11 Aug 2026

Adaptive Covariance Tapering for Large Datasets and Application to Spatial Interpolation of Storm Surge

Abstract: Covariance tapering is a popular approach for accommodating computational efficiency for the application of Gaussian process -based spatial interpolation for large datasets. This is accomplished by introducing sparsity in the GP covariance matrix, through the introduction of a compactly supported taper function. The support of the taper function around each spatial node is defined through the taper range variable. The latter is selected to achieve the desired degree of global sparsity in the covariance matrix, and defines the number of connected neighbors around each node. For problems with irregular nodal density, adaptive covariance tapering can be used to improve accuracy for the taper implementation. In this case, the taper ranges of the taper function have spatial variability, allowing uniform local sparsity to be achieved despite the data irregularities. The optimization of the taper ranges to accomplish this objective has a computational burden that is dependent on the size of the database, prohibiting its application to very large datasets. This paper formally considers the adoption of adaptive covariance tapers for such datasets. Though algorithmic developments are general, the problem is discussed for a specific application, the spatial interpolation of storm surge. For establishing computational efficiency in the optimization of the taper ranges we propose to utilize only a small subset of nodes, termed inducing points. An adaptive, iterative formulation is further developed to support the selection of the inducing points, shown to be critical for achieving the desired local sparsity for the remaining points. At each iteration, the taper range selection is performed using the current subset of inducing points, the achieved sparsity across all nodes is estimated, and then new inducing points are added within the sub-regions for which the discrepancy from the target local sparsity is the largest. The latter points are considered to have the highest expected utility as inducing points. Adding inducing points in close proximity is avoided through the inclusion of a clustering step. The implementation is demonstrated for interpolation of peak storm surge along the New Jersey coast, using two different domains, one with 64,379 nodes and one with 271,669 nodes.

11 Aug 2026

Geotechnical evaluation of overwash chenier beach deposits

Abstract: This study evaluates the long-term geotechnical effects of segmented breakwaters on shell-rich chenier deposits in southwestern Louisiana. The analysis integrates in-situ lightweight dynamic cone penetrometer (PANDA DCPT) profiles with multi-scale laboratory tests to compare a breakwater-protected (Hybrid) transect against an exposed (Natural) shoreline. Results indicate that the peak friction angle and maximum dilatancy of shell-hash occur at a site-specific optimal median grain size (D50) of approximately 1.0 mm, which geometrically coincides with the minimum void ratio. Shear strength inversely correlates with the coefficient of uniformity (Cu). In finer sediments with wider gradations (D50 < 1.0 mm), excess void fillers act as a lubricant that facilitates particle rearrangement and lowers shear strength. Conversely, in coarser mixtures (D50 > 1.0 mm), strength is reduced not by lubrication, but due to a loose, highly porous skeleton lacking sufficient contact points. At the field scale, PANDA DCPT profiles revealed distinct differences between the two sites. The protected transect retained a thinner, geotechnically weaker shell layer, ranging from 0.2 to 0.8 m thick. In contrast, the exposed shoreline maintained a robust thickness of 0.4 to 1.0 m. Although breakwaters effectively attenuate incoming wave energy, they disrupt natural winnowing processes and trap poorly sorted finer sediments. This hydrodynamic alteration shifts the soil fabric and introduces a coastal management trade-off. While breakwaters successfully limit short- term retreat, they produce a geotechnically weaker substrate that is susceptible to remobilization during future extreme wave events. Consequently, predictive morphodynamic models must dynamically refresh these coupled physical parameters to accurately assess the long-term resilience of engineered shorelines.

4 Aug 2026

Tacoma Harbor Navigation Improvement Project: Ship Simulation Study

Abstract: The US Army Engineer Research and Development Center (ERDC), in collaboration with the US Army Corps of Engineers Seattle District, conducted a preengineering design (PED)–level ship simulation study. The study aimed to validate and finalize proposed modifications to the federally maintained waterways in the Blair Waterway in the Port of Tacoma, Washington, and to assess the potential effects of such modifications on navigation. The proposed designs incorporate recommendations from feasibility-level ship simulations that ERDC con-ducted by in 2019. The proposed modifications to the Port of Tacoma include channel deepening, realignment, widening, and enlargement of the Blair Waterway turning basin. Additionally, the study evaluated the potential effects of a beneficial use of dredged material site, referred to as East Commencement Habitat Opportunity (ECHO), which would be located near the entrance to the Hylebos Waterway.

