Mountain Effect and Differences in Storm Floods between Northern and Southern Sources of the Songhua River Basin

In this study, the differences in annual rainstorm changes in the Second Songhua River Basin and the Nenjiang River basin and their causes were compared from the perspective of mountain effects. The following results were drawn: (1) Altitude effect is the primary factor leading to increased rainstorms in the southern source; (2) Slope effect primarily leads to differences of the weather systems in the two sources, and thus cause the difference of the rainstorms; (3) Slope effect is responsible for the greater fluctuation in the observed floods in the southern source. These landform differences eventually lead to the differences in the characteristics of floods in the southern and northern sources. Commensurability method was used to identify the period of rainstorms in the southern and northern sources. The results showed that although rainstorms do not appear at the same time in the two sources they are characteristic of a 10 years' period in both areas. These results can serve as hydrological references for flood control and long-term flood disaster predictions.

Google Earth-based dynamic visualization system for storm surge flood routing

To describe the dynamic process of flood routing intuitively and realistically when storm surge disaster occurs,a method for ArcGIS data and Google Earth(GE) data integration is proposed,which realizes the importing and integrating of basic geographic information into GE. Based on SketchUp and AutoCAD software,threedimension(3D) visualization of seawall and other tidal defense structures is achieved. By employing Microsoft Foundation Class Library(MFC),the related system modules and storm surge flood routing dynamic visualization system are developed. Therefore,dynamic visualization of flood routing process and interactive query of submerged area and inundated depth are implemented. A practical application case study of Tianjin Binhai New Area provides decision-making support for coastal seawall planning and storm surge disaster prevention and reduction.

Assessment of Land Erosion and Sediment Accumulation Caused by Runoff after a Flash-Flooding Storm Using Topographic Profiles and Spectral Indices

This research deals with the characterization of areas associated with flash floods and erosion caused by severe rainfall storm and sediment transport and accumulation using topographic attributes and profiles, spectral indices (SI), and principal component analysis (PCA). To achieve our objectives, topographic attributes and profiles were retrieved from ASTER-V2 DEM. PCA and nine SI were derived from two Landsat-OLI images acquired before and after the flood-storm. The images data were atmospherically corrected, sensor radiometric drift calibrated, and geometric and topographic distortions rectified. For validation purposes, the acquired photos during the flood-storm, lithological and geological maps were used. The analysis of approximately 100 colour composite combinations in the RGB system permitted the selection of two combinations due to their potential for characterizing soil erosion classes and sediment accumulation. The first considers the “Intensity, NDWI and NMDI”, while the second associates form index (FI), brightness index (BI) and NDWI. These two combinations provide very good separating power between different levels of soil erosion and degradation. Moreover, the derived erosion risk and sediment accumulation map based on the selected spectral indices segmentation and topographic attributes and profiles illustrated the tendency of water accumulation in the landscape, and highlighted areas prone to both fast moving and pooling water. In addition, it demonstrated that the rainfall, the topographic morphology and the lithology are the major contributing factors for flash flooding, catastrophic inundation, and erosion risk in the study area. The runoff-water power delivers vulnerable topsoil and contributes strongly to the erosion process, and then transports soil material and sediment to the plain areas through waterpower and gravity. The originality of this research resides in its simplicity and rapidity to provide a solid basis strategy for regional policies to address the real causes of problems and risks in developing countries. Certainly, it can help in the improvement of the management of water regulation structures to develop a methodology to maximize the water storage capacity and to reduce the risks caused by floods in the Moroccan Atlas Mountain (Guelmim region).

