Uncertainty evaluation of design rainfall for urban flood risk analysis

A reliable and long dataset describing urban flood locations, volumes and depths would be an ideal prerequisite for assessing flood frequency distributions. However, data are often piecemeal and long-term hydraulic modelling is often adopted to estimate floods from historical rainfall series. Long-term modelling approaches are time- and resource-consuming, and synthetically designed rainfalls are often used to estimate flood frequencies. The present paper aims to assess the uncertainty of such an approach and for suggesting improvements in the definition of synthetic rainfall data for flooding frequency analysis. According to this aim, a multivariate statistical analysis based on a copula method was applied to rainfall features (total depth, duration and maximum intensity) to generate synthetic rainfalls that are more consistent with historical events. The procedure was applied to a real case study, and the results were compared with those obtained by simulating other typical synthetic rainfall events linked to intensity-duration-frequency (IDF) curves. The copula-based multi-variate analysis is more robust and adapts well to experimental flood locations even if it is more complex and time-consuming. This study demonstrates that statistical correlations amongst rainfall frequency, duration, volume and peak intensity can partially explain the weak reliability of flood-frequency analyses based on synthetic rainfall events.     

Low Impact Development Measures Spatial Arrangement for Urban Flood Mitigation: An Exploratory Optimal Framework based on Source Tracking

Urban areas are vulnerable to flooding as a result of climate change and rapid urbanization and thus flood losses are becoming increasingly severe. Low impact development (LID) measures are a storm management technique designed for controlling runoff in urban areas, which is critical for solving urban flood hazard. Therefore, this study developed an exploratory simulation–optimization framework for the spatial arrangement of LID measures. The proposed framework begins by applying a numerical model to simulate hydrological and hydrodynamic processes during a storm event, and the urban flood model coupled with the source tracking method was then used to identify the flood source areas. Next, based on source tracking data, the LID investment in each catchment was determined using the inundation volume contribution ratio of the flood source area (where most of the investment is required) to the flood hazard area (where most of the flooding occurs). Finally, the resiliency and sustainability of different LID scenarios were evaluated using several different storm events in order to provide suggestions for flooding prediction and the decision-making process. The results of this study emphasized the importance of flood source control. Furthermore, to quantitatively evaluate the impact of inundation volume transport between catchments on the effectiveness of LID measures, a regional relevance index (RI) was proposed to analyze the spatial connectivity between different regions. The simulation–optimization framework was applied to Haikou City, China, wherein the results indicated that LID measures in a spatial arrangement based on the source tracking method are a robust and resilient solution to flood mitigation. This study demonstrates the novelty of combining the source tracking method and highlights the spatial connectivity between flood source areas and flood hazard areas.

     

福建省山洪灾害风险识别与定量分析

受极端天气、复杂下垫面和人类活动多重因素影响,山洪灾害在我国频发高发,且预测预报难度较大。本文基于全国山洪灾害调查评价成果,着眼于15-20 km~2的小流域,从降雨、下垫面、社会经济、现状防洪能力、涉水工程及监测预警设施配置率6个方面,提取了54个备选指标,运用主成分分析法进行降维处理,筛选了10个核心且独立的指标,构建了风险评估指标体系,建立了风险立方体模型,并运用福建省2306场历史山洪场次数据进行了模型验证。结果表明,基于小流域的山洪灾害风险识别可有效反映灾害对降雨和下垫面的响应关系;沿海台风暴雨高发区和内陆山区短时强降雨高值区是山洪灾害高风险区,涉及小流域1151个,面积近2万km~2,人口608万。     

Margin of Safety Based Flood Reliability Evaluation of Wastewater Treatment Plants: Part 1 – Basic Concepts and Statistical Settings

