نقشه کشی ریسک سیل قرن ۲۱
Abstract
1- Introduction
2- Methods
3- Study sites and data
4- Results
5- Discussion and conclusion
Acknowledgements
Appendix A. Supplementary data
References
Abstract
Assessing flood risk using stationary flood frequency analysis techniques is commonplace. However, it is increasingly evident that the stationarity assumption of these analyses does not hold as anthropogenic climate change could shift a site’s hydroclimate beyond the range of historical behaviors. We employ nonstationary flood frequency models using the generalized extreme value (GEV) distribution to model changing flood risk for select seasons at twelve National Parks across the U.S. In this GEV model, the location and/or scale parameters of the distribution are allowed to change as a function of time-variable covariates. We use historical precipitation and modeled flows from the Variable Infiltration Capacity model (VIC), a landsurface model that simulates land–atmosphere fluxes using water and energy balance equations, as covariates to fit a best nonstationary GEV model to each site. We apply climate model projections of precipitation and VIC flows to these models to obtain future flood probability estimates. Our model results project a decrease in flood risk for sites in the southwestern U.S. region and an increase in flood risk for sites in northern and eastern regions of the U.S. for the selected seasons. The methods and results presented will enable the NPS to develop strategies to ensure public safety and efficient infrastructure management and planning in a nonstationary climate.
Introduction
Anthropogenic climate change has increased global mean annual land-surface air temperatures and evidence supports a change in the behavior of precipitation (Hartmann et al., 2013) and streamflow extremes (Hirsch and Ryberg, 2012; Mallakpour and Villarini, 2015; Ahn and Palmer, 2016). Given the non-stationary nature of our climate system at present, the common assumption in traditional flood frequency analysis techniques that flood risk will remain stationary into the future must be questioned – climate change is anticipated to continue to shift hydroclimate beyond the range of historical behaviors (Milly et al., 2008).
As temperatures rise, we expect an increase in total precipitable water in the atmosphere (Trenberth et al., 2003), which was already observed over much of North America (Ross and Elliott, 1996). Consequently, Hartmann et al. (2013) suggest a likely observed increase in either the frequency or intensity of heavy precipitation events across North America, particularly in central North America. Studies using extreme value theory and precipitation-temperature scaling also generally support this claim (DeGaetano, 2009; Wasko and Sharma, 2017).