Adapting to climate change: a comparison of two strategies for dike heightening

In the Netherlands the current dike design policy is to design flood defence structures corresponding to an agreed flooding probability with an extra safety board of at least 0.5 m. For river dikes a return period of 1,250 years is used to determine the design water levels. A problem with this strategy is that it builds on assumptions with regard to the intrinsically uncertain probability distributions for the peak discharges. The uncertainty is considerable and due to (1) the measuring records that are limited to about 100 years and (2) the changing natural variability as a result of climate change. Although the probability distributions are regularly updated based on new discharge data the nature of the statistics is such that a change in the natural variability of the peak discharge affects the probability distribution only long after the actual change has happened. Here we compare the performance of the probabilistic dike design strategy with the older strategy, referred to as the ‘self-learning dike’. The basic principle of the latter strategy is that the dike height is kept at a level equal to the highest recorded water level plus a certain safety margin. The two flood prevention strategies are compared on the basis of the flooding safety over a 100-year period. The Rhine gauge station at Lobith serves as case study. The results indicate that the self-learning dike performs better than the probabilistic design in terms of safety and costs, both under current and climate change conditions.     

Real-time flood forecasting of the Tiber river in Rome

An adaptive, conceptual model for real-time flood forecasting of the Tiber river in Rome is proposed. This model simulates both rainfall-runoff transformations, to reproduce the contributions of 37 ungauged sub-basins that covered about 30% of the catchment area, and flood routing processes in the hydrographic network. The adaptive component of the model concerns the rainfall-runoff analysis: at any time step the whole set of the model parameters is recalibrated by minimizing the objective function constituted by the sum of the squares of the differences between observed and computed water surface elevations (or discharges). The proposed model was tested through application under real-time forecasting conditions for three historical flood events. To assess the forecasting accuracy, to support the decision maker and to reduce the possibility of false or missed warnings, confidence intervals of the forecasted water surface elevations (or discharges), computed according to a Monte Carlo procedure, are provided. The evaluation of errors in the prediction of peak values, of coefficients of persistence and of the amplitude of confidence intervals of prediction shows the possibility to develop a flood forecast model with a lead time of 12 h, which is useful for civil protection actions.     

Flood frequency analysis based on simulated peak discharges

Flood frequency approaches vary from statistical methods, directly applied on the observed annual maximum flood series, to adopting rainfall–runoff simulation models that transform design rainfalls to flood discharges. Reliance on statistical flood frequency analysis depends on several factors such as the selected probability distribution function, estimation of the function parameters, possible outliers, and length of the observed flood series. Through adopting the simulation approach in this paper, watershed-average rainfalls of various occurrence probabilities were transformed into the corresponding peak discharges using a calibrated hydrological model. A Monte Carlo scheme was employed to consider the uncertainties involved in rainfall spatial patterns and antecedent soil moisture condition (AMC). For any given rainfall depth, realizations of rainfall spatial distribution and AMC conditions were entered as inputs to the model. Then, floods of different return periods were simulated by transforming rainfall to runoff. The approach was applied to Tangrah watershed in northeastern Iran. It was deduced that the spatial rainfall distribution and the AMCs exerted a varying influence on the peak discharge of different return periods. Comparing the results of the simulation approach with those of the statistical frequency analysis revealed that, for a given return period, flood quantiles based on the observed series were greater than the corresponding simulated discharges. It is also worthy to note that existence of outliers and the selection of the statistical distribution function has a major effect in increasing the differences between the results of the two approaches.     

Test of a distributed modelling approach to predict flood flows in the karst Suoimuoi catchment in Vietnam

The major obstacles for modelling flood processes in karst areas are a lack of understanding and model representations of the distinctive features and processes associated with runoff generation and often a paucity of field data. In this study, a distributed flood-modelling approach, WetSpa, is modified and applied to simulate the hydrological features and processes in the karst Suoimuoi catchment in northwest Vietnam. With input of topography, land use and soil types in a GIS format, the model is calibrated based on 15 months of hourly meteorological and hydrological data, and is used to simulate both fast surface and conduit flows, and groundwater discharges from karst and non-karst aquifers. Considerable variability in the simulation accuracy is found among storm events and within the catchment. The simulation results show that the model is able to represent reasonably well the stormflows generated by rainfall events in the study catchment.     

