Hydraulic and hydrologic modeling has been moving to larger spatial scales with increased spatial resolution, and such models require a global database of river widths and depths to facilitate ...accurate river flow routing. Hydraulic geometry relationships have a long history in estimating river channel characteristics as a function of discharge. A simple near‐global database of bankfull widths and depths (along with confidence intervals) was developed based on hydraulic geometry equations and the HydroSHEDS hydrography data set. The bankfull width estimates were evaluated with widths derived from Landsat imagery for reaches of nine major rivers, showing errors ranging from 8 to 62% (correlation of 0.88), although it was difficult to verify whether the satellite observations corresponded to bankfull conditions. Bankfull depth estimates were compared with in situ measurements at sites in the Ohio and Willamette rivers, producing a mean error of 24%. The uncertainties in the derivation approach and a number of caveats are identified, and ways to improve the database in the future are discussed. Despite these limitations, this is the first global database that can be used directly in hydraulic models or as a set of constraints in model calibration.
Key Points
Developed a global river database
Used hydraulic geometry equations
Leveraged existing hydrologic datasets
Very high resolution synthetic aperture radar (SAR) sensors represent an alternative to aerial photography for delineating floods in built-up environments where flood risk is highest. However, even ...with currently available SAR image resolutions of 3 m and higher, signal returns from man-made structures hamper the accurate mapping of flooded areas. Enhanced image processing algorithms and a better exploitation of image archives are required to facilitate the use of microwave remote-sensing data for monitoring flood dynamics in urban areas. In this paper, a hybrid methodology combining backscatter thresholding, region growing, and change detection (CD) is introduced as an approach enabling the automated, objective, and reliable flood extent extraction from very high resolution urban SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values from images of floods. Images acquired during dry conditions enable the identification of areas that are not "visible" to the sensor (i.e., regions affected by "shadow") and that systematically behave as specular reflectors (e.g., smooth tarmac, permanent water bodies). CD with respect to a reference image thereby reduces overdetection of inundated areas. A case study of the July 2007 Severn River flood (UK) observed by airborne photography and the very high resolution SAR sensor on board TerraSAR-X highlights advantages and limitations of the method. Even though the proposed fully automated SAR-based flood-mapping technique overcomes some limitations of previous methods, further technological and methodological improvements are necessary for SAR-based flood detection in urban areas to match the mapping capability of high-quality aerial photography.
Microwave remote sensing of flood inundation Schumann, Guy J.-P.; Moller, Delwyn K.
Physics and chemistry of the earth. Parts A/B/C,
2015, 2015-00-00, 20150101, Letnik:
83-84
Journal Article
Recenzirano
•SAR for flood applications has grown considerably over the past decade.•Multitemporal SAR can monitor flood dynamics.•High-resolution SAR can map flooding in urban areas.•Long radar wavelengths can ...detect flooding under dense vegetation.•New SAR sensors expected to have significant impacts on flood applications.
Flooding is one of the most costly natural disasters and thus mapping, modeling and forecasting flood events at various temporal and spatial scales is important for any flood risk mitigation plan, disaster relief services and the global (re-)insurance markets. Both computer models and observations (ground-based, airborne and Earth-orbiting) of flood processes and variables are of great value but the amount and quality of information available varies greatly with location, spatial scales and time. It is very well known that remote sensing of flooding, especially in the microwave region of the electromagnetic spectrum, can complement ground-based observations and be integrated with flood models to augment the amount of information available to end-users, decision-makers and scientists. This paper aims to provide a concise review of both the science and applications of microwave remote sensing of flood inundation, focusing mainly on synthetic aperture radar (SAR), in a variety of natural and man-made environments. Strengths and limitations are discussed and the paper will conclude with a brief account on perspectives and emerging technologies.
In our changing world, floods are a threat of increasing concern. Within this context, flood mapping is important for both damage assessment and forecast improvement. Due to the suitability of ...synthetic aperture radar (SAR) for flood mapping, a broad range of SAR-based flood mapping algorithms has been developed during the past years. However, most of these algorithms were presented based on a single test case only and comparisons between methods are rare. This paper presents an in-depth assessment and comparison of the established pixel-based flood mapping approaches, including global and enhanced thresholding, active contour modeling and change detection. The methods were tested on medium-resolution SAR images of different flood events and lakes across the U.K. and Ireland and were evaluated on both accuracy and robustness. Results indicate that the most suited method depends on the area of interest and its characteristics as well as the intended use of the observation product. Due to its high robustness and good performance, tiled thresholding is suited for automated, near-real time flood detection and monitoring. Active contour models can provide higher accuracies but require long computation times that strongly increase with increasing image sizes, making them more appropriate for accurate flood mapping in smaller areas of interest.
In this paper we examine, for the first time, the potential of remote sensing to monitor flood dynamics in urban areas and constrain mathematical models of these processes. This is achieved through ...the development of a unique data set consisting of a series of eight space-borne synthetic aperture radar (SAR) and aerial photographic images of flooding of the UK town of Tewkesbury acquired over an eight day period in summer 2007. Previous observations of urban flooding have used single image and wrack mark data and have therefore been unable to adequately chart the propagation and recession of flood waves through complex urban topography. By using a combination of space-borne radar and aerial imagery we are able to show that remotely sensed imagery, particularly from the new TerraSAR-X radar, can reproduce dynamics adequately and support flood modelling in urban areas. We illustrate that image data from different remote sensing platforms reveal sufficient information to distinguish between models with varying degrees of channel–floodplain connectivity, particularly toward the end of the recession phase of the event. For this test case, our results also show that high resolution SAR imagery even when acquired from satellites can reveal important hydraulic characteristics difficult to simulate with current dynamic flood models. Hence, it is established, at least for this test case and event, that SAR imagery from as far as several hundred kilometers from the Earth's surface can deliver important information about floodplain dynamics that can be used to identify and help build suitable models, even in built-up environments.
