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 land-surface 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.

使用固定洪水频率分析技术评估洪水风险是司空见惯的。但是，越来越明显的是，这些分析的平稳性假设不成立，因为人为的气候变化可能会使某个地点的水文气候变化超出历史行为范围。我们使用非平稳洪水频率模型，使用广义极值（GEV）分布来模拟全美12个国家公园特定季节的洪水风险变化。在此GEV模型中，分布的位置和/或尺度参数允许随时变协变量的函数。我们使用历史降水和来自可变渗透能力模型（VIC）的模拟流量，该模型是使用水和能量平衡方程来模拟陆地-大气通量的地表模型，作为协变量以使最佳非平稳GEV模型适合每个站点。我们将降水和VIC流量的气候模型预测应用于这些模型，以获得未来的洪水概率估计。我们的模型结果预测，在选定的季节内，美国西南地区的地点的洪水风险降低，而美国北部和东部地区的地点的洪水风险增加。提出的方法和结果将使NPS能够制定战略，以确保在非平稳气候下的公共安全和有效的基础设施管理和规划。特定季节，美国北部和东部地区的站点遭受洪灾的风险增加。提出的方法和结果将使NPS能够制定战略，以确保在非平稳气候下的公共安全和有效的基础设施管理和规划。特定季节，美国北部和东部地区的站点遭受洪灾的风险增加。提出的方法和结果将使NPS能够制定战略，以确保在非平稳气候下的公共安全和有效的基础设施管理和规划。