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89 results for “river flooding”
Spatiotemporal patterns and implications of changing seasonal flooding extents on wetland landscapes of a transboundary Chobe River Basin in Southern Africa
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Flood Hazard Maps using Google Earth Engine: Thrace and Thessaly River Basin Districts (Greece)
<p>This dataset contains three raster files with a spatial resolution of 10 m, derived by the Google Earth Engine:</p> <p> </p> <p>1) DynamicWorld_Floods_2015_2023.tif: Number of days flooded for the River Basin District of Thrace (Greece) starting from 2015 until 2023</p> <p>2) Thessaly_2015_August2023.tiff: Number of days flooded for the River Basin District of Thessaly (Greece) starting from 2015 until August 2023</p> <p>3) Thessaly_2015_now.tiff: Number of days flooded for the River Basin District of Thessaly (Greece) starting from 2015 until January 2024</p> <p> </p>
A tightly coupled river-ocean model for simulating combined flood due to storm surge and river flow in coastal-urban areas
<p>Coastal flooding, resulting from storm surges or extreme river flows, causes significant causalities and damage to properties in low-lying areas. The simultaneous occurrence of river flows and storm surges, termed combined/compound events, exacerbates the flood risk compared to independent occurrences. Combined flood events are simulated with the help of hydraulic and hydrodynamic models using a loosely or tightly coupled approach. In the loosely coupled approach, a hydrodynamic model simulates storm surges first, and a hydraulic model then simulates inland flood due to river overflow considering surge as the boundary condition at the river mouth/estuary. Conversely, the tightly coupled approach involves simultaneous simulation of both river flow and storm surge by coding the mathematical representation of river and ocean flow dynamics in the same numerical model. This allows the interaction between river and ocean flows to be simulated anywhere in the combined river-ocean computational domain, making it highly relevant for simulating combined floods. However, existing models based on this approach encounter numerical instability, especially in inland regions where topography variation is steep and highly uneven. Also, such combined models are highly limited for large scale applications. Therefore, this research focuses on developing a tightly coupled 2D finite volume river-ocean model called IROMS-C2D. The developed model intends to address the limitations of the previous models and provide a stable solution framework for the simulation of combined flooding resulting from the interaction of storm surges and river flows in coastal urban areas. Further, it enhances our understanding of flood risks in coastal areas, particularly in urban settings, and facilitates the formulation of effective measures for flood control and adaptation of coastal infrastructure.</p>
A tightly coupled river-ocean model for simulating combined flood due to storm surge and river flow in coastal-urban areas
<p>Coastal flooding, resulting from storm surges or extreme river flows, causes significant causalities and damage to properties in low-lying areas. The simultaneous occurrence of river flows and storm surges, termed combined/compound events, exacerbates the flood risk compared to independent occurrences. Combined flood events are simulated with the help of hydraulic and hydrodynamic models using a loosely or tightly coupled approach. In the loosely coupled approach, a hydrodynamic model simulates storm surges first, and a hydraulic model then simulates inland flood due to river overflow considering surge as the boundary condition at the river mouth/estuary. Conversely, the tightly coupled approach involves simultaneous simulation of both river flow and storm surge by coding the mathematical representation of river and ocean flow dynamics in the same numerical model. This allows the interaction between river and ocean flows to be simulated anywhere in the combined river-ocean computational domain, making it highly relevant for simulating combined floods. However, existing models based on this approach encounter numerical instability, especially in inland regions where topography variation is steep and highly uneven. Also, such combined models are highly limited for large scale applications. Therefore, this research focuses on developing a tightly coupled 2D finite volume river-ocean model called IROMS-C2D. The developed model intends to address the limitations of the previous models and provide a stable solution framework for the simulation of combined flooding resulting from the interaction of storm surges and river flows in coastal urban areas. Further, it enhances our understanding of flood risks in coastal areas, particularly in urban settings, and facilitates the formulation of effective measures for flood control and adaptation of coastal infrastructure.</p>
Terrain changes following the 2015 Sag River Flood
<p>Datasets produced for the publication "Disparate permafrost terrain changes after a large flood observed from space" by Zwieback et al.</p> <p> </p>
Data from: Quantifying flooding regime in floodplain forests to guide river restoration
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Data used to estimate the influence of habitat protection, habitat heterogeneity, and periodic flooding on species richness and abundance of waterbirds of the lower Paraná River, Argentina
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CTD dataset of the Po river (Italy) during one ebb and flood phase on 26 July 2017
<p>CTD dataset: temperature and salinity profiles acquired in the water<br> column with CTD probes (Ocean Seven 316Plus and 304, Idronaut srl, 20 Hz<br> and 8 Hz sampling rate, respectively), starting from the Po river mouth<br> and navigating upstream along the river talweg 10-18 km depending on the<br> river branch and in any case detecting a complete freshwater column.<br> Two sets of samplings were conducted on the 26th July 2017 during a spring<br> tide cycle, both starting at the slack tide and following the ebb and<br> flood tidal phase for almost two hours. The CTD casts location was decided<br> a priori based on the experience of previous campaigns, trying to<br> match the largest number of casts within an appropriate time interval to<br> detect the freshwater. During the ebb tide, when the salt wedge was<br> shorter, some additional casts where conducted to increase the<br> longitudinal resolution of the campaign. The CTD raw data were extracted<br> along the water column every 10 cm. Part of this dataset is used for<br> validation purposed in the paper Bellafiore et al., submitted to Journal<br> of Geophysical Research - Oceans, title "Saltwater intrusion in a<br> Mediterranean delta under a changing climate".</p>
Application of Different Building Representation Techniques in HEC-RAS 2-D for Urban Flood Modeling Using the Toce River Experimental Case
<p>The output of numerical simulation in HEC-RAS 2-D</p>
Fig. 3 in Effects of the interannual variations in the flood pulse mediated by hypoxia tolerance: the case of the fish assemblages in the upper Paraná River floodplain
Fig. 3. Interannual variation of the absolute and mean ± s.e. values of dissolved oxygen (a, c) and water transparency (b, d) in lakes (circle) and river channels (square) of the upper Paraná River floodplain, in years of short (2000 and 2001) and moderate (2002 and 2003) floods. Numbers 1-6 are codes of the sampling stations (see Fig. 1).
