洪水淹没分析中的自适应逐点水位修正算法

洪涝灾害损失评估是防洪减灾科学决策的基础,其中洪水淹没分析是准确提取洪水淹没范围、水深及历时等灾情信息的关键。洪水淹没分析主要采用数字高程模型数据,由于DEM的格网分辨率与高程精度有限,常出现异常的洼地或平地,导致难以可靠地计算每个格网点处的流向,而传统方法采用统一高程的洼地填平处理又使得容易出现洪水演进过程中复杂起伏地形水面爬坡以及平坦地形水位断流的问题,为此提出顾及流速和淹没时间的自适应逐点水位修正算法,即在DEM坡面流模拟的基础上,根据洪水水流特性、地形、边界变化、水流速度、水深变化以及淹没点的淹没时间,计算水位修正值,对洪水演进过程中每个格网点的水位进行修正,采用多种地貌类型的DEM数据进行试验,证明洪水演进的淹没范围、水深及历时的实时计算结果准确可靠,可为快速评估灾害损失与防洪决策服务提供更为科学的依据。     

基于ArcEngine的洪水淹没分析与实现

本文使用ArcEngine开发组件提取DEM数据为二维数组,并据此对洪水淹没分析有关的一系列问题方法进行重点介绍,其中主要包括流域的提取、有源淹没和无源淹没等。同时依据这些方法在ArcEngine组件环境下使用C#语言实现了洪水淹没分析系统。     

基于GIS和RS的白龟山水库洪水淹没分析及其损失评估

随着GIS技术的发展,其在自然灾害中的应用越来越广泛,特别是在洪水淹没分析中的应用。本文基于GIS技术以及RS技术,以TM影像和DEM为数据源,分析平顶山市范围内白龟山水库淹没的范围,并对淹没损失做了初步的评估,为湖区周围土地的合理利用提供依据并为减灾预灾提供一定的支撑。     

激光点云数据的输电通道淹没分析

针对从数字高程模型(DEM)数据中提取有源淹没范围的算法实现中,种子蔓延算法的递归深度太深,在给定洪水水位条件下容易堆栈溢出的缺点.该文提出了两次遍历的实现方法解决了上述问题.利用直升机激光三维扫描技术获取到输电线路的点云数据,经过点云预处理、分离地面点、栅格化处理等操作,得到了高精度DEM数据.利用DEM数据的特点,通过ArcGIS Engine建立了快速、高效的洪水淹没深度识别模型和有源淹没范围提取模型.可用于模拟重现淹没范围,为分析输电线路灾情特征、制定应急处置方案提供决策支持.     

基于ArcGIS的洪水淹没分析模拟及可视化

基于数字高程模型(DEM)格网模型,通过改进迭代种子蔓延算法,实现给定水深情况下洪水淹没区的讣算模型,讨论洪水淹没演进过程可视化实现的关键技术,并使用ArcEngine开发包进行二次开发,以二维和二三维两种可视化方式,动态而形象地模拟在指定洪水水位下的洪水淹没演进过程.试验证明,所提出的实现方法切实有效,便于推广应用,为快速、准确及科学地进行洪灾评估洪水风险图的制作提供良好的基础,对洪涝灾害进行评估和预测分析具有重要意义.     

地震诱发堰塞湖下游淹没风险评估方法对比研究

为了提升地震诱发堰塞湖突发灾难应急处置能力和充分利用灾区基础数据开展高效决策,本文结合遥感影像、DEM、水文资料和GIS技术,开展利用水文流量演算法和二维水动力学模型法快速评估堰塞湖溃决后下游淹没风险的方法研究。通过对唐家山堰塞湖690m溃坝洪水算例的应用,分别计算基于上述两种方法的下游潜在淹没影响范围,得到的两种计算结果均显示该规模的洪水将淹没下游北川县城的结果。最后通过分析对比两种影响范围计算结果的精度、数据需求、计算时长,评估两种方法在地震诱发堰塞湖下游淹没风险快速评估研究中的时效性、准确性和互补性。     

基于DEM的洪水淹没分析

DEM是地表或空间现象起伏变化的数字表示，包含了地球表面上许多有用的地理信息，其中就包括水文信息，通过DEM来生成集水流域和水域网络是大多数地表水文分析模型的数据来源，在用DEM数据生成3维地面模型的基础上，重点介绍与洪水淹没分析有关的一些技术问题。     

三维GIS蓄滞洪区淹没分析与灾损评估

蓄滞洪区是江河防洪体系的重要组成部分.基于洪水淹没机理,通过对蓄滞洪区地表的连通性分析,构建淹没过程模型;用等量分析的思想建立了计算洪水淹没水深和淹没范围的淹没分析模型,并在三维GIS环境中实现淹没分析结果的三维动态可视化.将淹没分析结果与社会背景数据叠加,结合洪灾损失率,对淹没区内的各类资产进行洪灾损失评估,为蓄滞洪区的管理、防洪减灾决策提供快捷、直观形象的信息支持.     

