Evaluating The Correlation Between Electromagnetic Conductivity And Metal Detection To Identify Underground Storage Tanks: A Case Study Of Agbor, Delta State, South-South Nigeria
DOI:
https://doi.org/10.60787/jnamp.vol69no1.463Keywords:
Electrical conductivity, Correlation analysis, Electromagnetic induction, Environmental monitoring, Metal detectionAbstract
Underground storage tanks (USTs) pose environmental and safety risks in urban areas. This requires effective detection methods. This study investigates the relationship between electromagnetic induction conductivity and metal detection for UST installations at five Agbor, Delta State, Nigeria gas stations. The research aims to evaluate the effectiveness of combining these geophysical techniques for noninvasive UST detection in urban environments. A mixed-method approach was employed, utilizing a Geonics EM31 conductivity meter for EMI surveys and a Pulse Induction metal detector for precise localization. Data were collected using a 5-meter grid system to ensure adequate coverage of the study area across the selected sites. Environmental factors, including soil moisture and temperature, were recorded to assess their impact on measurements. Statistical analyses, including Pearson's correlation, regression, and ANOVA, were conducted to evaluate relationships between variables and assess inter-station differences. Results revealed a significant positive correlation between EMI conductivity and metal detection (r = 0.74, p < 0.05). Regression analysis confirmed that higher conductivity significantly predicts metal presence, with a moderate effect size (β = 0.35, p = 0.001). EMI conductivity values ranged from 13.234 to 22.123 mS/m, with higher values strongly associated with metal detection. Depth measurements of detected objects varied from 2.123 to 3.678 m. ANOVA results indicated significant differences in conductivity between stations (F(4, 14) = 3.45, p = 0.02). The study concludes that combining EMI conductivity and metal detection provides a reliable method for UST location in urban settings. However, environmental factors and depth variations can influence detection accuracy. These features improve noninvasive geophysical techniques for urban UST management and highlight the importance of evaluating site-specific conditions in detection strategies.
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