4 Aug 2026

Modeling Evaluation of a Bird Island Design in Hampton Roads, Virginia

Abstract: This report documents a numerical modeling investigation on the sediment transport and morphology changes surrounding designed marine habitats for seabirds in Hampton Roads, Virginia. It assembles and analyzes historical and newly collected wave and hydrodynamic data from the study area. The datasets are used to calibrate and validate coastal wave, hydrodynamic, and sediment transport models. It describes developments of model alternatives that correspond to different bird island designs. It evaluates current and sediment transport fields and seabed volume changes around the island under a representative normal year (2020) and under a storm simulation condition for a 50 yr return synthetic storm with corresponding sea level rise. Model simulations show weak current and sediment transport fields prior to the island construction. With alternative designs of the island, model results show significant changes in magnitudes and spatial distributions of current and sediment transport rate. Analysis of model bed volume changes demonstrates different erosion and deposition trends under the normal environment and under the storm simulation condition. The island design and configuration, including island orientation, island slopes, and material coverage, respond differently to the impact of physical forcing applied in the modeling.

3 Aug 2026

Mississippi Coastal Improvements Program (MsCIP) Barrier Island Restoration Long-Term Directional Wave, Circulation, and Water Level Analysis

Abstract: The Mississippi Sound barrier islands, including Ship Island, protect the Mississippi coast from wave-induced erosion during storms. Hurricane Camille (1969) breached Ship Island, and Hurricane Katrina (2005) widened the Camille Cut, increasing the mainland coast’s exposure to waves. To protect the coast, the US Army Corps of Engineers filled the cut with sand and restored Ship Island to its pre-Camille condition in 2020. To evaluate changes in wave height and potential changes in tides and residual currents, field observations via moorings and roving surveys were conducted pre- (2014–2016) and postrestoration (2022–2024). The tidal range and currents were found to be similar pre- and postrestoration, with slight decreases behind Ship Island. Behind and in front of Ship Is-land, the tidal ellipses shifted to being more shore parallel. The residual currents were primarily wind driven and showed little change in magnitude and direction around Ship Island during both summer and winter conditions. Waves passing through the Camille Cut were reduced, and the ratio of significant wave height behind to in front of Ship Island decreased from 0.40 to 0.25 following restoration. The Ship Island restoration reduced wave heights without significantly changing the tidal and residual currents in the Mississippi Sound.

27 Jul 2026

Size, Weight, Power, and Cost (SWaP-C) Evaluation for Global Navigation Satellite System (GNSS) Receivers and Antennas

Abstract: The purpose of this technical note is to provide a brief assessment of Global Navigation Satellite System (GNSS) receivers and antennas, focused specifically on vertical positioning. The work compares multiple GNSS receivers at various cost points and antennas of different types during static testing against a known benchmark. Results show that high-cost GNSS receivers do provide better results than low-cost GNSS receivers, but there are likely use cases that the low-cost receiver should provide adequate results. The geodetic-survey GNSS-type antenna provide better results than the helical-style antennas, but similarly, there are use cases that justify usage of the smaller and lighter helical-style antennas.

23 Jul 2026

Advances in Spatiotemporal Storm Surge Emulation: Database Imputation and Multi-Mode Latent Space Projection

Abstract: Surrogate models, also known as metamodels or emulators, have emerged as a valuable tool for storm surge hazard estimation. They are developed using numerical model results from a database of synthetic storms and have the potential to provide highly-accurate and efficient surge predictions for new storms beyond those in the database. Frequently, metamodels need to provide spatiotemporal predictions for the storm surge evolution over time, across a large geographic domain represented through appropriately chosen save points (SPs). This paper focuses on a specific type of metamodel, Gaussian process (GP) emulation, that has been proven versatile in past studies for this specific application. The development of the spatiotemporal metamodel in this setting may involve: (a) an imputation step to fill in missing data, associated with instances that nearshore and onshore SPs are dry; and (b) a dimensionality reduction step for projection to a latent space to improve the computational efficiency for the metamodel calibration and predictions. Advances are established across both these aspects by treating spatiotemporal storm surge responses as a three-dimensional tensor (across storm, time, and spatial domains), and by integrating techniques designed specifically for this tensor structure. For data imputation, low-rank tensor completion (LRTC) is adopted. LRTC leverages response correlations across all tensor dimensions, leading to improved imputation performance compared to established alternatives (for example, geospatial interpolation), by ensuring time-series smoothness between the imputed data and the available data in the original database. A combination of LRTC with imputation based on geospatial interpolation is also discussed. As a dimensionality reduction technique, higher-order singular value decomposition (HOSVD) is applied to separately reduce the spatial and temporal dimensions of the database, enabling the preservation of principal information associated with response correlation separately from each dimension within the latent space. Compared to the past use of principal component analysis for the augmented spatiotemporal dimensions, the separation promoted through HOSVD improves the latent output ability to capture complex surge variations, accommodating higher prediction accuracy for the metamodels developed based on this enhanced latent output structure. To improve efficiency in the metamodel calibration, different strategies are examined for grouping the HOSVD-based latent outputs. Beyond advancements associated with the metamodel development, the improvement in accuracy of the predicted surge time-series around its peak is also considered by introducing a correction step using predictions from a supplementary metamodel developed to strictly predict the peak-surge. The proposed advances are demonstrated using the Coastal Hazards System–North Atlantic (CHS-NA) database.

