Vulnerable Coastal Areas Research Articles

Assessing the Origin and Mapping the Extension of Salinity Around Shrimp Culture Ponds in Rio Grande Do Norte (Brazil)

The increasing installation of shrimp farms in vulnerable coastal areas around the world generates an environmental impact and makes it urgent to develop methodologies and studies for assessing and scaling the potential risks and sustainability of these activities. One of the main hazards of these activities is that the prolonged inundation of excavated ponds for shrimp farming allows the percolation of saltwater in the surroundings, resulting in increasing groundwater salinity. Saltwater intrusion in coastal aquifers, accompanied by salinization of soils, causes a decrease in available freshwater resources, a decline in crop productivity and the deterioration of the natural ecosystem. The coastal aquifer of Rio Grande do Norte State (Brazil) where, for years, several shrimp farm factories have been operating, reported some issues related to aquifer and soil salinization. The present study aims to assess the origin of and delineate groundwater salinization in a sector of this coastal aquifer using a low-budget procedure. The integration of hydrogeological and hydrogeochemical characterization by drilling shallow piezometers, measuring the hydrostatic level and analyzing the major ion concentrations of the groundwater has made it possible to establish that the origin of groundwater pollution in the studied area is caused by saltwater percolation from shrimp farms. The joint use of both characterization techniques has been shown to have an efficient cost–benefit ratio and less-intrusive methodology, which can be applied in other areas with similar environmental concerns.

Analysis of The Impact of Climate Change on The Vulnerability of Coastal Areas and Small Islands in Gili Air, North Lombok

This research analyzes the impact of climate change on the vulnerability of coastal areas and small islands in Gili Air, North Lombok. Climate change, including rising temperatures and sea levels, is affecting coastal ecosystems, such as coral reefs which are vulnerable to bleaching and death. This study identifies a trend of increasing built-up land on Gili Air in the 2013-2022 period, which is caused by tourism promotion policies. The impact of this policy causes an increase in the number of tourists and local residents, which then increases the need for tourism supporting facilities. These land cover changes and development pressures increase Gili Air's environmental and economic vulnerability to climate change. These findings emphasize the importance of comprehensive adaptation and mitigation strategies to preserve the sustainability of ecosystems and the livelihoods of local residents.

Two-Way Coupling of the National Water Model (NWM) and Semi-Implicit Cross-Scale Hydroscience Integrated System Model (SCHISM) for Enhanced Coastal Discharge Predictions

This study addresses the limitations of and the common challenges faced by one-dimensional river-routing methods in hydrological models, including the National Water Model (NWM), in accurately representing coastal regions. We developed a two-way coupling between the NWM and the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM). The approach demonstrated improvements in modeling coastal river dynamics, particularly during extreme events like Hurricane Matthew. The coupled model successfully captured tidal influences, storm surge effects, and complex river–river interactions that the standalone NWM missed. The approach revealed more accurate representations of peak discharge timing and magnitude as well as water storage and release in coastal floodplains. However, we also identified challenges in reconciling variable representations between hydrological and hydraulic models. This work not only enhances the understanding of coastal–riverine interactions but also provides valuable insights for the development of next-generation hydrological models. The improved modeling capabilities have implications for flood forecasting, coastal management, and climate change adaptation in vulnerable coastal areas.

Towards sustainable coastal management: a hybrid model for vulnerability and risk assessment

This paper presents the development of a Hybrid Model (HM) integrated with a Bayesian Network (BN) for comprehensive coastal vulnerability and risk assessment, with a focus on Konyaaltı Beach, Antalya, Turkey. The HM incorporates critical environmental parameters such as wind, waves, currents, and sediment transport to simulate conditions at vulnerable coastal areas and perform risk assessments for storm effects, flooding, and erosion. The model includes submodules for predicting coastal storms, quantifying sediment transport rates, assessing tsunami inundation severity, and categorizing storms based on beach typologies. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized for significant wave height predictions, enhancing the model's accuracy. The integration of hydrodynamic modeling, Bayesian networks, and ANFIS offers a robust framework for assessing coastal vulnerability and informing sustainable management practices. The study's results highlight the necessity for integrated risk management strategies, including adaptive infrastructure design, zoning and land use regulations, ecosystem-based management, and continuous monitoring and model refinement to enhance coastal resilience against dynamic environmental forces. This research provides valuable insights for mitigating the impacts of hazards on urban developments, contributing to the advancement of sustainable coastal management.

