Intraseasonal predictability of the duration of flooding above National Weather Service flood warning levels across the U.S. Midwest

Unpreparedness is often the main cause of the economic and social damages caused by floods. To mitigate these impacts, short-term forecasting has been the focus of several studies during the past decades; however, less effort has been paid to flood predictions at longer lead times. Here, we use forecasts by six models from the North American Multi-Model Ensemble project with a lead time from 0.5 to 9.5 months to predict the seasonal duration of floods above four National Weather Service flood categories (“action,” “flood,” “moderate” and “major”). We focus on 202 U.S. Geological Survey gage stations across the U.S. Midwest and use a statistical framework which considers precipitation, temperature, and antecedent wetness conditions as predictors. We find that the prediction skill of the duration of floods for the “action” and “flood” categories is overall low, largely because of the low accuracy of the climate forecasts rather than of the errors introduced by the statistical models. The prediction skill slightly improves when considering the shortest lead times (i.e., from 0.5 to 2.5 months) during spring in the Northern Great Plains, where antecedent wetness conditions play an important role in influencing the generation of floods. It is very difficult to draw strong conclusions with respect to the “moderate” and “major” flood categories because of the limited number of available events.     

Evaluating the effect of scale in flood inundation modelling in urban environments

Cellular‐based approaches for flood inundation modelling have been extensively calibrated and evaluated for the prediction of flood flows on rural river reaches. However, there has only been limited application of these approaches to urban environments, where the need for flood management is greatest. Practical application of two‐dimensional (2D) flood inundation models is often limited by computation time and processing power on standard desktop PCs when attempting to resolve flows on the high‐resolution grids necessary to replicate urban features. Consequently, it is necessary to evaluate the effectiveness of coarse grids to represent flood flows through urban environments. To examine these effects, LISFLOOD‐FP, a 2D storage cell model, is applied to hypothetical flooding scenarios in Greenfields, Glasgow. Grid resampling techniques in GIS software packages are evaluated and a bilinear gridding technique appears to provide the most accurate and physically intuitive results. A gridding method maintaining sharp elevation changes at building interfaces and neighbouring land is presented and estimates of the discretization noise associated with the coarse resolution grids suggest little improvement over current gridding methods. The variation in model results from the friction sensitivity analysis suggests a non‐stationary response to Manning's n with changing model resolution. Model results suggests that a coarse resolution model for urban applications is limited by the representation of urban media in coarse model grids. Furthermore, critical length scales related to building dimensions and building separation distances exist in urban areas that determine maximum possible grid resolutions for hydraulic models of urban flooding. Copyright ©, 2008 John Wiley & Sons, Ltd.     

Hydrometeorological controls and erosive response of an extreme alpine debris flow

On 29 August, 2003, an intense convective storm system affected the Fella River basin, in the eastern Italian Alps, producing rainfall peaks of approximately 390 mm in 12 h. The storm triggered an unusually large debris flow in the ungauged Rio Cucco basin (0·65 km²), with a volume of approximately 78 000 m³. The analysis of the time evolution of the rainstorm over the basin has been based on rainfall estimates from radar observations and data recorded by a raingauge network. Detailed geomorphological field surveys, carried out both before and after the flood of August 2003, and the application of a distributed hydrological model have enabled assessment of flood response, estimation of erosion volumes and sediment supply to the channel network. The accounts of two eyewitnesses have provided useful elements for reconstructing the time evolution and the flow processes involved in the event. Liquid peak discharge estimates cluster around 20 m³ s^?1 km^?2, placing this event on the flood envelope curve for the eastern Italian Alps. The hydrological analysis has shown that the major controls of the flood response were the exceptional cumulated rainfall amount, required to exceed the large initial losses, and the large rainfall intensities at hourly temporal scales, required to generate high flood response at the considered basin scale. Observations on the deposits accumulated on the alluvial fan indicate that, although the dominant flow process was a debris flow, sheetflood also contributed to fan aggradation and fluvial reworking had an important role in winnowing debris‐flow lobes and redistributing sediment on the fan surface. This points out to the large discharge values during the recession phase of the flood, implying an important role for subsurface flow on runoff generation of this extreme flash flood event. Copyright © 2009 John Wiley & Sons, Ltd.     

