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

Eight Recommendations to Enhance Biodiversity Outcomes of Nature-Based Solutions at Multiple Scales

Abstract: Ambitions to mainstream Nature-based Solutions (NbS) and achieve global implementation are hampered by the lack of transdisciplinary integration across disciplines and practice. Ecological knowledge, including an under-standing of how biodiversity can support, and be supported by, NbS design and implementation remains an under-studied component of the NbS concept despite its critical importance. Starting with a brief primer on the major roles that biodiversity plays in NbS performance, we present eight recommendations for enhancing biodiversity in NbS planning and implementation. This narrative expert synthesis draws from an interdisciplinary literature search and decades of experience across landscape ecology, environmental engineering, urban planning, wildlife management, ecological restoration, and conservation science. Recommendations emphasize the importance of considering the ecological mechanisms that support biodiversity (i.e., viable populations of coexisting species) and understanding the role of organismal life history, species interactions, habitat preferences, and metapopulation dynamics in determining NbS features’ ecological resilience and contributions to biodiversity enhancement (i.e., IUCN Global Standard Criterion 3). We also emphasize the importance of assessing biodiversity across spatial scales and dimensions (e.g., functional, phylogenetic) and monitoring and ecological management for anticipating and adapting to unexpected outcomes, invasive species, and ecosystem dis-services. This review is intended to increase connections between ecological science, conservation biology, and NbS implementation to support more biodiverse projects with more robust, resilient, and multifunctional performance and greater contributions to global conservation.

11 Aug 2026

Continental-scale mapping of forest tree density in North America using remote sensing and deep learning with uncertainty quantification

Abstract: Accurate, spatially consistent estimates of tree density remain elusive at continental scales, limiting our ability to assess forest structure, carbon stocks, and biodiversity. Existing global assessments have relied on simplified statistical models and sparse, heterogeneous ground data that are insufficient to capture nonlinear ecological interactions and spatial variability. To address these limitations, we integrated more than 600,000 harmonized ground-based forest inventory plots with satellite-derived vegetation indices, climate surfaces, soil properties, and topographic covariates to develop a deep learning framework for high-resolution mapping of tree density across North America. We evaluated four modeling approaches—generalized linear models, ridge regression, random forest, and a feedforward neural network. Among all models tested, the FFNN achieved the highest predictive accuracy, and was used to produce a wall-to-wall tree density map at 3 km resolution for the continent. We estimated that the total number of forest trees with diameter at breast height ≥ 10 cm across North America ranges from 339 to 514 billion, substantially lower than the widely cited estimate of 603 billion trees reported by Crowther et al. (2015). When smaller stems were included, totals more than doubled, reaching 738 billion to 1.12 trillion trees. We quantified uncertainty using Monte Carlo Dropout, generating pixel-level error estimates and confidence intervals. Spatial patterns reveal high tree densities in boreal and temperate forests, intermediate densities in mixed broadleaf regions, and relatively low densities in deserts, Mediterranean systems, and tundra. Compared to the global GLM-based benchmark by Crowther et al. (2015), our deep learning framework achieves markedly higher predictive accuracy, aligns more closely with national forest inventory statistics, and provides explicit uncertainty quantification, supporting applications in carbon accounting, biodiversity modeling, and ecosystem monitoring at scales through region specific calibration and validation.

11 Aug 2026

AFM Analysis of Rejuvenated Graphene Nanoplatelets for Nanoscale Reinforcement and Microwave-Induced Healing in Asphalt Binders

Abstract: Understanding nanoscale mechanisms governing reinforcement and healing in asphalt binders is essential for developing durable pavements. This study investigates graphene nanoplatelets (GnP) and rejuvenator-infused graphene (GnP-Rej) in a PG 67–22 binder using PF-QNM atomic force microscopy under unaged, PAV-aged, and microwave-treated conditions. GnP refined binder morphology, reducing surface roughness from ~2.1 nm to ~1.44 nm at 0.24 wt% and increasing stiffness through molecular confinement, with saturation beyond ~0.1 wt% due to agglomeration. Aging increased peri- and para-phase modulus by ~68% and ~61%, respectively, while GnP and GnP-Rej mitigated these effects. GnP-Rej exhibited dual-function behavior, enhancing local compliance and interfacial mobility. Microwave activation increased adhesion by up to ~51% without significant modulus change. The adhesion-based healing index confirmed consistent nanoscale recovery, with maximum healing observed at 0.24 wt% GnP-Rej. These results indicate that healing is governed by adhesion-controlled nanoscale recovery and provide mechanistic insight into the relationship between nanoscale behavior and improved asphalt performance.

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.

11 Aug 2026

Establishing Native Submersed Aquatic Vegetation at Times Beach, Buffalo, New York

Purpose: Establishing native submersed aquatic vegetation (SAV) in reservoirs, lakes, and ponds involves several considerations, including sources and types of transplant propagules, fluctuating water levels, and herbivory (Smart et al. 1998). Over the past 20 years, US Army Engineer Research and Development Center (ERDC) Environmental Lab researchers have developed methods for establishing native SAV that address these issues. While consistently and successfully applied in the southern United States (Dick et al. 2005), their applicability to northern waterbodies remains untested. This two-part demonstration study evaluated several SAV establishment techniques in a constructed wetland adjacent to Lake Erie, Buffalo, New York.

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

Environmental Data Intelligence Ecosystem (EDIE):Software Requirements Specification (SRS) v1.0

Abstract: The objective of this report is to evaluate the software requirements necessary to define the minimal viable product supporting the Environmental Data Intelligence Ecosystem (EDIE) software suite. The EDIE is designed to aid alignment of Defense State Memorandum of Agreement systems with Formerly Used Defense Sites systems and any future Environmental Division software packages into one common environment. Further the EDIE application will consolidate access and authentication, at the system level, to align with necessary Single Sign On requirements. The EDIE systems will serve as a hub for common communication and information dissemination among Environmental tools and systems.

3 Aug 2026

Customer Support Ticketing Analysis and Comparisons

Abstract: This report evaluates existing tools capable of satisfying the needs of our customer, whilst also identifying the possibilities of creating our own solution from scratch. As a vast majority of businesses use some form of information technology service management, many options already exist to solve this problem. We identify core values important to our customer and evaluate three different solutions and how they will support those values.