Background
Geologic and geotechnical conditions of soils where Nanka and Ajali Formations outcropped in Anambra Basin, Southeastern Nigeria were investigated and accessed. This was done using detailed mapping and mechanical soil laboratory tests to unravel the genesis and continued expansion of gully erosion in the study areas.
Results
Field study revealed that gully erosions are more pronounced in the study area with poor vegetation cover and a high degree of slope steepness. Grain size analysis revealed that the soils of the Nanka Formation have an average sand content value of 90.90% (sandy) and silt content value of 3.0% (low fine portions). The plasticity index of the fine portions indicates that the soils are weak plastic, with a mean value of 5.29%. The soils have an average cohesion value of 0.30 kg/cm2 indicating a very weak cohesion. The soils are highly permeable; with an average value of 2.67 × 10–3 cm/s. The compaction test further revealed that the soils are loosely compacted. The soils for the Ajali Formation have an average sand content value of 95.10% (sandy) and silt content value of 1.43% (low fine portions). The plasticity index of the fine portions indicates that the soils are weak plastic, with a mean value of 2.70%. The soils have an average cohesion value of 0.30 kg/cm2 indicating a very weak cohesion. The soils are highly permeable; with an average value of 2.70 × 10–3 cm/s. The compaction test revealed that the soils are loosely compacted.
Conclusion
After field surveys and laboratory analyses, it was found that the gully erosions have been developing respectively on steep slopes and non-vegetated areas, and their genesis facilitated by the cohesionless and very permeable nature of the sandy formations. Following those key findings, it was proposed many practices (agronomic and engineering mainly) that can help mitigate the formations as well as the expansion of this very damaging hazard type. The potential implications of these gully erosion include damaging of buildings, residential houses, bridges, and roads, loss of farmland and vegetation, isolation of villages and towns, increased migration of inhabitants as well as degradation of agricultural fertile land.
The 3-D depositional environment was built using seismic data. The depositional facies was used to locate channels with highly theif zones and distribution of various sedimentary facies. The integration core data and the gamma ray log trend from the wells within the studied interval with right boxcar/right bow-shape indicate muddy tidal flat to mixed tidal flat environments. The bell–shaped from the well logs with the core data indicate delta front with mouth bar, the blocky box- car trend from the well logs with the core data indicate tidal point bar with tidal channel fill. The integration of seismic to well log tie display a good tie in the wells across the field. The attribute map from velocity analysis revealed the presence of hydrocarbons in the identified sands (A, B, C, D1, D2, D4, D5). The major faults F1, F2, F3 and F4 with good sealing capacity are responsible for hydrocarbon accumulation in the field. Detailed petro physical analysis of well log data showed that the studied interval are characterized by sand-shale inter-beds. Eight reservoirs were mapped at depth intervals of 2886m to 3533m with their thicknesses ranging from 12m to 407m. Also the Analysis of the petrophysical results showed that porosity of the reservoirs range from 14% to 28 %; permeability range from 245.70 md to 454.7md; water saturation values from 21.65% to 54.50% and hydrocarbon saturation values from 45.50% to 78.50 %. The by-passed hydrocarbons were identified and estimated in low resistivity pay sands D1, D2 at depth of 2884m – 2940m, sand D5 at depth of 3114m – 3126m respectively. The model serve as a basis for establishing facies model in the field.
Non-carcinogenic health risk assessment and predicting of organic and heavy metal pollution of groundwater around Osisioma, Nigeria, using Artificial Neural Networks and Multi-Linear Modeling Principles has been done. 30 groundwater samples were collected systematically and analyzed for organic and heavy metal pollutants. The results of the analysis showed that the heavy metals and organic pollutants within the study area contributed to the pollution of groundwater resources in the locality. However, copper, ethylbenzene, xylene and toluene were within the recommended standard, whereas arsenic, iron, chromium, lead, and benzene were above the recommended standard for drinking water. Correlation matrix and principal component analysis assessment indicated weak correlation and that organic pollutants were major contributors to the loadings. The Contamination factor, Pollution load index, Metal pollution index, Geoaccumulation index, Potential ecological risk index, Elemental Contamination Index, and overall Metal Contamination Index showed no significant pollution, whereas the Heavy Metal Evaluation Index, Pollution Index of Groundwater results showed worrisome impact of the anthropogenic activities on the groundwater quality. Health risk assessment showed that children are more at risk than adults as it related to taking polluted water. MLR models performed better than the ANN. Seven (7) mathematical models were generated for the prediction of pollution indices. Based on the results, this study recommends regular monitoring of groundwater resources and the integration of ANN and MLR modeling approaches for the prediction of pollution indices.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.