Hasil untuk "Harbors and coast protective works. Coastal engineering. Lighthouses"

Suzanne G. Ayvazian, Donald Cobb, Cathleen Wigand et al.

Shellfish restoration and aquaculture are considered as innovative methods to mitigate in-water nutrients in coastal waters. Water quality was examined at two oyster aquaculture farms in Potter (2021–2023) and Pt Judith (2023) Ponds in southern Rhode Island, USA. Twice monthly, on a flooding tide, upstream and downstream positions were established and water quality measures were made using fluorometry sondes and laboratory analysis. Significant differences in chlorophyll <i>a</i>, turbidity, and nutrient concentrations between upstream and downstream positions were identified; however, the differences were not consistently greater upstream or downstream. Percent Chl <i>a</i> removed varied from −74% to 64% at Potter Pond among years and −51% to 29% at Point Judith Pond, indicating a deficit or increase in Chl <i>a</i> concentration downstream as compared to upstream over each sampling period. Chlorophyll <i>a</i> measured inside oyster bags was higher compared to the upstream position at Potter Pond, and results from the upstream, downstream, and within farm productivity experiment in both ponds suggest oyster byproducts may facilitate localized and seasonal phytoplankton production. Natural resource managers should consider that while oyster farms in coastal ponds can provide local water clarity through removal of phytoplankton, benefits may be site specific and seasonal.

Emma Verling, Maria Power, Melanie Biausque et al.

Marcos Filho Lima Bastos, Jordana Marques Kneipp, Clandia Maffini Gomes et al.

Background: By 2050, most of the global human population will live in coastal regions, and the climatic impacts on these areas represent a significant concern for governments, private sector companies, and societies. Thus, environmental management of coastal regions plays a central role in the global climate agenda. Methods: The study employed a mixed-methods approach, integrating quantitative and qualitative techniques to conduct a systematic literature review (SLR). This included the construction of networks of related topics, time series analysis, literature mapping, and the identification of research gaps. The databases used were Web of Science, Science Direct, and Scopus. The inclusion and exclusion criteria encompassed articles published between 2014 and 2023, off-topic articles, unavailable articles, or paid access articles. At the end, 96 studies were included in this RSL. Results: The results revealed a predominance of studies addressing climate management in coastal regions, primarily focused on adaptation strategies. However, there is a notable deficiency in studies that address integrated mitigation and adaptation strategies. Time series analysis predicted an increase in the focus on coastal management and climate change in the coming years. Conclusion: The research underscores the central role of coastal management in addressing climate change and achieving the Sustainable Development Goals (SDGs). It encourages multi-level management, integrating government officials, business leaders, and civil society in the development of more effective practices for climate change adaptation and mitigation.

Remo Luan Marinho da Costa Pereira, Luci Cajueiro Carneiro Pereira, Cesar Mosso

This study aimed to evaluate how tidal modulation influences breaking waves on a macrotidal beach along the Amazonian coast under varying climatic conditions. The study utilized medium-term data (2006–2018) from national and international institutions and short-term data (2012–2014) from in situ measurements at Ajuruteua Beach. Offshore winds and waves, predominantly from the northeast, were influenced by severe storms associated with La Niña and El Niño events. During these periods, wave heights exceeded 5 m, with wave periods ranging from 12 to 20 s. Tidal fluctuations (typically 5.0–6.0 m) modulated nearshore wave heights and periods, with variations determined by offshore conditions and climatic influences. Wave heights decreased from 2–5 m offshore to 1–2 m nearshore. At low tide, sandbanks dissipated wave energy, resulting in significantly smaller breaking waves (0.1–0.5 m) compared with high tide (1–1.8 m). The northern part of Ajuruteua Beach experienced a progressive retreat, with a total area loss of 0.15 km² and a shoreline retreat of 0.360 km between 2007 and 2021. The combination of high hydrodynamic energy and unregulated development led to the destruction of 43 buildings between 2007 and 2013 and an additional 44 houses between 2013 and 2021 within the intertidal zone. Moreover, the absence of coastal management strategies has exacerbated erosion, underscoring the urgent need for planning and regulatory frameworks. Based on the findings of this study, it is recommended that land use be regulated and both short- and long-term physical processes be systematically integrated into future coastal protection planning.

