Geostatistical methods for mapping groundwater nitrate concentrations: a case study of the El-Oued region

Abstract

Geostatistical modeling is a powerful tool for improving the characterization, management, and prediction of decision-making processes. The Wilaya of El-Oued is considered the backbone of agriculture in Algeria, covering 40% of the total cultivated area in the country. This makes it one of the regions with the highest consumption of agricultural fertilizers to meet the aspirations of local authorities in this field. Additionally, it has experienced significant population growth in recent years, coupled with a weak sewage network, which could lead to the direct contamination of groundwater and the region's natural resources. This study aims to test various deterministic interpolation methods, such as the inverse distance weighting (IDW) method, the radial basis function (RBF), and the geostatistical methodology (point kriging), for mapping nitrates in 113 wells in the El-Oued aquifer. We utilized Surfer 20 for this purpose. Given the significant differences in estimates based on the methods used, it is appropriate to evaluate the spatial distribution maps of nitrates obtained by comparing their predictive qualities through the calculation of the mean estimation error. The results indicate the superiority of the point kriging technique compared with deterministic estimates, with R2 estimation errors of about 0.067.