Optimizing coastal protection: Nature-based engineering for longitudinal drift reversal and erosion reduction

Traditional hard engineering solutions have shown weaknesses in mitigating erosion processes in vulnerable coastal areas, contributing in some cases to their aggravation, which makes it necessary to study innovative nature-based engineering solutions. This research deals with an in-depth analysis of hydro-morphodynamic modelling results for optimizing the geometry of maritime structures under longitudinal drift reversal conditions by mimicking and manipulating natural processes to promote wave energy dissipation and sediment retention through wave deformation due to obstacle interposition. The solutions draw inspiration from the full-scale observation data of two examples of longitudinal drift reversal. Additionally, numerical simulations were developed for predicting wave climate near the Iberian Peninsula shoreline under different scenarios. Hydrodynamics and morphodynamics modelling results are discussed based on the impact of a specific storm, considering different characteristics of protection structures, followed by parametric sensitivity analysis and comparative studies performed with an optimized solution. Results indicated this solution contributed to sediment accumulation downdrift near the shoreline, as there is no interruption of the longitudinal drift compared to traditional protection structures. At the alignment, the structure also improved nearshore sediment accretion, reduced areas of erosion relative to a no-structure scenario and exhibited behaviour akin to an emerged structure with its crest level. Compared to wholly submerged structures, it becomes a relevant coastal protection alternative, as it guarantees excellent protection on the adjacent coastal zone by safeguarding against tidal variations induced by storm surges and mean sea level rise due to climate change. Furthermore, there is a positive effect to help promote biodiversity whenever the structure is located in an intertidal zone. Despite the enormous computational effort required in the hydro-morphodynamic modelling process, this study shows that it is possible to create innovative engineering coastal solutions to induce longitudinal drift reversal and reduce erosion near the shoreline.

The future of the Portuguese (SW Europe) most vulnerable coastal areas under climate change – Part II: Future extreme coastal flooding from downscaled bias corrected wave climate projections

Episodic extreme coastal flooding is considered one of the most serious threats to the global coastlines, endangering infrastructure, ecosystems, and communities. The synchronized effects of extreme wave events, storm surges and astronomical tides are particularly worrying in the context of sea level rise (SLR), and a comprehensive understanding of their future dynamics remains challenging. In this study, an innovative approach for a vulnerability assessment of sandy low-lying coastal areas, based on dynamic ensemble projections is proposed. In the current Part II study, the combined effects of future projected SLR, tides, storm surges and wave action are investigated at five key-locations along the Portuguese coastline, considering projected digital terrain models, built upon the shoreline projections obtained in Part I. Future extreme total water levels are obtained through a probabilistic approach, and extreme wave events are defined considering high wave energy thresholds in a changing climate. Overall, extreme coastal flooding is projected across several urbanized sections along the Portuguese coastline, especially in areas without artificial protection infrastructures. Dune erosion is expected along the sandy stretches, reducing the natural protection against extreme coastal events up to 13.3%, and promoting widespread overtopping, leaving populations more exposed. Future projections reveal the episodic flooding of up to 1.47 km2 of land along the 14 km of analyzed coastline, threatening households and commercial hubs, besides services and communication routes. As physical and human losses may increase substantially in the future, our results call for the implementation of adequate coastal management and adaptation plans, strategically defined to withstand changes until 2100 and beyond.

The effects of land subsidence and its mitigating measures on shallow groundwater salinization in the low-lying coastal plain of East Japan

Land subsidence in low-lying coastal regions results from geological and human factors, causing inundation during high tides. Mitigation measures, like pumping stations and ditch systems, aim to address this challenge. However, their impact on groundwater salinity near tidal rivers is understudied. Using a coupled surface-subsurface model, we investigate this issue in the lower Nabaki River region, Shirako Town, Japan. The simulation reveals adverse effects of pumping stations that induce intrusion of saline water from the tidal river into surrounding groundwater. While they are designed to prevent floods, these stations and ditches may inadvertently raise groundwater vulnerability to saltwater contamination. Despite 2D model limitations, it offers valuable insights into coastal groundwater dynamics and salinization. This study provides important information for policymakers and land managers to better understand the consequences of flood mitigation strategies on groundwater quality in vulnerable coastal areas.

Exploring GIS Techniques in Sea Level Change Studies: A Comprehensive Review

Sea level change, a consequence of climate change, poses a global threat with escalating impacts on coastal regions. Since 1880, global mean sea level has risen by 8–9 inches (21–24 cm), reaching a record high in 2021. Projections by NOAA suggest an additional 10–12-inch increase by 2050. This paper explores research methodologies for studying sea level change, focusing on Geographic Information System (GIS) techniques. GIS has become a powerful tool in sea level change research, allowing the integration of spatial data, coastal process modeling, and impact assessment. This paper sets the link with sustainability and reviews key factors influencing sea level change, such as thermal expansion and ice-mass loss, and examines how GIS is applied. It also highlights the importance of using different scenarios, like Representative Concentration Pathways (RCP), for accurate predictions. The paper discusses data sources, index variables like the Coastal Vulnerability Index, and GIS solutions for modeling sea level rise impacts. By synthesizing findings from previous research, it contributes to a better understanding of GIS methodologies in sea level change studies. This knowledge aids policymakers and researchers in developing strategies to address sea level change challenges and enhance coastal resilience. Furthermore, global analysis highlights the pivotal roles of the United States and China in sea level change (SLC) and GIS research. In the Gulf Cooperation Council (GCC) region, rising temperatures have substantial impacts on local sea levels and extreme weather events, particularly affecting vulnerable coastal areas.