基于流域DEM遍历的3维淹没分析算法

在基于DEM遍历进行淹没分析基础上,提出了基于流域范围约束的DEM遍历算法,减少DEM遍历阶数,以提高计算速度。同时,将算法付诸于代码实现,在算例中与全局遍历进行对比测试。其对比结果表明,基于流域DEM遍历的淹没分析算法速度更快,计算结果可信。在大数据量条件下,速度优势更为明显,而在流域特征显著的地形条件下,计算结果精度高,与全局遍历结果基本一致。本文所研究的基于流域DEM遍历算法使得淹没分析更高效,对水文水力的研究与生产提供了捷径。     

一种面向海量数字高程模型数据的洪水淹没区快速生成算法

常见种子点填充算法在实现DEM数据下的洪水淹没区生成时,具有难以处理大数据量以及过多的递归计算易导致算法效率较低等缺点。针对此问题,本文提出一种面向海量DEM数据的洪水淹没区生成算法分块压缩追踪法,该算法采用条带分块和实时栅格压缩存储技术,以解决海量地形数据下的淹没分析计算问题。最后,通过将本算法与常见种子点填充算法和分块种子点填充算法进行了对比测试,实验结果表明本算法不仅较好地解决了海量DEM数据下的洪水淹没区生成问题,与常规种子点填充算法和分块种子点填充算法相比亦具有较高的计算效率。     

SAR与TM影像的IHS变换复合及其质量定量评价

本文采用四种典型的IHS变换方法,对同一地区的SAR与TM影像进行了复合,并对复合后图像的信息量及清晰度作了定性和定量分析。结果表明,用熵、联合熵和平均梯度这三个定量指标客观评价SAR与TM影像的复合效果,比目视评价结果准确有效,从而为选择最佳IHS变换方法进行多源遥感数据复合提供了依据。     

GIS Methodology for Characterizing Historical Conditions of the Willamette River Flood Plain, Oregon

Recent environmental developments have stimulated an interest in conservation and restoration of the historical Willamette River flood plain, both to protect against flooding and to provide wildlife habitat. In order to best utilize scarce resources, we characterized historical and modern river channel and flood‐plain conditions to evaluate changes and help prioritize restoration sites. Using cartographic and photographic data sources, we developed a Geographic Information System (GIS) to map active channels, side channels, islands and tributaries for four separate dates, as well as riparian and flood‐plain vegetation characteristics for pre‐European settlement and modern time periods. Coverages based on flood records and other boundaries were used to partition the flood plain into spatial subsets for analysis. The GIS allowed comparisons between historical and present conditions for a variety of environmental factors. Much of the pre‐settlement channel complexity has been removed. Total channel length in 1995 was 26% less than in 1850, with almost 58% of the river's side channels disconnected from the system. In addition, we found a 72% loss of flood‐plain forest from 1850 to 1995, since it was converted to agricultural and urban land uses. Selected river and flood‐plain variables were made available for a spatial model to prioritize potential locations for flood‐plain restoration.     

An innovative methodology for the prioritization of sub-catchments for flood control

Iran is dominated by arid and semi-arid climate with sporadic rainfall which creates seasonal floods and causes considerable damages and occasionally loss of life. The current research with the aim of flood damage reduction presents an innovative applied methodology for spatial optimization of flood control measures based on sub-catchments location. The presented methodology determines the contribution of each sub-catchment to the main catchment outlet flood peak and prioritizes sub-catchments for implementation of flood control measures. For this purpose catchment flood hydrographs are simulated by calibration and evaluation of a hydrologic model. The isochrones of the catchment have been computed and drawn and sub-catchment spatial distribution is investigated in relation to isochronal areas. Considering both spatial distribution and flooding potential of sub-catchments and their combined effects on the flood peak, their contribution to flood peak was modified by implementing flood control measure. Testing of this methodology on an experimental catchment indicated that sub-catchments located near the centroid of the catchment with an area of 64.6 km² have the greatest effects on flood peak for the overall catchment with an area of 284.6 km². It was concluded that flood control measures should be concentrated in these sub-catchments as the first priority.     

