The influence of hydroclimatic variability on flood frequency in the Lower Rhine

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• 作者：Willem H. J. Toonen ; Hans Middelkoop ; Tiuri Y. M. Konijnendijk ; Mark G. Macklin and Kim M. Cohen
• 刊名：Earth Surface Processes and Landforms
• 出版年：2016
• 出版时间：July 2016
• 年：2016
• 卷：41
• 期：9
• 页码：1266-1275
• 全文大小：847K
• ISSN：1096-9837

文摘

Climate change is expected to significantly affect flooding regimes of river systems in the future. For Western Europe, flood risk assessments generally assume an increase in extreme events and flood risk, and as a result major investments are planned to reduce their impacts. However, flood risk assessments for the present day and the near future suffer from uncertainty, coming from short measurements series, limited precision of input data, arbitrary choices for particular statistical and modelling approaches, and climatic non-stationarities. This study demonstrates how historical and sedimentary information can extend data records, adds important information on extremes, and generally improves flood risk assessments. The collection of specific data on the occurrence and magnitude of extremes and the natural variability of the floods is shown to be of paramount importance to reduce uncertainty in our understanding of flooding regime changes in a changing climate. For the Lower Rhine (the Netherlands and Germany) estimated recurrence times and peak discharges associated with the current protection levels correlate poorly with historical and sedimentary information and seem biased towards the recent multi-decadal period of increased flood activity. Multi-decadal and centennial variability in flood activity is recorded in extended series of discharge data, historical information and sedimentary records. Over the last six centuries that variability correlates with components of the Atlantic climate system such as the North Atlantic Oscillation (NAO) and Atlantic Multi-decadal Oscillation (AMO). These climatic non-stationarities importantly influence flood activity and the outcomes of flood risk assessments based on relatively short measurement series. Copyright