Variation of uncertainty of drainage density in flood hazard mapping assessment with coupled 1D–2D hydrodynamics model

Coupled 1D–2D hydrodynamic models are widely utilized in flood hazard mapping. Previous studies adopted conceptual hydrological models or 1D hydrodynamic models to evaluate the impact of drainage density on river flow. However, the drainage density affects not only river flow, but also the flooded area and location. Therefore, this work adopts the 1D–2D model SOBEK to investigate the impact of drainage density on river flow. The uncertainty of drainage density in flood hazard mapping is assessed by a designed case and a real case, Yanshuixi Drainage in Tainan, Taiwan. Analytical results indicate that under the same return period rainfall, reduction in tributary drainages in a model (indicating a lower drainage density) results in an underestimate of the flooded area in tributary drainages. This underestimate causes higher peak discharges and total volume of discharges in the drainages, leading to flooding in certain downstream reaches, thereby overestimating the flooded area. The uncertainty of drainage density decreases with increased rainfall. We suggest that modeling flood hazard mapping with low return period rainfalls requires tributary drainages. For extreme rainfall events, a lower drainage density could be selected, but the drainage density of local key areas should be raised.

     

Evaluation of the real-time TRMM-based multi-satellite precipitation analysis for an operational flood prediction system in Nzoia Basin,Lake Victoria,Africa

Many researchers seek to take advantage of the recently available and virtually uninterrupted supply of satellite-based rainfall information as an alternative and supplement to the ground-based observations in order to implement a cost-effective flood prediction in many under-gauged regions around the world. Recently, NASA Applied Science Program has partnered with USAID and African-RCMRD to implement an operational water-hazard warning system, SERVIR-Africa. The ultimate goal of the project is to build up disaster management capacity in East Africa by providing local governmental officials and international aid organizations a practical decision-support tool in order to better assess emerging flood impacts and to quantify spatial extent of flood risk, as well as to respond to such flood emergencies more expediently. The objective of this article is to evaluate the applicability of integrating NASA’s standard satellite precipitation product with a flood prediction model for disaster management in Nzoia, sub-basin of Lake Victoria, Africa. This research first evaluated the TMPA real-time rainfall data against gauged rainfall data from the year 2002 through 2006. Then, the gridded Xinanjiang Model was calibrated to Nzoia basin for period of 1985–2006. Benchmark streamflow simulations were produced with the calibrated hydrological model using the rain gauge and observed streamflow data. Afterward, continuous discharge predictions forced by TMPA 3B42RT real-time data from 2002 through 2006 were simulated, and acceptable results were obtained in comparison with the benchmark performance according to the designated statistic indices such as bias ratio (20%) and NSCE (0.67). Moreover, it is identified that the flood prediction results were improved with systematically bias-corrected TMPA rainfall data with less bias (3.6%) and higher NSCE (0.71). Although the results justify to suggest to us that TMPA real-time data can be acceptably used to drive hydrological models for flood prediction purpose in Nzoia basin, continuous progress in space-borne rainfall estimation technology toward higher accuracy and higher spatial resolution is highly appreciated. Finally, it is also highly recommended that to increase flood forecasting lead time, more reliable and more accurate short- or medium-range quantitative precipitation forecasts is a must.     

