<p>Extreme rainfall events are changing globally due to global warming, but the direction and severity of these changes vary across regions and locations. This study aimed to assess changes in extreme rainfall indices at the local level in northeastern Ethiopia using data from 1982 to 2021. The study applied statistical and graphical innovative trend analysis (ITA) methods to examine the patterns of rainfall indices. The findings revealed a significant positive trend in all the selected extreme rainfall indices (P &lt; 0.01), except for consecutive dry days (CDDs) at the Wereilu station. Meanwhile, at the Kabie station, total annual rainfall (RFTOT), maximum rainfall in one day (Rx1day), maximum consecutive five-day rainfall (Rx5day), heavy rainfall days (R10mm), simple daily intensity index (SDII), and consecutive wet days (CWDs) increased significantly (P &lt; 0.01), while the number of rainy days (Rdays) and very wet days (R95p) decreased significantly (P &lt; 0.05). The graphical ITA indicated that extreme indices exhibited varying magnitudes of change, with some showing opposing directions across different value ranges. This finding suggests that graphical analysis should be used alongside statistical monotonic trend analysis to better understand how extreme rainfall indices behave in complex ways. Overall, the results revealed significant changes in extreme rainfall indices, highlighting the need for effective adaptation measures to mitigate the effects of extreme rainfall events. This study provides crucial understandings of extreme rainfall events at the local level, offering valuable information for adaptation planning, particularly within rain-fed agricultural systems.</p>

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Changes in extreme rainfall indices in Wereilu district, northeastern Ethiopian highlands, using innovative trend analysis

  • Demeke Hailu,
  • Muluneh Woldetsadik,
  • Desalegn Yayeh Ayal

摘要

Extreme rainfall events are changing globally due to global warming, but the direction and severity of these changes vary across regions and locations. This study aimed to assess changes in extreme rainfall indices at the local level in northeastern Ethiopia using data from 1982 to 2021. The study applied statistical and graphical innovative trend analysis (ITA) methods to examine the patterns of rainfall indices. The findings revealed a significant positive trend in all the selected extreme rainfall indices (P < 0.01), except for consecutive dry days (CDDs) at the Wereilu station. Meanwhile, at the Kabie station, total annual rainfall (RFTOT), maximum rainfall in one day (Rx1day), maximum consecutive five-day rainfall (Rx5day), heavy rainfall days (R10mm), simple daily intensity index (SDII), and consecutive wet days (CWDs) increased significantly (P < 0.01), while the number of rainy days (Rdays) and very wet days (R95p) decreased significantly (P < 0.05). The graphical ITA indicated that extreme indices exhibited varying magnitudes of change, with some showing opposing directions across different value ranges. This finding suggests that graphical analysis should be used alongside statistical monotonic trend analysis to better understand how extreme rainfall indices behave in complex ways. Overall, the results revealed significant changes in extreme rainfall indices, highlighting the need for effective adaptation measures to mitigate the effects of extreme rainfall events. This study provides crucial understandings of extreme rainfall events at the local level, offering valuable information for adaptation planning, particularly within rain-fed agricultural systems.