Assessment of groundwater contamination risk with scenario analysis of hazard quantification for a karst aquifer in Antalya, Turkey


Cil A., Muhammetoglu A., Ozyurt N. N. , Yenilmez F., Keyikoglu R., Amil A., ...Daha Fazla

ENVIRONMENTAL EARTH SCIENCES, cilt.79, sa.9, 2020 (SCI İndekslerine Giren Dergi) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 79 Konu: 9
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1007/s12665-020-08932-5
  • Dergi Adı: ENVIRONMENTAL EARTH SCIENCES

Özet

Karst aquifers usually have high vulnerability to groundwater pollution. This study aims to assess the risk of groundwater contamination in karst aquifers by two index overlay methods of intrinsic vulnerability (COP and PI) and to discuss the importance of hazard index values on risk assessment. Altinova region of Antalya, with intensive agricultural activities, was chosen as the pilot study area (PSA) for application. Seasonal monitoring studies were conducted at 25 sampling wells for many water quality parameters in addition to soil characteristics and depth to groundwater. The areas for low, moderate and high levels of vulnerability and risk were determined, where more than 90% of the PSA was classified as having moderate to very high vulnerability levels according to COP and PI methods. For validation of risk analysis results, nitrate concentrations were correlated with risk intensity values. Both methods were successful to assess the vulnerability and risk to groundwater pollution with high correlation. In addition, the impacts of hazard index values on groundwater pollution risk were investigated for two scenario conditions which represent the increase in the relative amount of pollutants caused by the greenhouses. As a result, the karstic part of the PSA was assessed to have a high risk of groundwater contamination by the COP method, where immediate control measures are necessary. In conclusion, the selection of suitable vulnerability methods for karst aquifers and assignment of realistic hazard index values are highly effective on risk analysis results to represent the actual conditions.