产流模式空间分布对城市雨洪过程模拟的影响

通过耦合网格产流计算模型(GRGM)和暴雨洪水管理模型(SWMM)汇流计算模块构建了GRGM-SWMM模型。以贾鲁河中牟水文站控制流域(包括郑州市中心城区)为研究区,基于18场实测暴雨洪水资料探究了产流模式空间分布对洪水过程模拟精度的影响。结果表明:研究区超渗产流模式空间分布面积占比高达72%,城市下垫面仍以超渗产流模式为主;相较于仅考虑超渗产流计算的SWMM,考虑超渗、蓄满和混合等不同产流模式空间分布的GRGM-SWMM模型场次洪水产流量、流量过程模拟精度明显提高,产流量模拟相对误差平均降低33.26%、决定系数平均提高0.089,流量过程模拟均方根误差平均降低5.13 m^(3)/s、纳什效率系数和决定系数分别平均提高0.227、0.207。

基于MIKE FLOOD模型的湟水河上游洪水风险评估

湟水河上游段属于典型的山区性河段,河道比降大,暴雨洪水的突发性强,洪水流量大,历史短,具有巨大的破坏力,严重考验着河流的防洪能力。通过MIKE FLOOD耦合模型建立一二维水动力学模型评估现有防洪工程的防洪能力,预测了湟水河上游遭遇10年、50年、100年一遇洪水时的洪水风险情况,并且根据预测结果提出了相应的工程改进建议,为该地区的防洪救灾提供了技术支撑;同时根据计算结果也表明MIKE FLOOD耦合模型在山区性河流的风险评估中具有良好的适用性。

基于流溪河模型的任河流域城口段暴雨洪水模拟

为准确、有效地预报任河流域城口段暴雨洪水,以DEM、土地利用和土壤类型数据为基础,利用流溪河模型构建任河流域3级河道模型,选取20190627暴雨洪水手动优选模型参数,借助20170923、20180919暴雨洪水验证模型适用性;考虑降雨移动方向,利用优选模型模拟12 h降雨量为30、60、90、120、150 mm等5种情景洪水流量,分析各情景模拟特征。结果表明,参数优选后,20190627暴雨洪水洪峰误差减至2.79%,峰现时间提前5 h,模型模拟效果显著提升。20170923、20180919两次暴雨洪水洪峰误差小于20%、峰现误差小于3 h,满足模拟精度要求,流溪河模型可用于研究区暴雨洪水模拟。多情景下,30、60 mm降雨洪峰流量均小于150 m3/s;从90 mm降雨开始,洪峰流量急剧增加,增长率高达94.17%;降雨由上游往下游移动时洪水曲线至少出现1次峰值,反之洪水曲线仅有1次峰值,降雨量每增加30 mm,峰现时间提前1 h。流溪河模型在任河流域具有较好适用性,多情景模拟结果可为城口县设置暴雨洪水防治措施提供多视角支持。

有效不透水面分布对城市雨水径流的影响

城市区域不透水面分布错综复杂,汇流路径多样,不透水面有效性及其产流机制成为城市水文学的热点问题。研究以北京市主城区为对象,构建了基于汇水路径的有效不透水面的识别方法,拟合出总不透水面与有效不透水面的经验公式,定量识别了不透水面有效性对北京市主城区雨水径流的影响。结果表明:考虑不透水面有效性能显著提升模型模拟精度,针对不同城市化阶段,在各种重现期降雨情景下设置不同有效不透水面比例并进行模拟,发现有效不透水面对低重现期降雨产流过程的影响远大于高重现期降雨产流过程,且城市化前期有效不透水面增加会导致较大洪峰增长率,而城市化后期影响减小。研究可为优化城市地面格局,减缓城市洪涝灾害损失提供科学参考。

考虑Copula-LM-HMS耦联的台风情境下大坝洪水漫顶风险率计算

气候变化下台风风暴潮出现频次增加,形成的暴雨洪水对水库大坝安全产生极大威胁。由于部分地区实测流量资料缺少,基于雨量资料的随机模型与水文模型耦合模拟洪水过程线的研究亟待发展。针对现有小流域流量资料缺少问题,研究了基于降雨随机模型与水文模型的Copula-LM-HMS耦联模型,来模拟入库洪水并计算水库大坝洪水漫顶风险率。该模型通过Copula函数与拉丁超立方-蒙特卡罗抽样(Latin Hypercube-Monte Carlo Simulation)生成流域多组7日降雨数据,并通过变倍比放大法缩放处理得到相应降雨序列,利用HEC-HMS水文模型模拟洪水过程线并结合调洪演算得到坝前最高水位,同时考虑风浪作用来模拟台风情景下的库水位变化情况,计算大坝洪水漫顶风险率,并分析不同组合条件对洪水漫顶风险率的影响。余姚市四明湖水库实例分析表明,构建的Copula-LM-HMS耦合模型计算得到的拦河坝在未来台风情境下无漫顶风险,自溃坝最小漫顶风险为0.22%,最大漫顶风险达到2.68%;洪水漫顶风险与降雨分布及起调水位有关,同时风浪作用对洪水漫顶风险影响较大。基于耦合模型进行中小流域洪水漫顶风险率计算,不仅能考虑降雨系列之间的相关性、流域地形特征与实际调洪规则,还可延长无流量资料地区水库大坝应对台风情境下洪水风险的预报期,为保证水库大坝应对未来气候变化影响下的运行安全提供参考。

