI: 10.1007/s11069-021-04530-1
论文题名:
Spatio-temporal variability of dry and wet conditions over East Africa from 1982 to 2015 using quantile regression model
作者: Kalisa W.; Igbawua T.; Ujoh F.; Aondoakaa I.S.; Namugize J.N.; Zhang J.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 106, 期:3
起始页码: 2047
结束页码: 2076
语种: 英语
中文关键词: Climate change ; Drought ; East Africa ; Ecological zones ; Precipitation ; Quantile regression ; Rainy season
英文关键词: climate change ; drought ; ecological zonation ; extreme event ; precipitation assessment ; regression analysis ; spatiotemporal analysis ; wetting-drying cycle ; East Africa
英文摘要: Precipitation and temperature are critical climatic variables that drive catastrophic climatic events including droughts and floods. These variables continue to fluctuate, thereby producing even more extreme weather events across different parts of East African region. Using quantile linear regression (QLR) method, this study interrogated wet and dry conditions over a period of 34 years across East African region. The spatio-temporal quantile trends (time coefficient of precipitation) analysis is presented in 5 conditions (quantiles): extreme dry (1st), dry (10th), median (50th), wet (90th) and extreme wet (99th). For annual precipitation, the quantiles indicated a trend value of − 0.294, 0.205, − 0.425, − 0.069 and 0.145, respectively. This shows that the extreme dry (wet) values in annual mean precipitation over the region are decreasing (increasing) over time, while the reverse is the case for the long and short seasons. Differences in the regression coefficients of precipitation variables for the inter-quantile differences show that any increase or decrease in average precipitation changes the shape of the distribution of hydrological parameters, increasing or decreasing spread between the extreme quantiles. The precipitation deciles at different quantiles over 34 years reveal marked variations in the annual mean and the long and short rainy seasons. Finally, the results indicate significant variations in extreme wet and dry conditions across eight ecological zones in East Africa with variable slope along various quantiles. In conclusion, QLR method has shown the ability to provide superior detailed information on extreme wet and dry climatic conditions required for flood mitigation and water resources planning and management. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169112
Appears in Collections:气候变化与战略

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作者单位: College of Automation, Qingdao University, Qingdao, 266071, China; College of Computer Science and Technology, Qingdao University, Qingdao, 266071, China; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China; Department of Physics, Federal University of Agriculture, Makurdi, Nigeria; Center for Sustainability and Resilient Infrastructure and Communities (SaRIC), School of the Built Environment and Architecture, London South Bank University, London, United Kingdom; Rwanda Polytechnic, Integrated Polytechnic Regional Center, College of Kigali, Kigali, Rwanda

Recommended Citation:
Kalisa W.,Igbawua T.,Ujoh F.,et al. Spatio-temporal variability of dry and wet conditions over East Africa from 1982 to 2015 using quantile regression model[J]. Natural Hazards,2021-01-01,106(3)
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