Mubarak Abdullateef | Kaduna State University (original) (raw)

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Papers by Mubarak Abdullateef

Science World Journal, 2020

An important statistical distribution use in modeling such extreme events is the generalized extr... more An important statistical distribution use in modeling such extreme events is the generalized extreme value distribution while the generalized Pareto distribution is suitable in modeling threshold excesses of extreme values. In this study, monthly rainfall data from the Nigeria Meteorological Agency in Kaduna are fitted to the generalized extreme value distribution and for a suitable threshold of 251mm, threshold excesses were fitted to the generalized Pareto distribution and a return level computed for 25, 50 and 100 years return period respectively. The threshold excesses follow the Weibull distribution and are bounded above implying that there is a finite value which the maximum above the threshold cannot exceed. For the 25, 50 and 100 years return period, a return level of 350mm, 390mm and 490mm with probability of exceedances of 0.04, 0.02 and 0.01 respectively were observed. The result further show that with the increasing level of rainfall as return period increases, there is ...

The forecasting of the occurrence of events such as a social phenomenon, a natural disaster, a ph... more The forecasting of the occurrence of events such as a social phenomenon, a natural disaster, a physical observation, personal research, or otherwise based on historical data has helped individuals and organizations in making informed decisions and adequate arrangements for any eventuality that might occur. Rainfall is a physical event that occurs at certain periods, depending upon the geographical location. In the North West of Nigeria, rainfalls usually occur during the months of April to October. At earlier and late stages, the rainfall is usually characterized by strong winds which causes damages to houses, electricity installations and other monumental structures. Draught and flood are other problems associated with rainfall in the North West region of Nigeria. In this paper, two separate tools were employed to forecast the yearly rainfall of Kaduna metropolis which has suffered from severe problems of draught as well as flood in time past. The results obtained showed that Artif...

An important statistical distribution use in modeling such extreme events is the generalized extr... more An important statistical distribution use in modeling such extreme events is the generalized extreme value distribution while the generalized Pareto distribution is suitable in modeling threshold excesses of extreme values. In this study, monthly rainfall data from the Nigeria Meteorological Agency in Kaduna are fitted to the generalized extreme value distribution and for a suitable threshold of 251mm, threshold excesses were fitted to the generalized Pareto distribution and a return level computed for 25, 50 and 100 years return period respectively. The threshold excesses follow the Weibull distribution and are bounded above implying that there is a finite value which the maximum above the threshold cannot exceed. For the 25, 50 and 100 years return period, a return level of 350mm, 390mm and 490mm with probability of exceedances of 0.04, 0.02 and 0.01 respectively were observed. The result further show that with the increasing level of rainfall as return period increases, there is a high likelihood of monthly maximum rainfall increasing steadily over the years and this has great consequences on the environment. If this trend continues unchecked as a result of global warming, residents will continue to experience flood unless the government build more drainages and ensure that existing drainages are free from dirt to enhance proper channeling and free flow of water in the event of rainfall.

An important statistical distribution use in modeling such extreme events is the generalized extr... more An important statistical distribution use in modeling such extreme events is the generalized extreme value distribution while the generalized Pareto distribution is suitable in modeling threshold excesses of extreme values. In this study, monthly rainfall data from the Nigeria Meteorological Agency in Kaduna are fitted to the generalized extreme value distribution and for a suitable threshold of 251mm, threshold excesses were fitted to the generalized Pareto distribution and a return level computed for 25, 50 and 100 years return period respectively. The threshold excesses follow the Weibull distribution and are bounded above implying that there is a finite value which the maximum above the threshold cannot exceed. For the 25, 50 and 100 years return period, a return level of 350mm, 390mm and 490mm with probability of exceedances of 0.04, 0.02 and 0.01 respectively were observed. The result further show that with the increasing level of rainfall as return period increases, there is a high likelihood of monthly maximum rainfall increasing steadily over the years and this has great consequences on the environment. If this trend continues unchecked as a result of global warming, residents will continue to experience flood unless the government build more drainages and ensure that existing drainages are free from dirt to enhance proper channeling and free flow of water in the event of rainfall.

