Nonstationary Based Framework for Performance Enhancement of Coastal Flood Mitigation Strategies
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 6
Abstract
The flood protection topic has been the centerpiece of many studies due to the amplification of coastal vulnerabilities, especially on the east coast of the United States. In this study, increasing the reliability of the urban infrastructure has been addressed by a more accurate understanding of flood hazards and coastal protection strategies. The first step in this study is the hydrologic data analysis. Climate change and human activities have often caused an invalidation of stationarity assumption for simulation and forecasting flood hazards. Also, hydrological events often coincide with two or more natural events. Therefore, for a more accurate analysis, three approaches are introduced to assess the nonstationarity in data. Then, the nonstationary frequency analysis on a univariate distribution function and the joint probability distribution have been applied to define the frequency of flood hazards. First, a trade-off curve is plotted to contain all results of a nonstationary joint probability analysis that can be used to select the design value curve based on decision-makers’ preferences. The second step is the selection of coastal protection strategies. Strategies are selected based on their suitability and the characteristics of the protected area. The final step is to utilize a hydrologic distribution model, with the ability to simulate both rainfall and storm surge for obtaining a flood inundation map in order to test the strategies. Although, this model has certain limitations of not including wave dynamics and setup and wind speed. It succeeds in the integration of hydrologic and systems analyses, which is the main advantage of the methodology. The results show the significant value of a nonstationary analysis for obtaining design values and selecting comprehensive coastal protection strategies. The proposed methodology can be implemented in other coastal geographic settings.
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Data Availability Statement
All input data used in this research can be found from the publicly available domains of the National Oceanic and Atmospheric Administration (NOAA) National Weather Service, the NOAA Climate Prediction Center, the NOAA Tides and Currents, and the United States Geological Survey (USGS) National Map Service. All code generated during the study are available from the corresponding author by request.
Acknowledgments
The authors would like to thank Dr. M. Fereshtehpour, Dr. M. A. Olyaei D. Mahmoodzadeh (Ph.D. candidate), and Zahra Heydari (research assistant from the University of Tehran), as well as M. Taheri (Ph.D. candidate from the University of Waterloo), for their valuable comments in the preparation of this paper.
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Journal of Hydrologic Engineering
Volume 25 • Issue 6 • June 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Apr 9, 2019
Accepted: Dec 5, 2019
Published online: Mar 19, 2020
Published in print: Jun 1, 2020
Discussion open until: Aug 19, 2020
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