Search

Climate change has led to concerns about increasing river floods resulting from the greater water-holding capacity of a warmer atmosphere. These concerns are reinforced by evidence of increasing economic losses associated with flooding in many parts of the world, including Europe. Any changes in river floods would have lasting implications for the design of flood protection measures and flood risk zoning. However, existing studies have been unable to identify a consistent continental-scale climatic-change signal in flood discharge observations in Europe, because of the limited spatial coverage and number of hydrometric stations. Here we demonstrate clear regional patterns of both increases and decreases in observed river flood discharges in the past five decades in Europe, which are manifestations of a changing climate. Our results—arising from the most complete database of European flooding so far—suggest that: increasing autumn and winter rainfall has resulted in increasing floods in northwestern Europe; decreasing precipitation and increasing evaporation have led to decreasing floods in medium and large catchments in southern Europe; and decreasing snow cover and snowmelt, resulting from warmer temperatures, have led to decreasing floods in eastern Europe. Regional flood discharge trends in Europe range from an increase of about 11 per cent per decade to a decrease of 23 per cent. Notwithstanding the spatial and temporal heterogeneity of the observational record, the flood changes identified here are broadly consistent with climate model projections for the next century, suggesting that climate-driven changes are already happening and supporting calls for the consideration of climate change in flood risk management.

This study presents a new analytical framework for combining historical flood data derived from sedimentological records with instrumental river flow data to increase the reliability of flood risk assessments. Historical flood records were established for two catchments through re-analysis of sedimentological records; the Nant Cwm-du, a small, steep upland catchment in the Cambrian Mountains of Wales, and a piedmont reach of the River Severn in mid Wales. The proposed framework is based on maximum likelihood and least-square estimation methods in combination with a Generalised Logistic distribution; this enables the sedimentological data to be combined effectively with existing instrumental river flow data. The results from this study are compared to results obtained using existing industry standard methods based solely on instrumental data. The comparison shows that inclusion of sedimentological data can have an important impact on flood risk estimates, and that the methods are sensitive to assumptions made in the conversion of the sedimentological records into flood flow data. As current industry standard methods for flood risk analysis are known to be highly uncertain, the ability to include additional evidence of past flood events derived from sedimentological records as demonstrated in this study can have a significant impact on flood risk assessments.

A warming climate is expected to have an impact on the magnitude and timing of river floods; however, no consistent large-scale climate change signal in observed flood magnitudes has been identified so far. We analyzed the timing of river floods in Europe over the past five decades, using a pan-European database from 4262 observational hydrometric stations, and found clear patterns of change in flood timing. Warmer temperatures have led to earlier spring snowmelt floods throughout northeastern Europe; delayed winter storms associated with polar warming have led to later winter floods around the North Sea and some sectors of the Mediterranean coast; and earlier soil moisture maxima have led to earlier winter floods in western Europe. Our results highlight the existence of a clear climate signal in flood observations at the continental scale.

Using historical data of climate, land-use, hydrology and water quality from four catchments located in the south of England, this study identifies the impact of climate and land-use change on selected water quantity and water quality indicators. The study utilises a paired catchment approach, with two catchments that have experienced a high degree of urbanisation over the past five decades and two nearby, hydrologically similar, but undeveloped catchments. Multivariate regression models were used to assess the influence of rainfall and urbanisation on runoff (annual and seasonal), dissolved oxygen levels and temperature. Results indicate: (i) no trend in annual or seasonal rainfall totals, (ii) upward trend in runoff totals in the two urban catchments but not in the rural catchments, (iii) upward trend in dissolved oxygen and temperature in the urban catchments, but not in the rural catchments, and (iv) changes in temperature and dissolved oxygen in the urban catchments are not driven by climatic variables.

This study investigates whether long-term changes in observed series of high flows can be attributed to changes in land use via nonstationary flood-frequency analyses. A point process characterization of threshold exceedances is used, which allows for direct inclusion of covariates in the model; as well as a nonstationary model for block maxima series. In particular, changes in annual, winter, and summer block maxima and peaks over threshold extracted from gauged instantaneous flows records in two hydrologically similar catchments located in proximity to one another in northern England are investigated. The study catchment is characterized by large increases in urbanization levels in recent decades, while the paired control catchment has remained undeveloped during the study period (1970–2010). To avoid the potential confounding effect of natural variability, a covariate which summarizes key climatological properties is included in the flood-frequency model. A significant effect of the increasing urbanization levels on high flows is detected, in particular in the summer season. Point process models appear to be superior to block maxima models in their ability to detect the effect of the increase in urbanization levels on high flows.