Major flood disasters in Europe: 1950–2005

There is a need for comprehensive, standardised and georeferenced information on floods for political and economic decision-making. Relevant, accurate and up-to-date data is an important aspect for resource distribution, mitigation programmes, disaster monitoring and assessment. Despite this, there is a lack of spatial and thematic accurate global data for floods. In Europe, historic data on flood losses and casualties are neither comprehensive nor standardised, thus making long-term analyses at continental level difficult. In this article, we present a map and catalogue of the major flood events of the last 56 years in the European Union (EU), Bulgaria and Romania. This study is an effort to alleviate the lack of homogeneous and georeferenced information on flood disasters for large periods in Europe. The objectives of this paper are to identify and classify the major flood disasters of the last 56 years in the EU; to map the major flood disasters at pan-European scale with the support of a potential flood hazard map and ancillary GIS datasets; and to give a picture of the current situation for major floods in the EU on the basis of past events and current trends. The Emergency Events Database (EM-DAT) of the Centre of Research on Epidemiology of Disasters in Brussels (CRED) and United States Office for Foreign Disaster Assistance (OFDA) and NATHAN of Munich Re are two of the main public global databases for natural disasters. Information from EM-DAT and NATHAN on flood disasters producing more than 70 casualties and/or more than 0.005% of EU GDP in damage has been assessed for the production of the map and catalogue of major flood disasters in Europe.

Dynamic routing modeling for flash flood forecast in river system

A real-time flood-forecasting method coupled with the one-dimensional unsteady flow model was developed for the Danshuei River system in northern Taiwan. Based on the flow at current time, the flow at new time is calculated to provide the water stage forecasting during typhoons. Data, from two typhoons in 2000: Bilis and Nari, were used to validate and evaluate the model capability. First, the developed model was applied to validate and evaluate with and without discharge corrections at the Hsin-Hai Bridge in Tahan Stream, Chung-Cheng Bridge in Hsintien Stream, and Sir-Ho Bridge in the Keelung River. The results indicate that the calculated water stage profiles approach the observed data. Moreover, the water stage forecasting hydrograph with discharge correction is close to the observed water stage hydrograph and yields a better prediction than that without discharge correction. The model was then used to quantify the difference in prediction between different methods of real-time water stage correction. The model results reveal that water stages using the 1–6 h forecast with real-time stage correction exhibits the best lead times. The accuracy for 1–3 h lead time is higher than that for 4–6 h lead time, suggesting that the flash flood forecast in the river system is reasonably accurate for 1–3 h lead time only. The method developed is effective for flash flood forecasting and can be adopted for flood forecasting in complicated river systems.     

Delineating flood risk areas in Greater Dhaka of Bangladesh using geoinformatics

This paper illustrates the development of flood hazard and risk maps in Greater Dhaka of Bangladesh using geoinformatics. Multi-temporal RADARSAT SAR and GIS data were employed to delineate flood hazard and risk areas for the 1998 historical flood. Flood-affected frequency and flood depth were estimated from multi-date SAR data and considered as hydrologic parameters for the evaluation of flood hazard. Using land-cover, gemorphic units and elevation data as thematic components, flood hazard maps were created by considering the interactive effect of flood frequency and flood water depth concurrently. Analysis revealed that a major portion of Greater Dhaka was exposed to high to very high hazard zones while a smaller portion (2.72%) was free from the potential flood hazard. Flood risk map according to administrative division showed that 75.35% of Greater Dhaka was within medium to very high risk areas of which 53.39% of areas are believed to be fully urbanized by the year 2010.     

Application of neural network and MODIS 250m imagery for estimating suspended sediments concentration in Hangzhou Bay,China

Suspended sediments concentration (SSC) in surface water derived from bottom sediment resuspension or discharge of sediment-laden rivers is an important indication of coastal water quality and changes rapidly in high-energy coastal area. Since artificial neural networks (ANN) had been proven successful in modeling a variety of geophysical transfer functions, an ANN model to simulate the relationship between surface water SSC and satellite-received radiances was employed. In situ SSC measurements from the Hangzhou Bay and the Moderate-resolution Imaging Spectroradiometer (MODIS) 250 m daily products were adopted in this study. Significant correlations were observed between in situ measurements and band 1–2 reflectance values of MODIS images, respectively. Results indicated that application of ANN model with one hidden layer appeared to yield superior simulation performance (r ² = 0.98; n = 25) compared with regression analysis method. The RMSE for the ANN model was less than 10%, whereas the RMSE for the regression analysis was more than 25%. Results also showed that different tidal situations affect the model simulation results to some extent. The SSC of surface water in Hangzhou Bay is high and changes rapidly due to tidal flood and ebb during a tidal cycle. The combined utilization of Terra and Aqua MODIS data can capture the tidal cycle induced dynamic of surface water SSC. This study demonstrated that MODIS 250 m daily products and ANN model are useful for monitoring surface SSC dynamic within high-energy coastal water environments.     

