9 Jan 2025

National Ordinary High Water Mark Field Delineation Manual for Rivers and Streams: Final Version

Abstract: The ordinary high water mark (OHWM) defines the lateral extent of non-tidal aquatic features in the absence of adjacent wetlands in the United States. The federal regulatory definition of the OHWM, 33 CFR 328.3(c)(4), states the OHWM is “that line on the shore established by the fluctuations of water and indicated by physical characteristics such as [a] clear, natural line impressed on the bank, shelving, changes in the character of soil, destruction of terrestrial vegetation, the presence of litter and debris, or other appropriate means that consider the characteristics of the surrounding areas.” This is the first manual to present a methodology for nationwide identification and delineation of the OHWM. A two-page data sheet and field procedure outline a weight-of-evidence (WOE) methodology to organize and evaluate observations at stream sites. This manual presents a consistent, science-based method for delineating the OHWM in streams. It also describes regional differences and challenges in identifying the OHWM at sites disturbed by human-induced or natural changes and illustrates how to use remote data to structure field inquiries and interpret field evidence using the principles of fluvial science. The manual demonstrates that, in many landscape settings, the OHWM may be located near the bankfull elevation.

2 Jan 2025

Assessing the Validity and Accuracy of Wetland Indicator Status Ratings for Eight Species in Alaska Subregions

Abstract: Preexisting ecological information and plant species occurrence data were used to determine the accuracy and validity of the present regional and subregional wetland indicator status ratings for eight species: Andromeda polifolia, Arctous rubra, Carex canescens, Rhododendron tomentosum, Rubus arcticus, Salix arctica, Salix pulchra, and Viola palustris. Technical documentation was developed to either (1) support the current National Wetland Plant List (NWPL) subregion boundaries and wetland indicator status ratings for the NWPL Alaska Region or (2) support a proposed change to the subregions or wetland indicator status ratings for the NWPL Alaska Region, for inclusion into the next NWPL update. The project developed repeatable, quantitative methods for assignment of wetland indicator status rating. Analyses included multiple correspondence analysis (MCA), analysis of similarities (ANOSIM), nonmetric multidimensional scaling (NMDS), and principal component analysis (PCA). Prevalence index (PI) was used as a numeric approximation of wetland status for comparing observations across subregions. A pilot study on S. pulchra data evaluated regional assignments by machine learning and assessed the feasibility of correlation network analysis and Louvain clustering for wetland indicator status rating assignment as dictated by co-occurring species. The methods developed for this Alaska-specific study may be applied to any future regional or subregional updates to the NWPL.

18 Dec 2024

The Effects of Physical Form, Moisture, Humic Acids, and Mixtures on the Photolysis of Insensitive Munitions Compounds

Abstract: The explosive formulations IMX-101 and IMX-104 are replacing conventional explosives in munitions, making them safer to transport and handle. However, munitions manufacturing and military training can lead to the environmental release of constituent insensitive munitions compounds. These IMCs absorb ultraviolet light and transform photochemically into products with potentially greater toxicity. This study explores the effects of physical form, moisture, humic acids, and compound mixtures on the photolysis of solid and dissolved IMCs under UV-A and UV-B light. Irradiation of dry vs. moist solid IMC crystals yielded few measured products, and while photolysis rates were not significantly different, they were orders of magnitude slower than for aqueous IMCs. There was no significant difference in photolysis rates for aqueous IMCs irradiated with 0, 0.4, and 4 mg L-1 humic acids, but 40 and 400 mg L-1 humic acids inhibited NTO and enhanced NQ photolysis. Although organic and inorganic products were detected in the mixtures, an average of 15–35 % of the theoretical starting IMC masses was not accounted for. Overall, aqueous IMCs transformed 4–48 times faster than the solid IMCs, but the environmentally-relevant conditions tested were found to play a minor role in IMC photolysis.

19 Nov 2024

Finite Element Modeling of Aquatic Electrical Barriers—Voltage and Current Distributions: Brandon Road Lock and Dam Interbasin Project—Electric Fish Deterrent Design Recommendations

Abstract: Invasive carp (black, grass, silver, and bighead) are native to Asia and were imported into the US during the 1970s and 1980s to help fish farmers manage water quality and vegetation. Unfortunately, these carp became established in the Mississippi River and have led to a decline in native fish species. To prevent their spread from the Mississippi River Basin to the Great Lakes Basin via the Chicago Area Waterway System (CAWS), the US Army Corps of Engineers (USACE) operates a series of four electric dispersal barriers near Romeoville, Illinois in the Chicago Sanitary and Ship Canal (CSSC). To supplement these barriers, USACE was authorized to construct a series of aquatic nuisance species deterrents, including an electric deterrent, approximately 11 river miles downstream at Brandon Road Lock and Dam (BR). Throughout the BR electric deterrent design process, the dispersal barriers at the CSSC have served as the prototype systems used in the development of the concepts. Additionally, USACE has worked with the US Army Cold Regions Research Engineering Laboratory (CRREL) to develop a finite element numerical model (COMSOL) that predicts voltage and electric current distributions for a given electrode and waterway geometry.