Low-lying coastal urban areas are vulnerable to frequent and chronic flooding due to population growth, urbanization, and accelerated sea level rise originating from climate change. This paper is part one of a 2 paper series, however a detailed literature review on the concept and the technical aspects of both papers is presented. In the 2nd paper, the application of the concepts and the proposed methodology are utilized to set the mitigation strategies for quantification of reliability attributes. The case study is the Hunts Point wastewater treatment plant and its sewershed in Bronx, New York City. The suitability of two major rainfall stations of Central Park and LaGuardia airport in the vicinity of the case study is tested. The copula-based non-stationary 100–year flood frequency analysis of rainfall and storm surge is analyzed to obtain the design values of surge and rainfall. A differential evaluation Markov Chain with Bayesian interface is used in this paper for parameter estimation. In this study, the likelihood of joint probability of co-occurring heavy rainfall and storm surge is determined to illustrate the risk of joint events. Therefore, the copula-based non-stationary 100–year flood frequency analysis of rainfall and storm surge are performed to obtain the design values of surge and rainfall. A multi-criteria decision-making (MCDM) approach that incorporates the load-resistance concept is presented in Part 2 paper to assess the Margin of Safety flood reliability of a wastewater treatment plant (WWTP). The framework presented in this paper is applicable to other coastal sewersheds.

     

Flood Susceptibility Assessment by Using Bivariate Statistics and Machine Learning Models - A Useful Tool for Flood Risk Management

In Romania, as in the rest of the world, the flood frequency has increased considerably. Prahova river basin is among the most exposed catchments of the country to flood risk. It also represents the area of the present study for which the identification of surfaces with high susceptibility to flood phenomena was attempted by applying 2 hybrid models (adaptive neuro-fuzzy inference system and fuzzy support vector machine hybrid) and 2 bivariate statistical models (certainty factor and statistical index). The computation of Flood Potential Index (FPI) was possible by considering a number of 10 flood conditioning factors together with a number of 158 flood pixels and 158 non-flood pixels. Generally, the high and very high flood potential appears on around 25% of the upper and middle basin of Prahova river. The validation of the results was made through the ROC Curve model. One of the novelties of this research is related to the application of Fuzzy Support Vector Machine ensemble for the first time in a study concerning the evaluation of the susceptibility to a certain natural hazard.

     

城镇化背景下平原河网区暴雨洪水重现期变化分析——以太湖流域武澄锡虞区为例

以太湖流域武澄锡虞区典型雨量水文站为例,基于长时间序列逐日降雨与水位数据,采用累积距平法、皮尔逊频率曲线和克里金插值等方法对水位进行还现分析以及对暴雨洪水重现期进行分析,探讨了城镇化背景下典型平原河网区暴雨洪水重现期变化规律及成因。结果表明:(1)武澄锡虞区不同量级降雨重现期均有提前,极端降雨频率增大;武澄锡虞区小量级洪水事件(T=5, 10, 20 a)发生频率有所增加,而量级较大(T=50 a)的洪峰水位重现期在城区与郊区则差异显著。受圩垸影响的常州站1960年50年一遇洪峰水位在2010年增至68年一遇,洪峰水位整体降低,而郊区白芍山站1960年50年一遇洪峰水位在2010年则提前至32年,洪峰水位整体有所增加。(2)小量级洪水事件发生频率增加主要是由降雨增加、城镇扩张以及河网水系衰减所致,同等量级的暴雨导致洪峰水位不断增长;而闸泵和圩垸等水利工程建设加强了对较高量级洪水的调节作用,使高量级洪峰水位有所降低,减小了城区圩垸内洪水风险。对于不同量级的洪峰水位,下垫面特征变化和水利工程建设对其影响的程度则有所不同。分析结果可为研究该地区防洪安全提供技术支持。     

The Ven Te Chow Memorial Lecture: On Future Professional Activities Of The International Water Resources Association

ABSTRACT

The Upper Mississippi River Basin has experienced considerable hydrologic change in the last two centuries as a result of removal of wetland areas, deforestation and subsequent reforestation, changes in agricultural practices, urbanization, navigation projects, and the construction of levees. It is popularly accepted that the human-induced modifications to the river and its watersheds have increased the amount of flow in the Mississippi River, particularly during flooding events. Long-term streamgage records in the Upper Mississippi River Basin were analyzed to determine trends in streamflows and flooding. Over the 130 years of gaging there have been various periods in which the frequency and magnitude of floods have fluctuated. Trends in average flow and flooding are strongly correlated to coincident increases in average annual precipitation. For many portions of the watershed, precipitation and streamflows over the last three decades have been higher than any earlie period on record. Outside of the dominant influence of climate variation, only one major change on Mississippi River flood discharges is observed. Flood control reservoirs in the Missouri River watershed appear to produce a 10 per cent reduction in the average flood peak and average flood volume for the Mississippi River at St. Louis, Missouri.     

