29 Sep 2025

Introduction of the Pivox System—A Low-Cost, Rapidly Deployable Modular Lidar System

Abstract: Terrestrial light detection and ranging instruments can provide extremely valuable data for a multitude of applications in a wide variety of science and engineering fields. However, terrestrial lidar systems (TLS), are prohibitively expensive for many projects and require significant power and data resources to allow for the collection and transmittal of real-time lidar data, limiting their use in remote applications. To address the need for low-cost lidar data collection capabilities in remote environments, the US Army Corps of Engineers, Engineer Research Development Center, Cold Regions Research and Engineering Laboratory, and Geotechnical and Structures Laboratory (GSL) developed the Pivox System. The Pivox System integrates a Livox lidar sensor to a Raspberry Pi, allowing for real-time data collection, processing, and transmittal using a self-contained unit that also includes the power supply and communications equipment. We present data collected using the Pivox System in three diverse environments to measure changes in snow depth, the presence of lake ice, and erosion during a levee overtopping experiment.

26 Sep 2025

Rapid Assessment Tool for Channel Hydraulics and Floodplain Connectivity

Abstract: This technical note (TN) presents a rapid, nationally applicable web application for analyzing channel hydraulics and floodplain connectivity. The tool uses locally derived relative elevation models (REMs) that allow users to quantify hydraulics, like velocity and shear stress, and floodplain connectivity metrics, like inundation extent and storage volume (Haring and Dougherty, forthcoming).* By delineating cross sections directly from publicly available high-resolution terrain, the tool provides a rapid hydraulic assessment without requiring field survey data and also helps prioritize reaches for more detailed assessments.

25 Sep 2025

Effects of Suspended Sediment on Aquatic Organisms: A Literature Review and Database Effort

Abstract: The US Army Corps of Engineers (USACE) acknowledges that uncertainties and public perceptions regarding the effects of suspended sediment on aquatic organisms, particularly the concentration thresholds associated with harmful effects, present an ongoing challenge to its dredging mission. USACE is actively working to address these challenges through improved monitoring, research, and collaboration to support safer and more sustainable dredging practices. To help mitigate this uncertainty, 159 field- and laboratory-based studies describing the effects of sediment on aquatic organisms were reviewed and compiled in a database. No- and low-effect ecotoxicity data from this review were further analyzed to determine percentiles of effects data and species sensitivity distributions. The analysis indicated corals and freshwater crustaceans were most sensitive, followed by fish, while bivalves and marine crustaceans appeared to be the most tolerant of suspended sediment. This literature review provides a foundational framework for visualizing site-specific suspended sediment thresholds for effects concentrations associated with potential effects on aquatic species. It serves as a starting point for identifying critical data gaps for future research, layering in additional data, refining thresholds, and supporting more informed, site-specific decision-making moving forward.

25 Sep 2025

Considerations and Lessons Learned for Remote Sensing Data Acquisition of Understudied Wetland Vegetation Metrics

Purpose: Traditional field-based methods for monitoring wetland ecosystems are often limited by accessibility and cost, hindering comprehensive assessment of these vital habitats. These wetlands often present challenges for mapping and monitoring due to their size, location, and diverse vegetation types. Therefore, thorough planning and execution are essential for collecting reliable data for analysis and generating meaningful results. To overcome these challenges, we investigated how remote sensing data captured from uncrewed aerial systems (UAS), such as multispectral imagery and lidar, can be effectively used to develop and validate metrics for measuring wetland vegetation characteristics as an alternative to traditional field-based methods.

25 Sep 2025

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.

25 Sep 2025

Train Loadings on Bridges for US Army Installations: Guidance

Abstract: Railroad bridges on US Army installations must be rated to determine the safe load limits for the trains that utilize them. In addition to the standard Cooper E-80 loading required by the Federal Railroad Administration, specific locomotives and railcars that use the bridges must also be considered in the load ratings. For that purpose, this report documents the authors’ efforts to compile detailed dimensional- and axle-loading data on all Army-owned locomotives and railcars and then to develop a set of Army-specific rail equipment loadings for use in bridge load ratings. This report provides a detailed description of the data compilation and load development process that resulted in the Army-specific rail equipment loadings.

