A fuzzy framework for risk analysis of dam-break flood in climate change scenarios

The conventional Dam Break Risk (DBR) analysis methods do not consider qualitative (e.g., socio-environmental and ecological) losses in conjunction with quantitative (e.g., economic) losses. This article contributes a novel DBR analysis methodology in a fuzzy framework to address this issue. It quantifies risk effectively using a newly proposed Modified Aggregate Risk Index (MARI) that integrates information on three risk indicators (likelihood of dam-break flood, severity of consequent hazard, and exposure index). It can incorporate uncertain, ambiguous, and vague information on risk indicators by harnessing the advantages of both static and variable fuzzy set theories. The effect of uncertainty in weights assigned to different exposure indicators for MARI estimation is investigated by considering different options for weight estimation (conventional and fuzzy analytical hierarchy process, simplex fuzzy binary comparison method). The effectiveness of the proposed methodology is demonstrated through a study on the Hemavathy Dam (India) and its floodplain. Furthermore, to discern the effect of climate change on DBR, its future scenarios are determined by obtaining projections of MARI considering simulations of hydrometeorological variables from eleven CMIP6 GCMs (General Circulation Models) for four climate change scenarios (SSPs: 126, 245, 370, and 585). Results indicate that dam break/breach hazards are projected to be highest for SSP 585 scenario, but the highest DBR is projected for SSP 370 and 245 scenarios owing to differences in future projections of populations. The proposed methodology appears promising in determining information for devising DBR mitigation plans, even for dams in data-sparse areas.