Modelling flood heights of the Limpopo River at Beitbridge Border Post using extreme value distributions
| dc.contributor.advisor | Sigauke, Caston | |
| dc.contributor.advisor | Bere, Alphonce | |
| dc.contributor.author | Kajambeu, Robert | |
| dc.date.accessioned | 2017-06-08T17:13:53Z | |
| dc.date.available | 2017-06-08T17:13:53Z | |
| dc.date.issued | 2016 | |
| dc.description | MSc (Statistics) | |
| dc.description | Department of Statistics | |
| dc.description.abstract | Haulage trucks and cross border traders cross through Beitbridge border post from landlocked countries such as Zimbabwe and Zambia for the sake of trading. Because of global warming, South Africa has lately been experiencing extreme weather patterns in the form of very high temperatures and heavy rainfall. Evidently, in 2013 tra c could not cross the Limpopo River because water was owing above the bridge. For planning, its important to predict the likelihood of such events occurring in future. Extreme value models o er one way in which this can be achieved. This study identi es suitable distributions to model the annual maximum heights of Limpopo river at Beitbridge border post. Maximum likelihood method and the Bayesian approach are used for parameter estimation. The r -largest order statistics was also used in this dissertation. For goodness of t, the probability and quantile- quantile plots are used. Finally return levels are calculated from these distributions. The dissertation has revealed that the 100 year return level is 6.759 metres using the maximum likelihood and Bayesian approaches to estimate parameters. Empirical results show that the Fr echet class of distributions ts well the ood heights data at Beitbridge border post. The dissertation contributes positively by informing stakeholders about the socio- economic impacts that are brought by extreme flood heights for Limpopo river at Beitbridge border post | en_US |
| dc.format.extent | 1 online resource (xx, 86 leaves : color illustrations) | |
| dc.identifier.apacitation | Kajambeu, R. (2016). <i>Modelling flood heights of the Limpopo River at Beitbridge Border Post using extreme value distributions</i>. (). . Retrieved from http://hdl.handle.net/11602/676 | en_ZA |
| dc.identifier.chicagocitation | Kajambeu, Robert. <i>"Modelling flood heights of the Limpopo River at Beitbridge Border Post using extreme value distributions."</i> ., , 2016. http://hdl.handle.net/11602/676 | en_ZA |
| dc.identifier.citation | Kajambeu, R. 2016. Modelling flood heights of the Limpopo River at Beitbridge Border Post using extreme value distributions. . . http://hdl.handle.net/11602/676 | en_ZA |
| dc.identifier.ris | TY - Dissertation AU - Kajambeu, Robert AB - Haulage trucks and cross border traders cross through Beitbridge border post from landlocked countries such as Zimbabwe and Zambia for the sake of trading. Because of global warming, South Africa has lately been experiencing extreme weather patterns in the form of very high temperatures and heavy rainfall. Evidently, in 2013 tra c could not cross the Limpopo River because water was owing above the bridge. For planning, its important to predict the likelihood of such events occurring in future. Extreme value models o er one way in which this can be achieved. This study identi es suitable distributions to model the annual maximum heights of Limpopo river at Beitbridge border post. Maximum likelihood method and the Bayesian approach are used for parameter estimation. The r -largest order statistics was also used in this dissertation. For goodness of t, the probability and quantile- quantile plots are used. Finally return levels are calculated from these distributions. The dissertation has revealed that the 100 year return level is 6.759 metres using the maximum likelihood and Bayesian approaches to estimate parameters. Empirical results show that the Fr echet class of distributions ts well the ood heights data at Beitbridge border post. The dissertation contributes positively by informing stakeholders about the socio- economic impacts that are brought by extreme flood heights for Limpopo river at Beitbridge border post DA - 2016 DB - ResearchSpace DP - Univen KW - Extreme value theory KW - Bayesian approach KW - r-largest order statistics LK - https://univendspace.univen.ac.za PY - 2016 T1 - Modelling flood heights of the Limpopo River at Beitbridge Border Post using extreme value distributions TI - Modelling flood heights of the Limpopo River at Beitbridge Border Post using extreme value distributions UR - http://hdl.handle.net/11602/676 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11602/676 | |
| dc.identifier.vancouvercitation | Kajambeu R. Modelling flood heights of the Limpopo River at Beitbridge Border Post using extreme value distributions. []. , 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11602/676 | en_ZA |
| dc.language.iso | en | en_US |
| dc.rights | University of Venda | |
| dc.subject | Extreme value theory | en_US |
| dc.subject | UCTD | en_ZA |
| dc.subject | r-largest order statistics | en_US |
| dc.subject.ddc | 627.40968257 | |
| dc.subject.lcsh | Floods -- South Africa -- Limpopo | |
| dc.subject.lcsh | Flood control -- South Africa -- Limpopo | |
| dc.subject.lcsh | Flood damage -- South Africa -- Limpopo | |
| dc.subject.lcsh | Bridges -- Flood damage -- South Africa -- Limpopo | |
| dc.title | Modelling flood heights of the Limpopo River at Beitbridge Border Post using extreme value distributions | en_US |
| dc.type | Dissertation | en_US |