23 Apr 2026

Sediment Transport Modeling to Evaluate the Performance of a Dredged Channel at Pohoiki Bay, Hawaiʻi, Following the Kīlauea Lower East Rift Zone Eruption

Abstract: The Kīlauea volcano’s Lower East Rift Zone (LERZ), located approximately 20.5 miles south-southeast from Hilo on the Island of Hawaiʻi, erupted during the summer of 2018, destroying over 700 homes and advancing the shoreline east of the volcano into the Pacific Ocean. The recently formed lava field along the shoreline eroded into Pohoiki Bay, creating a black sand beach that closed access to a boat ramp that was vital to the local community. The US Army Corps of Engineers (USACE) Honolulu District, on behalf of the State of Hawaiʻi, requested the US Army Engineer Research and Development Center (ERDC) Coastal and Hydraulics Laboratory (CHL) conduct numerical modeling of the existing condition at and around the bay to evaluate the impact of dredging a channel through the beach to reconnect the boat ramp to the Pacific Ocean. The Coastal Modeling System (CMS) was used to evaluate the shoaling rates in the proposed channel. The model was validated with morphology change calculations from a sediment budget, and the results provide a range of possible shoaling rates in the channel. The results of this effort were used to inform the State of Hawaiʻi’s plans to complete construction of a dredged channel in November 2025.

23 Apr 2026

Development of an Agnostic Reservoir Model to Explore Wildfire Impact on Water Quality

Abstract: Despite the growing global concern surrounding the havoc caused by wildfires, there are still prominent gaps in knowledge regarding fire effects on nearby waterways. An agnostic CE-QUAL-W2 model was developed to look at the impact of wildfires on reservoir water quality, with a focus on harmful algal blooms. The model was informed using ten years of meteorological data from sites in the Pacific Northwest, United States. Wildfire scenarios were generated (one each for May, June, July, August, and September) using changes in temperature, total suspended solids, nutrients, dissolved oxygen, organic matter, and solar radiation typical of wildfires, informed via literature review. Harmful algal blooms showed the most sensitivity to fires that occurred prior to the growing season, likely due to the influx of phosphate accumulating in the system prior to growth. However, accumulation of nutrients for fires after the growing season showed impacts on blooms the following year. Increases in total dissolved solids during the fire could potentially lead to delays in initial bloom timing due to temporary light limitation. Results from the model runs indicate that wildfires can impact reservoir water quality and bloom dynamics not only immediately, but for months to years following a wildfire.

21 Apr 2026

Review of Computational Fluid Dynamics Capabilities to Analyze the Behavior of Amphibious Vessels During Surf-Zone Transit

Abstract: This US Army Engineer Research and Development Center (ERDC), Coastal and Hydraulics Laboratory (CHL) Engineering Technical Note (CHETN) provides an overview of the state of computational fluid dynamics (CFD) techniques for the analysis of amphibious vessels transiting or interacting with the surf zone. In this CHETN we present (1) a background of the problem set, (2) a general discussion of CFD techniques available for the simulation and analysis of waterborne vessel response in water, (3) a discussion of CFD analysis of amphibious vessels in the surf zone, and (4) a discussion of combined scaled and CFD analysis of amphibious vessels in the surf zone.

20 Apr 2026

New Poe Lock Emergency Closure System Physical Model Study

Abstract: The US Army Corps of Engineers (USACE)–Detroit District (LRE) has begun the process of designing a new emergency bulkhead for Poe Lock in Sault Ste. Marie, Michigan, and has requested assistance from the US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, in determining the hydraulic loads the bulkhead will experience during operation. The US Army Engineer Research and Development Center has constructed a 1:25 scale physical hydraulic model to estimate the hydraulic forces on the bulkhead and pressure on the bulkhead sill during lowering operations. Multiple bulkhead lowering speeds and bulkhead lip designs have been tested over the course of the study. This report provides time histories of the hydraulic loads and bulkhead pressures throughout the bulkhead lowering operations. These results will inform the design of the emergency bulkhead and the size of its operating equipment.

