Modified-DRASTIC, modified-SINTACS and SI methods for groundwater vulnerability assessment in the southern Tehran aquifer

J Environ Sci Health A Tox Hazard Subst Environ Eng. 2019;54(1):89-100. doi: 10.1080/10934529.2018.1537728. Epub 2018 Dec 30.

Abstract

This study aims to modify the SINTACS and DRASTIC models with a land-use (LU) layer and compares the modified-DRASTIC, modified-SINTACS and SI methods for groundwater vulnerability assessment (GVA) in the southern Tehran aquifer, Iran. Single parameter sensitivity analysis (SPSA) served to determine the most significant parameters for the modified-DRASTIC, modified-SINTACS and SI approaches, and to revise model weights from "theoretical" to "effective." The inherent implementation of LU in the SI model may explain its better performance compared to unenhanced versions of DRASTIC and SINTACS models. Validation of all models, using nitrate concentrations from 20 wells within the study area, showed the modified-SINTACS model to outperform other models. The SPSA showed that the vadose zone and LU strongly influenced the modified-DRASTIC and modified-SINTACS models, while SI was strongly influenced by aquifer media and LU. To improve performance, models were implemented using "effective" instead of "theoretical" weights. Model robustness was assessed using nitrate concentrations in the aquifer and the outcomes confirmed the positive impact of using "effective" versus "theoretical" weights in the models. Modified-SINTACS showed the strongest correlation between nitrate and the vulnerability index (coefficient of determination = 0.75). Application of the modified-SINTACS while using "effective" weights, led to the conclusion that 19.6%, 55.2%, 23.4%, and 1.6% of the study area housed very high, high, moderate and low vulnerability zones, respectively.

Keywords: Groundwater vulnerability; SINTACS; land-use; nitrate pollution; sensitivity analysis.

Publication types

  • Validation Study

MeSH terms

  • Environmental Monitoring / methods*
  • Groundwater / analysis*
  • Human Activities / statistics & numerical data
  • Humans
  • Industrial Waste / analysis
  • Iran / epidemiology
  • Manufacturing and Industrial Facilities / statistics & numerical data
  • Models, Theoretical*
  • Nitrates / analysis
  • Oil and Gas Fields
  • Risk Assessment
  • Waste Disposal Facilities / statistics & numerical data
  • Water Pollutants, Chemical / analysis
  • Water Pollution / analysis*

Substances

  • Industrial Waste
  • Nitrates
  • Water Pollutants, Chemical