Discrete principal‐monotonicity inference for hydro‐system analysis under irregular nonlinearities,data uncertainties,and multivariate dependencies. Part II: Application to streamflow simulation in the Xingshan Watershed,China

Provision of reliable scientific support to socio‐economic development and eco‐environmental conservation is challenged by complexities of irregular nonlinearities, data uncertainties, and multivariate dependencies of hydrological systems in the Three Gorges Reservoir (TGR) region, China. Among them, the irregular nonlinearities mainly represent unreliability of regular functions for robust simulation of highly complicated relationships between variables. Based on the proposed discrete principal‐monotonicity inference (DPMI) approach, streamflow generation in the Xingshan Watershed, a representative watershed in this region, is examined. Based on system characterization, predictor identification, and streamflow distribution transformation, DPMI parameters are calibrated through a two‐stage strategy. Results indicate that the modelling efficiency of DPMI is satisfactory for streamflow simulation under these complexities. The distribution transformation method and the two‐stage calibration strategy can deal with non‐normality of streamflow and temporally unstable accuracy of hydrological models, respectively. The DPMI process and results reveal that both streamflow uncertainty and its rising tendency increase with flow levels. The dominant driving forces of streamflow generation are daily lowest temperature and daily cumulative precipitation in consideration of performances in global and local scales. The temporal heterogeneity of local significances to streamflow is insignificant for meteorological conditions. There is significant nonlinearity between meteorological conditions and streamflow and dependencies among meteorological conditions. The generation mechanism of low flows is more complicated than medium flows and high flows. The DPMI approach can facilitate improving robustness of hydro‐system analysis studies in the Xingshan Watershed or the TGR region. Copyright © 2016 John Wiley & Sons, Ltd.     

Discrete principal‐monotonicity inference for hydro‐system analysis under irregular nonlinearities,data uncertainties,and multivariate dependencies. Part I: methodology development

Hydrological system analyses are challenged by complexities of irregular nonlinearities, data uncertainties, and multivariate dependencies. Among them, the irregular nonlinearities mainly represent inexistence of regular functions for robustly simulating highly complicated relationships between variables. Few existing studies can enable reliable simulation of hydrological processes under these complexities. This may lead to decreased robustness of the constructed models, unfeasibility of suggestions for human activities, and damages to socio‐economy and eco‐environment. In the first of two companion papers, a discrete principal‐monotonicity inference (DPMI) method is proposed for hydrological systems analysis under these complexities. Normalization of non‐normally distributed samples and invertible restoration of modelling results are enabled through a discrete distribution transformation approach. To mitigate data uncertainties, statistical inference is employed to assess the significance of differences among samples. The irregular nonlinearity between the influencing factors (i.e. predictors) and the hydrological variable of interest (i.e. the predictand) is interpreted as piecewise monotonicity. Monotonicity is further represented as principal monotonicity under multivariate dependencies. Based on stepwise classification and cluster analyses, all paired samples representing the responsive relationship between the predictors and the predictand are discretized as a series of end nodes. A prediction approach is advanced for estimating the predictand value given any combination of predictors. The DPMI method can reveal evolvement rules of hydrological systems under these complexities. Reliance of existing hydro‐system analysis methods on predefined functional forms is removed, avoiding artificial disturbances, e.g. empiricism in selecting model functions under irregular nonlinearities, on the modelling process. Both local and global significances of predictors in driving the evolution of hydrological variables are identified. An analysis of interactions among these complexities is also achieved. The understanding obtained from the DPMI process and associated results can facilitate hydrological prediction, guide water resources management, improve hydro‐system analysis methods, or support hydrological systems analysis in other cases. The effectiveness and advantages of DPMI will be demonstrated through a case study of streamflow simulation in Xingshan Watershed, China, in another paper. Copyright © 2016 John Wiley & Sons, Ltd.     