Xiangfen Liu, Junqi Yu, Yahua Li et al.

Plant growth-promoting rhizobacteria (PGPR) are used to assist phytoremediation. Synthetic PGPR can adapt to diverse sediment environments more effectively than single PGPR. However, their mechanisms of application in submerged macrophytes remediation of cadmium polluted sediment remains challenging. Here, we investigated the effect of synthetic PGPR on enhancing phytoremediation in cadmium polluted sediment and the underlying mechanisms promoting growth of submerged macrophytes. We conducted a comparison regarding the phytoremediation efficiencies of submerged macrophytes within cadmium polluted sediment under the conditions of the absence of PGPR, single PGPR and synthetic PGPR inoculation. The results indicated that the lower concentration of cadmium in the sediment was achieved under synthetic PGPR inoculation of two treatments, specifically decreased by 26.18 % and 25.55 %, because of the highest biota-sediment accumulation factor. Synthetic PGPR induced 44 %–88 % increase in the biomass of submerged macrophytes by regulating enzyme activities and photosynthesis system compared with the treatment with cadmium pollution only. The PGPR promoted significant increase of chlorophyll, the optimal/maximal quantum yield of PSⅡ (Fv/Fm) and carotenoids content with the highest increases in macrophytes inoculated with synthetic PGPR. Compared with the treatments inoculated with single PGPR, synthetic PGPR enhanced the activities of antioxidant enzymes to assist submerged macrophytes in resisting cadmium stress. Consequently, synthetic PGPR promoted the growth and cadmium accumulation of submerged macrophytes. Our research further observed that the translocation factor of the submerged macrophytes was below 1, showing that cadmium was not easily transferred within the macrophytes. Our study provides new perspectives into strategy development in microbe-assisted submerged macrophytes remediation of cadmium polluted sediment.

Pu Li, Kaiheng Hu, Lan Ning

Erosion of landslide dams by a natural debris flow as it travels down a sloping channel can dramatically increase flow size and destructive potential. Most research on the erosion of landslide dams focuses on those newly formed due to recent earthquakes or heavy rainfall. In this study, the debris-flow erosion of so-called highly-consolidated landslide dams (HCLDs) that are typically remnants of ancient earthquakes or rainfall events is investigated by using satellite image interpretation, field measurements, and mechanism analysis. Several HCLDs were identified in two catchments in Zhouqu and Ganluo counties in Gansu and Sichuan province, China, where two high-magnitude debris-flow events occurred in 2010 and 2020, respectively. The existence of HCLDs resulting in wide and narrow reaches alternatively alters the boundary conditions of debris flows and significantly affects the flow erosion and deposition processes. It is observed that the flow discharge increased notably after passing through or during narrowing sections of the channels and the estimated discharge amplification coefficients are approximately 3.3 and 2.7, respectively. The two cases demonstrate that rapid erosion through narrowing sections and subsequent headward erosion play a key role in the debris-flow volume growth by eroding HCLDs. Additionally, other mechanisms such as deposition of erodible material upstream of the dam, localized vortexes in converging and diverging sections, and collisional stresses within the debris flows can further contribute to the erosion of HCLDs and the amplification of debris-flow magnitude. Recognizing these hazardous effects of HCLDs on increasing debris-flow volume is helpful for making non-structural and engineering countermeasures against similar debris flow disasters.

Kıvanç Yüksel, Neşe Gülci, Abdullah Emin Akay et al.

