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Category: Publications: Engineer Research & Development Center (ERDC)
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  • 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.
  • The Forefront: A Review of ERDC Publications, Summer 2024

    Abstract: As the main research and development organization for the US Army Corps of Engineers (USACE), the Engineer Research and Development Center (ERDC) helps solve our nation’s most challenging problems. With seven laboratories under the ERDC umbrella, ERDC expertise spans a wide range of disciplines. This issue of the Forefront highlights several ERDC reports from FY22, many of which were highly recognized and widely downloaded. The Forefront team was honored in FY23 to receive both the Information Technology Laboratory’s Communication Award and the ERDC Communication Award for our Summer 2022 issue of the Forefront. The Forefront team and the Information Science and Knowledge Management Branch (ISKM) as a whole are committed to staying current with best practices and exploring new techniques to communicate ERDC’s research excellence. Through quality publications, dynamic presentations, and ongoing training opportunities, ISKM strives not only to support ERDC but also to blaze a path to clear, concise, and engaging scientific communication products. Remember, if it ever takes you more than five minutes to find an answer, contact us. We are here to help!
  • 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.
  • Case Study of Continental-Scale Hydrologic Modeling’s Ability to Predict Daily Streamflow Percentiles for Regulatory Application

    Abstract: Regulatory practitioners use hydroclimatic data to provide context to observations typically collected through field site visits and aerial imagery analysis. In the absence of site-specific data, regulatory practitioners must use proxy hydroclimatic data and models to assess a stream's hydroclimatology. One intent of current-generation continental-scale hydrologic models is to provide such hydrologic context to ungaged watersheds. In this study, the ability of two state-of-the-art, operational, continental-scale hydrologic modeling frameworks, the National Water Model and the Group on Earth Observation Global Water Sustainability (GEOGloWS) European Centre for Medium-Range Weather Forecasts (ECMWF) Streamflow Model, to produce daily streamflow percentiles and categorical estimates of the streamflow normalcy was examined. The modeled stream-flow percentiles were compared to observed daily streamflow percentiles at four United States Geological Survey stream gages. The model's performance was then compared to a baseline assessment methodology, the Antecedent Precipitation Tool. Results indicated that, when compared to baseline assessment techniques, the accuracy of the National Water Model (NWM) or GEOGloWS ECMWF Streamflow Model was greater than the accuracy of the baseline assessment methodology at four stream gage locations. The NWM performed best at three of the four gages. This work highlighted a novel application of current-generation continental-scale hydrologic models.
  • Automated Built-Up Infrastructure Land Cover Extraction Using Index Ensembles with Machine Learning, Automated Training Data, and Red Band Texture Layers

    Abstract: Automated built-up infrastructure classification is a global need for planning. However, in-dividual indices have weaknesses, including spectral confusion with bare ground, and computational requirements for deep learning are intensive. We present a computationally lightweight method to classify built-up infrastructure. We use an ensemble of spectral indices and a novel red-band texture layer with global thresholds determined from 12 diverse sites (two seasonally varied images per site). Multiple spectral indexes were evaluated using Sentinel-2 imagery. Our texture metric uses the red band to separate built-up infrastructure from spectrally similar bare ground. Our evaluation produced global thresholds by evaluating ground truth points against a range of site-specific optimal index thresholds across the 24 images. These were used to classify an ensemble, and then spectral indexes, texture, and stratified random sampling guided training data selection. The training data fit a random forest classifier to create final binary maps. Validation found an average overall accuracy of 79.95% (±4%) and an F1 score of 0.5304 (±0.07). The inclusion of the texture metric improved overall accuracy by 14–21%. A comparison to site-specific thresholds and a deep learning-derived layer is provided. This automated built-up infrastructure mapping framework requires only public imagery to support time-sensitive land management workflows.
  • The Military and Planning for Lithium-Ion Battery Recycling

