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Large-scale and small-scale spilt oil is as old as exploration activities in the Niger Delta region of Nigeria. There is a need to provide the exposure, geochemical and spatial characteristics in the Niger Delta Region of Nigeria because of the effects of the spilt oil on the communities and the environment. Some of the spilt oil-disaster impacts for exposed communities include psychological effects and socio-demographic characteristics. In this study, the characteristics, sources, spatial and socio-demographic risk predictions of the spilt oil discovered by Kolo Creek coastal residents are examined. A random sample of 900 residents of Kolo Creek coastal communities included exposure characteristics linked to health, the social and economic lifestyle of the communities. The demographic characteristics included age, gender, literacy, and occupation as covariates in the analyses. Respondents provided varied information on the amount of health, the social, and economic impacts. The highest and lowest direct exposure impact accounts 94.65±2.0% and 5.95±1.52% for smoggy weather and obstruction to watercourses respectively. The geochemical distribution pattern was examined using standard laboratory procedures. This investigation included the determination of the physical and chemical characteristics of water samples at the oil spill sites. Also, the biochemical oxygen demand (BOD), chemical oxygen demand (COD), total hydrocarbon content (THC), and total petroleum hydrocarbon (TPH) of both water and sediment samples were carried out. A strong correlation exists between these parameters (i.e. at p < 0.01) and indicate communalities greater than 0.5. The pollution distribution maps support the spatial distribution pattern and correlate significantly (p < 0.01) with the exposure distribution, and the geochemical distribution patterns.

Residents along the shoreline of the Orashi River have yearly been displaced and recorded loss of lives, farmland, and infrastructures. The Government’s approach has been the provision of relief materials to the victims instead of implementing adequate control measures. This research employs Shuttle Radar Topographic Mission and Google Earth imagery in developing a 3D floodplain map in ArcGIS 10.4. The result indicates the drainage system in the study area is observe to be dendritic with catchment of 79 subbasin with 76 pour point indicating the area is floodplain including 3D slope > 8 contain 1.15% and < 8 has 98.85% indicating floodplain area, aspect indicate west-facing slope are dark blue,3D hillshade indicate yellow is very low area and high area is pink and also the buffer analysis result reveals waterbodies reflecting blue with estimated area of 1.88 km2, yellow indicate 0.79 km2 of the shoreline, red indicate 0.81 km2 of the minor floodplain and pink contain 0.82 km2 with length of 32.82km. The result from google earth image in 2007 indicate absent of settlement ,2013 indicate minimal settlement and 2020 indicate major settlement in the study area when correlated with 3D Floodplain mapping before and during the flood in other to analyze and manage flooding for further purpose and majority of the area are under seize with flood like in 2020. Therefore, Remote Sensing and GIS techniques is useful for Floodplain mapping, risk analysis for control measures for better flood management.

Flood has been a serious hazard for the past decades in Nigeria at large. The incidence of 2012 and 2018 flood disaster in Yenagoa, Amassoma and other parts of the state have not been recover till date and the government is not consigned about the well been of the people. The major causes of the flood are attributed to increased rainfall and lack of drainages including dredging of rivers and disobeying of environmental law and infrastructure failure. Coastal Towns or communities are one of the most affected areas of flood and their farms and fishing implements were washed away by the floodwater in 2012 and 2018 in Bayelsa State. Flood management is needed for provision of time information so quick response can be done as soon as possible. Using SRTM data to produce digital elevation model and IDW Contour, the 3D model from ground data of Yenagoa metropolis using ArcGIS 10.6 to generate and analyze them. As a result of field survey, flood level calculation was made to classified flood hazard zones for migration, Agricultural Educational, and construction purpose such as land suitability. This was used in ascertaining the extent of the flooded area. The result reveals that an area of over 5.9888882km2 and riverine and coastal area is flooded, affecting more than 15 coastal and riverine communities. The finding also concludes that remote sensing data like SRTM data and Geospatial techniques seems effective in mapping and identifying areas prone to flooding. Therefore Remote sensing and Geospatial database should be established for proper flood mapping and the government should constantly dredge the area from time to time.

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