Hydrological and hydrodynamic modeling for flood damage mitigation in Brahmani–Baitarani River Basin,India

Stream flow forecast and its inundation simulations prior to the event are an effective and non-structural method of flood damage mitigation. In this paper, a continuous simulation hydrological and hydrodynamic model was developed for stream flow forecast and for spatial inundation simulation in Brahmani–Baitarani river basin, India. The hydrologic modelling approach includes rainfall-run-off modelling, flow routing, calibration and validation of the model with the field discharge data. CARTOSAT Digital Elevation Model of 30 m resolution, land use/land cover derived from the Indian Remote Sensing Satellite (IRS-P6) AWiFS and soil textural data of the study area were used in the modelling to compute topographic and hydraulic parameters. The hydrological model was calibrated with the help of field observed discharge data of 2006 and 2009 and validated with the data of 2008 and 2011. From the results, it is found that computed discharges are very well matching well with the observed discharges. The developed model can provide the stream flow forecast with more than 30 h lead time. Possible flood inundations were simulated using hydrodynamic modelling approach. CARTO Digital Elevation Model of 10 m resolution, landuse and the computed flood hydrographs were used in inundation simulations.     

Assessment and Management Flash Flood in Najran Wady Using GIS and Remote Sensing

Flash flood assessment and management are necessary for municipal, urban growth planning and emergency action plans. By using the Hydrologic Engineering Centers River Analysis System software, we can model flash flood events and calculate water surface profiles over the length of the modeled stream. After collecting elevation points by using GPS method, the digital elevation model can be calculated for the study area. Najran city has main flood stream passes beside King Abdullah Road based on facts and previous works. A small study area including the mainstream of Wady Najran and King Abdullah Road has chosen as test site. The used methodology has also been proved efficiently for identifying flood inundation maps. Water extent area overlapped by 52–86% for both used methods. At discharge Q = 15 m³/s, the road needs to be protected from the flood.     

Mapping spatio-temporal flood inundation dynamics at large river basin scale using time-series flow data and MODIS imagery

Flood inundation is crucial to the survival and prosperity of flora and fauna communities in floodplain and wetland ecosystems. This study tried to map flood inundation characteristics in the Murray-Darling Basin, Australia, utilizing hydrological and remotely sensed data. It integrated river flow time series and Moderate Resolution Imaging Spectroradiometer (MODIS) images to map inundation dynamics over the study area on both temporal and spatial dimensions. Flow data were analyzed to derive flow peaks and Annual Exceedance Probabilities (AEPs) using the annual flood series method. The peaks were linked with MODIS images for inundation detection. Ten annual maximum inundation maps were generated for water years 2001–2010, which were then overlaid to derive an inundation frequency map. AEPs were also combined with the annual maximum inundation maps to derive an inundation probability map. The resultant maps revealed spatial and temporal patterns of flood inundation in the basin, which will benefit ecological and environmental studies when considering response of floodplain and wetland ecosystems to flood inundation.     

Flood Inundation Hazard Modelling Using CCHE2D Hydrodynamic Model and Geospatial Data for Embankment Breaching Scenario of Brahmaputra River in Assam

In many flood prone river basins, water inundates vast areas of land causing loss of life and heavy damage to the dwellings in flood plains. It also impacts agricultural productivity and cause severe economic losses. One of the reasons for flooding in plains of Brahmaputra valley in north east India is embankment breaching. In this study, an attempt was made for probabilistic flood hazard modelling of July 2008 embankment breaching scenario of Brahmaputra river at Matmara village, Lakhimpur district in Assam, based on various numerical simulations with the help of Center for Computational Hydro science and Engineering hydro-dynamic model. The methodology was applied over 2146 km² flood prone area. Data inputs in the study include: Advanced Spaceborne Thermal Emission and Reflection Radiometer Digital Elevation Model, Pre-flood and Post flood satellite images of Landsat Enhanced Thematic Mapper Plus (ETM+) and other ancillary data. The simulation was carried out for various discharge levels based on flood frequency analysis. The result of the model includes spatial variations of inundated water depth and water velocity. The results were validated by comparing it with the post-flood ETM+ data and flood situation status report of National Informatics Centre. Flood hazard maps were prepared by carrying out a spatial analysis of simulated inundation depth and velocity. It was seen that the majority of flooded area fell into the very high and high categories. This information can be used to plan appropriate cost effective flood mitigation schemes.     

