July 01, 2018

The project is focused on the marine and coastal zone environments of The Gulf of Suez and portion of the Red Sea coast of Egypt, which are wealthy with natural resources that contribute to the national economy. The Red Sea and the Gulf of Suez area accommodate diverse human activities, including oil exploration and production, touristic activities, export and import harbors, etc. It is however, experience pollution threats due to such human activities and interactions. This research aimed at integrating in-situ measurements and remotely sensed data with outputs of a hydrodynamic model to simulate the oil pollution and generate a pollution distribution map. High-resolution satellite sensors including Sentinel 2 and Plantlab were functioned for monitoring oil pollution. Spectral band ratio of band 4 (infrared) over band 3 (red) underpinned the mapping of the point source pollution from the oil industrial estates.

This ratio is supporting the absorption windows detected in the hyper-spectral profiles. ASD in-situ hyper-spectral device was used to measure experimentally the oil pollution in marine environment. The experiment used to measure water behavior with three conditions a) clear water without oil, b) water covered with a layer of raw oil, and c) behavior of water a while after throwing raw oil. The spectral curve generated is clearly identified the absorption windows for oil pollution particularly at 600-700nm. MIKE 21 model was applied to simulate the dispersion of the oil contamination and create different scenarios for future crises management. The model requires precise data for sea bathymetry, tides, waves, atmospheric parameters. The required data were obtained partially from the online modeled data and the historical in-situ stations. The simulation enabled to predict the movement of the oil spill (i.e. speed and direction of dispersion) that would help creating an early warning system as a threshold for faster mitigation measures. The project proofed the concept and provided the robust methodology that could be easily in operation. The operability requires regular input of remotely sensed data that are not exists.

The idea it to extend the operation of monitoring the environment into forecasting modelling, the project has developed hydrodynamic model to simulate the pollution migration in case of oil incident. This is function of various environmental parameters including the wind direction and speed, the tide, the quantity of the oil.

The model has applied using two different modules (MIKE 21 and GNOME) and both provided efficient mechanism of forecasting the pollution migration. To transform this forecasting model to an early warning system there is a need for regular input of environmental data, HPCs computing facilities and human resources.


Division : Environmental Studies and Land use
Prof       : Prof. Dr. Islam Abou El-Magd