Groundwater risk mapping prediction using mathematical modeling and the Monte Carlo technique

Groundwater vulnerability to pollution and risk assessment are some of the main tools that groundwater resources management decision makers use to protect aquifers from being polluted by human activities at the surface. In this research study a new risk assessment method was investigated to better predict the vulnerable areas and incorporate risk probability into the forecast. The proposed method is a combination of the overlay-index algorithm and the processing simulation modeling method. For probability realization, the Monte Carlo method was used. In addition, an auxiliary program was developed to automate the calculation and post-processing of the results. To evaluate the proposed methodology, an aquifer in southwestern Iran was selected. Five thousand realizations were produced for use in the Monte Carlo method. The results showed that a risk map is different from a vulnerability map and the risk map is more realistic as a planning tool. It is necessary to use mathematical models and probability in long-term planning for groundwater management. This case study showed that the proposed method and the developed auxiliary program are easy to use and produce reliable results.