Dams are being constructed for different purposes such as water reservoir, Electricity generation, water control for irrigation, etc. About 60% of major rivers have been blocked by dams and had significant impacts on the river hydrology and morphology. Therefore, these changes have been resulted as biodiversity reduction, and destruction and deterioration of different ecosystems. In this study, we assessed the impacts of Rudbar dam, located in Lorestan province, using two methods as Modified Rapid Impact Assessment Model (MRIAM) and Bayesian Belief Networks () for both construction and operation phases of the project. In MRIAM, the impacts are being identified and then it assesses the significance of the identified impacts. The advantage of the MRIAM compare to Rapid Impact Assessment Model (RIAM) is in consideration of “Environmental susceptibility of affected area” which it has improved the RIAM to more efficient method. In the other hand, we applied the to assess the impacts of the Rudbar dam on the environmental factors in two parts as “reservoir-river upstream” and “downstream”. are working based on the Bayes Rule (1763) and distribute the information among the nodes where an applicable method provided helping environmental manager to have better management. are able to gather the heterogeneous information as a node and make the links between the nodes. Also, are able to aggregate the information and make a final decision. In overall, two methods showed that the most of the impacts are negative. Based on MRIAM, we found that 81.3% and 65.6% of the impacts negative and 18.7% and 34.4% of the impacts are positive in construction and operation phases, respectively. Based on , we found that about 72.6% and 69.1% of the negative impacts, for reservoir-river upstream and downstream respectively, are in the “High” Keywords : Environmental impact assessment, Bayesian Belief networks, Rapid Impact Assessment Model, Rudbar dam, Lorestan
