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  • 标题:Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
  • 本地全文:下载
  • 作者:Daniel Maposa ; James J. Cochran ; Maseka Lesaoana
  • 期刊名称:Jàmbá : Journal of Disaster Risk Studies
  • 印刷版ISSN:1996-1421
  • 电子版ISSN:2072-845X
  • 出版年度:2016
  • 卷号:8
  • 期号:1
  • 页码:185-193
  • DOI:10.4102/jamba.v8i1.185
  • 出版社:AOSIS
  • 摘要:In this article we fit a time-dependent generalised extreme value (GEV) distribution to annual maximum flood heights at three sites: Chokwe, Sicacate and Combomune in the lower Limpopo River basin of Mozambique. A GEV distribution is fitted to six annual maximum time series models at each site, namely: annual daily maximum (AM1), annual 2-day maximum (AM2), annual 5-day maximum (AM5), annual 7-day maximum (AM7), annual 10-day maximum (AM10) and annual 30-day maximum (AM30). Non-stationary time-dependent GEV models with a linear trend in location and scale parameters are considered in this study. The results show lack of sufficient evidence to indicate a linear trend in the location parameter at all three sites. On the other hand, the findings in this study reveal strong evidence of the existence of a linear trend in the scale parameter at Combomune and Sicacate, whilst the scale parameter had no significant linear trend at Chokwe. Further investigation in this study also reveals that the location parameter at Sicacate can be modelled by a nonlinear quadratic trend; however, the complexity of the overall model is not worthwhile in fit over a time-homogeneous model. This study shows the importance of extending the time-homogeneous GEV model to incorporate climate change factors such as trend in the lower Limpopo River basin, particularly in this era of global warming and a changing climate.
  • 关键词:nonstationary extremes; annual maxima; lower Limpopo River; generalised extreme value
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