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  • Evaluation of the Coastal Hazards System (CHS) Probabilistic Framework’s Storm Selection Methods Along the US West Coast

    Purpose: This Coastal and Hydraulics Engineering Technical Note (CHETN) evaluates the application of a traditional approach to screening and sampling historical storm events to quantify wave and water-level extremal distributions along the US West Coast, specifically focusing on Washington, Oregon, and California. High-fidelity simulations of storm events enable spatially explicit waves and water-level information in shallow nearshore regions, providing greater context than single-point tide gauges, wave buoys, or hindcast wave nodes in offshore waters. However, the computational expense associated with such simulations necessitates that a select number of events be chosen, ideally representative of the same extreme distribution created by the complete history of storms. Storm selection has previously been shown to be sensitive to the observational record length and the storm sample size but notably also region-specific characteristics such as the common (and uncommon) synoptic weather patterns and the alongshore variability of metocean conditions. The US Army Engineer Research and Development Center (ERDC), Coastal Hazards System (CHS), Stochastic Simulation Technique (SST), which was developed for the quantification of extratropical cyclone (XC) hazards based on extreme value analysis techniques, has previously been used to identify storms for high-fidelity simulations in several regions throughout the United States, including the Great Lakes (Nadal-Caraballo et al. 2012), US mid- and North Atlantic (Nadal-Caraballo et al. 2014; Nadal-Caraballo et al., “North Atlantic Coast,” 2015; Nadal-Caraballo et al., “Statistical Analysis,” 2015), and US South Atlantic (Yawn et al. 2024b) and Gulf of Mexico (Yawn et al. 2024a). However, coastal hazards for the US West Coast and the Pacific Basin are a consequence of multiple compounding oceanographic, meteorologic, and climatic phenomena contributing to waves and water levels with unique characteristics compared to tropical cyclone–dominated coasts. This effort defines total water levels as a combination of still-water levels (SWLs), incident wave runup, and infragravity runup as a proxy for the water elevation experienced at the shoreline during storm events. Dynamic total water levels during extreme events are then separated into individual contributions from oceanic and meteorological phenomena occurring at a variety of timescales, such as seasonal and monthly sea-level anomalies. Results from this analysis highlight future SST developments that will be required as part of a comprehensive CHS-Probabilistic Framework (CHS-PF) for the US West Coast and the Pacific Basin. Specifically, the methodology will need to (1) account for temporal clustering of storm sequences, (2) align with the parameters most relevant to US West Coast coastal storm risk management projects, and (3) develop an approach to create composite storm suites derived from extremes in multiple metocean parameters due to limited overlap between those storms that produce extremes in still water and those storms driving open-coast wave-induced extremes.
  • Coastal Hazards System–Gulf of Mexico (CHS-GoM)

    Abstract: The US Army Corps of Engineers completed the South Atlantic Coastal Study (SACS) to quantify storm surge and wave hazards, expanding the Coastal Hazards System (CHS) to the South Atlantic Division (SAD) domain. The goal of CHS-SACS was to quantify coastal storm hazards for present conditions and future mean sea level fluctuation scenarios to reduce flooding risk and increase resiliency in coastal environments. CHS-SACS was completed for three regions within the SAD domain, and this report focuses on the Gulf of Mexico (CHS-GoM). This study applied the CHS’ Probabilistic Framework with Joint Probability Method Augmented by Metamodeling Prediction (JPM-AMP) to perform a probabilistic coastal hazard analysis (PCHA) of tropical cyclone (TC) and extratropical cyclone (XC) responses, including new atmospheric and hydrodynamic numerical model simulations of synthetic TCs and historical XCs. This report documents the CHS probabilistic framework for the CHS-GoM region by executing the JPM-AMP, and comprising storm climate characterization, storm sampling, storm recurrence rate estimation, marginal distributions, correlation and dependence structures of TC atmospheric-forcing parameters, development of augmented storm suites, and assignment of discrete storm weights to the synthetic TCs. Coastal hazards were quantified for annual exceedance frequencies over the range of 10 yr−1 to 10−4 yr−1.
  • South Atlantic Coastal Study (SACS) Calibration and Validation of the Coastal Storm Modeling System (CSTORM) for Water Levels and Waves Part 3. Gulf of Mexico Domain

    Abstract: The US Army Corps of Engineers, South Atlantic Division, is currently engaged in the South Atlantic Coastal Study. One of the phases of this study is focused on conducting coastal storm modeling for the eastern and central Gulf of Mexico coastline of the United States. This technical report details the development of input for the Coastal Storm Modeling System (CSTORM) suite of models (WAVEWATCH III, ADCIRC, and STWAVE) for this project and presents the efforts made to calibrate model setups and validate results for eight historical tropical storm events impacting the study area.
  • South Atlantic Coastal Study (SACS) Calibration and Validation of the Coastal Storm Modeling System (CSTORM-MS) for Water Levels and Waves: Part 2. South Atlantic Coast Domain

    Abstract: The US Army Corps of Engineers, South Atlantic Division, is currently engaged in the South Atlantic Coastal Study. One of the phases of this study is focused on conducting coastal storm modeling for the southern Atlantic coastline of the United States. This technical report details the development of input for the Coastal Storm Modeling System suite of models (WAVEWATCH III, ADCIRC, and STWAVE) for this project and presents the efforts made to calibrate model setups and validate results for seven historical tropical storm events impacting the study area.
  • South Atlantic Coastal Study (SACS) Calibration and Validation of the Coastal Storm Modeling System (CSTORM-MS) for Water Levels and Waves: Part 1: Puerto Rico / US Virgin Island Domain