汉江上游晏家棚段全新世古洪水研究

通过对汉江上游详尽的野外考察,在湖北郧县晏家棚河段全新世黄土—古土壤地层中发现3层典型古洪水滞流沉积物。在沉积学的基础上,使用OSL技术断代,确定3期特大洪水事件分别在1 000~900 a BP,1 800~1 600 a BP和3 200~2 800 a BP期间发生。采用"古洪水SWD尖灭点高程法"确定这3期古洪水事件的洪峰水位介于176.20~176.73 m。运用Arc GIS耦合HEC-RAS水力模型,推求这3期古洪水事件的洪峰流量介于53 770~55 950 m3/s,并从多种角度验证了该模型计算结果的科学性和合理性。将此结果与实测洪水和历史洪水资料接续,构成万年尺度洪水水文数据序列,得到汉江上游晏家棚河段万年一遇和千年一遇洪水的流量分别为59 100和45 200m3/s。采用HEC-RAS模型对研究河段进行古洪水模拟,方法科学,结果可靠。将该河段洪水水文数据序列有效地延长到万年尺度,极大地提高了设计洪水的可靠性。     

Assessment of flood hazard,vulnerability and risk of mid-eastern Dhaka using DEM and 1D hydrodynamic model

Floods are regular feature in rapidly urbanizing Dhaka, the capital city of Bangladesh. It is observed that about 60% of the eastern Dhaka regularly goes under water every year in monsoon due to lack of flood protection. Experience gathered from past devastating floods shows that, besides structural approach, non-structural approach such as flood hazard map and risk map is effective tools for reducing flood damages. In this paper, assessment of flood hazard by developing a flood hazard map for mid-eastern Dhaka (37.16 km²) was carried out by 1D hydrodynamic simulation on the basis of digital elevation model (DEM) data from Shuttle Radar Topography Mission and the hydrologic field-observed data for 32 years (1972–2004). As the topography of the area has been considerably changed due to rapid land-filling by land developers which was observed in recent satellite image (DigitalGlobe image; Date of imagery: 7th March 2007), the acquired DEM data were modified to represent the current topography. The inundation simulation was conducted using hydrodynamic program HEC-RAS for flood of 100-year return period. The simulation has revealed that the maximum depth is 7.55 m at the southeastern part of that area and affected area is more than 50%. A flood hazard map was prepared according to the simulation result using the software ArcGIS. Finally, to assess the flood risk of that area, a risk map was prepared where risk was defined as the product of hazard (i.e., depth of inundation) and vulnerability (i.e., the exposure of people or assets to flood). These two maps should be helpful in raising awareness of inhabitants and in assigning priority for land development and for emergency preparedness including aid and relief operations in high-risk areas in the future.     

Coping with floods in the city of Dresden,Germany

During August 2002 and again in March 2005 as well as in April 2006 the city of Dresden was hit by floods. The flood in 2002 was an extreme event, only comparable to flooding in 1862 and 1890 in Dresden. The flood discharge in 2006 was the second highest discharge since 1940 at the Dresden gauge although its return period was only about 15 years. This special situation enables a comparison of the preparedness of authorities and households in the flood endangered city of Dresden in 2002 after a long period of relatively low flood discharges and in 2005/2006 just a few years after a severe flood event. Before August 2002, the flood risk awareness and flood preparedness of authorities and households in Dresden was low. The inundation channels and the Elbe riverbed had not been maintained well. Just 13% of the households had undertaken building precautionary measures. The severe flood situation as well as the low flood preparedness led to tremendous damage, e.g., losses to residential buildings amounted to 304 million €. After 2002, the municipal authorities in Dresden developed a new flood management concept and many households were motivated to undertake precautionary measures. Building precautionary measures had been actually undertaken by 67% of the households before the floods in 2005 and 2006. Flood damage was significantly lower, due to the less severe flood situations and the much better preparedness. It is an important challenge for the future to keep preparedness at a high level also without recurrent flood experiences.     

