wAbstract
@One of the major causes of groundwater pollution in Hamadan-Bahar
aquifer in western Iran is a nonpoint source pollution resulting
from agricultural activities. Withdrawal of over 88 of drinking
water from groundwater resources, adds urgency to the studies
leading to a better management of water supplies in this region.
In this study, the DRASTIC model was used to construct groundwater
vulnerability maps based on the gintrinsich (natural conditions
) and gspecifich (including management) concepts. As DRASTIC has
drawbacks to simulate specific contaminants, we conditioned the
rates on measured nitrate data and optimized the weights of the
specific model to obtain a nitrate vulnerability map for the region.
The performance of the conditioned DRASTIC model improved significantly
(R2 = 0.52) over the intrinsic (R2 = 0.12)
and specific (R2 = 0.19) models in predicting the groundwater
nitrate concentration. Our study suggests that a locally conditioned
DRASTIC model is an effective tool for predicting the region's
vulnerability to nitrate pollution. In addition, comparison of
groundwater tables between two periods 30 years apart indicated
a drawdown of around 50 m in the central plain of the Hamadan-Bahar
region. Our interpretation of the vulnerability maps for the two
periods showed a polluted zone developing in the central valley
requiring careful evaluation and monitoring.
Keywords: Groundwater vulnerability; SUFI2; Conditioning; Optimization;
Indexing method; Iranx
Introduction
Materials and methods
@Description f the study area
@DRASTIC model and model calibration
@Model parameterization
Results and discussion
Conclusions
Acknowledgments
References