GIS-based approach for flood analysis: case study of Keçidere flash flood event (Turkey)

The purpose of this study is to explain the formation mechanism of the floods which occurred in the Keçidere basin in 2009. In this study, discharge data in between 1981 and 2009, digital elevation model (DEM), satellite images and field works were used as a main data sources. LPT3 was applied to 29-year maximum flow data to produce different flood return periods such as 2, 5, 50, 100, 200, 500 and 1000-year flood. The DEM was created using 1:25,000 topographic contours with Topo to Raster interpolation techniques in geographical information systems (GIS). Land use and some geometric data were digitized using high resolution satellite images for hydraulic modelling purposes. Simulation of the 2009 flash flood event and different return periods flow data was done using one-dimensional hydraulic modelling with HEC-RAS. In the last phase, results obtained from the simulations and field works were compared based on fits statistics and mean absolute error in terms of extent and depth. An analysis of water extent and depth features observed during the highest flow ever measured in the basin revealed that the result overlapped with 500-year inundation extent. Overall, the results of the research indicate that GIS is an effective environment for floodplain mapping and analysis.     

超像元尺度下的多光谱图像超分辨率洪水淹没制图

超分辨率制图SRM (Super-resolution Mapping)技术可以有效地处理遥感图像中的混合像元,获得准确的地物类别分布信息。目前,SRM技术已经成功地应用于多光谱图像洪水淹没定位中,称为超分辨率洪水淹没制图SRFIM (Super-resolution Flood Inundation Mapping)。然而,现有的SRFIM方法往往基于像元尺度空间相关性,这种空间相关性考虑设定的矩形窗内的像元之间的空间关系,但实际情况下淹没区域与非淹没区域的形状是不规则的,因此这种像元尺度空间相关性不够准确,影响最终的洪水淹没制图精度。为了解决这一问题,提出了超像元尺度空间相关性下的多光谱图像超分辨率洪水淹没制图SSSC-SRFIM (Super-resolution Flood Inundation Mapping for Multispectral Image Based on Super-pixel Scale Spatial Correlation)。在SSSC-SRFIM中,首先利用双立方插值改善原始粗糙多光谱图像,获得改善后的图像,并利用光谱解混方法对改善后的图像进行光谱解混,获得具有每个亚像元属于淹没类别概率值的丰度图像;然后利用主成分分析法提取改善后图像的第一主成分,并利用基于多分辨率的图像分割算法分割第一主成分,获得不规则形状的超像元;再者将丰度图像与超像元进行整合计算,并引入随机游走算法计算各个超像元之间的空间相关性;最后,依据超像元空间相关性,利用基于类别单元的类别方法将淹没区域或非淹没区域标签分配给每个亚像元中,得到最终的洪水淹没制图结果。利用两个Landsat 8 OLI多光谱图像对该方法进行了评价。结果表明,与传统的SRFIM方法相比,本文提出的SSSC-SRFIM方法具有更好的效果。     

Flood risk analysis in the Kosi river basin, north Bihar using multi-parametric approach of Analytical Hierarchy Process (AHP)

The Kosi river in north Bihar plains, eastern India presents a challenge in terms of long and recurring flood hazard. Despite a long history of flood control management in the basin for more than 5 decades, the river continues to bring a lot of misery through extensive flooding. This paper revisits the flooding problem in the Kosi river basin and presents an in-depth analysis of flood hydrology. We integrate the hydrological analysis with a GIS-based flood risk mapping in parts of the basin. Typical hydrological characteristics of the Kosi river include very high discharge variability, and high sediment flux from an uplifting hinterland. Annual peak discharges often exceed the mean annual flood and the low-lying tracts of the alluvial plains are extensively inundated year after year. Our flood risk analysis follows a multi-parametric approach using Analytical Hierarchy Process (AHP) and integrates geomorphological, land cover, topographic and social (population density) parameters to propose a Flood Risk Index (FRI). The flood risk map is validated with long-term inundation maps and offers a cost-effective solution for planning mitigation measures in flood-prone areas.     

