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Archive: November, 2022
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  • Automation of Gridded HEC-HMS Model Development Using Python: Initial Condition Testing and Calibration Applications

    Abstract: The US Army Corps of Engineers’s (USACE) Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) rainfall-runoff model is widely used within the research community to develop both event-based and continuous rainfall-runoff models. The soil moisture accounting (SMA) algorithm is commonly used for long-term simulations. Depending on the final model setup, 12 to 18 parameters are needed to characterize the modeled watershed’s canopy, surface, soil, and routing processes, all of which are potential calibration parameters. HEC-HMS includes optimization tools to facilitate model calibration, but only initial conditions (ICs) can be calibrated when using the gridded SMA algorithm. Calibrating a continuous SMA HEC-HMS model is an iterative process that can require hundreds of simulations, a time intensive process requiring automation. HEC-HMS is written in Java and is predominantly run through a graphical user interface (GUI). As such, conducting a long-term gridded SMA calibration is infeasible using the GUI. USACE Construction Engineering Research Laboratory (CERL) has written a workflow that utilizes the existing Jython application programming interface (API) to batch run HEC-HMS simulations with Python. The workflow allows for gridded SMA HEC-HMS model sensitivity and calibration analyses to be conducted in a timely manner.
  • Risk-Based Prioritization of Operational Condition Assessments: Methodology and Case Study Results

    Abstract: USACE operates, maintains, and manages more than $232 billion of the Nation’s water resource infrastructure. USACE uses the Operational Condition Assessment (OCA) to allocate limited resources to assess condition of this infrastructure in efforts to minimize risks associated with performance degradation. The analysis of risk associated with flood risk management (FRM) assets includes consideration of how each asset contributes to its associated FRM watershed system, understanding the consequences of the asset’s performance degradation, and a determination of the likelihood that the asset will perform as expected given the current OCA condition ratings of critical components. This research demonstrates a proof-of-concept application of a scalable methodology to model the probability of a dam performing as expected given the state of its gates and their components. The team combines this likelihood of degradation with consequences generated by the application of designed simulation experiments with hydrological models to develop a risk measure. The resulting risk scores serve as an input for a mixed-integer optimization program that outputs the optimal set of components to conduct OCAs on to minimize risk in the watershed. This report documents the results of the application of this methodology to two case studies.
  • Numerical Analysis of Dike Effects on the Mississippi River Using a Two-Dimensional Adaptive Hydraulics Model (AdH)

    Abstract: This report describes the hydraulic effects of dikes on water surface elevation (WSE) and velocities in the Mississippi River near Vicksburg, MS, from Interstate 20 to Highway 80 using a previously calibrated 2D Adaptive Hydraulics numerical model. Dike heights and their associated hydraulic roughness values were varied to quantify the overall effects of adjustments to dike fields. Steady flows characterized as low, medium, and high conditions were simulated. The WSE and velocity difference plots were generated to illustrate the hydraulic effects on the river under all scenarios discussed above. Overall, the dike adjustments had negligible impacts on WSEs and showed minimal effects on velocities on a system wide scale.
  • National Ordinary High Water Mark Field Delineation Manual for Rivers and Streams : Interim Version

    Abstract: The ordinary high water mark (OHWM) defines the lateral extent of nontidal aquatic features in the absence of adjacent wetlands in the United States. The federal regulatory definition of the OHWM, 33 CFR 328.3(c)(7), 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.
  • The DEM Breakline and Differencing Analysis Tool—Step-by-Step Workflows and Procedures for Effective Gridded DEM Analysis

    Abstract: The DEM Breakline and Differencing Analysis Tool is the result of a multi-year research effort in the analysis of digital elevation models (DEMs) and the extraction of features associated with breaklines identified on the DEM by numerical analysis. Developed in the ENVI/IDL image processing application, the tool is designed to serve as an aid to research in the investigation of DEMs by taking advantage of local variation in the height. A set of specific workflow exercises is described as applied to a diverse set of four sample DEMs. These workflows instruct the user in applying the tool to extract and analyze features associated with terrain, vegetative canopy, and built structures. Optimal processing parameter choices, subject to user modification, are provided along with sufficient explanation to train the user in elevation model analysis through the creation of customized output overlays.
  • Cross Country Mobility (CCM) Modeling Using Triangulated Irregular Networks (TIN)

    Abstract: Cross country mobility (CCM) models terrain that has insufficient or unavailable infrastructure for crossing. This historically has been done with either hand-drawn and estimated maps or with raster-based terrain analysis, both of which have their own strengths and weaknesses. In this report the authors explore the possibility of using triangulated irregular networks (TINs) as a means of representing terrain characteristics used in CCM and discuss the possibilities of using such networks for routing capabilities in lieu of a traditional road-based network. The factors used to calculate CCM are modified from previous methods to capture a more accurate measurement of terrain characteristics. Using a TIN to store and represent CCM information achieves comparable results to raster cost analysis with the additional benefits of an integrated network useful for visualization and routing and a reduction in the number of related files. Additionally, TINs can in some cases more accurately show the contours of the landscape and reveal feature details or impediments that may be lost within a raster, thus improving the quality of CCM overlays.
  • Understanding Plant Volatiles for Environmental Awareness: Chemical Composition in Response to Natural Light Cycles and Wounding