Levee effects upon flood levels: an empirical assessment

This study used stream gauge records to assess the impact of levees on flood levels, providing an empirical test of theoretical and model predictions of the effects on local flood response. Focusing upon a study area in Illinois and Iowa for which levee records were available, we identified 203 gauges with ≥ 50 years hydrological record, including 15 gauges where a levee was constructed during the period of record. At these sites, step‐change analysis utilizing regression residuals tested levee‐related stage changes and levels of significance and quantified the magnitudes of stage changes. Despite large differences in stream sizes, levee alignments, and degree of floodplain constriction, the post‐levee rating‐curve adjustments showed consistent signatures. For all the study sites, stages for below bankfull (non‐flood) conditions were unaffected by levee construction. For above bankfull (flood) conditions, stages at sites downstream of their associated levees also were statistically indistinguishable before versus after levee construction. However, at all sites upstream of levees or within leveed reaches, stages increased for above bankfull conditions. These increases were abrupt, statistically significant, and generally large in magnitude – ranging up to 2.3 m (Wabash River at Mt. Carmel, IL). Stage increases began when discharge increased above bankfull flow and generally increased in magnitude with discharge until the associated levee(s) were overtopped. Detailed site assessments and supplementary data available from some sites helped document the dominant mechanisms by which levees can increase flood levels. Levee construction reduces the area of the floodplain open to storage of flood waters and reduces the width of the floodplain open to conveyance of flood flow. Floodplain conveyance often is underestimated or ignored, but Acoustic Doppler Current Profiler (ADCP) measurements analysed here confirm previous studies that up to 70% or more of the total discharge during large floods (~3% chance flood) can move over the floodplain. Upstream of levees and levee‐related floodplain constriction, backwater effects reduce flow velocities relative to pre‐levee conditions and, thus, increase stages for a given discharge. The empirical results here confirm a variety of theoretical predictions of levee effects but suggest that many one‐dimensional model‐based predictions of levee‐related stage changes may underestimate actual levee impacts. Copyright © 2011 John Wiley & Sons, Ltd.     

Multi-method global sensitivity analysis of flood inundation models

Global sensitivity analysis is a valuable tool in understanding flood inundation models and deriving decisions on strategies to reduce model uncertainty. In this paper, a sensitivity analysis of a one-dimensional flood inundation model (HEC-RAS) on the River Alzette, Luxembourg, is presented. It is impossible to define sensitivity in a unique way and different methods can lead to a difference in ranking of importance of model factors. In this paper five different methods (Sobol, Kullback–Leibler entropy, Morris, regionalised sensitivity analysis and regression) are applied and the outcomes on selected examples compared. It is demonstrated that the different methods lead to completely different ranking of importance of the parameter factors and that it is impossible to draw firm conclusions about the relative sensitivity of different factors. Moreover, the uncertainty inherent in the sensitivity methods is highlighted.     

Investigating the application of climate models in flood projection across the UK

Regional climate models (RCMs) have emerged as the preferred tool in hydrological impact assessment at the catchment scale. The direct application of RCM precipitation output is still not recommended; instead, a number of alternative methods have been proposed. One method that has been used is the change factor methodology, which typically uses changes to monthly mean or seasonal precipitation totals to develop change scenarios. However, such simplistic approaches are subject to significant caveats. In this paper, 18 RCMs covering the UK from the ENSEMBLES and UKCP09 projects are analysed across different catchments. The ensembles' ability in capturing monthly total and extreme precipitation is outlined to explore how the ability to make confident statements about future flood risk varies between different catchments. The suitability of applying simplistic change factor approaches in flood impact studies is also explored. We found that RCM ensembles do have some skill in simulating observed monthly precipitation; however, seasonal patterns of bias were evident across each of the catchments. Moreover, even apparently good simulations of extreme rainfall can mis‐estimate the magnitude of flood‐generating rainfall events in ways that would significantly affect flood risk management. For future changes in monthly mean precipitation, we observe the clear ‘drier summers/wetter winters’ signal used to develop current UK policy, but when we look instead at flood‐generating rainfall, this seasonal signal is less clear and greater increases are projected. Furthermore, the confidence associated with future projections varies from catchment to catchment and season to season as a result of the varying ability of the RCM ensembles, and in some cases, future flood risk projections using RCM outputs may be highly problematic. Copyright © 2013 John Wiley & Sons, Ltd.     