无人机倾斜摄影三维模型在城市雨洪风险评估中的应用

研究城市雨洪风险问题，对提高城市洪涝灾害监测、预报的准确性，以及促进城市防洪决策制定具有重要的意义。鉴于高精度的城市三维模型可以提供丰富地理信息，便于准确分析淹没情况，本文针对当前城市洪涝模型对地形数据的高敏感性，且雨洪风险评估研究的准确性受限于地形数据精度的问题，提出利用无人机倾斜摄影测量技术重建高精度实景三维模型，并结合GIS的空间分析功能，以淹没深度为关键指标进行研究区的雨洪风险评估。通过提取不同重现期下研究区的淹没深度信息，进行可视化渲染实现三维淹没分析，可以直观地看到研究区的淹没情况，作为暴雨内涝风险管理依据，同时对城市规划布局有一定的参考价值。     

Flood forecasting in Niger-Benue basin using satellite and quantitative precipitation forecast data

Availability of reliable, timely and accurate rainfall data is constraining the establishment of flood forecasting and early warning systems in many parts of Africa. We evaluated the potential of satellite and weather forecast data as input to a parsimonious flood forecasting model to provide information for flood early warning in the central part of Nigeria. We calibrated the HEC-HMS rainfall-runoff model using rainfall data from post real time Tropical Rainfall Measuring Mission (TRMM) Multi satellite Precipitation Analysis product (TMPA). Real time TMPA satellite rainfall estimates and European Centre for Medium-Range Weather Forecasts (ECMWF) rainfall products were tested for flood forecasting. The implication of removing the systematic errors of the satellite rainfall estimates (SREs) was explored. Performance of the rainfall-runoff model was assessed using visual inspection of simulated and observed hydrographs and a set of performance indicators. The forecast skill was assessed for 1–6 days lead time using categorical verification statistics such as Probability Of Detection (POD), Frequency Of Hit (FOH) and Frequency Of Miss (FOM). The model performance satisfactorily reproduced the pattern and volume of the observed stream flow hydrograph of Benue River. Overall, our results show that SREs and rainfall forecasts from weather models have great potential to serve as model inputs for real-time flood forecasting in data scarce areas. For these data to receive application in African transboundary basins, we suggest (i) removing their systematic error to further improve flood forecast skill; (ii) improving rainfall forecasts; and (iii) improving data sharing between riparian countries.     

基于哨兵数据相干性的洪水淹没范围确定方法

洪涝灾害会造成农田淹没、居民住宅损毁等危害,因此对洪水淹没范围进行实时、准确监测可有效进行灾后治理。利用光学传感器提取洪水淹没范围时,不能穿透云层,因此无法获取有效地面信息;而SAR使用微波波段,不受天气影响,在夜间也能成像。因此,SAR成为洪水灾害灾情评估的有力工具。本文利用2021年9月23日、10月5日、10月17日3景SAR雷达影像Sentinel-1A数据,计算相干性系数,设置阈值为0.2,提取水体淹没范围,分析其扩张范围及变化趋势,并根据生成的形变图分析水位抬升变化,验证了基于雷达数据的相干系数阈值提取方法监测洪水淹没范围,以及采用InSAR技术准确提取水体边界与分析水位上升趋势的可行性。     

Mapping floods due to Hurricane Sandy using NPP VIIRS and ATMS data and geotagged Flickr imagery

In this study, we present an approach to estimate the extent of large-scale coastal floods caused by Hurricane Sandy using passive optical and microwave remote sensing data. The approach estimates the water fraction from coarse-resolution VIIRS and ATMS data through mixed-pixel linear decomposition. Based on the water fraction difference, using the physical characteristics of water inundation in a basin, the flood map derived from the coarse-resolution VIIRS and ATMS measurements was extrapolated to a higher spatial resolution of 30 m using topographic information. It is found that flood map derived from VIIRS shows less inundated area than the Federal Emergency Management Agency (FEMA) flood map and the ground observations. The bias was mainly caused by the time difference in observations. This is because VIIRS can only detect flood under clear conditions, while we can only find some clear-sky data around the New York area on 4 November 2012, when most flooding water already receded. Meanwhile, microwave measurements can penetrate through clouds and sense surface water bodies under clear-or-cloudy conditions. We therefore developed a new method to derive flood maps from passive microwave ATMS observations. To evaluate the flood mapping method, the corresponding ground observations and the FEMA storm surge flooding (SSF) products are used. The results show there was good agreement between our ATMS and the FEMA SSF flood areas, with a correlation of 0.95. Furthermore, we compared our results to geotagged Flickr contributions reporting flooding, and found that 95% of these Flickr reports were distributed within the ATMS-derived flood area, supporting the argument that such crowd-generated content can be valuable for remote sensing operations. Overall, the methodology presented in this paper was able to produce high-quality and high-resolution flood maps over large-scale coastal areas.     