A multicriteria approach for flood risk mapping exemplified at the Mulde river,Germany

In this paper we develop a GIS-based multicriteria flood risk assessment and mapping approach. This approach includes flood risks which are not measured in monetary terms; it shows the spatial distribution of multiple risks, and it is able to deal with uncertainties in criteria values and to show their influence on the overall flood risk assessment. Additionally, the approach can be used to show the spatial allocation of the flood effects if risk reduction measures are implemented. The approach is applied to a pilot study for the River Mulde in Saxony, Germany, heavily affected by the hazardous flood in 2002. Therefore, a GIS database of economic, social and environmental risk criteria was created. Two different multicriteria decision rules, a disjunctive and an additive weighting approach, are utilised for an overall flood risk assessment in the area. For implementation, a software tool (FloodCalc) was developed supporting both, the risk calculation of the single criteria as well as the multicriteria analysis.

Application of bivariate extreme value distribution to flood frequency analysis: a case study of Northwestern Mexico

In Mexico, poverty has forced people to live almost on the water of rivers. This situation along with the occurrence of floods is a serious problem for the local governments. In order to protect their lives and goods, it is very important to account with a mathematical tool that may reduce the uncertainties in computing the design events for different return periods. In this paper, the Logistic model for bivariate extreme value distribution with Weibull-2 and Mixed Weibull marginals is proposed for the case of flood frequency analysis. A procedure to estimate their parameters based on the maximum likelihood method is developed. A region in Northwestern Mexico with 16 gauging stations has been selected to apply the model and regional at-site quantiles were estimated. A significant improvement occurs, measured through the use of a goodness-of-fit test, when parameters are estimated using the bivariate distribution instead of its univariate counterpart. Results suggest that it is very important to consider the Mixed Weibull distribution and its bivariate option when analyzing floods generated by a␣mixture of two populations.     

An overview of flood actions on buildings

This paper presents an overview of flood characteristics with respect to their applicability for estimating and analysing direct flood damage to buildings. The approach taken is to define “flood actions” as acts which a flood could directly do to a building, potentially causing damage or failure. This definition expands the traditional approach of analysing flood damage to buildings which often focuses on damage from slow-rise flood depth.

Flood actions may be energy transfers, forces, pressures, or the consequences of water or contaminant contact. This paper defines and categorises flood actions on buildings, indicating methods of quantification. The actions are classified in the following categories with respect to relative importance for flood damage assessment.

• High relevance and relatively predictable: Lateral pressure from water depth differential between the inside and outside of a building, lateral pressure from water velocity, and water contact due to slow-rise depth.

• Relevance varies and relatively predictable: Buoyancy.

• Relevance varies and difficult predictability: Capillary rise, erosion, debris, turbulence, waves, other velocity actions, other chemical actions, nuclear actions, and biological actions.

Due to the highly localised effects of some of the flood actions in the third category, coupled with their potentially significant impact, prediction of their impact on overall flood damage may be challenging. Awareness of their existence assists in developing an understanding of the uncertainties in flood damage estimation and analysis and in indicating areas which new research should tackle. In particular, work is needed in order to fully understand the physical processes by which flood damage arises and, hence, how flood damage may be prevented.     

