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Keywords:Nonstationary flood frequency analysis Nonstationary return period Risk of failure Nonstationary confidence intervals Generalized linear models Generalized additive models a b s t r a c tThe increasing effort to develop and apply nonstationary models in hydrologic frequency analyses under changing environmental conditions can be frustrated when the additional uncertainty related to the model complexity is accounted for along with the sampling uncertainty. In order to show the practical implications and possible problems of using nonstationary models and provide critical guidelines, in this study we review the main tools developed in this field (such as nonstationary distribution functions, return periods, and risk of failure) highlighting advantages and disadvantages. The discussion is supported by three case studies that revise three illustrative examples reported in the scientific and technical literature referring to the Little Sugar Creek (at Charlotte, North Carolina), Red River of the North (North Dakota/Minnesota), and the Assunpink Creek (at Trenton, New Jersey). The uncertainty of the results is assessed by complementing point estimates with confidence intervals (CIs) and emphasizing critical aspects such as the subjectivity affecting the choice of the models' structure. Our results show that (1) nonstationary frequency analyses should not only be based on at-site time series but require additional information and detailed exploratory data analyses (EDA); (2) as nonstationary models imply that the time-varying model structure holds true for the entire future design life period, an appropriate modeling strategy requires that EDA identifies a well-defined deterministic mechanism leading the examined process; (3) when the model structure cannot be inferred in a deductive manner and nonstationary models are fitted by inductive inference, model structure introduces an additional source of uncertainty so that the resulting nonstationary models can provide no practical enhancement of the credibility and accuracy of the predicted extreme quantiles, whereas possible model misspecification can easily lead to physically inconsistent results; (4) when the model structure is uncertain, stationary models and a suitable assessment of the uncertainty accounting for possible temporal persistence should be retained as more theoretically coherent and reliable options for practical applications in real-world design and management problems; (5) a clear understanding of the actual probabilistic meaning of stationary and nonstationary return periods and risk of failure is required for a correct risk assessment and communication.

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Multi-day rainfall events are an important cause of recent severe flooding in the UK, and any change in the magnitude of such events may have severe impacts upon urban structures such as dams, urban drainage systems and flood defences and cause failures to occur. Regional pooling of 1-, 2-, 5-and 10-day annual maxima for 1961 to 2000 from 204 sites across the UK is used in a standard regional frequency analysis to produce generalized extreme value growth curves for long return-period rainfall events for each of nine defined climatological regions. Temporal changes in 1-, 2-, 5-and 10-day annual maxima are examined with L-moments using both a 10 year moving window and the fixed decades of 1961-70, 1971-80, 1981-90 and 1991-2000. A bootstrap technique is then used to assess uncertainty in the fitted decadal growth curves and to identify significant trends in both distribution parameters and quantile estimates.There has been a two-part change in extreme rainfall event occurrence across the UK from 1961 to 2000. Little change is observed at 1 and 2 days duration, but significant decadal-level changes are seen in 5-and 10-day events in many regions. In the south of the UK, growth curves have flattened and 5-and 10-day annual maxima have decreased during the 1990s. However, in the north, the 10-day growth curve has steepened and annual maxima have risen during the 1990s. This is particularly evident in Scotland. The 50 year event in Scotland during 1961-90 has become an 8-year, 11-year and 25-year event in the East, South and North Scotland pooling regions respectively during the 1990s. In northern England the average recurrence interval has also halved. This may have severe implications for design and planning practices in flood control.

A change detection and thresholding methodology has been adapted from previous studies to determine the extent of flooding for 13 Sentinel-1 synthetic aperture radar images captured during the floods of winter 2015-2016 in Yorkshire, UK. Both available polarisations, VH and VV, have been processed to allow for a comparison of their respective accuracy for delineating surface water. Peak flood extents are found on 29 December 2015 during the aftermath of storms Eva and Frank. Results have been validated against a Sentinel-2 optical image, with both polarisations producing a total accuracy of 97%. Of the two polarisations, VV produces fewer misclassifications, mirroring the similar results reported in previous research. Mapped results are compared to the Environment Agency Flood Maps for Planning (EA FMP), with good correlation observed for inundation on the floodplains. Differences occur away from the floodplains, with the satellite data identifying pluvial flooding not highlighted by the EA FMP.