Reach scale floodplain inundation dynamics observed using airborne synthetic aperture radar imagery: Data analysis and modelling

Bates, Paul; Wilson, Matthew; Horritt, M. S.; Mason, David C.; Holden, Nick; Currie, Anthony

doi:10.1016/j.jhydrol.2005.12.028

Cited by 169 publications

(120 citation statements)

References 25 publications

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“…This assessment reveals that during midrecession, the number of separately wet floodplain objects reduces and the average area of each object increases identifying the point in the recession where the outer floodplain areas are drying up and consolidating into a few large ponded areas, which are slow to drain. Bates et al (2006) also showed this falling limb disconnect between channel and floodplain and ponding in a smaller number of floodplain areas for a much smaller floodplain in the UK. This might suggest that this process is common across different scales and climatic regimes.…”

Section: Surface Water Connectivitymentioning

confidence: 82%

“…The importance of these mechanisms, e.g. overtopping of topographical barriers and flow in floodplain channels, on the dynamics of floodplain inundation is crucial to the modelling of those dynamics in rural (Nicholas and Mitchell, 2003;Bates et al, 2006;Alsdorf et al, 2007) and urban areas (Schumann et al, 2011).…”

Section: Surface Water Connectivitymentioning

confidence: 99%

“…Also, increasingly, remotely sensed flood extent data are being successfully used to build, calibrate and validate complex large scale hydraulic models where the correct representation of dynamic flow processes are crucial (e.g. Bates et al, 2006;Wilson et al, 2007;Schumann et al, 2011;Bates, 2012;Neal et al, 2012). In addition, these remote sensing data are now being made readily available pre-processed, allowing wider use within the hydrological community.…”

Section: Introductionmentioning

confidence: 99%

“…The availability of sequences of flood extent provided by these methods are now allowing the validation of hydraulic models through a wider dynamic range of an event (Bates et al, 2006;Schumann et al, 2011), rather than just at a single point in the event, as well as being used in near real time to monitor floods (Chien et al, 2011;Auynirundronkool et al, 2012;McLaren et al, 2012). There are many potentially important flow processes active on a floodplain, such as floodplain channels and ditches providing flow connections (Nicholas and Mitchell, 2003) as well as barriers such as embankments, floodplain channel levees and woody debris blocking flow connections (Jeffiries et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

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Surface water connectivity dynamics of a large scale extreme flood

Trigg

Michaelides

Neal

et al. 2013

Journal of Hydrology

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During flood inundation, river water passes from the main channel into the floodplain through floodplain channels and diffusive overbank flow. This flood water is then distributed within the floodplain depending upon internal connections, barriers and storage, and finally returns back to the river through drainage connections. This surface water connectivity can be complex and is important to many aspects of floodplain functioning, including ecology, sediment movement and flood risk. However, there is currently no accepted way of quantifying this connectivity objectively. We quantify surface water connectivity geostatistically as an objectively measurable characteristic of an observed flood event using a time series of MODIS (Moderate Resolution Imaging Spectroradiometer) surface water product for an extreme large scale flood event (11,000 km 2 flooded area and 6 month duration) during 2011 in Bangkok, Thailand. We develop and apply a new gap filling method that better preserves the dynamic information of the event than simple aggregation methods. Comparison of MODIS results with the higher resolution Earth Observer 1 shows fundamental differences in the resolved connectivity with scale despite similar flooded area. The effect of the passage of the flood wave is directly observable in the river reach, as out-of-bank flooding progresses and increases connectivity along the river during rising water. Around peak flow, there is an increase in connectivity of the floodplain adjacent to the river as low lying areas fill. A step increase in connectivity is correlated with a major levee breach. During recession there is a rapid reduction in along river connectivity in the first week after the peak. This rapid reduction contrasted with a slow decrease in the floodplain connectivity as flooded depressions gradually drained reducing depth, while flood extent remained static for long periods. The connectivity analysis of the threshold in floodplain draining indicates that although spatial flood extent changes are small at this time, there is a reorganisation of the internal surface water connectivity within the flooded area. Thus through this measure of connectivity, we can see a clear structure to the event progression with new insights into flood dynamics that were not anticipated a priori.