A review of flood impact assessment approaches for underground infrastructures in urban areas: a focus on transport systems

ABSTRACT

Flooding events can produce significant disturbances in underground transport systems within urban areas and lead to economic and socioenvironmental well-known consequences, which can be worsened by variations in the occurrence of weather and climate extremes. A better comprehension of these impacts and their conditions is consequently needed. Hence, this paper presents a state-of-the-art literature review on flood impact assessment in “metro” systems, analysing their purposes and their shortcomings. This document shows the adaptation measures dealing with specific classes of pluvial flood damages, besides identifying prospective paths towards the application of suitable actions facing actual and projected hazards in metro systems worldwide.     

Flood threat anomaly for the low coastal areas of the English Channel based on analysis of recent characteristic flood occurrences

In the English Channel, extreme surge heights did not occur at the time of extreme high tides during the last decades and maximum recorded heights usually do not exceed the maximum astronomical tide by more than a few decimetres. To understand whether this lack of coincidence may be due to specific phenomena or only to chance, we have studied hourly tide records lasting a few decades from nine English and nine French stations as well as air pressure and wind data from nearby meteorological observatories. Among the case studies of moderate flooding at several coastal stations occurring during spring tide, we have selected those of 24–25/10/1980 and of 30/01/1983 to 02/02/1983 as representative of a normal situation without any special chance. The third case study 26–28/02/1990 was potentially more dangerous because of the storm intensity and duration; however, by chance, surge peaks occurred near the low tide. Finally, the propagation of the surge peak of 15–16/10/1987, which reached the maximum height recorded during all the instrumental period at several stations, has been followed all along the English Channel, using the hourly records of 12 tide-gauge stations and of 16 meteorological stations. The surge peak of this great storm, probably the strongest in the last two centuries, occurred everywhere at high tide and spread with the same velocity of the tidal wave. Fortunately, no major flooding occurred because it was the day after a neap tide. In conclusion, some good fortune has saved the low coastal areas of the English Channel from major floods during the last decades. However, the occurrence of the peak of a strong storm surge arriving near the western entrance of the Channel at the time of a great astronomical high tide is a possible event that could be devastating along both sides of the Channel coasts. Main parts of this paper have been presented orally in June 2005 at the joint INQUA–IGCP 495 Meeting “Dunkerque 2005” and in February 2006 at the ASLO-TOS-AGU “Ocean Sciences Meeting” (Honolulu, HI).     

The influence of hydroclimatic variability on flood frequency in the Lower Rhine

Climate change is expected to significantly affect flooding regimes of river systems in the future. For Western Europe, flood risk assessments generally assume an increase in extreme events and flood risk, and as a result major investments are planned to reduce their impacts. However, flood risk assessments for the present day and the near future suffer from uncertainty, coming from short measurements series, limited precision of input data, arbitrary choices for particular statistical and modelling approaches, and climatic non‐stationarities. This study demonstrates how historical and sedimentary information can extend data records, adds important information on extremes, and generally improves flood risk assessments. The collection of specific data on the occurrence and magnitude of extremes and the natural variability of the floods is shown to be of paramount importance to reduce uncertainty in our understanding of flooding regime changes in a changing climate. For the Lower Rhine (the Netherlands and Germany) estimated recurrence times and peak discharges associated with the current protection levels correlate poorly with historical and sedimentary information and seem biased towards the recent multi‐decadal period of increased flood activity. Multi‐decadal and centennial variability in flood activity is recorded in extended series of discharge data, historical information and sedimentary records. Over the last six centuries that variability correlates with components of the Atlantic climate system such as the North Atlantic Oscillation (NAO) and Atlantic Multi‐decadal Oscillation (AMO). These climatic non‐stationarities importantly influence flood activity and the outcomes of flood risk assessments based on relatively short measurement series. Copyright © 2016 John Wiley & Sons, Ltd.     