Probabilistic evaluation of seismic soil liquefaction potential based on SPT data

The performance-based liquefaction potential analysis was carried out in the present study to estimate the liquefaction return period for Bangalore, India, through a probabilistic approach. In this approach, the entire range of peak ground acceleration (PGA) and earthquake magnitudes was used in the evaluation of liquefaction return period. The seismic hazard analysis for the study area was done using probabilistic approach to evaluate the peak horizontal acceleration at bed rock level. Based on the results of the multichannel analysis of surface wave, it was found that the study area belonged to site class D. The PGA values for the study area were evaluated for site class D by considering the local site effects. The soil resistance for the study area was characterized using the standard penetration test (SPT) values obtained from 450 boreholes. These SPT data along with the PGA values obtained from the probabilistic seismic hazard analysis were used to evaluate the liquefaction return period for the study area. The contour plot showing the spatial variation of factor of safety against liquefaction and the corrected SPT values required for preventing liquefaction for a return period of 475 years at depths of 3 and 6 m are presented in this paper. The entire process of liquefaction potential evaluation, starting from collection of earthquake data, identifying the seismic sources, evaluation of seismic hazard and the assessment of liquefaction return period were carried out, and the entire analysis was done based on the probabilistic approach.     

广州东濠涌流域城市洪涝灾害情景模拟与风险评估

绘制直观与可靠的城市洪涝灾害风险区划图,为城市防洪排涝相关部门决策提供参考依据。以广州市东濠涌流域为研究区域,综合考虑城市降雨、径流、地形和排水系统特性,构建基于InfoWorks ICM的一维-二维耦合城市洪涝仿真模型,模拟暴雨重现期为1年、5年、50年情景下的洪涝过程并获取致灾因子数据。调研分析区域的孕灾环境、承灾体和防灾减灾能力概况,结合层次分析法、评价等级和阈值划分等进行洪涝灾害风险评估。结果表明:城市洪涝仿真模型在一维排水系统和二维地面淹没模拟上均有较好的精度和可靠性,保证了致灾因子数据的可靠性;风险区划图能较好地反映流域的风险分布;随着重现期增大,较高、高风险区的面积显著增加,为防洪排涝重点关注区域。     

基于非对称Archimedean Copula的三变量洪水风险评估

分析洪峰、洪量和历时三变量联合分布与风险概率及其设计分位数,为水利工程规划设计和风险评估提供参考依据。以珠江流域西江高要站52年洪水数据为例,采用非对称阿基米德M6 Copula函数与Kendall分布函数计算三变量洪水联合分布的“或”重现期、“且”重现期和二次重现期及其最可能的设计分位数。结果表明:“或”重现期的风险率偏高,“且”重现期的风险率偏低,二次重现期更准确地反映了特定设计频率情况下三变量洪水要素遭遇的风险率;按三变量“或”重现期或三变量同频率设计值推算的洪水设计值偏高,以最大可能概率推算的三变量洪水要素的二次重现期设计值可为防洪工程安全与风险管理提供新的选择。     

Peak discharge of a Pleistocene lava-dam outburst flood in Grand Canyon, Arizona, USA

The failure of a lava dam 165,000 yr ago produced the largest known flood on the Colorado River in Grand Canyon. The Hyaloclastite Dam was up to 366 m high, and geochemical evidence linked this structure to outburst-flood deposits that occurred for 32 km downstream. Using the Hyaloclastite outburst-flood deposits as paleostage indicators, we used dam-failure and unsteady flow modeling to estimate a peak discharge and flow hydrograph. Failure of the Hyaloclastite Dam released a maximum 11 × 10⁹ m³ of water in 31 h. Peak discharges, estimated from uncertainty in channel geometry, dam height, and hydraulic characteristics, ranged from 2.3 to 5.3 × 10⁵ m³ s⁻¹ for the Hyaloclastite outburst flood. This discharge is an order of magnitude greater than the largest known discharge on the Colorado River (1.4 × 10⁴ m³ s⁻¹) and the largest peak discharge resulting from failure of a constructed dam in the USA (6.5 × 10⁴ m³ s⁻¹). Moreover, the Hyaloclastite outburst flood is the oldest documented Quaternary flood and one of the largest to have occurred in the continental USA. The peak discharge for this flood ranks in the top 30 floods (>10⁵ m³ s⁻¹) known worldwide and in the top ten largest floods in North America.