This study presents a bivariate extension of the goodness-of-fit measure for regional frequency distributions developed by Hosking and Wallis [1993] for use with the method of L-moments. Utilising the approximate joint normal distribution of the regional L-skewness and L-kurtosis, a graphical representation of the confidence region on the L-moment diagram can be constructed as an ellipsoid. Candidate distributions can then be accepted where the corresponding theoretical relationship between the L-skewness and L-kurtosis intersects the confidence region, and the chosen distribution would be the one that minimises the Mahalanobis distance measure. Based on a set of Monte Carlo simulations it is demonstrated that the new bivariate measure generally selects the true population distribution more frequently than the original method. Results are presented to show that the new measure remains robust when applied to regions where the level of inter-site correlation is at a level found in real world regions. Finally the method is applied to two different case studies involving annual maximum peak flow data from Italian and British catchments to identify suitable regional frequency distributions.

The application of historical flood information as a tool for augmenting instrumental flood data is increasingly recognised as a valuable tool; most previous studies have focused on large catchments with historic settlements, this paper applies the approach to the smaller lowland system of the Sussex Ouse in Southeast England. The reassessment of flood risk on the Sussex Ouse is pertinent in light of severe flooding in October 2000 and heightened concerns of a perceived increase in flooding nationally. Systematic flood level readings from 1960 and accounts detailing past flood events within the catchment are compiled back to c.1750. This extended flood record provides an opportunity to reassess estimates of flood frequency over a timescale not normally possible within flood frequency analysis. This paper re-evaluates flood frequency at Lewes on the Sussex Ouse downstream of the confluence of the Sussex Ouse and River Uck. The paper considers the strengths and weaknesses in estimates resulting from contrasting methods of analysis and their corresponding data: (i) single site analysis of gauged annual maxima; (ii) combined analysis of systematic annual maxima augmented with historical peaks of estimated magnitude; (iii) combined analysis of systematic annual maxima augmented with historical peaks of estimated magnitude exceeding a known threshold, and (iv) sensitivity analysis including only the very largest historical flood events. Use of the historical information was found to yield much tighter confidence intervals of risk estimates, with uncertainty reduced by up to 40% for the 100 yr return frequency event when historical information was added to the gauged data.

A new generalized method is presented enabling the use of multiple donor sites when predicting an index flood variable in an ungauged catchment using a hydrological regression model. The method is developed from the premise of having an index flood prediction with minimum variance, which results in a set of optimal weights assigned to each donor site. In the model framework presented here, the weights are determined by the geographical distance between the centroids of the catchments draining to the subject site and the donor sites. The new method was applied to a case study in the United Kingdom using annual maximum series of peak flow from 602 catchments. Results show that the prediction error of the index flood is reduced by using donor sites until a minimum of six donors have been included, after which no or marginal improvements in prediction accuracy are observed. A comparison of these results is made with a variant of the method where donor sites are selected based on connectivity with the subject site through the river network. The results show that only a marginal improvement is obtained by explicitly considering the network structure over spatial proximity. The evaluation is carried out based on a new performance measure that accounts for the sampling variability of the index flood estimates at each site. Other results compare the benefits obtained by adding relevant catchment descriptors to a simple regression model with those obtained by transferring information from local donor sites.

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 decision-making 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.

There is growing concern that flooding is becoming more frequent and severe in Europe. A better understanding of flood regime changes and their drivers is therefore needed. The paper reviews the current knowledge on flood regime changes in European rivers that has traditionally been obtained through two alternative research approaches. The first approach is the data-based detection of changes in observed flood events. Current methods are reviewed together with their challenges and opportunities. For example, observation biases, the merging of different data sources and accounting for nonlinear drivers and responses. The second approach consists of modelled scenarios of future floods. Challenges and opportunities associated with flood change scenarios are discussed such as fully accounting for uncertainties in the modelling cascade and feedbacks. To make progress in flood change research, we suggest that a synthesis of these two approaches is needed. This can be achieved by focusing on long duration records and flood-rich and flood-poor periods rather than on short duration flood trends only, by formally attributing causes of observed flood changes, by validating scenarios against observed flood regime dynamics, and by developing low-dimensional models of flood changes and feedbacks. The paper finishes with a call for a joint European flood change research network.

