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. Classical statistical methods for flood frequency estimationassume stationarity in the gauged data. However, recent focus on climatechange and, within UK hydrology, severe floods in 2009 and 2015 has raisedthe profile of statistical analyses that include trends. This paper considers how parameter estimates for the generalised logisticdistribution vary through time in the UK. The UK Benchmark Network (UKBN2)is used to allow focus on climate change separate from the effects ofland-use change. We focus on the sensitivity of parameter estimates toadding data, through fixed-width moving window and fixed-start extendingwindow approaches, and on whether parameter trends are more prominent inspecific geographical regions. Under stationary assumptions, the addition of new data tends to further theconvergence of parameters to some final value. However, addition of asingle data point can vastly change non-stationary parameter estimates.Little spatial correlation is seen in the magnitude of trends in peak flowdata, potentially due to the spatial clustering of catchments in the UKBN2.In many places, the ratio between the 50-year and 100-year flood isdecreasing, whereas the ratio between the 2-year and 30-year flood isincreasing, presenting as a flattening of the flood frequency curve.

Have trends changed over time? A study of UK peak flow data and sensitivity to observation period