Modelling of oil spill impacts on shoreline in Egypt

Mehanna, Ahmed; Omar, Mohamed Y.; Hassan, Amr Ali; Turki, Eslam A.; Hegazy, El-Sayed; H.S.El-Kilani,

doi:10.1201/b15813-103

Cited by 2 publications

(1 citation statement)

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“…The spatial and temporal analysis of oil spill events is an important approach to addressing some of the most critical challenges presented by consistent oil spills in the Niger Delta (Whanda et al 2016). Data from various studies indicate that human error accounts for about 80% of the major oil spills in the world (Mehanna et al 2013, Alpers et al 2017, Mba et al 2019.…”

Section: Introductionmentioning

confidence: 99%

Where will the next oil spill incident in the Niger Delta region of Nigeria occur?

Wekpe,

Whitworth,

Baily

2024

Environ. Res. Commun.

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Oil spill incidents are almost a daily occurrence within the Niger Delta region of Nigeria with far reaching environmental, economic and social consequences. This study aimed at understanding the spatial and temporal context of the problem as a panacea for forecasting likely locations of oil spill incidents within the region. About 76.77% of crude oil spilt in the Niger Delta is lost to the environment with only about 23% of the crude oil recovered from the environment, this represents a very worrying statistic in terms of the known and unknown negative impacts of oil spills. Space Time Pattern Mining (STPM) tools were adapted to explore and interrogate historical spill data. Time series forecasting was then used for forecasting possible locations of future oil spills within the region. Results show that there is a pattern to oil spill occurrences in the Niger Delta with statistically significant hotspots identified in Rivers State, Bayelsa State and Delta State. Forecast root mean square error (RMSE) and forecast validation RMSE are -1.016328 and 1.035992 respectively. This suggests an ability of the model to fairly predict likely locations of future oil spills. This was further verified by counting the number of spills that occur within any area based on the predicted likelihood of spill occurrence. This study has shown that STPM tools can be deployed in understanding the occurrence and prediction of oil spill incidents. This will ultimately aid in the deployment of scarce management resources to where they are most needed.

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Section: Introductionmentioning

confidence: 99%