Stationarity of major flood frequencies and heights on the Ba River, Fiji, over a 122‐year record
ABSTRACT The economic impact of natural disasters on developing economies can be severe with the recovery diverting scarce funds that might otherwise be targeted at development projects and stimulating the need for international aid. In view of the likely sensitivity of low‐lying Pacific Islands to...
Published in: | International Journal of Climatology |
---|---|
Main Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2017
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1002/joc.4989 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.4989 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.4989 |
Summary: | ABSTRACT The economic impact of natural disasters on developing economies can be severe with the recovery diverting scarce funds that might otherwise be targeted at development projects and stimulating the need for international aid. In view of the likely sensitivity of low‐lying Pacific Islands to anticipated changes in climate, a 122‐year record of major flooding depths at the Rarawai Sugar Mill on the Ba River in the northwest of the Fijian Island of Viti Levu is analysed. Reconstructed largely from archived correspondence of the Colonial Sugar Refining Company, the time series comprises simple measurements of height above the Mill floor. It exhibits no statistically significant trends in either frequency or flood heights, once the latter have been adjusted for average relative sea‐level rise. This is despite persistent warming of air temperatures as characterized in other studies. There is a strong dependence of frequency (but not magnitude) upon El Niño‐Southern Oscillation ( ENSO ) phase, with many more floods in La Niña phases. The analysis of this long‐term data series illustrates the difficulty of detecting a global climate change signal from hazard data, even given a consistent measurement methodology ( cf HURDAT2 record of North Atlantic hurricanes) and warns of the strong dependence of any statistical significance upon choices of start and end dates of the analysis. |
---|