Assessment of past flood changes across Europe based on flood-generating processes

ABSTRACT

A rainfall–runoff model was employed to identify four major flood-generating processes corresponding to flood events identified from daily discharge data from 614 stations across Europe in the period 1961–2010: long-rain, short-rain, snowmelt, and rain-on-dry-soil flood events. Trend analyses were performed on the frequency of occurrence of each of the flood types continentally and in five geographical regions of Europe. Continentally, the annual frequency of flood events did not show a significant change over the investigation period. However, the frequency of both winter and summer long-rain events increased significantly, while that of summer snowmelt events decreased significantly. Regionally, the frequency of winter short and long-rain events increased significantly in Western Europe, while the frequency of summer snowmelt and short-rain events decreased in Northern Europe. The frequency of summer snowmelt events in Eastern Europe and winter short-rain events in Southern Europe showed a declining trend.     

Delineation of flood generating processes and their hydrological response

Knowledge about flood generating processes can be beneficial for numerous applications. Especially in the context of climate change impact assessment, daily patterns of meteorological and catchment state conditions leading to flood events (i.e., storylines) may be of value. Here, we propose an approach to identify storylines of flood generation using daily weather and snow cover observations. The approach is tested for and applied to a typical pre‐Alpine catchment in the period between 1961 and 2014. Five precipitation parameters were determined that describe temporal and spatial characteristics of the flood associated precipitation events. The catchment's snow coverage was derived using statistical relationships between a satellite‐derived snow cover climatology and station snow measurements. Moreover, (pre‐) event snow melt sums were estimated using a temperature‐index model. Based on the precipitation and catchment state parameters, 5 storylines were identified with a cluster analysis: These are (a) long duration, low intensity precipitation events with high precipitation depths, (b) long duration precipitation events with high precipitation depths and episodes of high intensities, (c) shorter duration events with high or (d) low precipitation intensity, respectively, and (e) rain‐on‐snow events. The event groups have distinct hydrological characteristics that can largely be explained by the storylines' respective properties. The long duration, high intensity storyline leads to the most adverse hydrological response, namely, a combination of high peak magnitudes, high volumes, and long durations of threshold exceedance. The results show that flood generating processes in mesoscale catchments can be distinguished on the basis of daily meteorological and catchment state parameters and that these process types can explain the hydrological flood properties in a qualitative way. Hydrological simulations of daily resolution can thus be analysed with respect to flood generating processes.     

The effects of river restoration on catchment scale flood risk and flood hydrology

A rising exposure to flood risk is a predicted consequence of increased development in vulnerable areas and an increase in the frequency of extreme weather events due to climate change. In the face of this challenge, a continued reliance on engineered at‐a‐point flood defences is seen as both unrealistic and undesirable. The contribution of ‘soft engineering’ solutions (e.g. riparian forests, wood in rivers) to integrated, catchment scale flood risk management has been demonstrated at small scales but not larger ones. In this study we use reduced complexity hydrological modelling to analyse the effects of land use and channel changes resulting from river restoration upon flood flows at the catchment scale. Results show short sections of river‐floodplain restoration using engineered logjams, typical of many current restoration schemes, have highly variable impacts on catchment‐scale flood peak magnitude and so need to be used with caution as a flood management solution. Forested floodplains have a more general impact upon flood hydrology, with areas in the middle and upper catchment tending to show reductions in peak magnitude at the catchment outflow. The most promising restoration scenarios for flood risk management are for riparian forest restoration at the sub‐catchment scale, representing 20–40% of the total catchment area, where reductions in peak magnitude of up to 19% are observed through de‐synchronization of the timings of sub‐catchment flood waves. Sub‐catchment floodplain forest restoration over 10–15% of total catchment area can lead to reductions in peak magnitude of 6% at 25 years post‐restoration. Copyright © 2016 John Wiley & Sons, Ltd.     

