Risk assessment of groundwater pollution using Monte Carlo approach in an agricultural region: an example from Kerman Plain, Iran

• Main Authors: Neshat, Aminreza, Pradhan, Biswajeet, Javadi, Saman
• Format: Article
• Language: English
• Published: Elsevier 2015
• Online Access: http://psasir.upm.edu.my/id/eprint/46188/1/Risk%20assessment%20of%20groundwater%20pollution%20using%20Monte%20Carlo%20approach%20in%20an%20agricultural%20region%20An%20example%20from%20Kerman%20Plain%2C%20Iran.pdf; http://psasir.upm.edu.my/id/eprint/46188/

In groundwater resource management, the risk assessment of groundwater pollution is an effective tool in arid and semi-arid regions, such as Kerman Plain, Iran. In addition to risk assessment, and the mapping of damage and pollution probability occurrence is considered as a fundamental phase of protective groundwater management in agricultural regions. To characterize risk index affecting the study area, a novel approach was developed by combining both damage map which was obtained by multiplying seven hydrogeological parameters of modified DRASTIC model with pollution and probability of pollution occurrence with consideration of uncertainty. The study area is located in an agricultural land; therefore, nitrate was used as a pollution parameter. The spatial distribution of nitrate concentration in the area was investigated by ordinary kriging. In addition, Monte Carlo simulation (MCS) and normal distribution function were used to evaluate the uncertainty of this parameter and the probability of pollution occurrence in the study area. Risk assessment parameters were constructed, classified, and integrated in a GIS environment. Groundwater movement induces the transport of pollutants underground. Thus, we proposed a new methodology combining damage map and Monte Carlo simulation for probability and parameters uncertainty. The proposed method can be used to monitor pollution damage on a regional scale and ensure effective groundwater resource management for reducing the amount of pollution for future. Damage index and risk classification were compared; results indicate a high degree of similarity. The regions with low and very low risks are located in the northeast, northwest, and central parts, where further studies could be conducted for the subsequent development and long-term design of protective measures.