A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.     

Effects of Threshold Drainage Area and Study Region Size on HAZUS Flood Analysis

This study investigates the trends and error bounds in HAZUS flood hazard modeling due to changes in two parameters: threshold drainage area and study region size. Using the city of Ozark, Missouri, U.S.A., as a case study area, we compared modeled floodplains, flood debris, and economic loss in 24 threshold drainage areas and 20 study region sizes. The results show that the total floodplain area and total economic loss decrease with increasing threshold drainage area while the total amount of flood debris has an increasing trend. A threshold drainage area of 2.00 square miles is regarded as the optimal parameter for future HAZUS flood modeling for Ozark, based on the comparison of modeled floodplains with the FEMA Q3 floodplains. The total floodplain area and total economic loss tend to be larger at a larger study region, while no clear trend has been observed in the amount of flood debris. A study region of one county is suggested for future flood modeling because this size produces stable flood estimates and is also a convenient choice.     

太湖流域洪涝灾害评估模型

在地理信息系统支持下建立了太湖流域DEM模型,并建立了全流域12类共24种土地利用类型、2194个圩区、1012个乡镇和94个报汛站点的空间数据库及属性数据库。在此基础上,根据实时报汛资料,通过插值得到各乡汛期圩外水位和降雨量。圩区采用排涝计算圩内内涝水量再与DEM叠加,非圩区用乡最高水位与DEM叠加,可获得全流域淹没水深栅格数据。统计不同乡镇、不同土地类型、不同淹没水深的淹没面积,并根据当年的社会经济数据,建立了太湖流域洪涝灾害损失评估模型。对1999年太湖流域洪涝灾害评估结果表明,模型具有一定的精度,可为流域防洪减灾决策提供依据。     

鄱阳湖地区洪涝灾害遥感分析

鄱阳湖是一个吞吐型,季节性的浅淡水湖,高水湖相,低水河相。有“高水是湖,低水似河”,“洪水一片,枯水一线”的独特景观。洪涝灾害发生时,给周边地区造成巨大损失。利用TM遥感卫星图片,以特征最明显的1998年特大洪涝灾害为例,对鄱阳湖地区洪涝灾害症结和防洪策略提出几点见解。     

基于GIS/RS的洪涝灾害承灾极限遥感估算方法

利用ＧＩＳ和遥感技术相结合的方式进行洪涝灾害灾情调查和损失评估,可以采用一种新的方法──洪涝灾害承灾极限估算法。洪涝灾害承灾极限是区域稳定性的一种表述方式,而灾害条件下区域的稳定性取决于人－地系统中致灾因中的Ｅ｛ｋ｝和承灾因子的Ｅ｛ｋ｝及致灾因子和承灾因中之间的耦合关系Ｅ｛ｋ,ｋ｝。本文从原理和方法上对此作了阐述,根据承灾极限计算原理,在ＤＥＭ数据的支持下,利用洪水期实时图像和正常水位时期遥感图像提取的信息,可以进行洪涝灾害的灾情评估。     

抚州市洪水淹没3D可视化系统研发

洪水淹没三维可视化能够很直观地反映洪水受灾情况,对防洪救灾部门确定减灾目标,进行防洪减灾规划等均具有重要的意义。本文首先分析了现阶段GIS在防洪救灾应用中的不足,然后结合江西省抚州城区的地形图,建立了相应的洪水淹没GIS数据库,并利用可视化开发语言Visual C++与ArcEngine组件库开发了抚州市三维洪水淹没查询系统,详细介绍了三维地形的生成、水位线、水淹没区域、经济附属物显示及淹没区经济损失统计等功能的实现过程,为防洪工作做出科学决策提供了参考。     

基于Flex和ArcGIS Server的城市防汛指挥系统的设计与实现

针对淮安目前防汛工作上存在的问题,在介绍了ArcGIS Server、RIA/Flex和.NET等相关技术的基础上以及分析研究了系统的总体设计结构、数据库管理设计等,结合淮安防汛减灾相关情况,设计开发了WebGIS城市防汛指挥系统,并介绍了该系统所实现的功能,以及系统开发过程中所采用的关键技术等。通过对该系统的研究应用...