A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk
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...
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Elsevier
2024-12-01
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| Series: | Journal of Hydrology X |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589915524000191 |
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| author | Adam Nayak Pierre Gentine Upmanu Lall |
| author_facet | Adam Nayak Pierre Gentine Upmanu Lall |
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| description | 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. |
| format | Article |
| id | doaj-art-b95723c20df848b086b737e1277809d3 |
| institution | Kabale University |
| issn | 2589-9155 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology X |
| spelling | doaj-art-b95723c20df848b086b737e1277809d32024-11-23T06:31:31ZengElsevierJournal of Hydrology X2589-91552024-12-0125100189A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood riskAdam Nayak0Pierre Gentine1Upmanu Lall2Department of Earth and Environmental Engineering, Columbia University, New York, NY 10027, USA; Columbia Water Center, Columbia Climate School, Columbia University, New York, NY 10027, USA; Learning the Earth with Artificial Intelligence and Physics (LEAP) National Science Foundation Center, Columbia University, New York, NY 10027, USADepartment of Earth and Environmental Engineering, Columbia University, New York, NY 10027, USA; Columbia Water Center, Columbia Climate School, Columbia University, New York, NY 10027, USA; Learning the Earth with Artificial Intelligence and Physics (LEAP) National Science Foundation Center, Columbia University, New York, NY 10027, USADepartment of Earth and Environmental Engineering, Columbia University, New York, NY 10027, USA; Columbia Water Center, Columbia Climate School, Columbia University, New York, NY 10027, USA; School of Complex Adaptive Systems, Arizona State University, Tempe, AZ 85281, USA; The Water Institute, Arizona State University, Tempe, AZ 85281, USA; Corresponding author.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.http://www.sciencedirect.com/science/article/pii/S2589915524000191Stochastic HydrologyClustered Regional FloodingCompound RiskNonstationarityClimate Variability and Change |
| spellingShingle | Adam Nayak Pierre Gentine Upmanu Lall A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk Journal of Hydrology X Stochastic Hydrology Clustered Regional Flooding Compound Risk Nonstationarity Climate Variability and Change |
| title | A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk |
| title_full | A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk |
| title_fullStr | A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk |
| title_full_unstemmed | A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk |
| title_short | A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk |
| title_sort | nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk |
| topic | Stochastic Hydrology Clustered Regional Flooding Compound Risk Nonstationarity Climate Variability and Change |
| url | http://www.sciencedirect.com/science/article/pii/S2589915524000191 |
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