A multi‐temporal analysis of AMSR‐E data for flood and discharge monitoring during the 2008 flood in Iowa

The objective of this work is to demonstrate the potential of using passive microwave data to monitor flood and discharge conditions and to infer watershed hydraulic and hydrologic parameters. The case study is the major flood in Iowa in summer 2008. A new Polarisation Ratio Variation Index (PRVI) was developed based on a multi‐temporal analysis of 37 GHz satellite imagery from the Advanced Microwave Scanning Radiometer (AMSR‐E) to calculate and detect anomalies in soil moisture and/or inundated areas. The Robust Satellite Technique (RST) which is a change detection approach based on the analysis of historical satellite records was adopted. A rating curve has been developed to assess the relationship between PRVI values and discharge observations downstream. A time‐lag term has been introduced and adjusted to account for the changing delay between PRVI and streamflow. Moreover, the Kalman filter has been used to update the rating curve parameters in near real time. The temporal variability of the b exponent in the rating curve formula shows that it converges toward a constant value. A consistent 21‐day time lag, very close to an estimate of the time of concentration, was obtained. The agreement between observed discharge downstream and estimated discharge with and without parameters adjustment was 65 and 95%, respectively. This demonstrates the interesting role that passive microwave can play in monitoring flooding and wetness conditions and estimating key hydrologic parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

Using the TCEV distribution function with systematic and non-systematic data in a regional flood frequency analysis

Due to the social and economic implications, flood frequency analysis must be done with the highest precision. For this reason, the most suitable statistical model must be selected, and the maximum amount of information must be used. Floods in Mediterranean rivers can be produced by two different mechanisms, which forces the use of a non-traditional distribution like the TCEV. The information can be increased by using additional non-systematic data, or with a regional analysis, or both. Through the statistical gain concept, it has been shown that in most cases the use of additional non-systematic information can decrease the quantile estimation error in about 50%. In a regional analysis, the␣benefit of additional information in one station, is propagated to the rest of␣the␣stations with only a small decrease with respect to the at-site equivalent analysis.     

Using the TCEV distribution function with systematic and non-systematic data in a regional flood frequency analysis

Due to the social and economic implications, flood frequency analysis must be done with the highest precision. For this reason, the most suitable statistical model must be selected, and the maximum amount of information must be used. Floods in Mediterranean rivers can be produced by two different mechanisms, which forces the use of a non-traditional distribution like the TCEV. The information can be increased by using additional non-systematic data, or with a regional analysis, or both. Through the statistical gain concept, it has been shown that in most cases the use of additional non-systematic information can decrease the quantile estimation error in about 50%. In a regional analysis, the␣benefit of additional information in one station, is propagated to the rest of␣the␣stations with only a small decrease with respect to the at-site equivalent analysis.     

Bayesian updating of flood inundation likelihoods conditioned on flood extent data

Previously we have detailed an application of the generalized likelihood uncertainty estimation (GLUE) procedure to estimate spatially distributed uncertainty in models conditioned against binary pattern data contained in flood inundation maps. This method was applied to two sites where a single consistent synoptic image of inundation extent was available to test the simulation performance of the method. In this paper, we extend this to examine the predictive performance of the method for a reach of the River Severn, west‐central England. Uniquely for this reach, consistent inundation images of two major floods have been acquired from spaceborne synthetic aperture radars, as well as a high‐resolution digital elevation model derived using laser altimetry. These data thus allow rigorous split sample testing of the previous GLUE application. To achieve this, Monte Carlo analyses of parameter uncertainty within the GLUE framework are conducted for a typical hydraulic model applied to each flood event. The best 10% of parameter sets identified in each analysis are then used to map uncertainty in flood extent predictions using the method previously proposed for both an independent validation data set and a design flood. Finally, methods for combining the likelihood information derived from each Monte Carlo ensemble are examined to determine whether this has the potential to reduce uncertainty in spatially distributed measures of flood risk for a design flood. The results show that for this reach and these events, the method previously established is able to produce sharply defined flood risk maps that compare well with observed inundation extent. More generally, we show that even single, poor‐quality inundation extent images are useful in constraining hydraulic model calibrations and that values of effective friction parameters are broadly stationary between the two events simulated, most probably reflecting their similar hydraulics. Copyright © 2004 John Wiley & Sons, Ltd.     

