Global Flood Mapper: a novel Google Earth Engine application for rapid flood mapping using Sentinel-1 SAR

Tripathy, Pratyush; Malladi, Teja

doi:10.1007/s11069-022-05428-2

Cited by 37 publications

(13 citation statements)

References 33 publications

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“…Their collection, however, is often hampered by extreme weather conditions during storm surges at the Baltic Sea coast. Only recently, Tripathy and Malladi (2022) showed that field photographs from stationary cameras might be used for validation. Another challenge for the comparison with hydrodynamic model results is the generally short duration of ESL.…”

Section: Validation Of Coastal Flood Extentsmentioning

confidence: 99%

A new modelling framework for regional assessment of extreme sea levels and associated coastal flooding along the German Baltic Sea coast

Kiesel

Lorenz

König

et al. 2023

Preprint

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Abstract. Hydrodynamic models are increasingly being used in recent years to map coastal floodplains on local to continental scales. On regional scales, however, high computational costs and the need for high-resolution data limit their application. Additionally, model validation constitutes a major concern, as in-situ data are hardly available or limited in spatial coverage to small parts of the study region. Here we address these challenges by developing a modelling framework, which couples a hydrodynamic coastal inundation model covering the German Baltic Sea coast with a hydrodynamic coastal ocean model of the western Baltic Sea, to produce high resolution (50 m) regional scale flood maps for the entire German Baltic Sea coast. Using a LiDAR derived digital elevation model with 1 m horizontal resolution, we derive and validate the elevation of dikes and natural flood barriers such as dunes. Using this model setup, we simulate a storm surge event from January 2019, a surge with a return period of 200 years and two sea-level rise scenarios for the year 2100 (200-year event plus 1 m and 1.5 m). We validate the simulated flood extents by comparing them to inundation maps derived from Sentinel-1 SAR satellite imagery, acquired between 1.5 and 3.5 hours after the peak of the 2019 surge, covering a large part of the study region. Our results confirm that the German Baltic Sea coast is exposed to coastal flooding, with flood extent varying between 118 km2 and 1016 km2 for the 2019 storm surge and a 200-year return water level plus 1.5 m of sea-level rise, respectively. Hotspots of coastal flooding are mostly located in the federal state of Mecklenburg Western Pomerania. Our results emphasise the importance of current plans to update coastal protection schemes along the German Baltic Sea coast over the course of the 21st century in order to prevent large-scale damage in the future.

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Section: Validation Of Coastal Flood Extentsmentioning

confidence: 99%

A new modelling framework for regional assessment of extreme sea levels and associated coastal flooding along the German Baltic Sea coast

Kiesel

Lorenz

König

et al. 2023

Preprint

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“…Discharge estimates from satellite microwave radiometry were accessed via the River and Reservoir Watch Version 4.5 processor of the Dartmouth Flood Observatory (Brakenridge et al, 2022) and were downloaded for River Watch stations 25, 29, and 30. Since an array of GEE scripts has been published in the recent past (e.g., Inman and Lyons, 2020;Moharrami et al, 2021;Tripathy and Malladi, 2022), we adopted the script of United Nations Platform for Space-based Information for Disaster Management and Emergency Response (UN-SPIDER, 2019) and slightly adjusted it, i.e., by setting the difference threshold to 1.3, thereby minimising false positive and false negative detections. For further handling and analysis, the data was vectorised in the ArcGIS Pro environment.…”

Section: Mapping Of Areas Prone To Monsoon Floodingmentioning

confidence: 99%

Assessing land elevation in the Ayeyarwady Delta (Myanmar) and its relevance for studying sea level rise and delta flooding