    Abstract: The US Army Corps of Engineers, South Atlantic Division, is currently engaged in the South Atlantic Coastal Study. One of the phases of this study is focused on conducting coastal storm modeling for the Puerto Rico and US Virgin Islands. This technical report details the development of input for the Coastal Storm Modeling System suite of models (WAVEWATCH III, ADCIRC, and STWAVE) for this project and presents the efforts made to calibrate model setups and validate results for four historical tropical storm events impacting the study area.
  • Estuarine Dams and Weirs: Global Analysis and Synthesis

    Abstract: Estuarine dams and weirs are constructed in estuaries for blocking the salt intrusion, securing freshwater, and stabilizing upstream water levels. While they can provide many social benefits, they also alter physical and sedimentary processes. To address this, we perform and extensive remote sensing and literature analysis. Remote sensing was conducted based on a global river database of 1531 rivers representing the largest rivers cumulatively draining 85 % of the landmass discharging into the global ocean. It was found that 9.7 % of global estuaries and deltas are currently affected by estuarine dams or weirs acting as the upstream limit of salt, tide, or storm surge intrusion. Most estuarine dams and weirs are located at x = 0–100 km inland from the mouth and their discharge intervals can be continuous. They are found most in river mouths which are wave-dominated followed by tide-dominated and then river-dominated. They can cause significant changes to the quantity and timing of freshwater discharge, tides, stratification, turbidity, sedimentation, oxygen conditions, phytoplankton blooms, and fish migration. We propose a conceptual model for physical and geomorphological change in mixed wave- and river-dominated and tide-dominated estuaries with estuarine dams.
  • Comprehensive Marsh Model Demonstration—Seven Mile Island Innovation Laboratory: Integrating Hydrodynamic, Morphodynamic, and Vegetation Modeling Components Using the Landlab Toolkit

    Abstract: Marshes are highly dynamic landscapes that are shaped through feedbacks between hydrodynamic, morphodynamic, and ecological processes. Future marsh resilience is therefore dependent on the interaction between these different drivers rather than any individual piece. Marshes face a variety of threats, both natural and anthropogenic, resulting in a need for restoration actions that increase survivability. Because many of these threats are unprecedented or acting at unprecedented rates, statistical models do not adequately represent future conditions and require process-based models to better capture the complex interactions between both physical and ecological processes. This report demonstrates how to develop a comprehensive marsh model that integrates tidal flow, morphodynamics, and vegetation growth using the Python based Landlab toolkit. The model was applied to a site within the Seven Mile Island Innovation Laboratory complex in coastal New Jersey.
  • Coastal Hazards System–South Atlantic (CHS-SA)

    Abstract: The US Army Corps of Engineers completed the South Atlantic Coastal Study (SACS) to quantify storm surge and wave hazards, allowing for the expansion of the Coastal Hazards System (CHS) to the South Atlantic Division (SAD) domain. The goal of CHS-SACS was to quantify storm hazards for present conditions and future sea level rise scenarios to reduce flooding risk and increase resiliency in coastal environments. CHS-SACS was completed for three regions within the SAD domain, and this report focuses on the South Atlantic (CHS-SA). This study applied the CHS’ Probabilistic Framework with Joint Probability Method Augmented by Metamodeling Prediction (JPM-AMP) to perform a probabilistic coastal hazard analysis (PCHA) of tropical cyclone (TC) and extratropical cyclone (XC) responses, leveraging new atmospheric and hydrodynamic numerical model simulations of synthetic TCs and historical XCs. This report documents the CHS probabilistic framework to perform the PCHA for CHS-SA by executing the JPM-AMP, including storm climate characterization, storm sampling, storm recurrence rate estimation, marginal distributions, correlation and dependence structures of TC atmospheric-forcing parameters, development of augmented storm suites, and assignment of discrete storm weights to the synthetic TCs. Coastal hazards were estimated for annual exceedance frequencies over the range of 10 yr−1 to 10−4 yr−1.
  • Tools and Technical Guidelines for Delineating the Extent of Tidal Waters: Proof of Concept

    Abstract: The delineation of shorelines in tidally influenced waters, as well as the inland extent of tidal influence of those waters, is often used to define the extent of federal and/or state jurisdictional boundaries, including the US Army Corps of Engineers’ (USACE) limits of jurisdiction under the Rivers and Harbors Act of 1899 (RHA) and Section 404 of the Clean Water Act. At present, USACE and other practitioners use a variety of field observations and desktop-based data sets, tools, and techniques to identify and delineate the lateral and longitudinal extent of USACE’s jurisdiction under the RHA for tidally influenced waters. Tidal waters, and thus federal jurisdiction under the RHA, “end where the rise and fall of the water surface can no longer be practically measured in a predictable rhythm.” However, the technical standards, definitions, and data to delineate tidal extent are also lacking. The uncertainty and ambiguity in what constitute tidal extent increases litigation risk and decreases repeatability and technical defensibility of USACE decisions. Nationally applicable technical guidance and rapid tools and techniques are needed to increase defensibility and consistency across all coastal USACE districts while also accelerating USACE Regulatory decision-making.
  • Scaling and Sensitivity Analysis of Machine Learning Regression on Periodic Functions

    Abstract: In this report we document the scalability and sensitivity of machine learning (ML) regression on a periodic, highly oscillating, and 𝐶∞ function. This work is motivated by the need to use ML regression on periodic problems such as tidal propagation. In this work, TensorFlow is used to investigate the machine scalability of a periodic function from one to three dimensions. Wall clock times for each dimension were calculated for a range of layers, neurons, and learning rates to further investigate the sensitivity of the ML regression to these parameters. Lastly, the stochastic gradient descent and Adam optimizers wall clock timings and sensitivities were compared.