Science World Journal, 2020

An important statistical distribution use in modeling such extreme events is the generalized extr... more An important statistical distribution use in modeling such extreme events is the generalized extreme value distribution while the generalized Pareto distribution is suitable in modeling threshold excesses of extreme values. In this study, monthly rainfall data from the Nigeria Meteorological Agency in Kaduna are fitted to the generalized extreme value distribution and for a suitable threshold of 251mm, threshold excesses were fitted to the generalized Pareto distribution and a return level computed for 25, 50 and 100 years return period respectively. The threshold excesses follow the Weibull distribution and are bounded above implying that there is a finite value which the maximum above the threshold cannot exceed. For the 25, 50 and 100 years return period, a return level of 350mm, 390mm and 490mm with probability of exceedances of 0.04, 0.02 and 0.01 respectively were observed. The result further show that with the increasing level of rainfall as return period increases, there is ...

The forecasting of the occurrence of events such as a social phenomenon, a natural disaster, a ph... more The forecasting of the occurrence of events such as a social phenomenon, a natural disaster, a physical observation, personal research, or otherwise based on historical data has helped individuals and organizations in making informed decisions and adequate arrangements for any eventuality that might occur. Rainfall is a physical event that occurs at certain periods, depending upon the geographical location. In the North West of Nigeria, rainfalls usually occur during the months of April to October. At earlier and late stages, the rainfall is usually characterized by strong winds which causes damages to houses, electricity installations and other monumental structures. Draught and flood are other problems associated with rainfall in the North West region of Nigeria. In this paper, two separate tools were employed to forecast the yearly rainfall of Kaduna metropolis which has suffered from severe problems of draught as well as flood in time past. The results obtained showed that Artif...

An important statistical distribution use in modeling such extreme events is the generalized extr... more An important statistical distribution use in modeling such extreme events is the generalized extreme value distribution while the generalized Pareto distribution is suitable in modeling threshold excesses of extreme values. In this study, monthly rainfall data from the Nigeria Meteorological Agency in Kaduna are fitted to the generalized extreme value distribution and for a suitable threshold of 251mm, threshold excesses were fitted to the generalized Pareto distribution and a return level computed for 25, 50 and 100 years return period respectively. The threshold excesses follow the Weibull distribution and are bounded above implying that there is a finite value which the maximum above the threshold cannot exceed. For the 25, 50 and 100 years return period, a return level of 350mm, 390mm and 490mm with probability of exceedances of 0.04, 0.02 and 0.01 respectively were observed. The result further show that with the increasing level of rainfall as return period increases, there is a high likelihood of monthly maximum rainfall increasing steadily over the years and this has great consequences on the environment. If this trend continues unchecked as a result of global warming, residents will continue to experience flood unless the government build more drainages and ensure that existing drainages are free from dirt to enhance proper channeling and free flow of water in the event of rainfall.

An important statistical distribution use in modeling such extreme events is the generalized extr... more An important statistical distribution use in modeling such extreme events is the generalized extreme value distribution while the generalized Pareto distribution is suitable in modeling threshold excesses of extreme values. In this study, monthly rainfall data from the Nigeria Meteorological Agency in Kaduna are fitted to the generalized extreme value distribution and for a suitable threshold of 251mm, threshold excesses were fitted to the generalized Pareto distribution and a return level computed for 25, 50 and 100 years return period respectively. The threshold excesses follow the Weibull distribution and are bounded above implying that there is a finite value which the maximum above the threshold cannot exceed. For the 25, 50 and 100 years return period, a return level of 350mm, 390mm and 490mm with probability of exceedances of 0.04, 0.02 and 0.01 respectively were observed. The result further show that with the increasing level of rainfall as return period increases, there is a high likelihood of monthly maximum rainfall increasing steadily over the years and this has great consequences on the environment. If this trend continues unchecked as a result of global warming, residents will continue to experience flood unless the government build more drainages and ensure that existing drainages are free from dirt to enhance proper channeling and free flow of water in the event of rainfall.