Influence of Land Use/Cover Change on Storm Runoff—A Case Study of Xitiaoxi River Basin in Upstream of Taihu Lake Watershed

Land use/cover change (LUCC) is one of the main boundary conditions which influence many hydrologic processes. In view of the importance of Taihu Lake Watershed in China and the urgency of discovering the impacts of LUCC on storm runoff, two flood events under five land cover scenarios in the Xitiaoxi River Basin of the upstream of Taihu Lake watershed were simulated by distributed hydrologic modeling system HEC-HMS. The influences of each land cover on storm runoff were discussed. It was concluded that under the same rainstorm the ascending order of runoff coefficient and peak flow produced by the 5 different land covers were woodland, shrub, grassland, arable land, and built-up land; the descending order of swelling time were woodland, shrub, grassland, arable land, and built-up land. Scenario of built-up land was the first to reach peak flow, then arable land, grassland, shrub, and woodland. There were close relationships between the runoff coefficients produced by the 5 different land covers. The degrees of impacts on runoff coefficient of land cover change modes were sorted by descending: woodland to built-up land, shrub to built-up land, grassland to built-up land, arable land to built-up land, woodland to arable land, shrub to arable land, arable land to grassland, shrub to grassland, grassland to arable land, and woodland to shrub. Urbanization will contribute to flood disaster, while forestation will mitigate flood disaster.

Rainfall occurrence and its relation to flood damage in China from 2000 to 2015

China is highly susceptible to flood disasters and subjected to great damage every year.Furthermore, the flood frequency has exhibited an increasing trend in recent years. Most flood events,including flash floods and river flood, are induced by rainfall. This study investigates annual variations of rainfall occurrence over China during the period from 2000 to 2015 at the national and regional scale using daily rainfall data from the Tropical Rainfall Measuring Mission. The Mann-Kendall test is performed for trend detection, and statistical data of flood damage published by China's government,including destroyed crop area, damaged buildings,direct economic loss, percentage of GDP(gross domestic product), and death toll are correlatively analysed with rainfall occurrences. The results show that storm rain events show the greatest variation among three rainfall types(moderate rain, heavy rain and storm rain). The variation coefficients of rainfall over Northeast China, North China, and Northwest China are the highest, whereas that for Southwest China is the smallest. Moderate rain, heavy rain over Central China, and moderate rain over Southwest China exhibits decreasing trends, whereas the remaining exhibit increasing trends. The correlation between the rainfall occurrences and these flood damage indices at the national scale shows that only direct economic loss has a strong positive correlation with rainfall occurrences, and the other indices have weaker correlations. The correlation is strong in three north regions, except for death toll in Northwest China. In contrast, the correlation between flood damage and rainfall is weak in East China, Central China, Southwest China, and South China. Overall,death toll is strongly correlated with the number of damaged buildings, implying that flood fatalities in China are likely associated with building collapse, and are dominated by specific extreme events. This study can provide a scientific reference for flood management in China.