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Section: Surface Water Connectivitymentioning

confidence: 82%

Section: Surface Water Connectivitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Surface water connectivity dynamics of a large scale extreme flood

Trigg

Michaelides

Neal

et al. 2013

Journal of Hydrology

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“…Matgen et al (2007) tested and compared methods for flood depth interpolation based on flood masks derived from SAR imagery. Bates et al (2006) used a 2-D hydraulic model approach to cross-compare the results with SAR derived flood extent maps, while Meinel et al (2003) presented concepts for computing water levels using elevation readings from intersecting IKONOS flood masks with LiDAR DEMs and terrestrial land/water line observations. Schumann et al (2007) used different regression models to fit the left and right bank elevation readings from SAR based water mask/DEM intersections.…”

Section: Introductionmentioning

confidence: 99%

Improved estimation of flood parameters by combining space based SAR data with very high resolution digital elevation data

Zwenzner

Voigt

2009

Hydrol. Earth Syst. Sci.

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Abstract. Severe flood events turned out to be the most devastating catastrophes for Europe's population, economy and environment during the past decades. The total loss caused by the August 2002 flood is estimated to be 10 billion Euros for Germany alone. Due to their capability to present a synoptic view of the spatial extent of floods, remote sensing technology, and especially synthetic aperture radar (SAR) systems, have been successfully applied for flood mapping and monitoring applications. However, the quality and accuracy of the flood masks and derived flood parameters always depends on the scale and the geometric precision of the original data as well as on the classification accuracy of the derived data products. The incorporation of auxiliary information such as elevation data can help to improve the plausibility and reliability of the derived flood masks as well as higher level products. This paper presents methods to improve the matching of flood masks with very high resolution digital elevation models as derived from LiDAR measurements for example. In the following, a cross section approach is presented that allows the dynamic fitting of the position of flood mask profiles according to the underlying terrain information from the DEM. This approach is tested in two study areas, using different input data sets. The first test area is part of the Elbe River (Germany) where flood masks derived from Radarsat-1 and IKONOS during the 2002 flood are used in combination with a LiDAR DEM of 1 m spatial resolution. The other test data set is located on the River Severn (UK) and flood masks derived from the TerraSAR-X satellite and aerial photos acquired during the 2007 flood are used in combination with a LiDAR DEM of 2 m pixel spacing. By means of these two examples the performance of the matching technique and the Correspondence to: H. Zwenzner (hendrik.zwenzner@dlr.de) scaling effects are analysed and discussed. Furthermore, the systematic flood mapping capability of the different imaging systems are examined. It could be shown that the combination of high resolution SAR data and LiDAR DEM allows the derivation of higher level flood parameters such as flood depth estimates, as presented for the Severn area. Finally, the potential and the constraints of the approach are evaluated and discussed.

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Flooding dynamics on the lower Amazon floodplain: 1. Hydraulic controls on water elevation, inundation extent, and river-floodplain discharge

2014

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[1] Modeling the routing of flood waters across large floodplains is challenging because flows respond to dynamic hydraulic controls from complex geomorphology, vegetation, and multiple water sources. In this study, we analyzed the topographic and hydrologic controls of inundation dynamics of a large floodplain unit (2440 km 2 ) along the lower Amazon River. We combined land topography derived from the Shuttle Radar Topography Mission (SRTM) with underwater topography derived from an extensive echo-sounding survey to generate a seamless digital elevation model (DEM). Floodplain inundation was simulated using LISFLOOD-FP, which combines one-dimensional river routing with two-dimensional overland flow, and a local hydrological model. For the first time, accurate simulation of filling and drainage of an Amazon floodplain was achieved with quantification of changes in water elevation, flooding extent, and river-floodplain exchange. We examined the role of diffuse overbank versus channelized flows on river-floodplain exchange. Diffuse overbank flows represent 93% of total river to floodplain discharge and 54% of floodplain to river discharge. Floodplain discharge during high-water was four times higher than field observation values when the SRTM v.4 DEM with no correction was used for simulation because of a 24.4 m elevation bias originating from residual motion errors of the SRTM interferometric baseline.

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Reach scale floodplain inundation dynamics observed using airborne synthetic aperture radar imagery: Data analysis and modelling

Cited by 169 publications

References 25 publications

Surface water connectivity dynamics of a large scale extreme flood

Surface water connectivity dynamics of a large scale extreme flood

Improved estimation of flood parameters by combining space based SAR data with very high resolution digital elevation data

Flooding dynamics on the lower Amazon floodplain: 1. Hydraulic controls on water elevation, inundation extent, and river-floodplain discharge

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