In this study, the effectiveness of different stabilization techniques implemented on the forest road cut slopes was investigated in terms of controlling erosion and runoff. Wood production residues, hydroseeding, and jute geotextile treatments were applied on study plots located on the example road. The amount of erosion and runoff were measured on the study plots which were established for different slope grades of 20°, 30°, and 40°. Then, the amount of erosion and runoff measured from the plots were compared to determine the performance of stabilization techniques on the cut slope. In the solution process, an Artificial Neural Network (ANN) model, which is one of the machine learning algorithms, was used to predict sediment yield from forest road cut slopes. The sediment yields averaged over the three slope grades from highest to lowest were measured as 6.41, 1.16, 0.65, and 0.45 g/m2 in the control plot with no treatment, jute geotextile, hydroseeding, and wood production residues, respectively. The averaged over the three runoff amounts slope grades from the highest to the lowest were determined as 6.82, 3.71, 1.64, and 1.30 mm/m2 in control the plot, jute geotextile, hydroseeding, and wood production residues, respectively. Comparing to the control plot, wood production residues, hydroseeding, and jute geotextile treatments reduced the sediment yields by 14, 10, and 5 times, respectively. On the other hand, wood production residues, hydroseeding, and jute geotextile applications reduced the runoff amount by 5, 4, and 2 times, respectively. As a result, it was found that wood production residues and hydroseeding treatment can be more efficient in reducing the amount of runoff and sediment yield compared to the jute geotextile treatment. The ANN method achieved high accuracy in predicting sediment yield and it was concluded that the ANN can be used as an effective method to evaluate soil slope stabilization techniques.

Ganggang Ke, Shengdong Cheng, Zhanbin Li et al.

Check dams, as one of the most representative soil and water conservation measures in the Loess Plateau region, primarily impact hydrological and hydrodynamic processes by regulating flows of water and sediment. Constrained by reservoir capacity, sediment accumulation within check dam systems affects their ability to intercept water and sediment. However, there has been limited research on the regulatory role of sediment-filled check dams on watershed hydrodynamics. This study focused on small watersheds in loess hilly gully areas and applied the MIKE SHE model to simulate hydrodynamic processes under different scenarios of filled check dam systems. The regulatory effect of different filled check dam system types on watershed hydrodynamics in the study area was analyzed. The results indicate that after sedimentation in various types of check dams, the peak flow can be reduced by 59.68%–68.66%, the flood duration can be extended by 42.74%–375.81%, and the runoff erosion power can be reduced by 62.92%–85.35%. The reduction in flood volume diminishes with increasing sedimentation, reaching a minimum of 2.42%. Moreover, there are varying degrees of reduction in runoff erosion dynamics in the main channels. These findings provide theoretical support for identifying the regulatory potential of sediment-filled check dam systems on hydrodynamic processes in small watersheds.

Longhui Pan, Rui Li, Benjin Yu et al.

Karst landscapes are plagued by severe soil erosion due to their fractured lithology and complex hydrology, posing persistent challenges to erosion assessment and ecological restoration. However, current approaches often fail to account for the spatial heterogeneity and hydrological complexity typical of karst terrains. This study developed and compared four vegetation restoration scenarios—the status quo scenario, linear scenario, patch scenario, and combined scenario—using an integrated modeling framework based on the Revised Universal Soil Loss Equation (RUSLE) and the sediment connectivity index (IC). The combined scenario, which integrates linear buffers with patch-based vegetation, showed superior performance in reducing both soil erosion and sediment connectivity. The patch scenario also shows strong adaptability in steep-slope areas because it effectively mitigates sediment transport potential. To improve restoration precision further, a slope- and karst desertification-sensitive vegetation configuration strategy was proposed. This study also introduced the use of bivariate Moran's I analysis to identify spatial hotspots of erosion and connectivity overlap. These results provide a novel methodology for evaluating multiscenario ecological restoration in karst regions. The findings offer practical guidance for implementing targeted soil and water conservation interventions and contribute to the broader goal of sustainable land management in ecologically fragile environments.

Carina Cristiane Korb, Laurindo Antonio Guasselli, Heinrich Hasenack et al.