River flood seasonality in the Northeast United States: Characterization and trends

The New England and Mid‐Atlantic regions of the Northeast United States have experienced climate‐induced increases in both the magnitude and frequency of floods. However, a detailed understanding of flood seasonality across these regions, and how flood seasonality may have changed over the instrumental record, has not been established. The annual timing of river floods reflects the flood‐generating mechanisms operating in a basin, and many aquatic and riparian organisms are adapted to flood seasonality, as are human uses of river channels and flood plains. Changes in flood seasonality may indicate changes in flood‐generating mechanisms, and their interactions, with important implications for habitats, flood plain infrastructure, and human communities. I applied a probabilistic method for identifying flood seasons at a monthly resolution for 90 Northeast U.S. watersheds with natural, or near‐natural, flood‐generating conditions. Historical trends in flood seasonality were also investigated. Analyses were based on peaks‐over‐threshold flood records that have, on average, 85 years of data and three peaks per year—thus providing more information about flood seasonality than annual maximums. The results show rich detail about annual flood timing across the region with each site having a unique pattern of monthly flood occurrence. However, a much smaller number of dominant seasonal patterns emerged when contiguous flood‐rich months were classified into commonly recognized seasons (e.g., Mar–May, spring). The dominant seasonal patterns identified by manual classification were corroborated by unsupervised classification methods (i.e., cluster analyses). Trend analyses indicated that the annual timing of flood‐rich seasons has generally not shifted over the period of record, but 65 sites with data from 1941 to 2013 revealed increased numbers of June–October floods—a trend driving previously documented increases in Northeast U.S. flood counts per year. These months have been historically flood‐poor at the sites examined, so warm‐season flood potential has increased with possible implications for aquatic and riparian organisms.     

An integrated approach of flash flood analysis in ungauged Mediterranean watersheds using post-flood surveys and unmanned aerial vehicles

This study analyzes the flash flood event of two ungauged ephemeral streams in Olympiada region (Chalkidiki, North Greece), which occurred at the 21–22 of November 2019. Aim of the study is to reconstruct the specific flash flood event, investigate the causes of flood generation mechanisms, evaluate the performance of SCS-CN hydrological and HEC-RAS hydraulic models, investigate the relation between extreme flash floods and human intervention, using the combination of ground and aerial observations obtained from the field survey and unmanned aerial vehicles (UAVs), respectively. The results of the specific discharge ranged between 9 and 11 m³ s⁻¹ km², values that are typical for flash flood events in Mediterranean region. The comparison between the observed and simulated values of flood extent showed sufficiently good performance of the hydraulic model (CSI = 82%). However, the statistical analysis of the observed and simulated flood depths displayed a flood depth overestimation by the applied model, despite that the values of the used statistic indexes are acceptable (RMSE = 0.35 m, SD = 0.53, NSE = 0.56, PBIAS = 11.26%). The model overestimation of flood depth was attributed to the DEM low resolution and quality. Ground and aerial observations depicted the alluvial fan activation, the alternation of flow paths and the huge sediment transport. Human intervention in main streams, urban sprawl, wet AMC and sediment transport were among the main factors that contributed to the flash flood generation. This integrated approach revealed the necessity of the constant evaluation and validation of hydrological and hydraulic models in small ungauged Mediterranean watersheds and ephemeral streams. The use of UAVs in combination with ground observations and hydraulic simulation could significantly contribute to the enhanced understanding of flash flood mechanisms, in the direction of flood risk mitigation, improvement of the planning efficiency of flood prevent measures, flood hazard estimation, evolution of flood warning systems and floodplain geomorphology analysis.     