Copula‐based flood frequency (COFF) analysis at the confluences of river systems

Many civil infrastructures are located near the confluence of two streams, where they may be subject to inundation by high flows from either stream or both. These infrastructures, such as highway bridges, are designed to meet specified performance objectives for floods of a specified return period (e.g. the 100 year flood). Because the flooding of structures on one stream can be affected by high flows on the other stream, it is important to know the relationship between the coincident exceedence probabilities on the confluent stream pair in many hydrological engineering practices. Currently, the National Flood Frequency Program (NFF), which was developed by the US Geological Survey (USGS) and based on regional analysis, is probably the most popular model for ungauged site flood estimation and could be employed to estimate flood probabilities at the confluence points. The need for improved infrastructure design at such sites has motivated a renewed interest in the development of more rigorous joint probability distributions of the coincident flows. To accomplish this, a practical procedure is needed to determine the crucial bivariate distributions of design flows at stream confluences. In the past, the copula method provided a way to construct multivariate distribution functions. This paper aims to develop the Copula‐based Flood Frequency (COFF) method at the confluence points with any type of marginal distributions via the use of Archimedean copulas and dependent parameters. The practical implementation was assessed and tested against the standard NFF approach by a case study in Iowa's Des Moines River. Monte Carlo simulations proved the success of the generalized copula‐based joint distribution algorithm. Copyright © 2009 John Wiley & Sons, Ltd.     

淮河具有行蓄洪区河系洪水预报水力学模型研究

针对淮河流域河系特点,建立淮河具有行蓄洪区河系洪水预报模型.干流河道洪水演进采用一维水动力学模型,钐岗分流量利用分流曲线法推求,利用虚拟线性水库法解决大洪水时支流洪水受干流顶托作用,临淮岗闸作为水力学模型的内边界条件进行处理,利用分流比法概化行洪过程,行洪区内只有蓄满时,才会有出流,行洪区内的洪水利用Muskingum...     

Enforced self‐organizing map neural networks for river flood forecasting

Self‐organizing maps (SOMs) have been successfully accepted widely in science and engineering problems; not only are their results unbiased, but they can also be visualized. In this study, we propose an enforced SOM (ESOM) coupled with a linear regression output layer for flood forecasting. The ESOM re‐executes a few extra training patterns, e.g. the peak flow, as recycling input data increases the mapping space of peak flow in the topological structure of SOM, and the weighted sum of the extended output layer of the network improves the accuracy of forecasting peak flow. We have investigated an ESOM neural network by using the flood data of the Da‐Chia River, Taiwan, and evaluated its performance based on the results obtained from a commonly used back‐propagation neural network. The results demonstrate that the ESOM neural network has great efficiency for clustering, especially for the peak flow, and super capability of modelling the flood forecast. The topology maps created from the ESOM are interesting and informative. Copyright © 2007 John Wiley & Sons, Ltd.     

Geographical analysis of river floods and their causes in southern East Siberia

Abstract

On the basis of analysing the genesis, recurrence and severity of flood hazards, a regional flood hazard analysis of the southern area of East Siberia has been carried out. The greatest flood hazard corresponds to the relatively densely populated area of southern East Siberia: the Upper Yenisei, Angara and Upper Lena river basins and the Lake Baikal watershed. Typically, the most hazardous floods include those caused by surges produced by damage to the dams of the Angara—Yenisei hydropower cascade; flash floods are also an extreme hazard. Maximum runoff factors were used to delineate regions within the study area, and the hazard severity was scored for the Irkutsk region. An inventory of the ice-dam and ice-jam areas, as well as of the streamflow sites with maximum runoff of different origins predominating in the Angara and Lena river basins, showed that the study area includes 78 and 19 ice-dam and ice-jam locations, respectively. A high recurrence of ice dams and ice jams is also observed on other rivers.     

