An uncertainty-based framework to quantifying climate change impacts on coastal flood vulnerability: case study of New York City

The continued development efforts around the world, growing population, and the increased probability of occurrence of extreme hydrologic events have adversely affected natural and built environments. Flood damages and loss of lives from the devastating storms, such as Irene and Sandy on the East Coast of the USA, are examples of the vulnerability to flooding that even developed countries have to face. The odds of coastal flooding disasters have been increased due to accelerated sea level rise, climate change impacts, and communities' interest to live near the coastlines. Climate change, for instance, is becoming a major threat to sustainable development because of its adverse impacts on the hydrologic cycle. Effective management strategies are thus required for flood vulnerability reduction and disaster preparedness. This paper is an extension to the flood resilience studies in the New York City coastal watershed. Here, a framework is proposed to quantify coastal flood vulnerability while accounting for climate change impacts. To do so, a multi-criteria decision making (MCDM) approach that combines watershed characteristics (factors) and their weights is proposed to quantify flood vulnerability. Among the watershed characteristics, potential variation in the hydrologic factors under climate change impacts is modeled utilizing the general circulation models' (GCMs) outputs. The considered factors include rainfall, extreme water level, and sea level rise that exacerbate flood vulnerability through increasing exposure and susceptibility to flooding. Uncertainty in the weights as well as values of factors is incorporated in the analysis using the Monte Carlo (MC) sampling method by selecting the best-fitted distributions to the parameters with random nature. A number of low impact development (LID) measures are then proposed to improve watershed adaptive capacity to deal with coastal flooding. Potential range of current and future vulnerability to flooding is estimated with and without consideration of climate change impacts and after implementation of LIDs. Results show that climate change has the potential to increase rainfall intensity, flood volume, floodplain extent, and flood depth in the watershed. The results also reveal that improving system resilience by reinforcing the adaptation capacity through implementing LIDs could mitigate flood vulnerability. Moreover, the results indicate the significant effect of uncertainties, arising from the factors' weights as well as climate change, impacts modeling approach, on quantifying flood vulnerability. This study underlines the importance of developing applicable schemes to quantify coastal flood vulnerability for evolving future responses to adverse impacts of climate change.