Improving the Accuracy of a Real-Time ADCIRC Storm Surge Downscaling Model
Creator:
Rucker, Carter
Date of publication:
March 30, 2020
Abstract Tesim:
During major storm events such as hurricanes, emergency managers rely on fast and accurate forecasting models to make important decisions concerning public safety. These models can be computationally costly and cannot quickly make predictions at the highest geospatial resolution. However, model output can be post-processed to mimic highr-esolution results with minimal additional computational cost. This research proposes methods for improvement in the accuracy of downscaling (enhancing the resolution of) a real-time storm surge forecasting model. Such improvements to downscaling methods include 1) expansion in its spatial applicability, 2) adding physics using water surface slopes, and 3) adding physics using friction losses across the ground surface.
This research builds upon a process that uses maximum water elevation output from the Advanced Circulation (ADCIRC) model and downscales these results to a finer resolution by extrapolating the water levels to small-scale topography. This downscaling process is referred to as the static method. The method was originally designed for use in North Carolina (NC), where results from an ADCIRC model designed specifically for NC were downscaled to a set of NC topographical data. By joining the static method with an ADCIRC output visualization tool, the downscaling process is now able to run faster with the same level of accuracy and can run on any ADCIRC model with downscaling data from any geographical region or given resolution. This process is used to provide extra guidance to emergency managers and decision makers during hurricanes.
The downscaling process is also improved by adding physics using the slopes method and the head loss method. The slopes method incorporates the slopes of the water levels produced by ADCIRC, rather than only the value of the water level. By interpolating ADCIRC output water elevation points into a smooth surface, slopes of this surface can be used to influence the elevations of downscaled water levels. The head loss method adds friction loss due to variations in the ground surface based on land cover types and friction associated with each type. As water travels over any surface, head loss, or a loss in energy, occurs at different rates depending on the surface roughness. This rudimentary hydrologic principle is applied to increase the accuracy of the downscaling process at minimal cost. The downscaling methods are applied for results from an ADCIRC simulation used in real-time forecasting, and then compared with results from an ADCIRC simulation with 10 times more resolution in Carteret County, NC. The static method tends to over-estimate the flood extents, and the slopes method is similar. However, the head loss method generates a downscaled flooding extent that is a close match to the predictions from the higher-resolution, full-physics model.
By improving the accuracy of downscaling methods at minimal computational cost and expanding the applicability of these downscaling methods, these methods can be used by emergency managers to provide a better estimation of flooding extents while simulating storm events.
Affiliation Label Tesim:
Coastal Resilience Center of Excellence
Conference Name:
ADCIRC Users Group Meeting 2020
Type:
http://purl.org/dc/dcmitype/Text
DOI:
https://doi.org/10.17615/wb7z-v398
Keyword:
Manning's equation, downscaling, GRASS, ADCIRC, overland flooding, GIS, land cover, and Python
Global to Channel Scale Water Level Forecasting and Analysis
Creator:
Ling, Guoming, Abdolali, Ali, Moghimi, Saeed, Pringle, Wiliam, Vinogradov, Sergey, van der Westhuysen, Andre, Wiraset, Dam, Westerink, Joannes, Blakely, Coleman, Massey, Chris, Woods, Brendan, Contreras, Maria Teresa, Tritinger, Amanda, Cobell, Zach, Owensby, Margret, Choi, Mindo, and Myers, Edward
Date of publication:
March 30, 2020
Abstract Tesim:
A multi-step process to creating better grids and to get to a global tidal model for ADCIRC
1. Process of merging shoreline databases together for better mesh development.
2. High resolution optimal meshes for the US East and Gulf of Mexico coasts
3. Hindcast of Hurricane Irma using ADCIRC + SWAN (to learn about how system performs)
4. Development of 30m and 120m meshes for the US East and Gulf Coasts
5. ADCIRC global tidal model development
Conference Name:
ADCIRC Users Group Meeting 2020
Type:
http://purl.org/dc/dcmitype/Text
DOI:
https://doi.org/10.17615/t82n-0h63
Keyword:
ADCIRC
Language Label:
English
ORCID:
Other Affiliation:
University of Notre Dame, NCEP NWS NOAA, CSDL NOS NOAA, University of Notre Dame and Argonne National Laboratory, ERDC USACE, and Water Institute of the Gulf
Person:
Ling, Guoming, Abdolali, Ali, Moghimi, Saeed, Pringle, Wiliam, Vinogradov, Sergey, van der Westhuysen, Andre, Wiraset, Dam, Westerink, Joannes, Blakely, Coleman, Massey, Chris, Woods, Brendan, Contreras, Maria Teresa, Tritinger, Amanda, Cobell, Zach, Owensby, Margret, Choi, Mindo, and Myers, Edward
Simulation of Idealized Compound Flood Events in Low-Gradients Coastal Watersheds
Creator:
Santiago-Collazo, Felix L.
Date of publication:
March 30, 2020
Abstract Tesim:
Low-gradient coastal watersheds can be susceptible to flooding from numerous mechanisms such as rainfall, tides, and storm surge. Compound flooding occurs when at least two of these mechanisms happen simultaneously or in close succession. In order to assess compound flooding, different inundation models, observed data, and/or a combination of these are linked through varying techniques. Here we present a one-dimensional (1-D) compound inundation model, which is based on the shallow water equations, capable of simulating the variations of the free water surface at the ocean domain (i.e. storm surge modeling), the rainfall-runoff at the upland region of the watershed (i.e. hydrology/hydraulics modeling), and compound flooding within the transition zone. To test this compound inundation model, a 1-D transect, representing a low-gradient coastal watershed, was developed and applied with numerous rainfall-runoff/tides/storm surge combinations. Future research will focus on simulating a “more-realistic” compound flood event. One of the main goals is to evaluate each flooding mechanism, separately and their combination, to aid in the identification of transition zones and enhance the production of compound flood maps for different regions of the coastal watershed. The relationship between rainfall-runoff, tides, and storm surge is nonlinear; therefore, adding the individual effects of these flooding mechanisms may overestimate the compound flood level at the transition zone. The desire is a more holistic compound inundation model that can be a critical tool for decision-makers, stakeholders and authorities by providing aid in disaster and evacuation planning to potentially save human lives and decrease property damage.
Conference Name:
ADCIRC Users Group Meeting 2020
Type:
http://purl.org/dc/dcmitype/Text
DOI:
https://doi.org/10.17615/h76m-4k15
Keyword:
shallow water equations, finite element, coastal watershed, compound flooding, ADCIRC, and numerical modeling
Modeling the Storm Surge and Compound Flooding from Hurricane Florence Using ADCIRC
Creator:
Ratcliff, John
Date of publication:
March 30, 2020
Abstract Tesim:
How to best model a storm with slow forward speed and record landfall using ADCIRC. Some new opportunities presented with this case for study with ADCIRC are:
• Landfalling East Coast storm with perpendicular approach for ADCIRC skill assessment
• Opportunity to identify/model compound flooding
• Contribute to ‘national’ parameter set for ADCIRC users
• Normalize forecast meteorological product (GAHM) with reanalysis products (OWI)
• Examine datum adjustment (MSL to NAVD88)