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Predicting peak inundation depths with a physics informed machine learning model.

• Authors : Lee CC; Urban Resilience.AI Lab, Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX, USA.; Huang L

• Source: Scientific reports [Sci Rep] 2024 Jun 27; Vol. 14 (1), pp. 14826. Date of Electronic Publication: 2024 Jun 27.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited

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High spatiotemporal-resolution mapping for a seasonal erosion flooding inundation using time-series Landsat and MODIS images.

• Authors : Zhu J; College of Agriculture, Yanbian University, Jilin, China.; Jin Y

• Source: Scientific reports [Sci Rep] 2024 Feb 20; Vol. 14 (1), pp. 4203. Date of Electronic Publication: 2024 Feb 20.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited

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Assessing impending hazards from summit eruptions: the new probabilistic map for lava flow inundation at Mt. Etna.

• Authors : Zuccarello F; Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, 95125, Catania, Italy. .; Bilotta G

• Source: Scientific reports [Sci Rep] 2023 Nov 09; Vol. 13 (1), pp. 19543. Date of Electronic Publication: 2023 Nov 09.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited

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Brief floodplain inundation provides growth and survival benefits to a young-of-year fish in an intermittent river threatened by water development.

• Authors : Pratt OP; School of Agriculture and Environment, The University of Western Australia, Perth, 6009, Australia. .; Beesley LS

Subjects: Rivers* ; Ecosystem*; Animals

• Source: Scientific reports [Sci Rep] 2023 Oct 18; Vol. 13 (1), pp. 17725. Date of Electronic Publication: 2023 Oct 18.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited

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Modeling rainfall-induced 2D inundation simulation based on the ANN-derived models with precipitation and water-level measurements at roadside IoT sensors.

• Authors : Wu SJ; Department of Civil and Disaster Prevention Engineering, National United University, Miaoli, 360302, Taiwan. .

• Source: Scientific reports [Sci Rep] 2023 Oct 17; Vol. 13 (1), pp. 17664. Date of Electronic Publication: 2023 Oct 17.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited

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Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine.

• Authors : Goyal MK; Department of Civil Engineering, Indian Institute of Technology, Indore, India. .; Rakkasagi S

• Source: Scientific reports [Sci Rep] 2023 Oct 13; Vol. 13 (1), pp. 17324. Date of Electronic Publication: 2023 Oct 13.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited

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Discriminating the occurrence of inundation in tsunami early warning with one-dimensional convolutional neural networks.

• Authors : Núñez J; Departamento de Obras Civiles, Universidad Técnica Federico Santa María, Valparaíso, 2390123, Chile.; Catalán PA

Subjects: Emergencies* ; Tsunamis*; Environment

• Source: Scientific reports [Sci Rep] 2022 Jun 20; Vol. 12 (1), pp. 10321. Date of Electronic Publication: 2022 Jun 20.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited

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A sensitivity study of rising compound coastal inundation over large flood plains in a changing climate.

• Authors : Peter Sheng Y; Coastal and Oceanographic Engineering Program, University of Florida, Gainesville, FL, 32611-6580, USA. .; Paramygin VA

Subjects: Cyclonic Storms* ; Floods*; Climate

• Source: Scientific reports [Sci Rep] 2022 Mar 01; Vol. 12 (1), pp. 3403. Date of Electronic Publication: 2022 Mar 01.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited

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Quantifying the inundation impacts of earthquake-induced surface elevation change by hydrological and hydraulic modeling.

• Authors : Ouyang M; Department of Environment Systems, The University of Tokyo, Kashiwa, 277-8563, Japan. .; Ito Y

• Source: Scientific reports [Sci Rep] 2021 Feb 19; Vol. 11 (1), pp. 4269. Date of Electronic Publication: 2021 Feb 19.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited

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Palaeo-tsunami inundation distances deduced from roundness of gravel particles in tsunami deposits

• Authors : Ishimura, Daisuke; Yamada, Keitaro

Subjects: 0301 basic medicine; Multidisciplinary; lcsh:R

• Source: Scientific Reports, Vol 9, Iss 1, Pp 1-8 (2019)Scientific Reports

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