► For the first time we assess remote sensing to monitor urban flood dynamics. ► Satellites deliver important information about urban floodplain dynamics. ► High resolution images reveal important hydraulic characteristics missing in models. ► This allows to distinguish between models with varying degrees of connectivity. ► It also helps improve suitable flood models where most flood risks are.
A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was ...present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high-resolution synthetic aperture radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high-resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18%, respectively.
The Surface Water and Ocean Topography (SWOT) mission will measure water surface elevations and inundation extents of rivers of the world but with limited temporal sampling. By comparing flood ...location and duration of 4,664 past flood events recorded by the Dartmouth Flood Observatory to SWOT's orbit ephemeris, we estimate that SWOT would have seen 55% of these, with higher probabilities associated with more extreme events and with those that displaced more than 10,000 people. However, SWOT measurements will exhibit uneven temporal sampling and may require a combination of data obtained at different times to accurately characterize large events. This is illustrated using recent flooding in the United States, in eastern Iowa and in Houston and surrounding areas from Hurricane Harvey. SWOT data have significant potential to improve flood forecasting models by offering data needed to enhance flow routing modeling, provided that users can overcome the potential hurdles associated with its temporal and spatial sampling characteristics.
Plain Language Summary
The Surface Water and Ocean Topography (SWOT) satellite mission will simultaneously measure water surface elevations and inundated areas for the Earth's land surface. Such information can be valuable for improving flood models and their calibration; however, SWOT temporal sampling will be limited, with most locations in the world being seen once every 7 to 10 days, which may cause it to miss floods. Using a record of global flood information, including duration and location, compiled by the Dartmouth Flood Observatory and the expected satellite orbit, we estimated that, if already operational, SWOT would have collected at least one measurement over 55% of these events. We illustrate SWOT data coverage using flood inundation maps generated for flooding in eastern Iowa (2008) and in Houston and surrounding areas, Texas, caused by Hurricane Harvey (2017). Due to the novelty of this kind of hydrological information, particularly in the way SWOT samples rivers in time and space, early engagement of potential users may be instrumental to maximize the utility of this open source of worldwide observations of rivers, lakes, and inundated land.
Key Points
SWOT temporal and spatial observation capabilities and limitations are evaluated using recent floods in eastern Iowa and from Hurricane Harvey
During its life cycle, SWOT may observe hundreds of flood events, including over data‐scarce regions
Dartmouth Flood Observatory data suggest that more destructive floods tend to last longer and are more likely to be observed by SWOT
This paper presents a new computationally efficient hydraulic model for simulating the spatially distributed dynamics of water surface elevation, wave speed, and inundation extent over large data ...sparse domains. The numerical scheme is based on an extension of the hydraulic model LISFLOOD‐FP to include a subgrid‐scale representation of channelized flows, which allows river channels with any width below that of the grid resolution to be simulated. The scheme is shown to be numerically stable and scalable, before being applied to an 800 km reach of the river Niger in Mali. The Niger application focused on the performance of four different model structures: a model without channels (two‐dimensional (2‐D) model), a model without a floodplain (one‐dimensional (1‐D) model), a model of the main channels and floodplain (1‐D/2‐D model), and the subgrid approach developed here. Inclusion of both the channel network and the floodplain was shown to be essential, meaning that large scale models of this region, including routing models for land surface schemes, will require a floodplain component. Including subgrid‐scale channels on the floodplain changed inundation dynamics over the delta significantly and increased simulation accuracy in terms of water level, wave propagation speed, and inundation extent. Furthermore, only the subgrid model showed a consistent parameterization when calibrated against either gauge or ICESat water level data, suggesting that connectivity provided by small channels is a strong control on the hydraulics of the floodplain, or, at the very least, that low resolution gridded hydraulic models require additional connectivity to represent the delta flow dynamics.
Key Points
A new sub‐grid hydraulic model was developed and evaluated
The model was designed for application over large data sparse regions
Assess the impact of small channels on the floodplain hydraulics
Rethinking flood hazard at the global scale Schumann, Guy J.‐P.; Stampoulis, Dimitrios; Smith, Andrew M. ...
Geophysical research letters,
16 October 2016, Letnik:
43, Številka:
19
Journal Article
Recenzirano
Odprti dostop
Flooding is governed by the amount and timing of water spilling out of channels and moving across adjacent land, often with little warning. At global scales, flood hazard is typically inferred from ...streamflow, precipitation or from satellite images, yielding a largely incomplete picture. Thus, at present, the floodplain inundation variables, which define hazard, cannot be accurately predicted nor can they be measured at large scales. Here we present, for the first time, a complete continuous long‐term simulation of floodplain water depths at continental scale. Simulations of floodplain inundation were performed with a hydrodynamic model based on gauged streamflow for the Australian continent from 1973 to 2012. We found the magnitude and timing of floodplain storage to differ significantly from streamflow in terms of their distribution. Furthermore, floodplain volume gave a much sharper discrimination of high hazard and low hazard periods than discharge. These discrepancies have implications for characterizing flood hazard at the global scale from precipitation and streamflow records alone, suggesting that simulations and observations of inundation are also needed.
Key Points
First continental‐wide long‐term event‐continuous 2‐D flood inundation computations
At‐a‐station discharge records do not directly translate to flood hazard
There is a need to rethink flood hazard assessment globally
PDF