    Purpose: Understanding the military challenges related to lithium-ion battery disposal and learning about current and future trends in recycling efforts can inform safer and less environmentally destructive end-of-life solutions. Established lead-acid battery recycling methods were compared to the still-evolving lithium-ion battery recycling processes. Executive Order (EO) 13817, EO 13953, and EO 14017 have prioritized the identification of critical minerals, including minerals necessary for lithium-ion battery production, and the need to strengthen supply chains as vital to national security. To support this national security effort, the military may be able to contribute to the domestic supply through employing efficient recycling practices and encouraging industry to move towards standardization. Evolving recycling practices, including efforts to eliminate hazards in spent lithium-ion batteries, may be able to help the military dispose of these items more safely and cost-effectively, especially in contingency locations.
  • Automated Mapping of Land Cover Type within International Heterogenous Landscapes Using Sentinel-2 Imagery with Ancillary Geospatial Data

    Abstract: A near-global framework for automated training data generation and land cover classification using shallow machine learning with low-density time series imagery does not exist. This study presents a methodology to map nine-class, six-class, and five-class land cover using two dates of a Sentinel-2 granule across seven international sites. The approach uses a series of spectral, textural, and distance decision functions combined with modified ancillary layers to create binary masks from which to generate a balanced set of training data applied to a random forest classifier. For the land cover masks, stepwise threshold adjustments were applied to reflectance, spectral index values, and Euclidean distance layers, with 62 combinations evaluated. Global and regional adaptive thresholds were computed. An annual 95th and 5th percentile NDVI composite was used to provide temporal corrections to the decision functions, and these corrections were compared against the original model. The accuracy assessment found that the regional adaptive thresholds for both the two-date land cover and the temporally corrected land cover could accurately map land cover type within nine-class, six-class, and five-class schemes. Lastly, the five-class and six-class models were compared with a manually labeled deep learning model (Esri), where they performed with similar accuracies. The results highlight performance in line with an intensive deep learning approach, and reasonably accurate models created without a full annual time series of imagery.
  • Opportunities for Upper Mississippi River System Sand to Support Coastal Beach Nourishment

    Abstract: This research presents an opportunity to review the concept, status, and cost of using Upper Mississippi River (UMR) riverine dredged sand to nourish coastal beaches for increased resilience. Several dredged placement sites, transport modes, commercial and industrial uses, and end-point destinations will be identified in regional assessments and several specific UMR sediment to Great Lakes beneficial use projects will be reviewed here and assessed in greater detail during this research investigation.
  • Using iThenticate for ERDC Publications: Avoiding and Addressing Unintentional Plagiarism

    Abstract: The US Army Engineer Research and Development Center (ERDC) conducts world-class research that supports national endeavors and the Army mission. To demonstrate the reliability of ERDC’s research and to preserve ERDC’s reputation, it is critical that ERDC publications meet quality standards. This includes reviewing publications for potential copyright infringement, which adds another level of assurance to the quality and integrity of ERDC’s published works. Therefore, this report aims to explain the benefits and purpose behind implementing iThenticate, a powerful antiplagiarism tool, into the ERDC In-formation Technology Laboratory–Information Science and Knowledge Management (ISKM) Branch’s publication process and to present thorough guidance on using iThenticate effectively. To accomplish this, this document outlines the basics of copyright law, how to use iThenticate, and how to provide proper attributions for both text and images. With this information, ISKM editors will be able to better communicate to authors the results of iThenticate reviews and to propose solutions for any issues that iThenticate may highlight.
  • Human Well-Being and Natural Infrastructure: Assessing Opportunities for Equitable Project Planning and Implementation

    Abstract: There is consensus within psychological, physiological, medical, and social science disciplines that active and passive exposure to nature enhances human well-being. Natural infrastructure (NI) includes elements of nature that can deliver these ancillary well-being benefits while serving their infrastructure-related purposes and, as such, offer great promise for agencies including the U.S. Army Corps of Engineers as a means of enhancing economic, environmental, and societal benefits in civil works projects. Yet, to date, NI are typically framed as alternatives to conventional infrastructure but are rarely competitive for project selection because there is no standardized approach to demonstrate their value or justify their cost. The infrastructure projects subsequently selected may not maximize societal well-being or distribute benefits equitably. A framework is needed to capture diverse and holistic benefits of NI. As part of ongoing research, this paper describes the components necessary to construct a framework for well-being benefits accounting and equitable distribution of NI projects and explores how they might be applied within a framework. We conclude with methodological examples of well-being accounting tools for NI that are based on ongoing research and development associated with this project. The findings provide insights and support for both the Engineering with Nature community and the community of NI practitioners at large.