Data assimilation of satellite-based actual evapotranspiration in a distributed hydrological model of a controlled water system

Advances in earth observation (EO) and spatially distributed hydrological modelling provide an opportunity to improve modelling of controlled water systems. In a controlled water system human interference is high, which may lead to incorrect parameterisation in the model calibration phase. This paper analyses whether assimilation of EO actual evapotranspiration (ETa) data can improve discharge simulation with a spatially distributed hydrological model of a controlled water system. The EO ETa estimates are in the form of eight-day ETa composite maps derived from Terra/MODIS images using the ITA-MyWater algorithm. This algorithm is based on the surface energy balance method and is calibrated for this research for a low-lying reclamation area with a heavily controlled water system: the Rijnland area in the Netherlands. Data assimilation (DA) with the particle filter method is applied to assimilate the ETa maps into a spatially distributed hydrological model. The hydrological model and DA framework are applied using the open source software SIMGRO and PCRaster-Python respectively. The analysis is done for a period between July and October 2013 in which a high discharge peak followed a long dry-spell. The assimilation of EO ETa resulted in local differences in modelled ETa compared to simulation without data assimilation, while the area average ETa remained almost the same. The modelled cumulative discharge graphs, with and without DA, showed distinctive differences with the simulation, with DA better matching the measured cumulative discharge. The bias of simulated cumulative discharge to the observed data reduced from 14% to 4% when using DA of EO ETa. These results showed that assimilating EO ETa may not only be effective in the more common applications of soil moisture and crop-growth modelling, but also for improving discharge modelling of controlled water systems.     

Moraine-Dammed Lakes study in the chenab and The Satluj River Basins using IRS data

Moraine-dammed lakes are normally formed near glacier terminus. These lakes can burst due to excessive melting and can cause floods in the valleys. Many such floods have been reported in the Himalayas and other parts of the World. In this paper, an inventory of these lakes in the Satluj and the Chenab basins has been reported. During the investigation, 22 lakes in the Satluj and 31 lakes in the Chenab basin were mapped. In the Chenab basin, two lakes are of very large size, their areal extent is 105 and 55 ha, located in toposheet number 52 HI 1 and 52H02, respectively. These lakes were selected for detail monitoring. The lake near the Geepang glacier, is located in toposheet number 52H 02 and its area was 27 ha in 1976. Using the satellite data, areal extent of the lake was monitored. The lake area was almost doubled to 55 ha in 2001. This suggested that, lake size is constantly increasing and it can cause outburst flood. The maximum possible depth of lake was estimated by taking the average difference of maximum and minimum height of moraine dam from the Survey of India toposheet. By considering the average depth, the volume of the lake water and the instantaneous discharge of 350 mVsec were estimated. This is large discharge for a small stream like the Geepang Gath and it can damage many civilian and defense establishments. Therefore, further detail field investigations of this lake are needed to assess threat potential and to develop strategy to avoid this flash flood.     

Impact of missing flow on active inundation areas and transformation of parafluvial wetlands in Punarbhaba–Tangon river basin of Indo-Bangladesh

Punarbhaba river of Indo-Bangladesh has experienced hydro-ecological alteration after installation of Komardanga dam in 1992 and consequently wetland and inundation areas have undergone into transformation. The present work intends to explore the impact of flow attenuation on contemporary and upcoming flood extent and flood plain wetlands. In post-dam condition, average and maximum flows are attenuated by 36 and 41%, respectively, and as a result the active flood prone area is squeezed considerably by 39.72%. Average flood water depth is also reduced by 37.87% (4.45metre) after flow modification. Due to shrinkages of flood prone areas, wetland area is also reduced from 215.70 to 90.40 km² and larger part of the present wetland area is under stress and critical state. Predicted flood prone areas in next 25 years will be 328.91 km² and consequently 65.63 km² wetland areas may further be under hydro-ecological threats. Release of ecological flow is essential to restore and preserve the wetland.     