基于SPI的京津冀地区旱涝时空 变化特征分析

以京津唐地区及周边地区37个气象站点1961~2010年逐月降水为基础资料,以地理信息系统技术为处理平台,结合滑动t检验、SPI指数（SPI, standard precipitation index） 方法和空间插值IDW（inverse distance weighting）等,分析京津冀地区年降水量趋势性、突变性、以及各地区旱涝发生等级、发生频率、旱涝发生频率的空间分布特征、降水突变点前后时段各地区旱涝特性的转变。结果表明：(1)近五十年,京津冀地区北部降水减少,南部降水增加,整体呈减少趋势,降水在1996年前后两时段变化剧烈;(2)北京、承德、唐山为旱涝交替高发区,秦皇岛、石家庄为洪涝高发区,张家口为干旱易发区;(3)变化期和基准期前后比较,各地区旱涝特征变化显著,整体的趋势是干旱形势加重,洪涝趋势减弱。     

三峡特大流域洪水预报方案应用与分析

摘要：基于三峡工程572个遥测站点，进行三峡以上覆盖面积约39万km2流域的洪水预报方案制作，通过2008年汛期7场洪水的检验，证明方案可行、满足需要。洪水预报实践经验表明：多模型多方案组合预报、半分布式模型选用和通过相关关系确定各单元河网汇流参数以及流域分级预报、逐级检验是大型、特大型流域预报方案成功制作的关键；同时未来降雨接入、实时校正是提高实时预报精度、增长预见期的有效手段。     

A Robust Method to Update Local River Inundation Maps Using Global Climate Model Output and Weather Typing Based Statistical Downscaling

Global warming is changing the magnitude and frequency of extreme precipitation events. This requires updating local rainfall intensity-duration-frequency (IDF) curves and flood hazard maps according to the future climate scenarios. This is, however, far from straightforward, given our limited ability to model the effects of climate change on the temporal and spatial variability of rainfall at small scales. In this study, we develop a robust method to update local IDF relations for sub-daily rainfall extremes using Global Climate Model (GCM) data, and we apply it to a coastal town in NW Spain. First, the relationship between large-scale atmospheric circulation, described by means of Lamb Circulation Type classification (LCT), and rainfall events with potential for flood generation is analyzed. A broad ensemble set of GCM runs is used to identify frequency changes in LCTs, and to assess the occurrence of flood generating events in the future. In a parallel way, we use this Weather Type (WT) classification and climate-flood linkages to downscale rainfall from GCMs, and to determine the IDF curves for the future climate scenarios. A hydrological-hydraulic modeling chain is then used to quantify the changes in flood maps induced by the IDF changes. The results point to a future increase in rainfall intensity for all rainfall durations, which consequently results in an increased flood hazard in the urban area. While acknowledging the uncertainty in the GCM projections, the results show the need to update IDF standards and flood hazard maps to reflect potential changes in future extreme rainfall intensities.

     

无资料城区管网排水过程概化模拟研究

许多城市地区都没有可用的排水管网数据,从而降低了城市雨洪模拟的准确性,因此需要一种新的方法来表征管网的排水能力。提出了雨水井等效排水法(RIA)和仅在道路上等效排水法(CIR)两种表征管网排水能力的方法,采用高效高分辨率的城市雨洪模型,以西咸新区为研究区域,模拟了城市内涝积水过程,并与实测数据进行了对比。通过实际降雨与设计降雨条件下的内涝结果发现,较原有的模拟方法,该方法可以精准的表征管网排水能力,提高模型的准确性。     

长江三峡区间暴雨洪水分析

利用１９６５～１９８９年三峡区间３４个雨量站逐日降水量资料，计算了区间逐年的面暴雨和洪水，初步揭示了区间暴雨洪水的基本特征。指出三峡区是长江流域多暴雨区之一，平均情况下了７月和９月，暴雨出现机会较基他月份多。三峡区间年最大洪峰出现在５－９月，约有１／３的区间洪水可与万县洪水遭遇，区间洪水可使宜昌流量增加，还计算了２４ｈ，３ｄ区间面暴雨及洪水的频率，为三峡工程二期围堰安全度汛和施工安排，提供了三峡区     

