CC Massarra, CJ Friedland, BD Marx, JC Dietrich (2020). “Multihazard Hurricane Fragility Model for Wood Structure Homes Considering Hazard Parameters and Building Attributes Interaction.” Frontiers in Built Environment, 6, 147, DOI: 10.3389/fbuil.2020.00147.
Then, to best utilize this new mesh, a multi-resolution approach is implemented to use meshes of varying resolution when and where it is required. It is hypothesized that by `switching’ from coarse- to fine-resolution meshes, with the resolution in the fine mesh concentrated only at specific coastal regions influenced by the storm at that point in time, both accuracy and computational gains can be achieved. As the storm approaches the coastline and the landfall location becomes more certain, the simulation will switch to a fine-resolution mesh that describes the coastal features in that region. Application of the approach during Hurricanes Matthew and Florence revealed the predictions to improve in both accuracy and efficiency, as compared to that from single simulations on coarse- and fine-resolution meshes, respectively.
Finally, the efficiency of the approach is further improved in the case of Hurricane Matthew, by using multiple smaller fine-resolution meshes instead of a single high-resolution mesh for the entire U.S. southeast coast. Simulations are performed utilizing predicted values of water levels, wind speeds, and wave heights, as triggers to switch from one mesh to another. Results indicate how to achieve an optimum balance between accuracy and efficiency, by using the above-mentioned triggers, and through a careful selection of the combination meshes to be used in the approach. This research has the potential to improve the storm surge forecasting process. These gains in efficiency are directly a savings in wall-clock time, which can translate into more time to invest in better models and/or more time for the stakeholders to consider the forecast guidance.
In late May 2019, the SWAN developers released a new version. Whenever this happens, the new version needs to be implemented into the coupled SWAN+ADCIRC, thus replacing an older version in the coupled model.
Starting with the upcoming release version 55 of ADCIRC, the coupled SWAN has been upgraded to its latest release version 41.31. It replaces the older version 41.10.
This upgrade is mostly a benefit to users of SWAN+ADCIRC. It has been almost 4 years since the last upgrade, and we had skipped a new SWAN version (41.20) during that time. Thus, this upgrade is adding features and bug fixes from two newer versions (41.20 and 41.31). SWAN has added several capabilities that will be advantageous to users of SWAN+ADCIRC.
However, a few of its changes will cause differences in the wave predictions, as described below. Users will likely need to re-calibrate their input settings for SWAN.
CC Massarra, CL Friedland, BD Marx, JC Dietrich (2020). “Binary Building Attribute Imputation, Evaluation, and Comparison Approaches for Hurricane Damage Data Sets.” Journal of Performance of Constructed Facilities, 34(3), 04020036, DOI: 10.1061/(ASCE)CF.1943-5509.0001433.
A stochastic climate emulator will first be developed to simulate 1000s of realizations of chronological climate patterns (forced by satellite and GCM products) to create future storm events coupled with sea level rise scenarios. A library of high fidelity, open source, hydrodynamic and morphodynamic simulations (ADCIRC+SWAN and XBeach) will then be used to develop a surrogate model to predict erosion and flooding for each future realization. Triggers like beach width, dune height, and community preferences will be used to identify how often communities will need to re-nourish, contingent on future climate and sea level rise scenario.
JC Dietrich, DL Anderson. “Sustainability of Barrier Island Protection Policies under Changing Climates.” U.S. Coastal Research Program, 2019 Academic Research Opportunities, 2019/10/18 to 2021/10/17, $226,624 (Dietrich: $226,624).
Thirty-nine combinations of global damage response variables were investigated. Of these models, six DS and one complete failure model met the evaluation criteria. Maximum significant wave height was the only significant hazard variable for the DS models, while maximum 3-s gust wind speed, maximum surge depth, and maximum water speed were found to be significant predictors for the complete failure model. Model prediction external accuracy ranged from 81% to 87%.
CC Massarra, CJ Friedland, BD Marx, JC Dietrich (2019). “Predictive Multi-Hazard Hurricane Data-Based Fragility Model for Residential Homes.” Coastal Engineering, 151, 10-21, DOI: 10.1016/j.coastaleng.2019.04.008.