Optimal GIS interpolation techniques and multivariate statistical approach to study the soil-trace metal(loid)s distribution patterns in the agricultural surface soil of Matehuala, Mexico

• DOI: 10.1016/j.hazadv.2023.100243
• Publication Date: 2023-01-20T08:46:24Z
• Authors: Arnab Saha; Bhaskar Sen Gupta; Sandhya Patidar; Nadia Martínez-Vi...
• Keywords: Inverse distance weighting; Trace metal; Interpolation; Soil test

Soils in the past mining areas are susceptible to trace metal(loid)s deposition and pose a health risk humans. The purpose of this work is evaluate distribution patterns contamination characteristics agricultural surface soils regions. contaminated site near an abandoned area, which surrounded by land used for maize cultivation. multivariate statistical approach GIS interpolation techniques often spatial mapping predict concentrations arsenic (As) other metals (i.e., Al, Fe, Mn, Sr) that have not been sampled. mean relative error (MRE) root square (RMSE) values were correlate efficiency deterministic (Inverse Distance Weighting- IDW, Local Polynomial- LP, Radial Basis Functions- RBF) as well geostatistical methods (Ordinary Kriging- OK Empirical Bayesian EBK). results revealed all predicted concentration soil with moderate accuracy. It was found contained enrichment (up 185 mg/kg), up five times background (35 8.5 Mexican guidelines (22 mg/kg). analysis cross-validation method IDW LP consistently provided most accurate predictions while OK, EBK, RBF less accurate. Overall, these help prediction at unexplored sites establish requirement amelioration soil.