| dc.creator |
Obisesan, Kazeem O. |
|
| dc.creator |
Afolabi, Yusuf O. |
|
| dc.date |
2019-10-07T12:08:15Z |
|
| dc.date |
2019-10-07T12:08:15Z |
|
| dc.date |
2015 |
|
| dc.date.accessioned |
2022-10-20T08:35:06Z |
|
| dc.date.available |
2022-10-20T08:35:06Z |
|
| dc.identifier |
2394-2894 |
|
| dc.identifier |
http://dspace.cbe.ac.tz:8080/xmlui/handle/123456789/397 |
|
| dc.identifier.uri |
http://hdl.handle.net/123456789/79246 |
|
| dc.description |
This study examined the variability of extreme rainfall (mm) in all states of Nigeria including Abuja (FCT) from 1971 to 2012. Generalized extreme value (GEV) theory
was employed to extract out the monthly extreme rainfall as the response variable which possessed a bimodal structure and is best captured with beta distribution from existing
literatures and the current study. Generalized linear models (GLMs) of beta distribution type therefore explored the variability in rainfall encountered by each state to explain the
extreme rainfall model using betareg package in R. It was validated that Oyo, Cross River, Akwa Ibom, Imo ,Niger,Kwara, Kebbi, and Zamfara states contributed to the model
at 5 percent significant level as affirmed by z-statistics and exploratory data analysis (EDA). This is an indication to the states validated by the extreme rainfall model to be prone to yearly flooding while the rest of the states not validated by the model are likely to encountered flooding whenever there is extreme rainfall which is a recent trend due to global warming. Therefore, structure and re-engineering solutions must be put in place in all parts of the country to avoid flooding. |
|
| dc.format |
application/pdf |
|
| dc.language |
en |
|
| dc.relation |
Volume 2;Issue No: 4 |
|
| dc.subject |
Beta Distribution, Extreme Rainfall Model, Generalized Linear Models, Rainfall Variability. |
|
| dc.title |
On the use of Probability with Generalized Linear Models for Evaluating Extreme Rainfall in Nigeria |
|
| dc.type |
Article |
|