Figure S1 in Behaviour of two predator fishes Esox lucius Linnaeus, 1758 and Silurus glanis Linnaeus, 1758 during two successive floods in the French Aisne River
Figure S1. – Cumulative distance and number of recorded movements upstream and downstream versus waterflow between October 2020 and March 2021 for northern pikes.
Figure 7 in Behaviour of two predator fishes Esox lucius Linnaeus, 1758 and Silurus glanis Linnaeus, 1758 during two successive floods in the French Aisne River
Figure 7. – Habitats used during the two floods by male and female northern pikes. One bar represents one pike, and the number of detections during the flood is indicated on top of each bar.
Figure 2 in Behaviour of two predator fishes Esox lucius Linnaeus, 1758 and Silurus glanis Linnaeus, 1758 during two successive floods in the French Aisne River
Figure 2. – Evolution of the waterflow between December 2020 and April 2021 (Photos of the restored Pignicourt spawning area taken before, during and after the floods. The water level rose considerably, flooding the spawning area and the surrounding fields in winter, before dropping again considerably from the end of February. The flow indicated was measured in Berry-auBac).
Figure 6 in Behaviour of two predator fishes Esox lucius Linnaeus, 1758 and Silurus glanis Linnaeus, 1758 during two successive floods in the French Aisne River
Figure 6. – Kilometric points recorded (A) and fixes (B) of the pike no 111 between October 2020 and March 2021.
Supplementary Information for 'Catastrophic outburst floods along the middle Yarlung Tsangpo River: Responses to coupled fault and glacial activity on the southern Tibetan Plateau
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Figure 2 from: Casimiro ACR, Garcia DAZ, Vidotto-Magnoni AP, Britton JR, Agostinho AA, De Almeida FS, Orsi ML (2018) Escapes of non-native fish from flooded aquaculture facilities: the case of Paranapanema River, southern Brazil. Zoologia 35: 1-6. https://doi.org/10.3897/zoologia.35.e14638
Figure 2 Number of fish species escaped (native, non-native and hybrid) in the Lower and Middle Paranapanema River basin during the floods of 1996/1997 (Orsi and Agostinho 1999) and 2015/2016.
Figure 1 from: Casimiro ACR, Garcia DAZ, Vidotto-Magnoni AP, Britton JR, Agostinho AA, De Almeida FS, Orsi ML (2018) Escapes of non-native fish from flooded aquaculture facilities: the case of Paranapanema River, southern Brazil. Zoologia 35: 1-6. https://doi.org/10.3897/zoologia.35.e14638
Figure 1 Map of the Paranapanema River basin with the location of the evaluated areas (red dots: fish production, blue dots: 'fish and pay').
Fig. 2 in The Influence Of Spring Flood Water Levels On The Distribution And Numbers Of Terns (On The Example Of The Lower Desna River)
Fig. 2. The numbers of tern colonies on the Lower Desna in the years of high water (2013) and low water (2014) during the spring FLood.
Fig. 2 in Influence of environmental parameters on fish assemblage of a Neotropical river with a flood pulse regime, Central Brazil
Fig. 2. Ordination of the co-structure resulting from the co-inertia analysis between the fish assemblages and quantitative (a) and qualitative (b) environmental parameters (square arrow edge = stretch; circle = fish assemblage). Numbers represent the stretch sampled at low (L) or high (H) waters. Letter codes correspond to the main fish species that contributed to the costructure and are listed in Table 1. CD = channel depth; CW = channel width; DO = dissolved oxygen; ST = Secchi transparency; RS/S/L/R = river substrate/sand/leaves/roots; RVC/H = river vegetation cover/high; RVC/A/H = river vegetation cover absent/ high; RS/S/L = river substrate/sand/leaves; RVC/F = river vegetation cover/flooded. Boxes indicate scales.
Integrated machine learning and GIS-based bathtub models to assess the future flood risk in the Kapuas River Delta, Indonesia
<p>To use the data and the code, please cite the following article: </p> <p>Joko Sampurno, Randy Ardianto, Emmanuel Hanert; Integrated machine learning and GIS-based bathtub models to assess the future flood risk in the Kapuas River Delta, Indonesia. <em><em>Journal of Hydroinformatics</em></em> 2022; jh2022106. DOI: <a href="https://doi.org/10.2166/hydro.2022.106">https://doi.org/10.2166/hydro.2022.106</a></p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.