Seeger

Minderhoud²,

Peffeköver³

et al. 2023

Preprint

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Abstract. With their low lying, flat topography, river deltas and coastal plains are extremely prone to relative sea level rise and other water related hazards. This calls for accurate elevation data for flood risk assessments, especially in the densely populated Southeast Asian deltas. However, in data-poor countries such as Myanmar, where high accuracy elevation data is not accessible, often only global satellite based digital elevation models (DEMs), suffering from low vertical accuracy and remote sensing artefacts, can be used by the public and scientific community. As the lack of accurate elevation data hampers the assessment of flood risk, studying available information on land elevation and its reliability is essential, particularly in the context of sea level rise impact. Here, we assess the performance of ten global DEMs in the Ayeyarwady Delta (Myanmar) against the new, local, so called AD-DEM, which was generated based on topographical map elevation data. To enable comparison, all DEMs were converted to a common vertical datum tied to local sea level. While both CoastalDEM v2.1 and FABDEM, perform comparably well, showing the highest correspondence in comparison with AD-DEM and low elevation spot heights, the FABDEM outperforms the CoastalDEM v2.1 by the absence of remote sensing artefacts. The AD-DEM provides a high accuracy, open source and freely available, independent elevation dataset suitable for evaluating land elevation data in the Ayeyarwady Delta and studying topography and flood risk at large scale, while small scale investigations may benefit from a FABDEM locally improved with data from the AD-DEM. Based on latest IPCC projections of sea level rise, the consequences of DEM selection for assessing the impact of sea level rise in the Ayeyarwady Delta are shown. We highlight the need for addressing particularly low lying populated areas within the most seaward districts with risk mitigation and adaptation strategies while also more inland delta population should be made aware to face a higher risk of flooding due to relative sea level rise in the next ~100 years.

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Section: Mapping Of Areas Prone To Monsoon Floodingmentioning

confidence: 99%

Assessing land elevation in the Ayeyarwady Delta (Myanmar) and its relevance for studying sea level rise and delta flooding

Seeger¹,

Minderhoud²,

Peffeköver³

et al. 2023

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. With their low lying, flat topography, river deltas and coastal plains are extremely prone to relative sea level rise and other water-related hazards. This calls for accurate elevation data for flood risk assessments, especially in the densely populated Southeast Asian deltas. However, in data-poor countries such as Myanmar, where high accuracy elevation data are not accessible, often only global satellite-based digital elevation models (DEMs), suffering from low vertical accuracy and remote sensing artefacts, can be used by the public and scientific community. As the lack of accurate elevation data hampers the assessment of flood risk, studying available information on land elevation and its reliability is essential, particularly in the context of sea level rise impact. Here, we assess the performance of 10 global DEMs in the Ayeyarwady Delta (Myanmar) against the new, local, so-called AD-DEM, which was generated based on topographical map elevation data. To enable comparison, all DEMs were converted to a common vertical datum tied to local sea level. While both CoastalDEM v2.1 (Kulp and Strauss, 2021) and FABDEM (Hawker et al., 2022) perform comparably well, showing the highest correspondence in comparison with AD-DEM and low-elevation spot heights, FABDEM outperforms CoastalDEM v2.1 by the absence of remote sensing artefacts. The AD-DEM provides a high-accuracy, open and freely available, and independent elevation dataset suitable for evaluating land elevation data in the Ayeyarwady Delta and studying topography and flood risk at large scale, while small-scale investigations may benefit from a FABDEM locally improved with data from the AD-DEM. Based on the latest Intergovernmental Panel on Climate Change (IPCC) projections of sea level rise, the consequences of DEM selection for assessing the impact of sea level rise in the Ayeyarwady Delta are shown. We highlight the need for addressing particularly low-lying populated areas within the most seaward districts with risk mitigation and adaptation strategies while also the more inland delta population should be made aware of facing a higher risk of flooding due to relative sea level rise in the next ∼ 100 years.

show abstract

Global Flood Mapper: a novel Google Earth Engine application for rapid flood mapping using Sentinel-1 SAR

Cited by 37 publications

References 33 publications

A new modelling framework for regional assessment of extreme sea levels and associated coastal flooding along the German Baltic Sea coast

A new modelling framework for regional assessment of extreme sea levels and associated coastal flooding along the German Baltic Sea coast

Assessing land elevation in the Ayeyarwady Delta (Myanmar) and its relevance for studying sea level rise and delta flooding

Assessing land elevation in the Ayeyarwady Delta (Myanmar) and its relevance for studying sea level rise and delta flooding

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