BEWARE database: A Bayesian-based system to assess wave-driven flooding hazards on coral reef-lined coasts
Dates
Publication Date
2017-11-13
Time Period
2017
Citation
Pearson, S.G., Storlazzi, C.D., van Dongeren, A.R., Tissier, M.F.S., Reniers, A.J.H.M., 2017, BEWARE database: A Bayesian-based system to assess wave-driven flooding hazards on coral reef-lined coasts: U.S. Geological Survey data release, https://doi.org/10.5066/F7T43S20.
Summary
A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, ‘XBNH’) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef Environments” (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts. Building on previous work, BEWARE improves system understanding of reef hydrodynamics by examining the intrinsic reef and extrinsic forcing factors controlling runup and flooding on reef-lined coasts. The Bayesian estimator has high predictive skill for the XBNH model outputs that are flooding indicators, and was validated for a number of available field cases. BEWARE is a potentially powerful tool for use in early warning [...]
Summary
A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, ‘XBNH’) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef Environments” (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts. Building on previous work, BEWARE improves system understanding of reef hydrodynamics by examining the intrinsic reef and extrinsic forcing factors controlling runup and flooding on reef-lined coasts. The Bayesian estimator has high predictive skill for the XBNH model outputs that are flooding indicators, and was validated for a number of available field cases. BEWARE is a potentially powerful tool for use in early warning systems or risk assessment studies, and can be used to make projections about how wave-induced flooding on coral reef-lined coasts may change due to climate change.
These data accompany the following publication: Pearson, S.G., Storlazzi, C.D., van Dongeren, A.R., Tissier, M.F.S., and Reniers, A.J.H.M., 2017, A Bayesian-based system to assess wave-driven flooding hazards on coral reef-lined coasts: Journal of Geophysical Research—Oceans, https://doi.org/10.1002/2017JC013204.
Low-lying tropical coasts fronted by coral reefs are threatened by the effects of climate change, sea-level rise, and flooding caused by waves. However, the reefs on these coasts differ widely in their shape, size, and physical characteristics; the wave and water level conditions affecting these coastlines also vary in space and time. These factors make it difficult to predict flooding caused by waves along coral reef-lined coasts. We created a system (“BEWARE”) that estimates how different wave, water level, and reef combinations can lead to flooding. This tool tells us what information is needed to make good predictions of flooding. BEWARE can be used to make short-term predictions of flooding in early warning systems, or long-term predictions of how climate change will affect flooding caused by waves on coral reef-lined coasts. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, ‘XBNH’) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef Environments” (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts. Building on previous work, BEWARE improves system understanding of reef hydrodynamics by examining the intrinsic reef and extrinsic forcing factors controlling runup and flooding on reef-lined coasts. The Bayesian estimator has high predictive skill for the XBNH model outputs that are flooding indicators, and was validated for a number of available field cases. BEWARE is a potentially powerful tool for use in early warning systems or risk assessment studies, and can be used to make projections about how wave-induced flooding on coral reef-lined coasts may change due to climate change.
title
BEWARE_Database.nc
url
TBD
variables
name
ID
units
-
name
numComponents
units
-
name
eta0
units
Offshore water level [m]
name
H0
units
Offshore significant wave height [m]
name
H0L0
units
Offshore wave steepness, -
name
beta_ForeReef
units
Fore reef slope [-]
name
beta_Beach
units
Beach slope [-]
name
W_reef
units
Reef width [m]
name
Cf
units
Dimensionless friction coefficient [-]
name
etaMean_innerReefFlat
units
mean water level at the inner reef flat [m]
name
etaMean_meanReefFlat
units
mean water level averaged across the three reef flat observation points (reef crest, mid-reef, inner reef) [m]
name
Hm0
units
ignificant wave height at the inner reef flat calculated as Hm0 = 4*sqrt(m0) of the total spectrum there [m]
name
Hm0_VLF
units
significant wave height at the inner reef flat calculated as Hm0 = 4*sqrt(m0) of the VLF-filtered spectrum there [m]
name
Hm0_IG
units
significant wave height at the inner reef flat calculated as Hm0 = 4*sqrt(m0) of the IG-filtered spectrum there [m]
name
Hm0_LF
units
significant wave height at the inner reef flat calculated as Hm0 = 4*sqrt(m0) of the LF-filtered spectrum there [m]
name
Hm0_SS
units
significant wave height at the inner reef flat calculated as Hm0 = 4*sqrt(m0) of the SS-filtered spectrum there [m]
name
Tm1_0
units
mean spectral wave period (Tm-1,0) as calculated from the m-1, m0 moments of the total spectrum at the inner reef flat [s]
name
R2pIndex
units
runup (2% exceedance value) on beach slope [m]
name
etaComponents
units
1) - eta_offshore [m] offshore water level (should be same as WL variable) 2) - eta_setup [m] wave setup (mean water level minus offshore WL) 3) - eta_vlf2 [m] (mean of highest 2% of filtered VLF time series) 4) - eta_ig2 [m] (mean of highest 2% of filtered IG time series) 5) - eta_ss2 [m] (mean of highest 2% of filtered SS time series) 6) - eta_2p [m] (mean of highest 2% of original time series across all frequencies)
