Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management

Matgen, Patrick; Schumann, Guy; Henry, Jean-Baptiste; Hoffmann, Lucien; Pfister, Laurent

doi:10.1016/j.jag.2006.03.003

Cited by 228 publications

(142 citation statements)

References 34 publications

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“…The spatial detail of the simulated inundation depths depends on the discretization level of the model setup which is usually below 100 m horizontal resolution (Horritt and Bates, 2002;Falter et al, 2014). The near-real-time application of hydrodynamic-numeric models is hampered by the need to provide appropriate estimates of initial and boundary conditions, to assimilate model simulations and observations (Matgen et al, 2007) and by considerable computational costs . Computation time depends particularly on the size of the computational domain and its spatial resolution (Falter et al, 2013) and the complexity level of model equations (Horritt and Bates, 2002).…”

Section: State Of the Art And Related Workmentioning

confidence: 99%

Social media as an information source for rapid flood inundation mapping

Fohringer

Dransch

Kreibich

et al. 2015

Nat. Hazards Earth Syst. Sci.

206

129

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Abstract. During and shortly after a disaster, data about the hazard and its consequences are scarce and not readily available. Information provided by eyewitnesses via social media is a valuable information source, which should be explored in a more effective way. This research proposes a methodology that leverages social media content to support rapid inundation mapping, including inundation extent and water depth in the case of floods. The novelty of this approach is the utilization of quantitative data that are derived from photos from eyewitnesses extracted from social media posts and their integration with established data. Due to the rapid availability of these posts compared to traditional data sources such as remote sensing data, areas affected by a flood, for example, can be determined quickly. The challenge is to filter the large number of posts to a manageable amount of potentially useful inundation-related information, as well as to interpret and integrate the posts into mapping procedures in a timely manner. To support rapid inundation mapping we propose a methodology and develop "PostDistiller", a tool to filter geolocated posts from social media services which include links to photos. This spatial distributed contextualized in situ information is further explored manually. In an application case study during the June 2013 flood in central Europe we evaluate the utilization of this approach to infer spatial flood patterns and inundation depths in the city of Dresden.

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Section: State Of the Art And Related Workmentioning

confidence: 99%

Social media as an information source for rapid flood inundation mapping

Fohringer

Dransch

Kreibich

et al. 2015

Nat. Hazards Earth Syst. Sci.

206

129

View full text Add to dashboard Cite

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“…Two main techniques may be distinguished: (1) direct measuring techniques such as those from the proposed swath altimetry "Surface Water and Ocean Topography" (SWOT) mission and (2) indirect measuring techniques based on the estimation of river stages at the land-water interface using topographic maps or Digital Elevation Models (DEM) (e.g. Smith, 1997;Brakenridge et al, 1998;Raclot, 2006;Schumann et al, 2007a;Matgen et al, 2007a). The reliability and repeatability are the main advantages associated with water level products stemming from wide swath altimetry.…”

Section: Introductionmentioning

confidence: 99%

Towards the sequential assimilation of SAR-derived water stages into hydraulic models using the Particle Filter: proof of concept

Matgen

Montanari

Hostache

et al. 2010

Hydrol. Earth Syst. Sci.

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142

108

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Abstract. With the onset of new satellite radar constellations (e.g. Sentinel-1) and advances in computational science (e.g. grid computing) enabling the supply and processing of multimission satellite data at a temporal frequency that is compatible with real-time flood forecasting requirements, this study presents a new concept for the sequential assimilation of Synthetic Aperture Radar (SAR)-derived water stages into coupled hydrologic-hydraulic models. The proposed methodology consists of adjusting storages and fluxes simulated by a coupled hydrologic-hydraulic model using a Particle Filterbased data assimilation scheme. Synthetic observations of water levels, representing satellite measurements, are assimilated into the coupled model in order to investigate the performance of the proposed assimilation scheme as a function of both accuracy and frequency of water level observations. The use of the Particle Filter provides flexibility regarding the form of the probability densities of both model simulations and remote sensing observations. We illustrate the potential of the proposed methodology using a twin experiment over a widely studied river reach located in the Grand-Duchy of Luxembourg. The study demonstrates that the Particle Filter algorithm leads to significant uncertainty reduction of water level and discharge at the time step of assimilation. However, updating the storages of the model only improves the model forecast over a very short time horizon. A more effective way of updating thus consists in adjusting both states and inputs. The proposed methodology, which consists in updatCorrespondence to: P. Matgen (matgen@lippmann.lu) ing the biased forcing of the hydraulic model using information on model errors that is inferred from satellite observations, enables persistent model improvement. The present schedule of satellite radar missions is such that it is likely that there will be continuity for SAR-based operational water management services. This research contributes to evolve reactive flood management into systematic or quasi-systematic SAR-based flood monitoring services.

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“…[5]), which had been used by e.g. [1], [6] and [7] for flood boundary delineation in medium resolution SAR imagery or fully automatic texture based maximum likelihood methods [7], which are able to detect water bodies independent of the sensor incidence angle.…”

Section: Comparison Of Pixel-based and Object-based Approachesmentioning

confidence: 99%

Automatic Extraction of Water Bodies from TerraSAR-X Data

Hahmann

Roth

Martinis

et al. 2008

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium

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Medium resolution SAR satellite data have been widely used for water and flood mapping in recent years. Since the beginning of 2008 high resolution radar data with up to one meter pixel spacing of the TerraSAR-X satellite are operationally available. The improved ground resolution of the system offers a high potential for water detection. However, image analysis gets more challenging due to the large amount of image objects that are visible in the data. Water body detection methods are reviewed with regard to their applicability for TerraSAR-X data. Flood detection approaches for rapid disaster mapping are presented in this paper.

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Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management

Cited by 228 publications

References 34 publications

Social media as an information source for rapid flood inundation mapping

Social media as an information source for rapid flood inundation mapping

Towards the sequential assimilation of SAR-derived water stages into hydraulic models using the Particle Filter: proof of concept

Automatic Extraction of Water Bodies from TerraSAR-X Data

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