Contamination Risk Evaluation of Groundwater in the Canton of Portoviejo-Ecuador, using Susceptibility Index and two Intrinsic Vulnerability Models
DOI : 10.3844/ajessp.2017.65.76
American Journal of Environmental Sciences
Volume 13, Issue 1
The present study aims to investigate the applicability of DRASTIC, GOD and SI models in evaluating the groundwater vulnerability and risk of contamination in the Canton of Portoviejo, Ecuador. The groundwater vulnerability to contamination has been evaluated using DRASTIC and GOD models. Both models were able to classify the study area into different sectors of variable vulnerability. The coincidence of the two models is high, especially in the sectors with high vulnerability. Evaluation of the groundwater risk of contamination has been carried out by combining the contaminant load index with the elaborated groundwater vulnerability classes using DRASTIC and GOD methodologies. The resultant maps of both models reveal that in the areas with high vulnerability the land usages tend to introduce high contaminant load and therefore, the groundwater beneath these areas is subject to higher risk of contamination. The risk maps elaborated using DRASTIC and GOD models have more coincidence than vulnerability maps elaborated using the same models. This is partially because of the contaminant load index which is identical in the both cases. The groundwater risk of contamination has been also evaluated using Susceptibility Index (SI) model. The resultant SI risk map was compared with the risk maps elaborated using DRASTIC and GOD. The results indicate a comparable products; however, they have more similarity with DRASTIC outputs. The maps of groundwater risk of contamination in the canton using different models show a comparable results, especially when accepting one risk category shift as acceptable error. The coincidence in this case is 98, 94 and 88% between DRASTIC and GOD, DRASTIC and SI, GOD and SI respectively. The results of the study recommend SI and GOD models to study the risk of groundwater contamination especially in data limitation conditions.
© 2017 Suhail Sharadqah. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.