Google Earth as a data source for investigating river forms and processes: Discriminating river types using form-based process indicators

Google Earth provides potential for exploiting an enormous reservoir of freely-available remotely sensed data to support river science and management. In this paper, we consider how the platform can support investigation of river physical forms and processes by developing an empirically-based reach-scale classification of semi-natural European single thread to transitional rivers. Using strict reach and image selection criteria, we identified 194 reaches of 68 rivers for analysis. Measurements of channel dimensions and counts of in-channel and floodplain features, standardised for reach length and channel width where necessary, were used to derive a series of geomorphologically-relevant process indicators. A suite of multivariate analyses were then applied to this data set, resulting in the discrimination of five river types: laterally stable, laterally active sinuous-meandering; transitional (near-braided); bedrock; and cascade/step dominated. The results of the classification were tested by examining the characteristics and distribution of the river classes in relation to known independent controls of river form including reach-scale energy and valley confinement conditions. Our results show that if methods of data extraction are carefully developed, physically meaningful river reach discrimination can be achieved using Google Earth. Although there are limits to the types of information that can be extracted such that field investigations cannot always be avoided, there is enormous potential to mine Google Earth across different space and time scales, supporting the assembly of large, reliable data sets relevant to river forms and processes in a very cost-effective way. © 2019 John Wiley & Sons, Ltd.     

复杂河道洪水预报系统研究——以淮河王家坝至小柳巷区间流域为例

随着社会经济的快速发展,洪水灾害造成的损失日益严重.洪水预报作为一项重要的防洪非工程措施,对防洪、抗洪工作起着至关重要的作用.淮河洪水危害的严重性和洪水演进过程的复杂性使得淮河洪水预报系统的研究长期以来受到高度重视.本文以王家坝至小柳巷区间流域为例,以河道洪水演算为主线,采用新安江三水源模型进行子流域降雨径流预报,概化具有行蓄洪区的干流河道,进行支流与干流、行蓄洪区与干流的洪水汇流耦合计算,采用实时更新的基于多元回归的方法确定水位流量关系,并以上游站点降雨径流预报模型提供的流量作为上边界条件、以下游站点的水位流量关系作为下边界条件,结合行蓄洪调度模型,建立具有行蓄洪区的河道洪水预报系统,再与基于K-最近邻(KNN)的非参数实时校正模型耦合,建立淮河中游河道洪水预报系统.采用多年资料模拟取得了较好的预报效果,并以2003和2007年大洪水为例进行检验,模拟结果精度较高,也证明了所建预报系统的合理性和适用性.     

Applicability of Wakeby distribution in flood frequency analysis: a case study for eastern Australia

Parametric method of flood frequency analysis (FFA) involves fitting of a probability distribution to the observed flood data at the site of interest. When record length at a given site is relatively longer and flood data exhibits skewness, a distribution having more than three parameters is often used in FFA such as log‐Pearson type 3 distribution. This paper examines the suitability of a five‐parameter Wakeby distribution for the annual maximum flood data in eastern Australia. We adopt a Monte Carlo simulation technique to select an appropriate plotting position formula and to derive a probability plot correlation coefficient (PPCC) test statistic for Wakeby distribution. The Weibull plotting position formula has been found to be the most appropriate for the Wakeby distribution. Regression equations for the PPCC tests statistics associated with the Wakeby distribution for different levels of significance have been derived. Furthermore, a power study to estimate the rejection rate associated with the derived PPCC test statistics has been undertaken. Finally, an application using annual maximum flood series data from 91 catchments in eastern Australia has been presented. Results show that the developed regression equations can be used with a high degree of confidence to test whether the Wakeby distribution fits the annual maximum flood series data at a given station. The methodology developed in this paper can be adapted to other probability distributions and to other study areas. Copyright © 2014 John Wiley & Sons, Ltd.     