Changes in flood characteristics and the flood driving mechanism in the mountainous Haihe River Basin,China

ABSTRACT

Recently, the land surface in the Haihe River basin has changed, influencing the flood processes in the basin. To quantify this impact, seven typical sub-catchments were selected from different hydrological regions of the Haihe River basin for study. The non-parametric Mann-Kendall test was used to analyse for trends, and the non-parametric Pettitt test was adopted to detect any change point in the flood time series. Then, a hydrological model was established to simulate the effects of each potential driving factor on flood peak and volume. It was shown that flood peak and volume time series had decreased significantly, and the change point was around the year 1980. Groundwater depletion was not the main contribution to flood peak (FP) and volume (FV) decrease. In the Shifokou, Mubi and Lengkou sub-catchments, small hydraulic structures are the main driving factors for FP and FV decreasing. In the Xitaiyu, Daomaguan and Fuping sub-catchments, both land-use change and hydraulic structures are the main driving factors. The decreasing percentage decreases with the increase of the flood magnitude. The results provide valuable information for flood simulation and control in the Haihe River basin.     

Bivariate flood frequency analysis using the copula function: a case study of the Litija station on the Sava River

As an alternative to the commonly used univariate flood frequency analysis, copula frequency analysis can be used. In this study, 58 flood events at the Litija gauging station on the Sava River in Slovenia were analysed, selected based on annual maximum discharge values. Corresponding hydrograph volumes and durations were considered. Different bivariate copulas from three families were applied and compared using different statistical, graphical and upper tail dependence tests. The parameters of the copulas were estimated using the method of moments with the inversion of Kendall's tau. The Gumbel–Hougaard copula was selected as the most appropriate for the pair of peak discharge and hydrograph volume (Q‐V). The same copula was also selected for the pair hydrograph volume and duration (V‐D), and the Student‐t copula was selected for the pair of peak discharge and hydrograph duration (Q‐D). The differences among most of the applied copulas were not significant. Different primary, secondary and conditional return periods were calculated and compared, and some relationships among them were obtained. Copyright © 2014 John Wiley & Sons, Ltd.     

Investigating potential future changes in surface water flooding hazard and impact

Surface water flooding (SWF) is a recurrent hazard that affects lives and livelihoods. Climate change is projected to change the frequency of extreme rainfall events that can lead to SWF. Increasingly, data from Regional Climate Models (RCMs) are being used to investigate the potential water-related impacts of climate change; such assessments often focus on broad-scale fluvial flooding and the use of coarse resolution (>12 km) RCMs. However, high-resolution (<4 km) convection-permitting RCMs are now becoming available that allow impact assessments of more localised SWF to be made. At the same time, there has been an increasing demand for more robust and timely real-time forecast and alert information on SWF. In the UK, a real-time SWF Hazard Impact Model framework has been developed. The system uses 1-km gridded surface runoff estimates from a hydrological model to simulate the SWF hazard. These are linked to detailed inundation model outputs through an Impact Library to assess impacts on property, people, transport, and infrastructure for four severity levels. Here, a set of high-resolution (1.5 km and 12 km) RCM data has been used as input to a grid-based hydrological model over southern Britain to simulate Current (1996–2009) and Future (~2100s; RCP8.5) surface runoff. Counts of threshold-exceedance for surface runoff and precipitation (at 1-, 3- and 6-hr durations) are analysed. Results show that the percentage increases in surface runoff extremes, are less than those of precipitation extremes. The higher-resolution RCM simulates the largest percentage increases, which occur in winter, and the winter exceedance counts are greater than summer exceedance counts. For property impacts, the largest percentage increases are also in winter; however, it is the 12-km RCM output that leads to the largest percentage increase in impacts. The added-value of high-resolution climate model data for hydrological modelling is from capturing the more intense convective storms in surface runoff estimates.