TY - JOUR
T1 - Characterization, geostatistical modeling and health risk assessment of potentially toxic elements in groundwater resources of northeastern Iran
AU - Joodavi, Ata
AU - Aghlmand, Reza
AU - Podgorski, Joel
AU - Dehbandi, Reza
AU - Abbasi, Ali
PY - 2021
Y1 - 2021
N2 - Study region: Northeastern Iran. Study focus: In northeastern Iran, water needed for municipal and agricultural activities mainly comes from groundwater resources. However, it is subject to substantial anthropogenic and geogenic contamination. We characterize the sources of groundwater contamination by employing an integrated approach that can be applied to the identification of large-scale contamination sources in other regions. An existing dataset of georeferenced water quality parameters from 676 locations in northeast of Iran was analyzed to investigate the geochemical properties of groundwater. Gridding of the parameters graphically illustrates the areas affected by high concentrations of As, Cl−, Cr, Fe, Mg2+, Na+, NO3−, Se, and SO42-. We then identified potential anthropogenic and geogenic contamination sources by employing random forest (RF) regression modeling. New hydrological insights for the region: Random forest (RF) models show that the major ions, As, Cr, Fe, and Se content of groundwater are mainly determined by geology in the study area. Modeling also links groundwater NO3− contamination with sewage discharge into aquifers as well as the application of nitrogenous and animal-waste fertilizers. Areas of high salinity result from evaporate deposits and irrigation return flow. Medium to high non-carcinogenic health risk is found in areas with high concentrations of geogenic As and Cr in groundwater. Our approach can be applied elsewhere to analyze regional groundwater quality and associated health risks as well as identify potential sources of contamination.
AB - Study region: Northeastern Iran. Study focus: In northeastern Iran, water needed for municipal and agricultural activities mainly comes from groundwater resources. However, it is subject to substantial anthropogenic and geogenic contamination. We characterize the sources of groundwater contamination by employing an integrated approach that can be applied to the identification of large-scale contamination sources in other regions. An existing dataset of georeferenced water quality parameters from 676 locations in northeast of Iran was analyzed to investigate the geochemical properties of groundwater. Gridding of the parameters graphically illustrates the areas affected by high concentrations of As, Cl−, Cr, Fe, Mg2+, Na+, NO3−, Se, and SO42-. We then identified potential anthropogenic and geogenic contamination sources by employing random forest (RF) regression modeling. New hydrological insights for the region: Random forest (RF) models show that the major ions, As, Cr, Fe, and Se content of groundwater are mainly determined by geology in the study area. Modeling also links groundwater NO3− contamination with sewage discharge into aquifers as well as the application of nitrogenous and animal-waste fertilizers. Areas of high salinity result from evaporate deposits and irrigation return flow. Medium to high non-carcinogenic health risk is found in areas with high concentrations of geogenic As and Cr in groundwater. Our approach can be applied elsewhere to analyze regional groundwater quality and associated health risks as well as identify potential sources of contamination.
KW - Groundwater quality
KW - Health risk assessment
KW - Iran
KW - Random forest modelling
KW - Toxic elements
UR - http://www.scopus.com/inward/record.url?scp=85112006517&partnerID=8YFLogxK
U2 - 10.1016/j.ejrh.2021.100885
DO - 10.1016/j.ejrh.2021.100885
M3 - Article
AN - SCOPUS:85112006517
SN - 2214-5818
VL - 37
SP - 1
EP - 15
JO - Journal of Hydrology: Regional Studies
JF - Journal of Hydrology: Regional Studies
M1 - 100885
ER -