Spatial patterns of homogeneous pooling groups for flood frequency analysis

Abstract

Several methods for the exploration and modelling of spatial point patterns are introduced to study the spatial patterns of homogeneous pooling groups for flood frequency analysis. The study is based on selected catchments in Great Britain, where a high density of gauging stations has been established. Initial pooling groups are formed using the K-means clustering algorithm with appropriately selected similarity measures. The pooling groups are subsequently revised to improve the homogeneity in the hydrological response. Spatial patterns of the initial and final pooling groups are explored in terms of intensity and dependence of the spatial distribution of the catchments. A test against a spatial point process is used to confirm or reject the initial impression of spatial clustering. Changes in the spatial patterns from the initial to the final pooling groups are examined using two comparison methods. The spatial pattern analysis described above can be used to answer the following questions: whether homogeneous catchments tend to exist in the vicinity of each other; whether the improvement in homogeneity tends to form more clustered pooling groups; and how the spatial patterns observed can be used to direct the selection of pooling variables.     

Assessment of the mapping capabilities of ERS-1 SAR data for flood mapping: a case study in Germany

GAF examined, under contract to DARA (German Space Agency), the applicability of ERS-1 SAR data for flood mapping under operational conditions. The flood event investigated was the flooding in the Rhine valley in winter 1993–1994. In order to carry out an examination close to the end-user needs, the specific user requests concerning information about flood events were identified. The mapping accuracy in view of the flood extent and the flood level, the production of flood maps as well as the demonstration of the runoff turned out to be the most interesting points. The specific user information needs were considered in the project objectives to define the applicability as well as the deficits of ERS-1 data concerning an operational use for flood mapping. After a detailed analysis of the time aspects of the traditional mapping method and a satellite data analysis, a visual interpretation as well as an automatic classification were applied, including various filter steps to derive the flood boundary. As a result, the visual interpretation proved to be the more accurate method. Crucial domains for both the visual interpretation and the automatic classification turned out to be settlements, forests and bushes as well as regions with layover and foreshortening effects. The comparison between the flood level derived from satellite data and the flood level registered by the water authority boards brought a height difference which ranged between 0·5 and 2·0 m. The relatively coarse resolution and problems with correct interpretation of the flood line proved to be the reason for this difference. In general the results are convenient, but in relation to field measurements of the water level they are too inaccurate. A cost and benefit analysis as well as a proposal for an operational GIS system using ERS-1 SAR data are still under investigation. © 1997 John Wiley & Sons, Ltd.     

A comparison of three methods for regional flood frequency analysis in Saudi Arabia

The objective of the study was to compare the relative accuracy of three methodologies of regional flood frequency analysis in areas of limited flood records. Thirty two drainage basins of different characteristics, located mainly in the southwest region of Saudi Arabia, were selected for the study. In the first methodology, region curves were developed and used together with the mean annual flood, estimated from the characteristics of drainage basin, to estimate flood flows at a location in the basin. The second methodology was to fit probability distribution functions to annual maximum rainfall intensity in a drainage basin. The best fitted probability function was used together with common peak flow models to estimate the annual maximum flood flows in the basin. In the third methodology, duration reduction curves were developed and used together with the average flood flow in a basin to estimate the peak flood flows in the basin. The results obtained from each methodology were compared to the flood records of the selected stations using three statistical measures of goodness-of-fit. The first methodology was found best in a case of having short length of record at a drainage basin. The second methodology produced satisfactory results. Thus, it is recommended in areas where data are not sufficient and/or reliable to utilise the first methodology.     

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.     