2017年汉江秋季洪水特性及预报调度分析

2013年丹江口大坝加高工程完成后,遭遇连续枯水,各年度蓄水严重不足,2017年发生明显秋汛,防汛部门科学调度,取得了统筹防洪、大坝蓄水安全与监测试验等多目标共赢的成果。通过分析汉江2017年秋汛的水雨情发展、洪水地区组成、水情预报及水库调度等,解析了汉江此次秋汛过程的降雨、洪水特性,水情预报精度水平及水库调度的成效。分析表明：汉江9月上中旬降雨起筑底作用,9月23日开始的连续强降雨过程累计雨量大、覆盖面积广,直接导致汉江连续涨水过程;丹江口入库洪水最大15 d洪量接近秋季10 a一遇,丹皇区间最大7 d洪量超过秋季20 a一遇;丹江口水库实施拦洪削峰调度,削峰率均在50%以上,削减中游干流主要站洪峰水位约2 m,避免了中下游分洪民垸和杜家台分洪。     

基于降雨资料的雨量预警指标阈值求解模型

为保证雨量预警指标阈值在有效周期范围内发挥预警作用,通过分析现有雨量预警指标阈值的确定方法,提出了基于区域临界雨量法-降雨灾害同频率法-R/S分析法的雨量预警指标阈值求解模型。将该模型应用于江苏省泰兴市降雨时间序列的分析,对最大日降水量时间序列进行阈值确定、趋势分析,并用指标阈值进行预警验证。结果表明,该模型的雨量预警指标阈值确定结果相较单一模型更为准确,且具有一定的时效性,可为农村基层防汛预报预警提供参考。     

DEM resolution effects on machine learning performance for flood probability mapping

Floods are among the devastating natural disasters that occurred very frequently in arid regions during the last decades. Accurate assessment of the flood susceptibility mapping is crucial in sustainable development. It helps respective authorities to prevent as much as possible their irreversible consequences. The Digital Elevation Model (DEM) spatial resolution is one of the most crucial base layer factors for modeling Flood Probability Maps (FPMs). Therefore, the main objective of this study was to assess the influence of the spatial resolution of the DEMs 12.5 m (ALOS PALSAR) and 30 m (ASTER) on the accuracy of flood probability prediction using three machine learning models (MLMs), including Random Forest (RF), Artificial Neural Network (ANN), and Generalized Linear Model (GLM). This study selected 14 causative factors in the flood as independent variables, and 220 flood locations were selected as dependent variables. Dependent variables were divided into training (70%) and validation (30%) for flood susceptibility modeling. The Receiver Operating Characteristic Curve (ROC), Kappa index, accuracy, and other statistical criteria were used to evaluate the models' accuracy. The results showed that resolving the DEM alone cannot significantly affect the accuracy of flood probability prediction regardless of the applied MLM and independently of the statistical model used to assess the performance accuracy. In contrast, the factors such as altitude, precipitation, and distance from the river have a considerable impact on floods in this region. Also, the evaluation results of the models showed that the RF (AUC_12.5,30m = 0.983, 0.975) model is more accurate in preparing the FPM than the ANN (AUC_12.5,30m = 0.949, 0.93) and GLM (AUC_12.5,30m = 0.965, 0.949) models. This study's solution-oriented findings might help water managers and decision-makers to make the most effective adaptation and mitigation measures against potential flooding.     

Restoring Ice-jam Floodwater to a Drying Delta Ecosystem

Abstract

Overbank flooding is essential to the ecological health of riparian landscapes, particularly river deltas. One of the world's largest freshwater deltas, the Peace-Athabasca Delta (PAD) in northern Canada, has experienced a series of wetting and drying cycles because of inter-annual variations in flooding. Recent research has found that most of the major floods affecting this system are produced by spring ice jams. For approximately two decades, however, the combination of climatic and flow-regulation effects precluded significant ice-jam flooding of the PAD. Resultant drying caused major changes to the ecology of the delta and led to the evaluation of a number of methods to restore water flows. Since most of delta is contained within a national park (Wood Buffalo National Park), a major goal was to employ non-structural measures. Hence, in an effort to manage the water problems of this delta, the final report of a multi-agency “Northern River Basins Study” made the recommendation that the spring flow-release strategy of the upstream hydro electric reservoir be modified to increase the probability of ice-jam flooding near the PAD. This was to be conducted in years when downstream hydrometeorological conditions (snowpack magnitude and ice-cover strength) appeared conducive to ice-jam formation. Such favourable conditions developed in the spring of 1996, a natural ice jam began to develop, and regulated flows were increased to assist in potential flooding. As a result, the PAD experienced its first major flood in over 20 years. This paper reviews the hydrometeorological conditions that led to the ice-jam formation, compares the conditions to historical events, analyzes the spatial extent of the flood, and evaluates the effectiveness of the flow release.     

