Browsing by Author "Prawan Koppula"
Now showing 1 - 1 of 1
- Results Per Page
- Sort Options
Item Geoelectrical resistivity imaging as a reliable input for building sustainable agroecological models: a case in southwestern Nigeria(Springer, 2025) Oyeyemi, Kehinde D.; Shiv Mangal Gupta2; Prawan Koppula; Kushal Pal Singhing issues such as diminishing soil fertility and insufficient crop yield. Geoelectrical resistivity imaging serves as a valuable tool for constructing enduring agroecological models. This research presents findings of the application of geoelectrical resistivity imaging to evaluate the agricultural soil quality in terms of nutrients, moisture levels, and organic matter content. Five parallel 100-m-length 2D electrical resistivity tomography (ERT) profiles were conducted, with a minimum spacing of 5 m and reaching a maximum depth of six levels (30 m). Additionally, soil parameters and nutrient content of twenty soil samples from the study area were analyzed to assess the soil fertility level for agricultural practice. The results revealed that the subsoil can be categorized into three geoelectrical units based on inverse model resistivity values: water-saturated soils (5–20 Ωm), moist soils (21–80 Ωm), and dry soils (>100 Ωm). The near-surface subsoils up to about 10 m exhibit higher moisture content, indicating potentially enhanced soil fertility due to improved water availability for plant growth and nutrient uptake. Measured soil parameters reveal ranges of organic matter content (41–98%), electrical conductivity (0.15–0.48 dS/m), and pH values (4.11–8.11). Furthermore, the concentrations of microelements within the near-surface subsoils samples were measured, showing ranges of 176–315 ppm for nitrogen, 25.78–99.78 ppm for phosphorus, and 149–605 ppm for potassium. This study highlights the significance and effectiveness of the geoelectrical resistivity method in evaluating soil fertility for precision agriculture purposes. The method strengthens the core of agroecological models by offering vital subsurface and spatial insights. It empowers well-informed decision-making, supports the practice of sustainable land management, and actively fosters the growth of robust agricultural systems.