25 Sep 2025

From Analog to Digital: A Systematic Workflow for Converting Published Landform Maps to Georeferenced Datasets

Abstract: Reference datasets for geomorphological analysis often require the integration of multiple data sources, including legacy maps and published figures that exist only as scanned images or hard copies. This report documents a systematic five-step workflow for converting landform information from these analog sources into georeferenced point datasets suitable for digital analysis. The methodology encompasses acquiring and evaluating imagery, georeferencing using ground control points, manually digitizing landform polygons, converting to centroid points using a systematic grid-based approach, and assigning attributes with quality control measures. In a case study on East Asia, we demonstrate the workflow’s practical application by processing 15 published sources to generate over 2 million labeled landform points representing approximately 1,015 km² of land across China and Mongolia. The dataset encompasses seven landform classes commonly found in arid environments: active washes, alluvial fans, bedrock, pediments, playas, sand dunes, and sand sheets. Quality assessments using analyst confidence ratings revealed reliable classification performance for most landform types. This workflow provides researchers with an efficient approach to leveraging existing published landform data, thus expanding the spatial coverage and temporal depth of reference datasets that are available for geomorphological analysis and machine learning applications.

25 Sep 2025

Expansion of a Landform Reference Dataset in the Chihuahuan Desert for Dust Source Characterization Applications

Abstract: This report details the development of an extensive landform reference dataset for the Chihuahuan Desert region to support validation of a machine-learning-based landform classification model. Building upon previous work by Cook et al. (2022), we expanded both the quantity and spatial coverage of reference points to better represent the study domain’s geomorphic diversity. Analysts integrated information from published literature, government databases, and satellite imagery interpretation to create a dataset of 236,582 points across 12 landform classes, aligned to a 500 m resolution grid. The bedrock/pediment/plateau class was the dominant class (58%), followed by alluvial fans (21%), aeolian sands (11%), and aeolian dunes (5%). Approximately 85% of the reference points received high analyst confidence ratings, and ratings were especially high for classes with distinctive signatures, such as bedrock features, fine-grained lake deposits, urban/developed areas, water, and agricultural lands. Classification challenges consistently emerged in transitional zones between land-forms, areas with anthropogenic modifications, and complex landform assemblages where mapping resolution proved insufficient. The resulting dataset is a valuable resource for model validation and offers insights into arid region geomorphology. Additionally, it has the potential to support multiple applications, including dust hazard forecasting, terrain mobility assessment, soil property inference, and rangeland management.

24 Sep 2025

Assessing Heat Pump Technologies in Cold Regions for Army Installations

Abstract: Air-source heat pumps (ASHPs) can efficiently provide building heating and cooling. To assess the performance of ASHPs in cold regions for the Army Installation Technology Transition Program, we installed an air-to-air minisplit ASHP in Fairbanks, Alaska. This Interior Alaska location is exposed to extreme cold. The appropriate size of the unit was determined using building size and air temperatures from the location. Using monitoring equipment, the heating performance of the unit was analyzed using measurements collected over the winter months. Finally, the coefficient of performance (COP) was calculated, and a thermal camera was used to assess the heating performance qualitatively. The ASHP effectively heated the building during the project, and ASHPs are therefore recommended for use in cold regions.

24 Sep 2025

Simulating Environmental Conditions for a Severe Dust Storm in Southwest Asia Using the Weather Research and Forecasting Model: A Model Configuration Sensitivity Study

Abstract: Dust aerosols create hazardous air quality conditions that affect human health, visibility, and military operations. Numerical weather prediction models are important tools for predicting atmospheric dust by simulating dust emission, transport, and chemical evolution. We assessed the Weather Research and Forecasting (WRF) model’s ability to simulate the atmospheric conditions that drove a major dust event in Southwest Asia during July–August 2018. We evaluated five WRF configurations against satellite observations and Reanalysis Version 5 (ERA5) reanalysis data, focusing on the event’s synoptic evolution, storm progression, vertical structure, and surface wind fields. Results revealed substantial differences between configurations using Noah and Noah Multiparameterization (Noah-MP) land surface models (LSMs), with Noah providing a superior representation of meteorological conditions despite theoretical expectations of similar performance in arid environments. The best-performing configuration (Noah LSM, Mellor–Yamada–Nakanishi–Niino planetary boundary layer scheme, and spectral nudging) of the five considered accurately simulated the progression of a low-level jet streak and the associated surface winds responsible for dust mobilization throughout the event. This study supports the US Army Engineer Research and Development Center’s efforts to improve dust forecasting and establishes a foundation for evaluating dust emission parameterizations by isolating meteorological forcing errors from dust model physics.