石家庄市“2012．7”暴雨洪水分析

石家庄市通过对2012年7月29日至31日暴雨洪水特性分析,掌握暴雨洪水规律,最大1h暴雨量级达到10年一遇,次降雨相当于3年一遇,受短历时强降雨影响,鹿泉及石家庄市区出现较为严重的城市内涝。形成了石家庄市2012年最大的一场暴雨洪水过程。     

Multiple Kernel Learning with Maximum Inundation Extent from MODIS Imagery for Spatial Prediction of Flood Susceptibility

Identifying flood prone areas is essential for basin management. In this paper, a spatial prediction technology of flood susceptibility based on multiple kernel learning (MKL) is proposed. We establish the flood susceptibility model by using EasyMKL, nonlinear MKL (NLMKL), Representative MKL(RMKL), Generalized MKL(GMKL), support vector machine(SVM) with linear kernel and SVM with Gaussian radial base function(RBF) kernel, The spatial prediction of flood susceptibility in Sanhuajian basin of the Yellow River is carried out. We use MODIS remote sensing images to obtain historical flood inundation sites in the study area. Then, ten flood conditioning factors are used as inputs to the flood susceptibility model. The model performance is evaluated in terms of accuracy (ACC), balanced F Score (F1 score), and areas under the curve (AUC). According to the results, MKL significantly outperforms the SVM adopting single kernel, and NLMKL(ACC=0.833,F1=0.841,AUC=0.889) demonstrates the best comprehensive performance. The flood susceptibility map generated by MODIS remote sensing images and MKL, therefore, can provide effective help for researchers and decision makers in flood management.

     

晋城市片区洪涝过程响应分析与马路行洪模拟

以晋城市金村区为例,利用SWMM与ICM-2D模型进行多情景洪涝过程模拟,分析降雨雨型与下垫面对晋城市片区内涝的影响;构建双层SWMM模拟马路行洪,分析金村大道和珏山路的淹没特征,并与ICM-2D模型模拟结果进行对比验证。结果表明:随着雨峰系数与降雨重现期的增大,地表洪水总量、淹没范围与水深增大,危险性等级提高;同一降雨重现期下的雨峰与洪峰间的时间间隔随雨峰系数的增大而减小;当52.53%的下垫面转化为不透水面时,同一降雨重现期下的综合径流系数约增加0.5;金村大道市委党校路段与珏山路水西村路段是主要易涝区,淹没面积分别为0.50hm²和1.31hm²;双层SWMM在识别易涝点与推求洪水淹没要素方面具有较好的适用性。     

Urban stream overflow probability in a changing climate: Case study of the Seoul Uicheon Basin,Korea

Flooding from the overflow of rivers and streams can cause major disruption in urban areas that is likely to have significant effects on human activities and the environment. Such consequences could be exacerbated by enhanced levels of precipitation resulting from future climate change. Various options are available for responding to flooding; however, further studies are needed to improve the design flood criteria in order to cope with the uncertainties of a changing climate. This study investigated an improved methodology for the evaluation of the overflow probability of urban streams. This was achieved through the application of Monte Carlo simulations (MCSs) and climate change scenarios that incorporated an increased probability of overbank flooding. An estimation of the probability of future rainfall in the Uicheon Basin of Korea, using chaos disintegration with regional climate model (RCM) scenario data, indicated a projected increase of 4.4%–9.6%. The results for 100-year flooding under projected conditions of climate change, based on a hydrologic overflow inundation model, showed that flooded areas could increase by 58.1% compared with current levels, depending on the climate change scenarios. However, forecasts based on MCSs indicated that extreme rainfall could increase by 94.9%. Thus, an overflow analysis that reflects both extreme hydrologic events and more frequent flooding due to climate change could provide a more reliable means of forecasting extreme events, as well as helping to prevent natural disasters associated with unexpected extreme flooding. The results obtained in this study would provide useful data for stakeholders and decision makers to both enhance policy standards and formulate measures to reduce the risk of urban flooding within the context of a changing climate.