A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to Characterize compound flood risk

IF 3.1 Q2 GEOSCIENCES, MULTIDISCIPLINARY Journal of Hydrology X Pub Date : 2024-09-30 DOI:10.1016/j.hydroa.2024.100189
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Abstract

Traditional approaches to flood risk management assume flood events follow an independent, identically distributed (i.i.d.) random process from which static risk measures are computed. Modern risk accounting strategies also consider nonstationarity or long-term trends in the mean and moments of the associated flood probability distributions. However, few approaches consider how extreme hydroclimatic events cluster in both space and time, compounding damage risks. Here we introduce a compound flood risk simulator that models and conditionally forecasts future variability in regional flooding events that cluster in time, given trends and oscillations in a variable climate signal. A modular, novel integration of wavelet signal processing, nonstationary time series forecasting, k-nearest neighbor (KNN) bootstrapping, multivariate copulas, and modified Neyman-Scott (NS) event clustering process provides users the ability to model interannual and sub-annual clustering of flood risk. Our semi-parametric flood generator specifically targets the clustered temporal dynamics of jointly modeled flood intensity, duration, and frequency over a finite future period of a decade or more, thereby providing a foundation for adaptation approaches that integrate temporally clustered flood risk into planning, response and recovery.
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用于描述复合洪水风险的聚类区域极端水文气候非稳态随机模拟器
传统的洪水风险管理方法假定洪水事件遵循独立、同分布(i.i.d.)的随机过程,并据此计算静态风险度量。现代风险核算策略还考虑了相关洪水概率分布的均值和矩值的非平稳性或长期趋势。然而,很少有方法会考虑极端水文气候事件如何在空间和时间上聚集,从而使损害风险复合化。在此,我们介绍了一种复合洪水风险模拟器,该模拟器可根据可变气候信号中的趋势和振荡情况,模拟并有条件地预测未来区域洪水事件在时间上的集群变化。小波信号处理、非稳态时间序列预测、k-近邻(KNN)自引导、多变量协方差和修正的奈曼-斯科特(NS)事件聚类过程的模块化、新颖集成,为用户提供了洪水风险的年际和次年聚类建模能力。我们的半参数洪水生成器专门针对联合建模的洪水强度、持续时间和频率在未来十年或更长时间内的时间动态聚类,从而为将时间聚类洪水风险纳入规划、响应和恢复的适应方法奠定了基础。
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来源期刊
Journal of Hydrology X
Journal of Hydrology X Environmental Science-Water Science and Technology
CiteScore
7.00
自引率
2.50%
发文量
20
审稿时长
25 weeks
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