Large-scale attribution of trend in UK flood flow data

Kjeldsen, Thomas; Svensson, Cecilia; Miller, James

doi:10.7558/bhs.2012.ns29

Cited by 2 publications

(4 citation statements)

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“…Land use change can affect the number of reported floods e.g. Kjeldsen (2010) and Kjeldsen et al (2012) suggested that increased urbanisation has a pronounced effect on flood hydrology. In this work we used population and number of dwellings as a measure of exposure but not as a driver of increased hazard such as higher runoff.…”

Section: Discussionmentioning

confidence: 99%

“…There is high year-to-year climate led variation in the UK with no significant long term trends in flood frequency (Robson et al 1998, Macdonald 2006, Marsh and Harvey 2012. There is evidence for a shorter term (40-50 year) trend in the UK (Robson 2002) and significant trends were found in the UK in recent decades (Kjeldsen et al 2012). Hannaford and Marsh (2008) found significant positive trends in the frequency and magnitude of flood events in 'relatively undisturbed' catchments in the UK in the last four decades of the 20 th century.…”

Section: Introductionmentioning

confidence: 99%

“…Flood events have typically been evaluated using river flow data and the analysis of the frequency of peak flows (Robson et al 1998, Robson 2002, Macdonald 2006, Petrow and Merz 2009, Delgado et al 2010, Kjeldsen et al 2012, Marsh and Harvey 2012. Long flow series are rare, with few records extending over 70 years (Macdonald and Black 2010).…”

Section: Introductionmentioning

confidence: 99%

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Trends in reported flooding in the UK: 1884–2013

Stevens

Clarke

Nicholls

2016

Hydrological Sciences Journal

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Abstract:A long term dataset of reported flooding based on reports from the UK Meteorological Office and the UK Centre for Ecology and Hydrology is described. This is possibly a unique dataset as the authors are unaware of any other 100+ year records of flood events and their consequences on a national scale. Flood events are classified by severity based upon qualitative descriptions. There is an increase in the number of reported flood events over time associated with an increased exposure to flooding as floodplain areas were developed. The data was de-trended for exposure, using population and dwelling house data. The adjusted record shows no trend in reported flooding over time, but there is significant decade to decade variability. This study opens a new approach considering flood occurrence over a long timescale using reported information (and thus likely effects on society) rather than just considering trends in extreme hydrological conditions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Trends in reported flooding in the UK: 1884–2013

Stevens

Clarke

Nicholls

2016

Hydrological Sciences Journal

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“…The total number and percentage of models in which the normality assumption could not be accepted are also shown in each table. As already seen in Kjeldsen et al (2012), in general there appear to be little difference in the proportions of significant and non-significant coefficients for the non-natural and near-natural catchments, although a marked difference can be seen for model (c) in the summer series. In Fig.…”

Section: A Closer Look At Undisturbed Catchmentsmentioning

confidence: 71%

Non-stationarity in annual and seasonal series of peak flow and precipitation in the UK

Prosdocimi

Kjeldsen

Svensson

2014

Nat. Hazards Earth Syst. Sci.

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Abstract. When designing or maintaining an hydraulic structure, an estimate of the frequency and magnitude of extreme events is required. The most common methods to obtain such estimates rely on the assumption of stationarity, i.e. the assumption that the stochastic process under study is not changing. The public perception and worry of a changing climate have led to a wide debate on the validity of this assumption. In this work trends for annual and seasonal maxima in peak river flow and catchment-average daily rainfall are explored. Assuming a two-parameter log-normal distribution, a linear regression model is applied, allowing the mean of the distribution to vary with time. For the river flow data, the linear model is extended to include an additional variable, the 99th percentile of the daily rainfall for a year. From the fitted models, dimensionless magnification factors are estimated and plotted on a map, shedding light on whether or not geographical coherence can be found in the significant changes. The implications of the identified trends from a decisionmaking perspective are then discussed, in particular with regard to the Type I and Type II error probabilities. One striking feature of the estimated trends is that the high variability found in the data leads to very inconclusive test results. Indeed, for most stations it is impossible to make a statement regarding whether or not the current design standards for the 2085 horizon can be considered precautionary. The power of tests on trends is further discussed in the light of statistical power analysis and sample size calculations. Given the observed variability in the data, sample sizes of some hundreds of years would be needed to confirm or negate the current safety margins when using at-site analysis.

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Large-scale attribution of trend in UK flood flow data

Cited by 2 publications

References 10 publications

Trends in reported flooding in the UK: 1884–2013

Trends in reported flooding in the UK: 1884–2013

Non-stationarity in annual and seasonal series of peak flow and precipitation in the UK

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