20 Apr 2026

Surf Zone Hazards Before and After a Beach Nourishment in Virginia, USA

Abstract: Beach nourishment is the leading coastal protection technique in the United States to combat erosion, enhance resilience to storm surge, and maintain recreational value. Despite these benefits, anecdotal reports suggest that beach nourishments elevate the surf zone hazard to beach patrons by steepening the beach face and altering the shoreface morphology such that conditions are more favorable for rip current formation. This study analyzes lifeguard rescue reports collected on the United States Atlantic Coast before and after a 2019 beach nourishment in Virginia Beach, Virginia, to assess whether the nourishment was correlated with an increased hazard to beach patrons. The data indicate that regardless of nourishment status, rescues were most probable during periods of high rip current probability (moderate to large wave heights and low-obliquity wave angles), along with low water level. To formally quantify pre-versus post-nourishment hazards, the proportion of rescues observed in nourished versus unnourished beach zones was compared with bootstrapped distributions of the pre-nourishment rescue proportions. Although the proportion of rescues in the nourished section of the beach exceeds the pre-nourishment average, it is not outside the overall range of pre-nourishment values obtained by random resampling. Consequently, there is insufficient evidence to conclude that the existing coastal management beach nourishment strategy increased the hazard to beach patrons at Virginia Beach.

15 Apr 2026

Satellite Image Quality Classification with ImageNet Transfer Learning and Data Fusion

Abstract: This Coastal and Hydraulics Engineering Tech Note (CHETN) documents the development of a convolutional neural network (CNN) to automate quality control on image classification, a process previously done by subject matter experts (SMEs), within the Littoral Zone Maneuver Support Tool (LZMST). LZMST was created to support rapid exploration of an unknown littoral region by analyzing global satellite data and wave and current models to best estimate the coastal conditions and help identify potential hazards. In support of this mission, images from Landsat-8 (Roy et al. 2014) and Sentinel-2a/2b (Drusch et al. 2012) are graded on their predicted usefulness for LZMST, which is usually done by expert selection. A CNN model is developed to automate this task, by utilizing transfer learning on a CNN using ImageNet (Krizhevsky et al. 2017) weights combined with a small data set of classifications from the CoastSat (Vos et al. 2019) python application. Because the expert selection of images is incredibly time consuming, the data set used to develop this tool was small (approximately 3,500 images), which can make creation of a data-driven algorithm difficult. This CHETN highlights the usefulness of using transfer learning to eliminate the need for large data sets and demonstrates that ImageNet weights can be successfully used to assist in quality detection on multispectral imagery from the Landsat-8 and Sentinel-2a/2b missions.

15 Apr 2026

Field Evaluation of the Automated Barge Clearing Deterrent (ABCD): Hydrodynamic, Navigation, and Fish Response Effects

Abstract: The escape and subsequent spread of invasive carp (notably, bighead carp [Hypophthalmichthys nobilis] and silver carp [H. molitrix]) from aquaculture ponds and sewage lagoons into the Mississippi and Illinois Rivers poses a significant risk to further spread of these fish into the Great Lakes. Prior research demonstrated that commercial tows can transport juvenile invasive carp through locks and other barriers to fish migration. A recent physical model study recommended a linear array of bubble diffusers, the Automated Barge Clearing Deterrent (ABCD), for further evaluation in mitigating the transport of small fish in commercial tows. The present field study evaluated the ABCD for navigation safety and barge junction flushing capacity. An instrumented commercial tow executed 119 lock approaches with the ABCD both operating and idle. Pilot interviews and tow trajectory analysis indicated no significant navigation safety issues. The measured velocity data, fish recapture data, and a simple fish displacement model indicated that the ABCD produced sufficient flow to expel all passive objects and many small juvenile invasive carp. However, the ABCD is less likely to expel large juvenile invasive carp due to their stronger swimming ability. The ABCD and two alternative configurations prove strong contenders for further development and application.

