The importance of vegetation change in the prediction of future tropical cyclone flood statistics

Abstract:

Global sea level rise is a near certainty over the next century (e.g., Stocker et al. 2013 [IPCC] and references therein). With sea level rise, coastal topography and land cover (hereafter “landscape”) is expected to change and tropical cyclone flood hazard is expected to accelerate (e.g., Irish et al. 2010 [Ocean Eng], Woodruff et al. 2013 [Nature], Bilskie et al. 2014 [Geophys Res Lett], Ferreira et al. 2014 [Coast Eng], Passeri et al. 2015 [Nat Hazards]). Yet, the relative importance of sea-level rise induced landscape change on future tropical cyclone flood hazard assessment is not known. In this paper, idealized scenarios are used to evaluate the relative impact of one class of landscape change on future tropical cyclone extreme-value statistics in back-barrier regions: sea level rise induced vegetation migration and loss. The joint probability method with optimal sampling (JPM-OS) (Resio et al. 2009 [Nat Hazards]) with idealized surge response functions (e.g., Irish et al. 2009 [Nat Hazards]) is used to quantify the present-day and future flood hazard under various sea level rise scenarios. Results are evaluated in terms of their impact on the flood statistics (a) when projected flood elevations are included directly in the JPM analysis (Figure 1) and (b) when represented as additional uncertainty within the JPM integral (Resio et al. 2013 [Nat Hazards]), i.e., as random error. Findings are expected to aid in determining the level of effort required to reasonably account for future landscape change in hazard assessments, namely in determining when such processes are sufficiently captured by added uncertainty and when sea level rise induced vegetation changes must be considered dynamically, via detailed modeling initiatives.

Acknowledgements: This material is based upon work supported by the National Science Foundation under Grant No. CMMI-1206271 and by the National Sea Grant College Program of the U.S. Department of Commerce’s National Oceanic and Atmospheric Administration under Grant No. NA10OAR4170099. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of these organizations. The STOKES ARCC at the University of Central Florida provided computational resources for storm surge simulations.