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。     

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.     

Flood inundation mapping in a part of Mahanadi river basin

Man has had to live with floods since the very inception of his existence. Fury of flood causes heavy damages to both life and property. Accurate flood inundation data is one of the essential requirements for effective management of flood problem. Remote Sensing methods are well suited for acquiring flood inundation data because of synoptic, repetitive coverage of the satellite data. This paper briefs on an attempt to map flood inundated areas in a part of Mahanadi river basin using remote sensing data.     

时序Sentinel-1A数据支持的长江中下游汛情动态监测

合成孔径雷达（SAR）因其对地观测全天候、全天时优势,成为多云多雨天气限制下洪水动态监测中不可或缺的数据来源之一。由于GEE（Google Earth Engine）云计算平台的兴起和短重访Sentinel-1数据的可获取性,洪水监测与灾害评估目前正面向动态化、广域化快速发展。顾及洪水淹没区土地覆盖变化的复杂性和发生时间的不确定性,基于时序Sentinel-1A卫星数据提出了针对大尺度范围、连续长期的汛情自动检测及动态监测方法。该方法首先,利用图像二值化分割时序SAR数据实现水体时空分布粗制图,逐像素计算时间序列中被识别为水体候选点的频率。然后,利用Sentinel-2光学影像对精度较粗的初期SAR水体提取结果进行校正,得到精细的水体分布图。最后,针对不同频率区间的淹没特点,采用差异化的时序异常检测策略识别淹没范围：对低频覆水区利用欧氏距离检测时序断点,以提取扰动强度大、淹没时间短的洪涝灾害区;对高频覆水区利用标准分数（Z-Score）检测时序断点,以提取季节性水体覆盖区。在GEE平台上利用该方法,实现了2020-05—10长江中下游地区全域洪水淹没范围时空信息的自动、快速、有效监测,揭示了不同区域汛情发展模式的差异性。本文提出的洪水快速监测方法对大尺度下的汛情动态监测、灾害定量评估和快速预警响应具有重要的现实意义。     

Multi-source data fusion and modeling to assess and communicate complex flood dynamics to support decision-making for downstream areas of dams: The 2011 hurricane irene and schoharie creek floods,NY

In light of climate and land use change, stakeholders around the world are interested in assessing historic and likely future flood dynamics and flood extents for decision-making in watersheds with dams as well as limited availability of stream gages and costly technical resources. This research evaluates an assessment and communication approach of combining GIS, hydraulic modeling based on latest remote sensing and topographic imagery by comparing the results to an actual flood event and available stream gages. On August 28th 2011, floods caused by Hurricane Irene swept through a large rural area in New York State, leaving thousands of people homeless, devastating towns and cities. Damage was widespread though the estimated and actual floods inundation and associated return period were still unclear since the flooding was artificially increased by flood water release due to fear of a dam break. This research uses the stream section right below the dam between two stream gages North Blenheim and Breakabeen along Schoharie Creek as a case study site to validate the approach. The data fusion approach uses a GIS, commonly available data sources, the hydraulic model HEC-RAS as well as airborne LiDAR data that were collected two days after the flood event (Aug 30, 2011). The aerial imagery of the airborne survey depicts a low flow event as well as the evidence of the record flood such as debris and other signs of damage to validate the hydrologic simulation results with the available stream gauges. Model results were also compared to the official Federal Emergency Management Agency (FEMA) flood scenarios to determine the actual flood return period of the event. The dynamic of the flood levels was then used to visualize the flood and the actual loss of the Old Blenheim Bridge using Google Sketchup. Integration of multi-source data, cross-validation and visualization provides new ways to utilize pre- and post-event remote sensing imagery and hydrologic models to better understand and communicate the complex spatial-temporal dynamics, return periods and potential/actual consequences to decision-makers and the local population.     

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。