14 Apr 2026

Physics-enhanced Machine Learning Models for Streamflow Discharge Forecasting

Abstract: Accurate river discharge forecasts for short to intermediate time intervals are crucial for decision-making related to flood mitigation, the seamless operation of inland waterways management, and optimal dredging. River routing models that are physics based, such as RAPID (‘routing application for parallel computation of discharge’) or its variants, are used to forecast river discharge. These physics-based models make numerous assumptions, including linear process modeling, accounting for only adjacent river inflows, and requiring brute force calibration of hydrological input parameters. As a consequence of these assumptions and the missing information that describes the complex dynamics of rivers and their interaction with hydrology and topography, RAPID leads to noisy forecasts that may, at times, substantially deviate from the true gauged values. In this article, we propose hybrid river discharge forecast models that integrate physics-based RAPID simulation model with advanced data-driven machine learning (ML) models. They leverage runoff data of the watershed in the entire basin, consider the physics-based RAPID model, take into account the variability in predictions made by the physics-based model relative to the true gauged discharge values, and are built on state-of-the-art ML models with different complexities. We deploy two different algorithms to build these hybrid models, namely, delta learning and data augmentation. The results of a case study indicate that a hybrid model for discharge predictions outperforms RAPID in terms of overall performance. The prediction accuracy for various rivers in the case study can be improved by a factor of four to seven.

2 Apr 2026

Analyzing Historical Snow Trends in Interior Alaska

Abstract: This study examines 40 years (water years 1982–2021) of snowpack characteristics to consider its hydrological implications in the 5350 km² Chena River basin. Using observations and a fine-scale physics model, we analyzed trends of snow water equivalent (SWE), snow onset and disappearance, and snow cover duration (SCD). New hydrological insights for the region: Results indicate a decline in SWE across the modeled domain, averaging a decrease of 3 mm per decade, with larger decreases (up to 10 mm per decade) at lower elevations. While domain-averaged SWE trends were not statistically significant, observed SCD showed statistically significant decreases: - 5.2, - 5.0, and - 4.4 days per decade at Teuchet Creek, Fairbanks F.O., and Little Chena Ridge, respectively. Notably, observations at SNOTEL stations and modeling revealed no statistically significant change in domain-averaged Rain-on-Snow (ROS) events over the 40-year period, contrasting some regional future estimates of increased ROS frequency. Peak streamflow did not consistently correlate with peak SWE levels, suggesting that other environmental factors such as ROS events and rapid temperature increases (e.g., a 10◦C spike observed in 1992) are key drivers of hydrological outcomes. These findings improve understanding of complex subarctic hydrological processes impacting permafrost and highlight the need for adaptive water resource management to mitigate multi-factor risks like flooding and wildfire, requiring proactive planning.

2 Apr 2026

Storylines for the 1997 New Year’s Flood: The role of Watershed Antecedent Conditions and Future Warming in Shaping Discharge in the Truckee River Watershed

Abstract: The 1997 New Year’s flood was among the most devastating floods in the Truckee River watershed located in western Nevada. This event resulted from complex interactions of flood drivers, such as extreme precipitation, wet antecedent watershed conditions, warm temperatures and rapid snowmelt. We leveraged simulated forcings from the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) and a process-based hydrological model to recreate the 1997 New Year’s flood for the Truckee River watershed across four climate warming levels ranging from the current temperatures to + 4◦ C. For each scenario, we conducted ensemble simulations with the same forcing but with 100 different seasonal watershed antecedent conditions, which were randomly sampled from long-term hydrological simulations. The results show that the 1997 New Year’s flood can be reproduced or exceeded consistently only when the antecedent watershed conditions are wet, specifically when streamflows are above the 75th percentile of the climatological value. There is negligible change in ensemble mean peakflows for Truckee River near Reno; however, there are increases of 18% and 14% under the warming levels of + 3◦ C and + 4◦ C, respectively. The increases in peakflows under future climate warming are attributed to wetter antecedent watershed conditions and enhanced snowmelt. Furthermore, the largest increases in peakflows occur at small, high-elevation headwater basins along the Sierra Nevada crest. This study highlights that changes in extreme flood events will result from the complex interplay of multiple flood drivers. It also demonstrates the potential of storyline approaches to analyze future realizations of these extreme events under different climate scenarios.