The Use of Radar Imagery in Riverine Flood Inundation Studies

Schumann, Guy; Bates, Paul; Baldassarre, Giuliano Di; Mason, David C.

doi:10.1002/9781119940791.ch6

Cited by 19 publications

(5 citation statements)

References 76 publications

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“…Yan et al [2015] summarized the integration of low-cost spaceborne data with flood modeling, focusing in particular on the use of freely available remote data sets, such as digital elevation models (DEMs), radar altimeter measurements, and SAR imagery. What clearly emerges from these comprehensive overviews is that the monitoring of water extent (A) and water surface elevation (h) appears quite trustworthy [see e.g., Alsdorf et al, 2007;Schumann et al, 2009Schumann et al, , 2012Birkinshaw et al, 2010;Bercher and Kosuth, 2013], whereas the monitoring of river flows from satellite is constrained by the lack of knowledge of the river bathymetry and flow velocity, which cannot be directly inferred from satellite instruments.…”

Section: Hydraulic Modeling With Remote Sensing Data: Experiences Andmentioning

confidence: 99%

On the use of SRTM and altimetry data for flood modeling in data‐sparse regions

Domeneghetti

2016

Water Resources Research

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The growing availability of remotely sensed data has fostered the implementation of hydraulic modeling in poorly gauged regions. However, these applications suffer the lack of knowledge of river bathymetry, which cannot be directly inferred from satellite instruments. This study explores the possibility to set up, calibrate, and validate a hydrodynamic model which geometry is based on global and freely available satellite data. First, the study tests two different procedures for inferring the river bathymetry under the water surface level. Second, focusing on a Po River stretch of ∼140 km (Northern Italy), the study further assesses the suitability of spaceborne topographic and remotely sensed altimetry data (i.e., ERS‐2 and ENVISAT) for implementing and calibrating hydrodynamic models. Referring to 90 m SRTM (Shuttle Radar Topography Mission) digital elevation model for the representation of the riverbed morphology, the work analyzes the performances of different 1‐D numerical models which cross sections are modified according to two approaches: (1) Channel Bankfull depth (CB) and (2) Slope‐Break (SB) approach. The calibration and validation processes are performed by referring to extended altimetry time series (∼16 years of data), while the accuracy and trustworthiness of 1‐D models are tested with reference to a quasi‐2‐D model based on detailed geometry data. Results show that both CB and SB approaches enhance the performance of SRTM‐based models. In particular, the SB approach is completely based on satelliteborne data and shows Nash‐Sutcliffe efficiency, MAE, and RMSE values similar to those obtained with the benchmark model.

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Section: Hydraulic Modeling With Remote Sensing Data: Experiences Andmentioning

confidence: 99%

On the use of SRTM and altimetry data for flood modeling in data‐sparse regions

Domeneghetti

2016

Water Resources Research

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“…SAR images, which originates from both the input images and the classification algorithm itself. As a matter of fact, classification overall accuracy of flooded areas varies considerably and only in rare cases exceeds 90% [30].…”

Section: Remote Sensing Flood Extent Observation For Calibration And/...mentioning

confidence: 99%

Improvement of Flood Extent Representation with Remote Sensing Data and Data Assimilation

Nguyen,

Ricci,

Fatras

et al. 2021

Preprint

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“…River reaches tend to be monitored and studied at much smaller scale than that typically acquired with wide-swath EO imagery, and therefore monitoring those reaches for situational awareness does actually require much higher spatial resolutions. Very high-resolution images (<5 m) also become a prerequisite when monitoring and modeling urban areas where most assets at risk of flooding are located and where city-block scale often dictates the ability to model or monitor flood inundation patterns accurately [31]. Here, airborne repeat overpasses are commonly the preferred choice, or indeed drones, but from space, constellations of multiple fine resolution SAR systems may present a possible solution or even alternative.…”

Section: High-resolution Maps At Any Timementioning

confidence: 99%

Assisting Flood Disaster Response with Earth Observation Data and Products: A Critical Assessment

et al. 2018

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Floods are among the top-ranking natural disasters in terms of annual cost in insured and uninsured losses. Since high-impact events often cover spatial scales that are beyond traditional regional monitoring operations, remote sensing, in particular from satellites, presents an attractive approach. Since the 1970s, there have been many studies in the scientific literature about mapping and monitoring of floods using data from various sensors onboard different satellites. The field has now matured and hence there is a general consensus among space agencies, numerous organizations, scientists, and end-users to strengthen the support that satellite missions can offer, particularly in assisting flood disaster response activities. This has stimulated more research in this area, and significant progress has been achieved in recent years in fostering our understanding of the ways in which remote sensing can support flood monitoring and assist emergency response activities. This paper reviews the products and services that currently exist to deliver actionable information about an ongoing flood disaster to emergency response operations. It also critically discusses requirements, challenges and perspectives for improving operational assistance during flood disaster using satellite remote sensing products.

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The Use of Radar Imagery in Riverine Flood Inundation Studies

Cited by 19 publications

References 76 publications

On the use of SRTM and altimetry data for flood modeling in data‐sparse regions

On the use of SRTM and altimetry data for flood modeling in data‐sparse regions

Improvement of Flood Extent Representation with Remote Sensing Data and Data Assimilation

Assisting Flood Disaster Response with Earth Observation Data and Products: A Critical Assessment

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