31 Mar 2025

USACE Relief Wells for Dams and Levees: History and Current Practice

Abstract: The purpose of this study was to review relief well practices within the United States Army Corps of Engineers (USACE). A literature review was performed on the history and use of relief wells relief and the state of practice within the USACE. As part of this study, a survey about relief well use and maintenance practice was prepared and distributed to selected Districts containing a large number of relief wells to determine their standard operating procedures for using those wells and to learn the history of their use. Responses obtained from these Districts were tabulated and classified according to the subject categories requested. Research needs and tools were requested as part of the survey, and a large portion of the responses indicated that there is an important need for research into biofouling prevention and remediation. Finally, a laboratory experiment was performed on several commercial-off-the-shelf sensors to measure effluent flow remotely. The results of the experiment showed that remote sensing of relief well flow is viable. It was found that pore pressures could be used to measure the relief well flows over a wide range of flow rates and with an error of 10 percent or less on average. Ultrasonic sensors also performed well during testing, with an average error of 10 percent or less.

21 Jan 2025

Engineering With Nature: Natural Infrastructure for Mission Readiness at U.S. Navy and Marine Corps Installations

Abstract: This book illustrates some of the current challenges and hazards experienced by military installations, and the content highlights activities at eight U.S. Navy and Marine Corps military installations to achieve increased resilience through natural infrastructure.

19 Nov 2024

Deep Learning Approach for Accurate Segmentation of Sand Boils in Levee Systems

Abstract: Sand boils can contribute to the liquefaction of a portion of the levee, leading to levee failure. Accurately detecting and segmenting sand boils is crucial for effectively monitoring and maintaining levee systems. This paper presents SandBoilNet, a fully convolutional neural network with skip connections designed for accurate pixel-level classification or semantic segmentation of sand boils from images in levee systems. In this study, we explore the use of transfer learning for fast training and detecting sand boils through semantic segmentation. By utilizing a pretrained CNN model with ResNet50V2 architecture, our algorithm effectively leverages learned features for precise detection. We hypothesize that controlled feature extraction using a deeper pretrained CNN model can selectively generate the most relevant feature maps adapting to the domain, thereby improving performance. Experimental results demonstrate that SandBoilNet outperforms state-of-the-art semantic segmentation methods in accurately detecting sand boils, achieving a Balanced Accuracy (BA) of 85.52%, Macro F1-score (MaF1) of 73.12%, and an Intersection over Union (IoU) of 57.43% specifically for sand boils. This proposed approach represents a novel and effective solution for accurately detecting and segmenting sand boils from levee images toward automating the monitoring and maintenance of levee infrastructure.

14 Nov 2024

Application of Deep Learning for Segmenting Seepages in Levee Systems

Abstract: Seepage is a typical hydraulic factor that can initiate the breaching process in a levee system. If not identified and treated on time, seepages can be a severe problem for levees, weakening the levee structure and eventually leading to collapse. Therefore, it is essential always to be vigilant with regular monitoring procedures to identify seepages throughout these levee systems and perform adequate repairs to limit potential threats from unforeseen levee failures. This paper introduces a fully convolutional neural network to identify and segment seepage from the image in levee systems. To the best of our knowledge, this is the first work in this domain. Applying deep learning techniques for semantic segmentation tasks in real-world scenarios has its own challenges, especially the difficulty for models to effectively learn from complex backgrounds while focusing on simpler objects of interest. This challenge is particularly evident in the task of detecting seepages in levee systems, where the fault is relatively simple compared to the complex and varied background. We addressed this problem by introducing negative images and a controlled transfer learning approach for semantic segmentation for accurate seepage segmentation in levee systems.

29 Oct 2024

Influence of Fines Content on the Progression of Backward Erosion Piping

Abstract: Backward erosion piping is a form of internal erosion that endangers the structural stability of levees and dams. Understanding the factors that influence this form of erosion can result in improved risk assessment and more appropriate modifications to new and existing structures. Historically, it has been assumed that the presence of silt size particles would reduce the gradient required for erosion. This study investigated the influence of fines content on backward erosion piping through a series of laboratory experiments on silty sands. Laboratory results show that as the fines content increased in the samples, so too did the gradient required to produce and progress piping to failure. The results indicate that a new factor is needed to properly account for silt content in backward erosion piping (BEP) risk assessment of silty sands.