The report presents a review of methods used in Europe for trend analysis, climate change projections and non-stationary analysis of extreme precipitation and flood frequency. In addition, main findings of the analyses are presented, including a comparison of trend analysis results and climate change projections. Existing guidelines in Europe on design flood and design rainfall estimation that incorporate climate change are reviewed. The report concludes with a discussion of research needs on non-stationary frequency analysis for considering the effects of climate change and inclusion in design guidelines. Trend analyses are reported for 21 countries in Europe with results for extreme precipitation, extreme streamflow or both. A large number of national and regional trend studies have been carried out. Most studies are based on statistical methods applied to individual time series of extreme precipitation or extreme streamflow using the non-parametric Mann-Kendall trend test or regression analysis. Some studies have been reported that use field significance or regional consistency tests to analyse trends over larger areas. Some of the studies also include analysis of trend attribution. The studies reviewed indicate that there is some evidence of a general increase in extreme precipitation, whereas there are no clear indications of significant increasing trends at regional or national level of extreme streamflow. For some smaller regions increases in extreme streamflow are reported. Several studies from regions dominated by snowmelt-induced peak flows report decreases in extreme streamflow and earlier spring snowmelt peak flows. Climate change projections have been reported for 14 countries in Europe with results for extreme precipitation, extreme streamflow or both. The review shows various approaches for producing climate projections of extreme precipitation and flood frequency based on alternative climate forcing scenarios, climate projections from available globa

The effect of urban land cover on catchment flood response is evaluated using a lumped rainfall–runoff model to analyse flood events from selected UK catchments with mixed urban and rural land use. The present study proposes and evaluates a series of three extensions to an existing model to enable a better representation of urban effects, namely: an increase in runoff volume, reduced response time and a decrease in baseflow (resulting from decreased infiltration). Based on observed flood events from seven catchments, cross-validation methods are used to compare the predictive ability of the model variants with that of the original unmodified model. The results show that inclusion of urban effects increases the predictive ability of the model across catchments, despite large between-event variability of model performance. More detailed investigations into the relationship between model performance and individual event characteristics (antecedent soil moisture, rainfall duration, depth and intensity) did not reveal systematic inabilities of the model to reproduce certain types of events. Finally, it is demonstrated that the new extended model has the ability to simulate urban effects in accordance with the expected changes in storm runoff patterns.

In November 2009, record-breaking rainfall resulted in severe, damaging flooding in Cumbria, in the north-west of England. This paper presents an analysis of the river flows and lake levels experienced during the event. Comparison with previous maxima shows the exceptional nature of this event, with new maximum flows being established at 17 river flow gauging stations, particularly on catchments influenced by lakes. The return periods of the flood peaks are estimated using the latest Flood Estimation Handbook statistical procedures. Results demonstrate that the event has considerably reduced estimates of flood frequency and associated uncertainty. Analysis of lake levels suggests that their record high levels reduced their attenuating effect, significantly affecting the timing and magnitude of downstream peaks. The peak flow estimate of 700 m3s-1 at Workington, the lowest station on the Derwent, was examined in the context of upstream inputs and was found to be plausible. The results of this study have important implications for the future development of flood frequency estimation methods for the UK. It is recommended that further research is undertaken on the role of abnormally elevated lake levels and that flood frequency estimation procedures in lake-influenced catchments are reviewed.

The potential role of rural land use in mitigating flood risk and protecting water supplies continues to be of great interest to regulators and planners. The ability of hydrologists to quantify the impact of rural land use change on the water cycle is however limited and we are not able to provide consistently reliable evidence to support planning and policy decisions. This shortcoming stems mainly from lack of data, but also from lack of modelling methods and tools. Numerous research projects over the last few years have been attempting to address the underlying challenges. This paper describes these challenges, significant areas of progress and modelling innovations, and proposes priorities for further research. The paper is organised into five inter-related subtopics: (1) evidence-based modelling; (2) upscaling to maximise the use of process knowledge and physics-based models; (3) representing hydrological connectivity in models; (4) uncertainty analysis; and (5) integrated catchment modelling for ecosystem service management. It is concluded that there is room for further advances in hydrological data analysis, sensitivity and uncertainty analysis methods and modelling frameworks, but progress will also depend on continuing and strengthened commitment to long-term monitoring and inter-disciplinarity in defining and delivering land use impacts research.

