AbstractUncertainties are predominant in hydropower development that lead to risks of time and cost overruns. The overruns’ assessment requires quantitative data that is difficult to obtain and sometimes partially or completely unavailable. Accordingly, this study proposes an expert fuzzy-based system for assessing the impact of uncertainties on time and cost overrun. A Bayesian network analysis is used wherein the experts’ opinions are incorporated through an analytic hierarchy process for the uncertainty’s likelihood and impact. A fuzzy inference system is used to incorporate the decision maker’s optimistic and pessimistic approaches. The proposed methodology is illustrated through a 3×42  MW run-of-river Myntdu Leshka Hydroelectric project in India. The project’s initial likely completion time was five years with a cost of ₹3,630 million at the 1999 price level. The results state that the project’s time and cost overruns lie between 158% and 196% and between 235% and 276%, respectively, under optimistic and pessimistic conditions. Such a methodology has not been applied by past studies for hydropower projects, which is the study’s main contribution. The methodology can be easily applied by construction project developers globally in different fields by varying the uncertainties, their likelihood, and impact scales as per different risk perceptions and regional conditions.Practical ApplicationsThe methodology shown in the current study can be applied by hydropower and other construction project developers globally. The likelihood and impact scales, fuzzy optimistic and pessimistic rule base, and number and type of uncertainties can be changed easily based on the developers’ perceptions. In the case of hydropower projects, this method should be applied once the detailed project report (DPR) is prepared and prior to its submission to the approval authority.

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