    Abstract: Plants emit a bouquet of volatile organic compounds (VOCs) in response to both biotic and abiotic stresses and, simultaneously, eavesdrop on emitted signals to activate direct and indirect defenses. By gaining even a slight insight into the semantics of interplant communications, a unique awareness of the operational environment may be obtainable (e.g., knowledge of a disturbance within). In this effort, we used five species of plants, Arabidopsis thaliana, Panicum virgatum, Festuca rubra, Tradescantia zebrina, and Achillea millefolium, to produce and query VOCs emitted in response to mechanical wounding and light cycles. These plants provide a basis for further investigation in this communication system as they span model organisms, common house plants, and Arctic plants. The VOC composition was complex; our parameter filtering often enabled us to reduce the noise to fewer than 50 compounds emitted over minutes to hours in a day. We were able to detect and measure the plant response through two analytical methods. This report documents the methods used, the data collected, and the analyses performed on the VOCs to determine if they can be used to increase environmental awareness of the battlespace.
  • Meteorological Influences of a Major Dust Storm in Southwest Asia during July–August 2018

    Abstract: Dust storms can be hazardous for aviation, military activities, and respiratory health and can occur on a wide variety of spatiotemporal scales with little to no warning. To properly forecast these storms, a comprehensive understanding of the meteorological dynamics that control their evolution is a prerequisite. To that end, we chose a major dust storm that occurred in Southwest Asia during July–August 2018 and conducted an observation-based analysis of the meteorological conditions that influenced the storm’s evolution. We found that the main impetus behind the dust storm was a large-scale meteorological system (i.e., a cyclone) that affected Southwest Asia. It seems that cascading effects from this system produced a smaller, near-surface warm anomaly in Mesopotamia that may have triggered the dust storm, guided its trajectory over the Arabian Peninsula, and potentially catalyzed the development of a small low-pressure system over the southeastern end of the peninsula. This low-pressure system may have contributed to some convective activity over the same region. This type of analysis may provide important information about large-scale meteorological forcings for not only this particular dust storm but also for future dust storms in Southwest Asia and other regions of the world.
  • Network Development and Autonomous Vehicles: A Smart Transportation Testbed at Fort Carson

    Abstract: In this work, a smart transportation testbed was utilized at Fort Carson to demonstrate three use cases for the primary purpose to plan, develop, demonstrate, and employ autonomous vehicle technologies at military installations and within the surrounding communities to evaluate commercially available Connected and Automated Vehicles and the potential to reduce base operating costs, improve safety and quality of life for military service members and their families, and deliver services more efficiently and effectively. To meet this purpose, an automated vehicle shuttle, an unmanned aerial system, and a wireless network were used and tested during the project. Results for the automated shuttle indicated that de-spite the quantity of data generated by operations, the contractors may not be ready to share information in a readily usable format. Additionally, successful use by the public is predicated on both knowing their mobility patterns and staff members promoting trust in the technology to prospective riders. Results for the unmanned aerial system showed successful identification of foreign object debris and runway cracks at the airfield. The wireless network is now operational and is used for additional work which utilizes the installed traffic cameras.
  • A 𝘬-Means Analysis of the Voltage Response of a Soil-Based Microbial Fuel Cell to an Injected Military-Relevant Compound (Urea)

    Abstract: Biotechnology offers new ways to use biological processes as environmental sensors. For example, in soil microbial fuel cells (MFCs), soil electro-genic microorganisms are recruited to electrodes embedded in soil and produce electricity (measured by voltage) through the breakdown of substrate. Because the voltage produced by the electrogenic microbes is a function of their environment, we hypothesize that the voltage may change in a characteristic manner given environmental disturbances, such as the contamination by exogenous material, in a way that can be modelled and serve as a diagnostic. In this study, we aimed to statistically analyze voltage from soil MFCs injected with urea as a proxy for gross contamination. Specifically, we used 𝘬-means clustering to discern between voltage output before and after the injection of urea. Our results showed that the 𝘬-means algorithm recognized 4–6 distinctive voltage regions, defining unique periods of the MFC voltage that clearly identify pre- and postinjection and other phases of the MFC lifecycle. This demonstrates that 𝘬-means can identify voltage patterns temporally, which could be further improve the sensing capabilities of MFCs by identifying specific regions of dissimilarity in voltage, indicating changes in the environment.