15 Oct 2024

Deployable Resilient Installation Water Purification and Treatment System (DRIPS): Relief Well Biofouling Treatment of Dams and Levees

Abstract: The US Army Corps of Engineers (USACE) conducts regular inspections and maintenance of relief wells to ensure their proper functionality and to identify early signs of malfunction or potential failure. Expenses associated with labor, materials, and transportation are the primary cost drivers of relief-well maintenance. To minimize labor hours and materials, a treatment approach intended to improve logistics and reduce material costs during relief-well treatment was developed and tested. This approach employed external UVC, mechanical brush treatments, and chlorinated-gas-infused water to produce liquid sodium hypochlorite (NaClO). Preliminary bench-scale testing with chlorine, oxalic acid, and UVC informed the selection of field testing methods and optimal amendment concentrations. Field demonstrations were conducted annually over three years. During the demonstrations, the system underwent continuous optimization to enhance its efficiency. Different locations in Mississippi (Grenada Dam, Eagle Lake, and Magna Vista) were selected for testing. Both new and traditional treatment approaches yielded adequate results, achieving microbial reduction at 96% to 100%. The development and refinement of this system demonstrated that relief wells can be treated within a comparable timeframe and with similar efficiency while utilizing fewer purchased chemicals and materials.

21 May 2024

Engineering With Nature: An Atlas, Volume 3

Abstract: Engineering With Nature: An Atlas, Volume 3 showcases EWN principles and practices “in action” through 58 projects from around the world. These exemplary projects demonstrate what it means to partner with nature to deliver engineering solutions with triple-win benefits. The collection of projects included were developed and constructed by a large number of government, private sector, nongovernmental organizations, and other organizations. Through the use of photographs and narrative descriptions, the EWN Atlas was developed to inspire interested readers and practitioners with the potential to engineer with nature.

28 Feb 2024

Ecological Model to Evaluate Borrow Areas in the Lower Mississippi River

Abstract: An aquatic analysis of constructing borrow areas adjacent to the main line levees in the Lower Mississippi River was conducted as part of an Environmental Impact Statement for upgrading the levee system. A Habitat Suitability Index (HSI) regression model based on field collections was developed to predict fish species richness as a function of the morphometry and water quality of borrow areas. The HSI score was multiplied by acres of borrow areas created during construction to obtain habitat units (HUs) for each alternative indicating a substantial gain of fishery habitat in the floodplain. Environmental features identified by the model to increase fish species richness and overall habitat heterogeneity include the shape of the pit (e.g., bowl-shaped with deep water rather than long rectangular with shallower water), the availability of littoral areas for fish spawning and rearing, using best management practices such as tree screens and bank stabilization to lower turbidity, adding islands, and creating sinuous shorelines. The project results in an overall gain in aquatic habitat by creating permanent or semi-permanent water bodies on the floodplain that our research indicates may be occupied by at least 75 species of fish contributing to the overall biodiversity of the lower Mississippi River.

12 Jan 2024

Levees and Dams at Fort Riley, Kansas, and the Response to the 1951 Flood

Abstract: This project provides a historic context and inventory for the levees and dams constructed at Fort Riley, Kansas. The purpose of this historic con-text and inventory is to determine the levees and dams’ eligibility for listing in the National Register of Historic Places (NRHP). Determinations of eligibility to the NRHP are then made based on the significance of the levees and dams and the degree to which they retain their integrity for conveying that significance. The authors inventoried and evaluated three levees and two lake dams on the installation. Based on the historic context and inventory, researchers for this project have determined that none of the levees and dams are eligible for the inclusion in the NRHP nor was there enough evidence for a noncontiguous historic district at Fort Riley.

4 May 2022

Calculation of Levee-Breach Widening Rates

Abstract: Inundation modeling is often conducted for levee systems to understand current flood risks. The extent of inundation caused by a breach in the levee is highly influenced by the widening rate of the levee breach. This study presents an approach for calculating levee-breach widening rates based on average flow velocity through the breach, embankment height, and erosion characteristics of the soil. Estimates of soil erodibility are derived through an analysis of the measurements of soil erodibility presented in the National Cooperative Highway Research Program (NCHRP) Report 915 database. Levee-breach widening rate curves are calculated based on these erosion properties to demonstrate the approach, and default curves are presented for typical levees built from coarse-grained soils and fine-grained soils. While the most accurate approach for a site is to calculate site-specific widening rate curves based on estimates of local soil erodibility, the default curves presented provide a suitable starting point for initial inundation modeling.