Flood frequency analysis is used for establishing a relationship between flood magnitude and frequency of occurrence (return period) and for estimating the design-flood at a given location of interest. The approach can be implemented locally (At-Site Flood Frequency Analysis, SFFA); or regionally (Regional Flood Frequency Analysis, RFFA), which is used to limit unreliable extrapolation when available data record lengths are short as compared to the recurrence interval of interest, or for predicting the flooding potential at locations where no observed data are available. Both SFFA and RFFA are mature disciplines and consolidated methodologies are available for many European regions. As a result, different European countries, and sometimes even different regions within a country, have adopted different methodologies, which are often selected on the basis of traditional approaches or restricted due to limitation of available data. The main objective of the COST Action ES0901 European procedure for flood frequency estimation (FloodFreq, http://www.cost-floodfreq.eu/), which started in 2010, is to undertake a pan-European comparison and evaluation of methods for flood frequency estimation under the various climatologic and geographic conditions found in Europe, and different levels of data availability, as required by European Flood Directive (2007/60/EC). In particular, Working Group 2 (WG2) is focusing on an assessment of statistical methods for flood frequency estimation. In the first phase of WG2, state-of-the-art methods were collected from all member countries of the WGs, and presented in a report form. In this report, the description of applied frequency analysis methods is presented. The report also include a catalogue of flood data availability/unavailability across Europe together with relevant information (e.g., catchment descriptors, climatological [see above] and hydrological characteristics, indications on frequency distribution recommended for use in floo

The objective of this study is to undertake a preliminary investigation of trend in annual maximum series of peak flood data in the United Kingdom, as a precursor to developing a more complete procedure for non-stationary flood frequency estimation. A fifth of the trends in series that are at least 20 years long are significant at the 5% level (of in total 388 series). Most of the significant trends are positive, and are located in the north and west. The largest positive trends occur for short records in the most recent decades. Trends were also investigated for various subsets of the data, based on different catchment characteristics. There is an indication that the range of trend values observed for urban catchments is larger than the range observed for the rural subset, and that storage of water, whether in lakes and reservoirs or in permeable geology, has an ameliorating effect on trend magnitude.

Monthly duration curves have been constructed from climate data across Europe to help address the relative frequency of ecologically critical low flow stages in temporary rivers, when flow persists only in disconnected pools in the river bed. The hydrological model is 5 based on a partitioning of precipitation to estimate water available for evapotranspiration and plant growth and for residual runoff. The duration curve for monthly flows has then been analysed to give an estimate of bankfull flow based on recurrence interval. The corresponding frequency for pools is then based on the ratio of bank full discharge to pool flow, arguing from observed ratios of cross-sectional areas at flood 10 and low flows to estimate pool flow as 0.1% of bankfull flow, and so estimate the frequency of the pool conditions that constrain survival of river-dwelling arthropods and fish. The methodology has been applied across Europe at 15 km resolution, and can equally be applied under future climatic scenarios.

The paper uses a simple water balance model that partitions the precipitation between actual evapotranspiration, quick flow and delayed flow, and has sufficient complexity to capture the essence of climate and vegetation controls on this partitioning. Using this model, monthly flow duration curves have been constructed from climate data across Europe to address the relative frequency of ecologically critical low flow stages in semi-arid rivers, when flow commonly persists only in disconnected pools in the river bed. The hydrological model is based on a dynamic partitioning of precipitation to estimate water available for evapotranspiration and plant growth and for residual runoff. The duration curve for monthly flows has then been analysed to give an estimate of bankfull flow based on recurrence interval. Arguing from observed ratios of cross-sectional areas at flood and low flows, hydraulic geometry suggests that disconnected flow under "pool" conditions is approximately 0.1% of bankfull flow. Flow duration curves define a measure of bankfull discharge on the basis of frequency. The corresponding frequency for pools is then read from the duration curve, using this (0.1%) ratio to estimate pool discharge from bank full discharge. The flow duration curve then provides an estimate of the frequency of poorly connected pool conditions, corresponding to this discharge, that constrain survival of river-dwelling arthropods and fish. The methodology has here been applied across Europe at 15 km resolution, and the potential is demonstrated for applying the methodology under alternative climatic scenarios.