Probabilistic Assessment of Groundwater Quality and Fluoride Exposure Risk for North-Eastern Rajasthan, India

Fluoride risk has been highlighted for many regions in India, particularly the north-western parts that include Rajasthan amongst the most severely affected. Comprehensive probabilistic analysis incorporating all the sources of uncertainties is essential for proper assessment of the exposure risk. In this study, a Monte Carlo simulation (MCS) based methodology is formulated for probabilistic assessment of water quality and contaminant risk. This is demonstrated with groundwater quality data from semiarid regions of Rajasthan. Measurement uncertainty is addressed and nonparametric method is implemented for the risk analysis. A method to ascertain the required number of MCS simulations for such application is proposed. Results indicate that the deterministic estimate could undervalue the water quality parameters as well as the actual fluoride exposure risk. This could be a reason for the increasing number of affected people in the region despite the remediation measures (based on deterministic estimates) being implemented. Therefore, water quality and contaminant risk assessment should be preferably conducted in a probabilistic approach and periodically performed with updated data for monitoring temporal variations.