Coastal wetlands play important environmental roles. However, their hydrogeomorphological dynamics remain poorly understood under scenarios of extreme climate events. The aim of this study was to characterize the temporal and spatial variability of hydrogeomorphological attributes (vegetation, water, and soil) in the wetlands of Lagoa do Peixe National Park, Brazil. The methodology involved applying Principal Component Analysis (PCA) in both temporal (T) and spatial (S) modes, decomposing spectral indices for each attribute to identify variability patterns. The results revealed that vegetation and water are strongly correlated with seasonal dynamics influenced by ENSO (El Niño/La Niña) events. Soils reflected their textural characteristics, with a distinct temporal response to the water balance. PCA proved to be a useful tool for synthesizing large volumes of multitemporal data and detecting dominant variability patterns. It highlighted the Lagoon Terraces and the Lagoon Fringe, where low slopes amplified hydrological variations. Temporal variability was more responsive to climate extremes, with implications for ecosystem conservation, while spatial variability was modulated by geomorphology.

Leo van Rijn, Luitze Perk, Bas van Maren et al.

The particle size and the settling velocity of sediments are key parameters in sediment transport studies. However, it remains surprisingly difficult to determine particle size and settling velocity distribution of fine-grained sediments (mud-sand). A large range of methodologies exist to measure either the particle size distribution or to measure the settling velocity. An important influential parameter is the shape of fine-grained sediments, with clay minerals being shaped as plates rather than as spheres. Furthermore, the settling velocity of fine particles is influenced by turbulent shear and flocculation processes. Sometimes, the sediment samples are pre-treated (destroying inter-particle bonds) to measure the primary particle sizes involved while in other cases samples are not pre-treated in order to represent the effect of flocs. As a result, a large uncertainty exists in the way particle size and settling velocity should be measured. A range of methodologies (sedimentation, video camera, and laser-diffraction) to measure the settling velocity and particle size distribution in the field and in the laboratory is used and compared. The labour-intensive sedimentation methods measure a particle size distribution which can be used for sedimentation studies. The particle size distribution measured by the most commonly applied laser diffraction method is representative of the plate diameter of the clay particles, but the corresponding settling velocity is not correct. This difference can be explained by the shape of the clay particles through a derivation of the settling velocity of non-spherical particles resulting in a simple relationship to convert the particle size measured by laser diffraction to a representative particle size to be used in sedimentation studies. A comparison of the settling velocity measured by an in situ settling method and by a video camera method shows good agreement for high concentrations (> 2000 mg/L) but deviating results for low concentrations (< 500 mg/L).

Wei Huang, Shouqian Li, Yongjun Lu et al.

Rapid development of inland waterways and marine transportation has resulted in the construction of large ships and an increase in ship speed. Consequently, severe local scour erosion of restricted water beds occurs due to propellers, endangering the surrounding buildings and navigating in the scour area. Thus, investigating bed scouring caused by propeller jets for water-related structures and maintaining navigational safety in restricted waterways is highly important. Therefore, this work combines propeller jet wash flume experiments and dimensionless analysis to investigate the evolution of the three-dimensional (3D) morphology of bed scour with varying clearance heights and the use of noncohesive sediments. The temporal evolution of jet scouring was manifested mainly as the development of the scour area's length, depth, and width, and the entire scouring process could be divided into initial, development, and equilibrium stages. The initial stage occupied more than 60% of the scouring process, and the shape of the center profile of the scour area can be expressed by a third-order function. By analyzing the scour depth variation with time, this study proposed a logarithmic equation for the temporal development process of the maximum scour depth in the scour region, which was used to predict the variation in the maximum propeller depth on the surface of the noncohesive sand bed with time.

Mia Mohammad Imran, Tarannum Shaila Zaman

Large Language Models (LLMs) are increasingly used in empirical software engineering (ESE) to automate or assist annotation tasks such as labeling commits, issues, and qualitative artifacts. Yet the reliability and reproducibility of such annotations remain underexplored. Existing studies often lack standardized measures for reliability, calibration, and drift, and frequently omit essential configuration details. We argue that LLM-based annotation should be treated as a measurement process rather than a purely automated activity. In this position paper, we outline the \textbf{Operationalization for LLM-based Annotation Framework (OLAF)}, a conceptual framework that organizes key constructs: \textit{reliability, calibration, drift, consensus, aggregation}, and \textit{transparency}. The paper aims to motivate methodological discussion and future empirical work toward more transparent and reproducible LLM-based annotation in software engineering research.

