A Physics-Based Classification of Coastal Land-Margins based on Surface Flow

Santiago-Collazo, Félix L.; Bilskie, Matthew V.; Bacopoulos, Peter; Konsoer, Kory; Hagen, Scott C.

doi:10.1002/essoar.10509380.1

Cited by 2 publications

(7 citation statements)

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“…In locations where the maximum water levels from both flooding mechanisms coincide, the linear superposition of these individual flood levels overestimates the total water level, leading to larger errors versus considering them in the same simulation (Huang et al., 2021). Thus, the existence of a non‐linear relationship between the coastal and pluvial processes is evident in a compound inundation event (Bilskie & Hagen, 2018; Bilskie et al., 2021) and may even increase its non‐linearity levels in future scenarios as a result of climate change and anthropogenic effects (Santiago‐Collazo et al., 2021a, 2021b, 2021c, 2021d; K. Xu et al., 2023). Furthermore, the compounding effects of multiple flood mechanisms should be considered when developing compound flood models and their outcomes (e.g., flood maps), especially in low‐gradient coastal land‐margin (Zhang & Najafi, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Rainfall frequency quantiles were obtained from NOAA's Atlas 14 (Bonnin et al., 2006). Maximum water level profiles for each simulation under each flooding scenario are available at FigShare (Santiago‐Collazo et al., 2021b). Time to peak water level profiles for each simulation under each flooding scenario are available at FigShare (Santiago‐Collazo et al., 2021c).…”

Section: Data Availability Statementmentioning

confidence: 99%

“…Maximum water level profiles for each simulation under each flooding scenario are available at FigShare (Santiago‐Collazo et al., 2021b). Time to peak water level profiles for each simulation under each flooding scenario are available at FigShare (Santiago‐Collazo et al., 2021c). The different combinations of the environmental forcing parameters created using the Random Sampling Technique are available in FigShare (Santiago‐Collazo et al., 2021d).…”

Section: Data Availability Statementmentioning

confidence: 99%

“…Time to peak water level profiles for each simulation under each flooding scenario are available at FigShare (Santiago‐Collazo et al., 2021c). The different combinations of the environmental forcing parameters created using the Random Sampling Technique are available in FigShare (Santiago‐Collazo et al., 2021d). The compound inundation modeling framework developed in this research is available on Zenodo (Santiago‐Collazo et al., 2023).…”

Section: Data Availability Statementmentioning

confidence: 99%

See 3 more Smart Citations

Compound Inundation Modeling of a 1‐D Idealized Coastal Watershed Using a Reduced‐Physics Approach

Santiago‐Collazo,

Bilskie,

Bacopoulos

et al. 2024

Water Resources Research

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Low‐gradient coastal watersheds are susceptible to flooding caused by various flows such as rainfall‐runoff, astronomical tides, storm surges, and riverine flows. Compound flooding occurs when at least one coastal flood driver occurs simultaneously or in close succession with a pluvial and/or fluvial flood driver, such as during a tropical cyclone event. This study presents a one‐dimensional (1‐D), reduced‐order physics compound inundation model tested over an idealized coastal watershed transect under various forcing conditions (e.g., coastal and pluvial) that varied in magnitude, time, and space. This study aims to evaluate each flooding mechanism and the associated hydrodynamic responses by performing a sensitivity analysis and developing a non‐linear equation that could correlate the flood drivers with the severity of its flood. Compound inundation levels are affected by the magnitude and timing of each flooding mechanism. Results highlight the need to consider momentum exchange during a compound event and the importance of reduced‐physics approaches that can improve the interaction between flood drivers when paired with a moving coupling node approach. The desire is a more holistic compound inundation model that can be a critical tool for decision‐makers, stakeholders, and authorities who provide evacuation planning to save human lives and enhance resilience.

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Section: Discussionmentioning

confidence: 99%

Section: Data Availability Statementmentioning

confidence: 99%

Section: Data Availability Statementmentioning

confidence: 99%

Section: Data Availability Statementmentioning

confidence: 99%

See 2 more Smart Citations

Compound Inundation Modeling of a 1‐D Idealized Coastal Watershed Using a Reduced‐Physics Approach

Santiago‐Collazo,

Bilskie,

Bacopoulos

et al. 2024

Water Resources Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Rainfall frequency quantiles were obtained from NOAA's Atlas 14 (Bonnin et al, 2006). Maximum water level profiles for each simulation under each flooding scenario are available at FigShare (Santiago-Collazo et al, 2021b).Time to peak water levels profiles for each simulation under each flooding scenario, are available at FigShare (Santiago-Collazo et al, 2021c). The different combinations of the environmental forcing parameters created using the Random Sampling Technique are available at FigShare (Santiago-Collazo et al, 2021d).…”

Section: Open Researchmentioning

confidence: 99%

Pre-Print: Compound Inundation Modeling of a 1-D Idealized Coastal Watershed Using a Reduce-Physics Approach

Santiago-Collazo,

Bilskie,

Bacopoulos

et al. 2024

Preprint

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Low-gradient coastal watersheds are susceptible to flooding caused by various flows such as rainfall-runoff, astronomical tides, storm surges, and riverine flows. Compound flooding occurs when at least one coastal flood driver occurs simultaneously or in close succession with a pluvial and/or fluvial flood driver, such as during a tropical cyclone event. This study presents a one-dimensional (1-D), reduced-order physics compound inundation model tested over an idealized coastal watershed transect under various forcing conditions (e.g., storm surge, astronomical tides, and rainfall) that varied in magnitude, time, and space. This study aims to evaluate each flooding mechanism and the associated hydrodynamic responses to identify generalized coastal transition zones and enhance the production of flood maps for varying regions in a coastal watershed. Compound inundation levels are affected by the magnitude and timing of each flooding mechanism. The desire is a more holistic compound inundation model that can be a critical tool for decision-makers, stakeholders, and authorities who provide evacuation planning to save human lives and enhance resilience.

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A Physics-Based Classification of Coastal Land-Margins based on Surface Flow

Cited by 2 publications

References 0 publications

Compound Inundation Modeling of a 1‐D Idealized Coastal Watershed Using a Reduced‐Physics Approach

Compound Inundation Modeling of a 1‐D Idealized Coastal Watershed Using a Reduced‐Physics Approach

Pre-Print: Compound Inundation Modeling of a 1-D Idealized Coastal Watershed Using a Reduce-Physics Approach

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