Mapping cation exchange capacity using a Veris-3100 instrument and invVERIS modelling software.

Area of Science:

• Soil Science
• Geophysics
• Environmental Science

Background:

• Cation exchange capacity (CEC) is crucial for soil nutrient retention and structural stability.
• Accurate 3D mapping of CEC is essential for effective land management and agricultural practices.

Purpose of the Study:

• To develop and validate a 3D mapping method for soil CEC using electrical conductivity.
• To establish a reliable linear regression model for predicting CEC from electrical conductivity data at various soil depths.

Main Methods:

• Electrical conductivity (ECa) data were collected using Veris-3100 along transects.
• Quasi-3D inversion (invVeris V1.1) estimated true electrical conductivity (σ).
• Linear regression (LR) was established between σ and measured CEC at multiple depths.

Main Results:

• A strong linear regression model (CEC=1.77+0.33×σ) with R²=0.89 was developed.
• Cross-validation showed high accuracy (RMSE=1.69 cmol(+)/kg, R²=0.88) for topsoil and subsurface CEC prediction.
• Subsoil CEC prediction accuracy was limited by data availability in areas with rapid EC changes.

Conclusions:

• The developed method effectively predicts 3D CEC distribution in topsoil and subsurface layers.
• Improving EC data density in areas of rapid spatial variation can enhance subsoil CEC prediction.
• This approach offers a valuable tool for precision agriculture and soil resource management.