18 Oct 2024

Automated Change Detection in Ground-Penetrating Radar using Machine Learning in R

Abstract: Ground-penetrating radar (GPR) is a useful technique for subsurface change detection but is limited by the need for a subject matter expert to process and interpret coincident profiles. Use of a machine learning model can automate this process to reduce the need for subject matter expert processing and interpretation. Several machine learning models were investigated for the purpose of comparing coincident GPR profiles. Based on our literature review, a Siamese Twin model using a twinned convolutional network was identified as the optimum choice. Two neural networks were tested for the internal twinned model, ResNet50 and MobileNetV2, with the former historically having higher accuracy and the latter historically having faster processing time. When trained and tested on experimentally obtained GPR profiles with synthetically added changes, ResNet50 had a higher accuracy. Thanks to this higher accuracy, less computational processing was needed, leading to ResNet50 needing only 107 s to make a prediction compared to MobileNetV2 needing 223 s. Results imply that twinned models with higher historical accuracies should be investigated further. It is also recommended to test Siamese Twin models further with experimentally produced changes to verify the changed detection model’s accuracy is not merely specific to synthetically produced changes.

26 Sep 2024

A Geospatial Model for Identifying Stream Infrastructure Locations

Abstract: Management of hydraulic infrastructure for flood control, hydropower, navigation, and water supply is a critical component of the Army Dams and Transportation Infrastructure Program (ADTIP). This project provides a tool to locate stream infrastructure using a one-dimensional approach supplemented with geospatial filtering that only needs digital elevation model (DEM) files as primary input. The regions in and around Forts Liberty, Sill, and Cavazos were selected as study areas, and stream networks with corresponding stream elevation profiles were created and searched for elevation changes that met vertical threshold and search window criteria. Recall, Fβ, and a ratio of under to overprediction were used to evaluate performance. The search algorithm generally overpredicts the number of stream infrastructure locations and especially so for large search windows (20 or 25 cells) and small vertical threshold values (5 or 10 m). Overall, it was found that midrange vertical threshold values (2 or 2.5 m with long search windows (20 or 25 cells) with the land cover classification (LCC) check applied yielded results that minimized false negatives and overpredictions. The significance of this tool is that it may reduce costly field investigations, or at least aid in the prioritization of site visits for hydraulic infrastructure managers.

25 Sep 2024

Comparing the Thermal Infrared Signatures of Shallow Buried Objects and Disturbed Soil

Abstract: The alteration of physical and thermal properties of native soil during object burial produces a signature that can be detected using thermal infrared (IR) imagery. This study explores the thermal signature of disturbed soil compared to buried objects of different compositions (e.g., metal and plastic) buried 5 cm below ground surface (bgs) to better understand the mechanisms by which soil disturbance can impact the performance of aided target detection and recognition (AiTD/R). IR imagery recorded every five minutes were coupled with meteorological data recorded on 15-minute intervals from 1 July to 31 October 2022 to compare the diurnal and long-term fluctuations in raw radiance within a 25 × 25 pixel area of interest (AOI) above each target. This study examined the diurnal pattern of the thermal signature under several varying environmental conditions. Results showed that surface effects from soil disturbance increased the raw radiance of the AOI, strengthening the contrast between the object and background soil for several weeks after object burial. Enhancement of the thermal signature may lead to expanded windows of object visibility. Target age was identified as an important element in the development of training data sets for machine learning (ML) classification algorithms.

25 Sep 2024

Thermography Conversion for Optimal Noise Reduction

Abstract: Computer vision applications in terms of raw thermal radiance are limited by byte size. Normalizing the raw imagery reduces functional complexities that could otherwise aide a computer processing algorithm. This work explores a method to normalize 16-bit signed integer (I16) into unsigned 8-bit (U8) while maintaining the integrity of the correlation coefficients between the raw data sets and the environmental parameters that affects thermal anomaly detectability.

24 Sep 2024

Validation of Sample Extraction and Analysis Techniques for Simultaneous Determination of Legacy and Insensitive Munitions (IM) Constituents

Abstract: Currently, no standardized method exists for the analysis of insensitive munitions (IM) in environmental matrices such as water, soils, and tis-sues. However, standardized methods, such as United States Environmental Protection Agency (EPA) 8330B, exist for legacy munitions for water and soil matrices. The lack of standardized methods for IM analysis leads researchers to use a wide variety of incomplete and overlapping analytical methodologies. The overall project’s first phase, Strategic Environmental Research and Development Program (SERDP) Environmental Restoration (ER)–2722, was to develop and optimize methods to address these methodological gaps by creating analytical methods for simultaneous analysis of IM and legacy munitions in water, soil, and tissue matrices. The main objective of the current project phase, Environmental Security Technology Certification Program (ESTCP) ER19-5078, is to build upon the previous work in phase one and to focus on the validation of the newly developed methods. Synergizing with the main objective of the overall project, the methods were validated and submitted to the EPA for inclusion as a possible addendum to EPA 8330B.

19 Sep 2024

The Arctic Deployable Resilient Installation Water Purification and Treatment System (DRIPS): Microgrid Integration with Geoenabled Water Production and Disinfection Systems for Installations

Abstract: The purpose of the Arctic Deployable Resilient Installation water Purification and treatment System (DRIPS) is to be a critical asset in disaster response and military operations by providing a reliable and effective means of producing potable water and disinfection in a challenging and unpredictable environment, such as in an extremely cold climate. The objective of this effort was to deliver, integrate, and demonstrate the Arctic DRIPS to show that it can provide drinkable water to users of the microgrid within polar climate zones. Its adaptability, mobility, and comprehensive water treatment capabilities make it an invaluable resource for addressing water-related emergencies and water disruptions and for sustaining critical missions. It also addresses a point of need by improving the ability to meet demands while reducing convoy requirements and the logistical foot-print and ensuring the well-being of affected installations during disaster responses, training operations, normal water disruptions, and emergency preparation. The DRIPS was delivered to Fort Wainwright, a sub-Arctic installation, to demonstrate the integration of a water treatment component within a microgrid structure and to help them be better prepared to meet their water and energy requirement goals. The microgrid integration requirements were met upon implementation of this project.