Fuzzy-based Probabilistic Ecological Risk Assessment Approach: A Case Study of Heavy Metal Contaminated Soil

Abstract

The ecological risk assessment tools, viz. index of geoaccumulation (I geo) and enrichment factor (EF), are the classical models for the assessment of risk related to the soil and sediment contamination. These models are well classified into several classes for the assessment of contamination risk. The vagueness in the estimation of risk associated with these models creates voids for computational approaches. In the present study, fuzzy-based probabilistic model was developed to restrict the vagueness of risk estimation. Both I geo and EF were taken as input variables for aggregate risk determination. The linguistic attributes were assigned for risk estimation and qualitative scale presented as trapezoidal fuzzy number. For the validation of methodology, a case study was taken into the account for risk determination. The fuzzy-based aggregate risk assessment revealed high risk of cadmium and arsenic toxicity in the study area with the risk score of 0.751 and 0.698, respectively. The fuzzy-based risk assessment is a conceptual methodology that restricts the vagueness in the estimation of risk for better decision-making approach.