SPATIAL INVESTIGATION OF SULFATE IN GROUNDWATER OF ASMARA, ERITREA

Abstract

This study examines the spatial distribution and prediction of sulfate levels in groundwater of Asmara, Eritrea. The research integrates data from wells and applies ordinary kriging and semi-variogram analysis. The study classifies the area into three zones based on standard categories: excellent, good, and poor quality. Data analysis indicates a skewed sulfate dataset requiring log transformation for normality. The semi-variogram analysis identifies hole effect as the best model for prediction, where the study's prediction map reveals that most of the areas meet the desired sulfate levels. The findings provide valuable insights for sustainable water management, guiding decision-making and highlighting the significance of geostatistics and GIS technology in predicting groundwater quality.