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Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique

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, name...

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Detalles Bibliográficos
Autores principales: Maposa, Daniel, Cochran, James J., Lesaoana, Maseka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AOSIS 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6014040/
https://www.ncbi.nlm.nih.gov/pubmed/29955284
http://dx.doi.org/10.4102/jamba.v8i1.185
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author Maposa, Daniel
Cochran, James J.
Lesaoana, Maseka
author_facet Maposa, Daniel
Cochran, James J.
Lesaoana, Maseka
author_sort Maposa, Daniel
collection PubMed
description 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.
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spelling pubmed-60140402018-06-28 Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique Maposa, Daniel Cochran, James J. Lesaoana, Maseka Jamba Original Research 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. AOSIS 2016-05-12 /pmc/articles/PMC6014040/ /pubmed/29955284 http://dx.doi.org/10.4102/jamba.v8i1.185 Text en © 2016. The Authors http://creativecommons.org/licenses/by/2.0/ Licensee:AOSIS. This work is licensed under the Creative Commons Attribution License.
spellingShingle Original Research
Maposa, Daniel
Cochran, James J.
Lesaoana, Maseka
Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
title Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
title_full Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
title_fullStr Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
title_full_unstemmed Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
title_short Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
title_sort modelling non-stationary annual maximum flood heights in the lower limpopo river basin of mozambique
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6014040/
https://www.ncbi.nlm.nih.gov/pubmed/29955284
http://dx.doi.org/10.4102/jamba.v8i1.185
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