Allysson Allex Araújo, Marcos Kalinowski, Maria Teresa Baldassarre

In recent years, Software Engineering (SE) scholars and practitioners have emphasized the importance of integrating soft skills into SE education. However, teaching and learning soft skills are complex, as they cannot be acquired passively through raw knowledge acquisition. On the other hand, hackathons have attracted increasing attention due to their experiential, collaborative, and intensive nature, which certain tasks could be similar to real-world software development. This paper aims to discuss the idea of hackathons as an educational strategy for shaping SE students' soft skills in practice. Initially, we overview the existing literature on soft skills and hackathons in SE education. Then, we report preliminary empirical evidence from a seven-day hybrid hackathon involving 40 students. We assess how the hackathon experience promoted innovative and creative thinking, collaboration and teamwork, and knowledge application among participants through a structured questionnaire designed to evaluate students' self-awareness. Lastly, our findings and new directions are analyzed through the lens of Self-Determination Theory, which offers a psychological lens to understand human behavior. This paper contributes to academia by advocating the potential of hackathons in SE education and proposing concrete plans for future research within SDT. For industry, our discussion has implications around developing soft skills in future SE professionals, thereby enhancing their employability and readiness in the software market.

Adam Bloomston, Elizabeth Burke, Megan Cacace et al.

In this paper, we first situate the challenges for measuring data quality under Project Lighthouse in the broader academic context. We then discuss in detail the three core data quality metrics we use for measurement--two of which extend prior academic work. Using those data quality metrics as examples, we propose a framework, based on machine learning classification, for empirically justifying the choice of data quality metrics and their associated minimum thresholds. Finally we outline how these methods enable us to rigorously meet the principle of data minimization when analyzing potential experience gaps under Project Lighthouse, which we term quantitative data minimization.

Christoph Treude, Marco A. Gerosa

Artificial intelligence (AI), including large language models and generative AI, is emerging as a significant force in software development, offering developers powerful tools that span the entire development lifecycle. Although software engineering research has extensively studied AI tools in software development, the specific types of interactions between developers and these AI-powered tools have only recently begun to receive attention. Understanding and improving these interactions has the potential to enhance productivity, trust, and efficiency in AI-driven workflows. In this paper, we propose a taxonomy of interaction types between developers and AI tools, identifying eleven distinct interaction types, such as auto-complete code suggestions, command-driven actions, and conversational assistance. Building on this taxonomy, we outline a research agenda focused on optimizing AI interactions, improving developer control, and addressing trust and usability challenges in AI-assisted development. By establishing a structured foundation for studying developer-AI interactions, this paper aims to stimulate research on creating more effective, adaptive AI tools for software development.

Bilal Hassan, Areg Karapetyan, Aaron Chung Hin Chow et al.

Climate change and sea-level rise (SLR) pose escalating threats to coastal cities, intensifying the need for efficient and accurate methods to predict potential flood hazards. Traditional physics-based hydrodynamic simulators, although precise, are computationally expensive and impractical for city-scale coastal planning applications. Deep Learning (DL) techniques offer promising alternatives, however, they are often constrained by challenges such as data scarcity and high-dimensional output requirements. Leveraging a recently proposed vision-based, low-resource DL framework, we develop a novel, lightweight Convolutional Neural Network (CNN)-based model designed to predict coastal flooding under variable SLR projections and shoreline adaptation scenarios. Furthermore, we demonstrate the ability of the model to generalize across diverse geographical contexts by utilizing datasets from two distinct regions: Abu Dhabi and San Francisco. Our findings demonstrate that the proposed model significantly outperforms state-of-the-art methods, reducing the mean absolute error (MAE) in predicted flood depth maps on average by nearly 20%. These results highlight the potential of our approach to serve as a scalable and practical tool for coastal flood management, empowering decision-makers to develop effective mitigation strategies in response to the growing impacts of climate change. Project Page: https://caspiannet.github.io/

Hashini Gunatilake, John Grundy, Rashina Hoda et al.