Development of a thresholds approach for real‐time flash flood prediction in complex geomorphological river basins

Flash floods represent one of the deadliest and costliest natural disasters worldwide. The hydrological analysis of a flash flood event contributes in the understanding of the runoff creation process. This study presents the analysis of some flash flood events that took place in a complex geomorphological Mediterranean River basin. The objective of the present work is to develop the thresholds for a real‐time flash flood forecasting model in a complex geomorphological watershed, based on high‐frequency data from strategically located hydrological and meteorological telemetric stations. These stations provide hourly real‐time data which were used to determine hydrological and meteorological parameters. The main characteristics of various hydrographs specified in this study were the runoff coefficients, lag time, time to peak, and the maximum potential retention. The estimation of these hydrometeorological parameters provides the necessary information in order to successfully manage flash floods events. Especially, the time to peak is the most significant hydrological parameter that affects the response time of an oncoming flash flood event. A study of the above parameters is essential for the specification of thresholds which are related to the geomorphological characteristics of the river basin, the rainfall accumulation of an event, the rainfall intensity, the threshold runoff through karstic area, the season during which the rainfall takes place and the time intervals between the rainstorms that affect the soil moisture conditions. All these factors are combined into a real‐time‐threshold flash flood prediction model. Historical flash flood events at the downstream are also used for the validation of the model. An application of the proposed model is presented for the Koiliaris River basin in Crete, Greece. Copyright © 2011 John Wiley & Sons, Ltd.     

Explanatory analysis of the relationship between atmospheric circulation and occurrence of flood‐generating events in a coastal city

The aim of this study is to enhance the understanding of the occurrence of flood‐generating events in urban areas by analysing the relationship between large‐scale atmospheric circulation and extreme precipitation events, extreme sea water level events and their simultaneous occurrence, respectively. To describe the atmospheric circulation, we used the Lamb circulation type (LCT) classification and re‐grouped it into Lamb circulation classes (LCC). The daily LCCs/LCTs were connected with rare precipitation and water‐level events in Aarhus, a Danish coastal city. Westerly and cyclonic LCCs (W, C, SW and NW) showed a significantly high occurrence of extreme precipitation. Similarly, for extreme water‐level events westerly LCCs (W and SW) showed a significantly high occurrence. Significantly low occurrence of extreme precipitation and water‐level events was obtained in easterly LCCs (NE, E and SE). For concurrent events, significantly high occurrence was obtained in LCC W. We assessed the change in LCC occurrence frequency in the future based on two regional climate models (RCMs). The projections indicate that the westerly directions in LCCs are expected to increase in the future. Consequently, simultaneous occurrence of extreme water level and precipitation events is expected to increase in the future as a result of change in LCC frequencies. The RCM projections for LCC frequencies are uncertain because the representation of current LCCs is poor; a large number of days cannot be classified and the frequencies of the days that can be classified differ from the observed time series. Copyright © 2015 John Wiley & Sons, Ltd.     

余震序列性质判定单参数判据的统计研究

收集整理了1970~2004年中国大陆地区293次记录相对完备的M₀≥5.0地震序列, 其中孤立型地震68次、 主余型地震174次、 多震型地震52次。 选择h值、 b值、 能量熵、 震级差等9个表征序列特征的参数, 分震后不同时段进行计算。 在0.05的置信水平下, 对每一参数及规定的主震后时段, 分孤立型地震、 主余型地震及多震型地震三类统计其总体均值及置信区间, 以此作为序列类型划分的判据。 在此基础上对序列参数的变化特征及其序列分类能力进行讨论。 总的来看, 所选参数大多具有一定的序列分类能力, 其中部分参数数值分布范围与主震震级有关, 主震不同则序列分类标准有差异, 如能量熵、 时间熵、 序列主震与最大或次大余震的震级差等参数; 部分参数数值分布范围随时间变化, 震后不同时段有不同的序列分类判据, 如归一化频次、 h值等参数; 参数的有效时段存在差异, 并且部分参数始终无序列分类能力, 如b值、 归一化能量、 平均震级等。 对有一定序列分类能力的参数, 给出具体的适用条件及与时间或序列主震震级相关的判别指标。 平均来看, 能量熵、 主震与统计时段内最大地震的震级差等参数具有相对较高的识别准确率。     

基于Copula函数的连河通江湖泊防洪安全设计:以洪泽湖为例

湖泊作为一种蓄水单元,尤其是大型过水性湖泊,是一种典型的平原型水库,在功能上与山谷型水库具有许多相似之处,但由于其特殊的地理地形构造,使得入湖洪水过程与入库洪水过程存在着较大的差异.在防洪安全设计研究中,山谷型水库关注的多是坝址洪水,即总的入库洪水过程,而对于湖泊来说,还需要关注各个分区的入湖洪水过程对湖区洪水演进的影...     

