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The effect of depth‐duration‐frequency model recalibration on rainfall return period estimates
Author(s) -
Vesuviano Gianni,
Stewart Elizabeth,
Spencer Peter,
Miller James D.
Publication year - 2021
Publication title -
journal of flood risk management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.049
H-Index - 36
ISSN - 1753-318X
DOI - 10.1111/jfr3.12703
Subject(s) - return period , environmental science , flood myth , precipitation , calibration , storm , duration (music) , climatology , meteorology , natural hazard , statistics , hydrology (agriculture) , geography , mathematics , geology , art , literature , archaeology , geotechnical engineering
In November 2009 and December 2015, two record‐breaking 24‐hr rainfalls occurred in Cumbria, UK, significantly changing the perception of flood risk for local communities. FEH13, the current UK rainfall depth‐duration‐frequency (DDF) model, estimated return periods of around 1,000 years for both events. The previous model, FEH99, received criticism from panel engineers responsible for making technical safety decisions relating to reservoirs for appearing to estimate relatively short return periods for extreme events. Although FEH13 is more consistent with current probable maximum precipitation (PMP) estimates, there is high uncertainty in both models due to the limited number of extremes captured by UK rain gauges. Furthermore, neither model included the 2009 or 2015 event in its calibration. Here, we re‐calibrate FEH13 using additional gauged rainfall data collected in Cumbria during 2006–2016, including the record‐breaking 2009 and 2015 storms. Using the updated calibration data set reduces the estimated return periods of the 2009 and 2015 events to approximately 140 years each. This case study illustrates the considerable uncertainty in short‐sample records, demonstrates the importance of maximising the quantity of relevant calibration data, shows that perception of risk depends upon the method and data used, and illustrates the difficulty of separating trends and natural variability.

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