Application of SWAN+ADCIRC to tide-surge and wave simulation in Gulf of Maine during Patriot's Day storm

The southern coast of the Gulf of Maine in the United States is prone to flooding caused by nor'easters. A state-of-the-art fully-coupled model, the Simulating WAves Nearshore(SWAN) model with unstructured grids and the ADvanced CIRCulation(ADCIRC) model, was used to study the hydrodynamic response in the Gulf of Maine during the Patriot's Day storm of 2007, a notable example of nor'easters in this area. The model predictions agree well with the observed tide-surges and waves during this storm event. Waves and circulation in the Gulf of Maine were analyzed. The Georges Bank plays an important role in dissipating wave energy through the bottom friction when waves propagate over the bank from offshore to the inner gulf due to its shallow bathymetry. Wave energy dissipation results in decreasing significant wave height(SWH) in the cross-bank direction and wave radiation stress gradient, which in turn induces changes in currents. While the tidal currents are dominant over the Georges Bank and in the Bay of Fundy, the residual currents generated by the meteorological forcing and waves are significant over the Georges Bank and in the coastal area and can reach 0.3 m/s and 0.2 m/s, respectively. In the vicinity of the coast, the longshore current generated by the surface wind stress and wave radiation stress acting parallel to the coastline is inversely proportional to the water depth and will eventually be limited by the bottom friction. The storm surge level reaches 0.8 m along the western periphery of the Gulf of Maine while the wave set-up due to radiation stress variation reaches 0.2 m. Therefore, it is significant to coastal flooding.

暴雨洪涝灾情快速监测评估技术框架体系与应用:以2022年6月北江流域洪水灾情分析为例

【目的】暴雨洪涝灾情快速评估在洪灾应急救援和灾后恢复重建中发挥着重要作用,但仍面临诸多挑战。为快速监测和评估洪涝灾情,建立一套集成天空地网多源信息与多种技术的暴雨洪涝灾情快速监测评估技术框架体系,【方法】以2022年6月北江暴雨洪灾为例,综合利用雨量、河道水位、网络淹没图片和视频、卫星遥感影像、地面调研测绘和无人机低空航测等多源数据、水文模型和地理空间分析技术,通过实地调研测绘和无人机航测,结合遥感影像、水力学模型和地理空间分析技术,快速识别本次洪水淹没深度范围、分析淹没区内的受灾人口、房屋、农田等基本灾情,在洪水灾情分析的实战中检验集成天空地网多源信息的暴雨洪涝灾情快速监测评估技术。【结果】结果显示:清远市新增的淹没面积为478 km^(2),其中淹没农田307 km^(2)(64%),淹没区内有74119栋房屋和167306人;韶关市新增的淹没面积为90 km^(2),其中淹没农田46 km^(2)(51%),淹没区内有15629栋房屋和78037人。【结论】结果表明:无人机航测结合地面RTK高程和洪痕测绘,将在洪涝灾情快速调查评估中发挥越来越重要的作用;卫星影像可快速揭示洪水淹没区的总体格局,但受云层遮档和过境时间的影响,难以获取最大淹没范围;洪涝淹没区公众提供的各类网络众包信息是最直接和现时的洪涝灾情信息,需要认真核实和充分利用;结合河道等各类实测水位,HAND模型可以快速估算出淹没深度范围,有很大的推广应用价值。通过对本次北江洪涝灾情的快速模拟和初步分析,充分展示了各类前沿技术在洪涝灾情快速识别中的独特作用,可为洪涝灾情应急监测方案设计和技术准备提供参考。

基于GIS构建邯郸市某区SWMM雨洪模型的方法研究

以河北省邯郸市某区雨水管网为例,通过建立GIS管网、划分子汇水区、构建地面高程图、绘制土地利用类型图及计算模型参数,借助GIS空间数据及融合理论和SWMM产流、汇流理论搭建雨洪模型,模拟4种不同重现期的降雨情境,验证模型的准确性,分析模型运行后雨水管网排水能力。结果表明,该方法建立模型的准确性高、适用性强,连续性误差均在5%以内,可直观反映雨洪情况。

深圳河流域城市洪涝风险分析

日益严峻的城市洪涝灾害严重威胁着城市安全和可持续发展,准确评估城市洪涝风险对于保护人民群众生命财产安全至关重要。本研究基于元胞自动机洪水模拟模型构建深圳河流域洪涝仿真模型,采用综合主观层次分析法和客观权重赋权法的博弈论组合赋权法对各指标赋权,评估和预测不同降雨情景下深圳河流域城市洪涝风险。结果表明:深圳河流域城市洪涝高风险区存在典型的时空差异,随着暴雨重现期的增加,面积占比从2年一遇的0.20%增加到100年一遇的0.82%;中低风险区面积占比从2年一遇的67.4%减少到100年一遇的64.7%。研究结果可有效识别深圳河流域洪涝风险分布,为完善深圳河流域洪涝综合防治体系,提升城市洪涝防御能力和韧性提供借鉴与参考。