Empathy plays a crucial role in software engineering (SE), influencing collaboration, communication, and decision-making. While prior research has highlighted the importance of empathy in SE, there is limited understanding of how empathy manifests in SE practice, what motivates SE practitioners to demonstrate empathy, and the factors that influence empathy in SE work. Our study explores these aspects through 22 interviews and a large scale survey with 116 software practitioners. Our findings provide insights into the expression of empathy in SE, the drivers behind empathetic practices, SE activities where empathy is perceived as useful or not, and the other factors that influence empathy. In addition, we offer practical implications for SE practitioners and researchers, offering a deeper understanding of how to effectively integrate empathy into SE processes.

Md Meftahul Ferdaus, Nathan Alton Cooper, Austin B. Schmidt et al.

Predicting ocean wave behavior is challenging due to the difficulty in choosing suitable numerical models among many with varying capabilities. This review examines the development and performance of numerical wave models in coastal engineering and oceanography, focusing on the difference between phase-averaged spectral models and phase-resolving models. We evaluate the formulation, governing equations, and methods of widely used third-generation phase-averaged spectral models (SWAN, WAVEWATCH III, MIKE 21 SW, TOMAWAC, and WAM) alongside advanced phase-resolving models (FUNWAVE, SWASH, COULWAVE, and NHWAVE) that employ Boussinesq-type equations and non-hydrostatic formulations. The review begins with early parameterized models and progresses to contemporary third-generation models, which solve the wave action conservation equation with few spectral constraints. A comparison of the models' efficiency, accuracy in nearshore conditions, ability to resolve nonlinear wave-wave interaction, simulate wave breaking, diffraction, and wave-current interactions is provided. Applications in operational forecasting, extreme event simulation, coastal structure design, and assessing climate change impacts are discussed. The validation of these models and the statistical metrics and intercomparison studies used are addressed. A discussion of the limitations in computational scalability, physics parameterization, and model coupling is provided, along with emerging trends in high-resolution modeling and hybrid models. This review guides researchers in evaluating which models to use in coastal and oceanographic research.

Scott F. Jones, Ariane Arias-Ortiz, Dennis Baldocchi et al.

Coastal wetlands are hotspots of carbon sequestration, and their conservation and restoration can help to mitigate climate change. However, there remains uncertainty on when and where coastal wetland restoration can most effectively act as natural climate solutions (NCS). Here, we synthesize current understanding to illustrate the requirements for coastal wetland restoration to benefit climate, and discuss potential paths forward that address key uncertainties impeding implementation. To be effective as NCS, coastal wetland restoration projects will accrue climate cooling benefits that would not occur without management action (additionality), will be implementable (feasibility) and will persist over management-relevant timeframes (permanence). Several issues add uncertainty to understanding if these minimum requirements are met. First, coastal wetlands serve as both a landscape source and sink of carbon for other habitats, increasing uncertainty in additionality. Second, coastal wetlands can potentially migrate outside of project footprints as they respond to sea-level rise, increasing uncertainty in permanence. To address these first two issues, a system-wide approach may be necessary, rather than basing cooling benefits only on changes that occur within project boundaries. Third, the need for NCS to function over management-relevant decadal timescales means methane responses may be necessary to include in coastal wetland restoration planning and monitoring. Finally, there is uncertainty on how much data are required to justify restoration action. We summarize the minimum data required to make a binary decision on whether there is a net cooling benefit from a management action, noting that these data are more readily available than the data required to quantify the magnitude of cooling benefits for carbon crediting purposes. By reducing uncertainty, coastal wetland restoration can be implemented at the scale required to significantly contribute to addressing the current climate crisis.