Large wood distribution,mobility, and recruitment in an inter‐dam river reach: A comparison with geomorphic process on the Garrison Reach of the Missouri River pre and post the historical 2011 flood

This study assessed the effect of the largest flood since dam regulation on geomorphic and large wood (LW) trends using LW distributions at three time periods on the 150 km long Garrison Reach of the Missouri River. In 2011, a flood exceeded 4390 m³/s for a two‐week period (705% above mean flow; 500 year flood). LW was measured using high resolution satellite imagery in summer 2010 and 2012. Ancillary data including forest character, vegetation cover, lateral bank retreat, and channel capacity. Lateral bank erosion removed approximately 7400 standing trees during the flood. Other mechanisms, that could account for the other two‐thirds of the measured in‐channel LW, include overland flow through floodplains and islands. LW transport was commonly near or over 100 km as indicated by longitudinal forest and bank loss and post‐flood LW distribution. LW concentrations shift at several locations along the river, both pre‐ and post‐flood, and correspond to geomorphic river regions created by the interaction of the Garrison Dam upstream and the Oahe Dam downstream. Areas near the upstream dam experienced proportionally higher rates of bank erosion and forest loss but in‐channel LW decreased, likely due to scouring. A large amount of LW moved during this flood, the chief anchoring mechanism was not bridges or narrow channel reaches but the channel complexity of the river delta created by the downstream reservoir. Areas near the downstream dam experienced bank accretion and large amounts of LW deposition. This study confirms the results of similar work in the Reach: despite a historic flood longitudinal LW and channel trends remain the same. Dam regulation has created a geomorphic and LW pattern that is largely uninterrupted by an unprecedented dam regulation era flood. River managers may require other tools than infrequent high intensity floods to restore geomorphic and LW patterns. Copyright © 2018 John Wiley & Sons, Ltd.     

Regionalisation of the parameters of the log‐Pearson 3 distribution: a case study for New South Wales,Australia

The index flood method is widely used in regional flood frequency analysis (RFFA) but explicitly relies on the identification of ‘acceptable homogeneous regions’. This paper presents an alternative RFFA method, which is particularly useful when ‘acceptably homogeneous regions’ cannot be identified. The new RFFA method is based on the region of influence (ROI) approach where a ‘local region’ can be formed to estimate statistics at the site of interest. The new method is applied here to regionalize the parameters of the log‐Pearson 3 (LP3) flood probability model using Bayesian generalized least squares (GLS) regression. The ROI approach is used to reduce model error arising from the heterogeneity unaccounted for by the predictor variables in the traditional fixed‐region GLS analysis. A case study was undertaken for 55 catchments located in eastern New South Wales, Australia. The selection of predictor variables was guided by minimizing model error. Using an approach similar to stepwise regression, the best model for the LP3 mean was found to use catchment area and 50‐year, 12‐h rainfall intensity as explanatory variables, whereas the models for the LP3 standard deviation and skewness only had a constant term for the derived ROIs. Diagnostics based on leave‐one‐out cross validation show that the regression model assumptions were not inconsistent with the data and, importantly, no genuine outlier sites were identified. Significantly, the ROI GLS approach produced more accurate and consistent results than a fixed‐region GLS model, highlighting the superior ability of the ROI approach to deal with heterogeneity. This method is particularly applicable to regions that show a high degree of regional heterogeneity. Copyright © 2014 John Wiley & Sons, Ltd.