华南中小流域设计暴雨洪水同频率检验与重现水平推算

暴雨洪水同频率假定是否成立和暴雨洪水遭遇概率分布是中小流域设计洪水计算的依据,为检验其合理性,采用鉴江上游曹江流域典型强降水流域1967—2013年逐时暴雨洪水观测资料,分析了华南中小流域最大面雨量R和对应场次最大洪峰流量Q的边缘分布和联合分布的遭遇概率,并推算其设计重现水平。研究结果表明:暴雨和洪水同频遭遇概率较小;对于特定设计频率,洪峰流量与流域面雨量的遭遇概率随流域面雨量增大而增大;流域面雨量和洪峰流量的遭遇条件概率显示存在着多种防洪风险管理选择;相对于“或”联合重现期和“且”重现期,二次重现期更准确地反映R-Q组合的风险率。

城市雨洪内涝三维实景动态模拟表达方法研究

受全球气候变暖、城市化进程加快的共同影响,近年来城市极端降雨事件频发导致内涝灾害发生。基于水文、水动力模型得到的城市雨洪数值模拟结果难以展示降雨、内涝渐变过程等问题。提出雨洪内涝过程三维实景动态模拟表达方法,首先采用GAST(GPU Accelerated Surface Water Flow and Transport Model)水动力模型对雨洪内涝过程数值模拟,通过Godunov类型有限体积法进行数值离散,采用GPU并行技术加速计算获取不同输出时间下的数值模拟结果,创新设计了GAST模型数值模拟结果与数字高程模型数据耦合方法,构建了数字淹没网格模型(Digital Inundation Grid Model,DIGM),基于WebGL和三维地理信息系统(3D Geographic Information System,3D GIS)技术开发三维实景动态可视化引擎,构建雨洪内涝过程三维实景动态渲染机制,对雨洪内涝过程三维实景动态模拟进行表达。最后,采用本方法实现了西安2020年7月10日2次强降雨致涝过程三维实景动态模拟表达,结果生动直观准确,与实测结果吻合度高,表明该方法可有效弥补现有城市雨洪内涝数值模拟表达方法的不足,具有良好的应用价值。

珠江流域2022年暴雨洪水分析

2022年珠江流域暴雨洪水范围广、强度大、持续时间长。为了分析此次暴雨洪水成因,比较其与历史相似洪水的异同,从而进一步掌握珠江流域暴雨洪水规律并为流域防汛抗洪工作提供参考,分析了2022年珠江流域暴雨洪水特性,概述了致洪暴雨的天气背景、降雨过程,重点从洪水过程、洪水组成、水利工程作用、与历史暴雨洪水比较等方面进行了分析总结。结果表明:2022年5月下旬至7月上旬,珠江流域累计面降雨量较常年同期偏多5成,其中北江、韩江均为1961年以来同期最多;受其影响,珠江流域接连发生2次流域性较大洪水、8次编号洪水,其中北江发生1915年以来最大洪水;采用中国洪水预报系统进行洪水组成分析,西江干流洪水以红水河、柳江、郁江、桂江来水为主,不同场次洪水洪量占比不同,北江干流洪水以连江来水为主,其次为区间产流,韩江干流洪水主要来自于梅江和汀江;经与2005年、2008年历史大洪水对比,2022年珠江流域暴雨历时明显偏长,且暴雨中心位置偏西偏北,洪水过程次数也明显偏多,2022年北江洪水量级为特大洪水,大于2005年和2008年,但西江洪水量级明显小于2005年和2008年。在应对此次洪水过程中,流域防洪工程联合调度运用防洪效益十分明显,有效避免了西江、北江洪水恶劣遭遇,确保了重要地区防洪安全。