22 Jul 2026

Snow Model Complexity Evaluation for Real-Time Streamflow Forecasting

Abstract: The prediction and forecasting of flooding within snow-dominated watersheds is critical to understanding the risk to downstream infrastructure and population centers and providing the public accurate and timely flood warnings. The ability for flood and water resource management agencies like the U.S. Army Corps of Engineers (USACE) to accurately forecast flooding events has become increasingly important due to growing likelihood of rain-on-snow (ROS) flooding events in recent years. Three snow methods, in ascending order of complexity, i) Temperature Index (TI), ii) Hybrid (RTI), and iii) Energy Balance (EB), can be used to model snowpack and streamflow, however, to our knowledge a comprehensive comparison of all three snow methods using the same modeling framework has never been published. We used the USACE Hydrologic Engineering Center’s Hydrological Modeling System (HEC-HMS) with a pseudo-bootstrapping approach to determine the ability of each snow method to model three water years with significant ROS flooding events in the Truckee River watershed. Comparing four model validation statistics (KGE, NSE, RSR, and PBIAS) we found minimal differences between the snow methods in their ability to simulate snow water equivalent and streamflow at distinct locations within the Truckee River watershed. Our results also indicate that the calibration period is an important factor in the simulation skill of all three snow methods. Total model time (model set up, calibration, and computational time) for the Hybrid and Energy Balance methods was 5-7x and 8-10x longer than the TI method. Using our results, we provide recommended use cases for each snow method.

20 Jul 2026

Autonomous Dredging in USACE: Opportunities, Constraints, Available Technology, and Technology Gaps

Abstract: The US Army Corps of Engineers (USACE) dredges over 200 million cubic yards of sediment while maintaining federal waterways annually, at a cost exceeding one billion dollars. The dredging industry has identified autonomous dredging as a near-term possibility with long-term potential for implementation into standard USACE operations. USACE has the opportunity to identify where this emerging technology fits within its current dredging practice. In FY 2024, a team composed of project stakeholders from USACE districts and the US Engineer Research and Development Center (ERDC) experts across a range of dredging disciplines convened to distill their opinions into a special report outlining the opportunities and obstacles anticipated for USACE to implement autonomous dredging into its future dredging practice.

17 Jul 2026

Improved Beneficial Use of Dredged Material (BUDM) Laboratory Methods for Low-Stress Consolidation

Abstract: The purpose of this Dredging Operations and Environmental Research (DOER) Program technical note (TN) is to present the improved laboratory methods for low-stress consolidation to support the beneficial use of dredged material (BUDM). Despite the growing practice of BUDM to support coastal environments, significant knowledge gaps persist in the behavior (e.g., consolidation and erodibility) of hydraulically placed cohesive sediments. The consolidation of deposited sediment dictates the resultant surface elevation, a key design component controlling the hydroperiod and shear strength of wetland ecosystems, which are key indicators of the long-term health and stability of the wetland. The existing US Army Corps of Engineers (USACE) consolidation testing of ultrasoft materials utilizes settling columns that rely on highly time-consuming, experimental laboratory methods that are prone to human-induced errors. Therefore, an updated laboratory methodology that incorporates scientific advancements to manage consolidation and erodibility measurements is essential to providing practical testing with a higher degree of certainty for BUDM designers and ultimately helping to support USACE’s goal of reaching 70% BUDM.