Abstract
In the present study, a new wetland risk assessment approach based on the fuzzy inference system (FIS) was developed and proposed for the first time to improve the traditional ESCOM's wetland classification and risk assessment index (WCRAI). As two of the twenty-five Iranian wetlands of international importance, the Kani Barazan and Choghakhor wetlands were selected as the study areas due to their significant roles in protecting the biodiversity of their regions. The wetlands are supported by the international Ramsar Convention on Wetlands to mandate and encourage the local authorities for their conservation and sustainable exploitation. In this regard, the Iranian Department of Environment, in cooperation with UNDP/GEF, selected these wetlands to demonstrate new approaches to managing the wetland areas protected by the Conservation of Iranian Wetlands Project (CIWP). A real-time wetland monitoring station with hydrological instruments, including water level, air temperature, air humidity, and water quality multi-parameter sensors recording water temperature, pH, specific conductance, and dissolved oxygen, was implanted at the deepest part of both wetlands. The manual sampling of water quality parameters was also carried out periodically during specific time intervals. The relative importance of the wetland health indicators involved in the FIS was determined using the analytic hierarchy process (AHP). In turn, the health level categories of both wetlands were assessed using the traditional and proposed wetland risk assessment approaches. The efficiency of the proposed method was evaluated with the considered scenarios, and it was shown to be a more flexible and appropriate approach for wetland health assessment. Furthermore, the observed differences between the health level categories of the first case study indicated the importance of using the AHP-FIS method to improve the traditional ESCOM's WCRAI.
Risk assessment of malathion on health indicators of catfish: Food and water security prospective research
