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Forecasting of Future Flooding and Risk Assessment under CMIP6 Climate Projection in Neuse River, North Carolina

机译:Neuse River,北卡罗来纳州CMIP6气候预测下未来洪水和风险评估的预测

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Hydrological extremes associated with climate change are becoming an increasing concern all over the world. Frequent flooding, one of the extremes, needs to be analyzed while considering climate change to mitigate flood risk. This study forecast streamflow and evaluate risk of flooding in the Neuse River, North Carolina considering future climatic scenarios, and comparing them with an existing Federal Emergency Management Agency study. The cumulative distribution function transformation method was adopted for bias correction to reduce the uncertainty present in the Coupled Model Intercomparison Project Phase 6 (CMIP6) streamflow data. To calculate 100-year and 500-year flood discharges, the Generalized Extreme Value (L-Moment) was utilized on bias-corrected multimodel ensemble data with different climate projections. Out of all projections, shared socio-economic pathways (SSP5-8.5) exhibited the maximum design streamflow, which was routed through a hydraulic model, the Hydrological Engineering Centers River Analysis System (HEC-RAS), to generate flood inundation and risk maps. The result indicates an increase in flood inundation extent compared to the existing study, depicting a higher flood hazard and risk in the future. This study highlights the importance of forecasting future flood risk and utilizing the projected climate data to obtain essential information to determine effective strategic plans for future floodplain management.
机译:与气候变化相关的水文极端正在成为世界各地的越来越多的问题。在考虑气候变化以减轻洪水风险时,需要分析一个极端的洪水。本研究预测流出并评估了Neuse河流,北卡罗来纳州的洪水风险,考虑到未来的气候情景,并将其与现有联邦应急管理局的研究进行比较。采用累积分布函数变换方法进行偏置校正,以减少耦合模型交流项目阶段6(CMIP6)流流数据中存在的不确定性。为了计算100年和500年的洪水排放,通过不同的气候预测,利用了广义极值(L-TLAGE)进行了偏置的多模型集合数据。除了所有预测中,共享的社会经济途径(SSP5-8.5)展示了最大的设计流流程,通过液压模型,水文工程中心河流分析系统(HEC-RAS)进行路由,以产生洪水淹没和风险地图。结果表明,与现有的研究相比,洪水淹没程度增加,描绘了未来较高的洪水危害和风险。本研究强调了预测未来洪水风险,并利用预计的气候数据来获得基本信息,以确定未来洪泛平坦管理的有效战略计划的重要信息。

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