Collins O. Molua * and Doris N. Nwachuku
Department of Physics, University of Delta, Agbor, Nigeria
*Corresponding author: collins.molua@unidel.edu.ng
This research addressed the problem of defining the complex soil-plant-water relations in tropical agroecosystems, where the heterogeneity of the subsurface can be unhelpful to standard surface-based surveillance. The objective of the research was to develop a series of non-invasive geophysical studies using remote sensing to measure the effects of subsurface moisture dynamics on plant physiological performance in Agbor, Delta State, Nigeria. The technique involved Electrical Resistivity Tomography (ERT) using the Abem Terrameter SAS 1000 to map the resistivity of the system at 15 predetermined locations (S1-S15). To measure soil bulk density, porosity, and hydraulic conductivity, physical soil sampling was used to obtain ground truth data, and plant health was assessed using leaf area index (LAI) and transpiration rates. The Normalized Difference Vegetation Index (NDVI) calculated from satellite imagery was employed to track vegetation changes over time. Spreadsheet software SPSS v.26 and OriginPro were used to perform statistical procedures, such as Pearson correlation and regression modeling, to assess the correlation between resistivity and moisture. Findings The findings indicated a significant negative relationship, with the lowest resistivity (70 ?m) in wetlands (S6) having the highest soil moisture (25.2%) and coupling index (0.78). On the other hand, drier plantations (S11) had high resistivity (150 ?m) and lower moisture (15.5%). Moisture reserves found in deep parts of weathered regions were numerically associated with higher transpiration rates (5.8 mm/day). The conclusion was that a combination of ERT and remote sensing offers a better high-resolution system for accurate farming. Results provide a testable benchmark for planning and sustainable land use in tropical areas with respect to irrigation.