A deep-learning model for rapid spatiotemporal prediction of coastal water levels

With the increasing impact of climate change and relative sea level rise, low-lying coastal communities face growing risks from recurrent nuisance flooding and storm tides. Thus, timely and reliable predictions of coastal water levels are critical to resilience in vulnerable coastal areas. Over the past decade, there has been increasing interest in utilizing machine learning (ML) based models for emulation and prediction of coastal water levels. However, flood advisory systems still rely on running computationally demanding hydrodynamic models. To alleviate the computational burden, these physics-based models are either run at small scales with high resolution or at large scales with low resolution. While ML-based models are very fast, they face challenges in terms of ensuring reliability and ability to capture any surge levels. In this paper, we develop a deep neural network for spatiotemporal prediction of water levels in coastal areas of the Chesapeake Bay in the U.S. Our model relies on data from numerical weather prediction models as the atmospheric input and astronomical tide levels, while its outputs are time series of predicted water levels at several tide gauge locations across the Chesapeake Bay. We utilized a CNN-LSTM setting as the architecture of the model. The CNN part extracts the features from a sequence of gridded wind fields and fuses its output to several independent LSTM units. The LSTM units concatenate the atmospheric features with respective astronomical tide levels and produce water level time series. The novel contribution of the present work is in spatiotemporality and in prioritization of the physical relationships in the model to maintain a high analogy to hydrodynamic modeling, either in the network architecture or in the selection of predictors and predictands. The results show that this setting yields a strong performance in predicting coastal water levels that cause flooding from minor to major levels. We also show that the model stands up successfully to the rigorous comparison with a high-fidelity ADCIRC model, yielding mean RMSE and correlation coefficient of 14.3 cm and 0.94, respectively, in two extreme cases, versus 12.30 cm and 0.96 for the ADCIRC model. The results highlight the practical feasibility of employing fast yet inexpensive data-driven models for resilient coastal management.

Assessing Social Vulnerability to Coastal Hazards: A Case Study of Bandar Lampung City Coastal Area

Bandar Lampung City’s coastal area is highly susceptible to coastal hazards due to its location within the subduction zone of the Indo-Australian and Eurasian tectonic plates. Additionally, the presence of the Anak Krakatau volcano in the Sunda Strait further increases the vulnerability of the city’s coast to natural disasters. This study analyses the current social vulnerability in the coastal area of Bandar Lampung City. The aim is to provide a starting point for disaster management and policy planning in the city. To determine the level of social vulnerability in the coastal area of Bandar Lampung City, social vulnerability mapping is conducted by overlaying four indices: population, population density, sex ratio, and dependency ratio. The data indicates that there is significant variation in the level of social vulnerability among the coastal areas of Bandar Lampung City. Specifically, 8 out of 25 villages in the coastal area of Bandar Lampung City exhibit high levels of social vulnerability. The villages of Bumi Waras, Pesawahan, and Keteguhan have the highest levels of social vulnerability in the coastal area of Bandar Lampung City. As revealed by this study, the indicators of population size and dependency ratio have the most significant impact on the level of social vulnerability. These findings are expected to provide valuable input to stakeholders in their efforts to reduce social vulnerability in coastal areas.

Community Adaptation to Heat stress − Social Network Analysis

Rising climate disasters underscore the overlooked impact of heat stress on health and productivity in densely populated Southeast Asia, particularly vulnerable coastal areas like India's. This study in the Indian Sundarbans employs surveys and social network analysis to explore heat stress effects, community adaptation, and support networks. Recognizing community significance, it views resilience as a blend of agency, wisdom, and networks. The research unveils rural adaptive behaviours, co-occurring stress responses, and network use for health solutions. These insights aim to enhance health advisories and crisis responses, fostering resilience in communities facing escalating climate challenges. The research covered 747 households from nine village segments, examining heat stress adaptation and social support networks. Social Network Analysis revealed internal and external sources of support for heat stress-induced health issues. The study employed matrices and network analysis tools to represent co-occurrence patterns of adaptation strategies and support networks. Findings highlighted collective adaptive behaviour and the role of social connections in combating climatic stress. The study outlines dual interventions to mitigate heat stress impacts: enhancing endogenous community adaptability and optimizing social-institutional networks for external support. Occupational profiling, socio-economic context, and health access can identify vulnerable groups. Perceived impacts can serve as early health crisis indicators, though not always linked to adaptive actions. Diverse adaptive activities co-occur, reflecting collective behaviour, but less central actions require attention. Medical care usage for heat stress remains minimal. Social networks lack local health providers needing community-level provisions. A comprehensive mitigation plan for identified vulnerable communities aims to bridge knowledge gaps, promote equitable healthcare access, and strengthen adaptive capacity through informed interventions.

Seasonal tracking of the Moroccan Mediterranean coastal risks between Tangier and Ksar-Sghir

The Mediterranean coast stretching from Tangier to Ksar Sghir within the Tangier-Tetouan-Al Hoceima region represents a crucial coastal area. This region's coastal environment faces multiple challenges, including demographic pressures and the evolving impacts of climate change which result in sea-level rise. Our research takes a comprehensive approach, integrating sedimentary and mineralogical analysis, along with the application of GIS tools for data processing and visualization. Through this research, we aim to identify vulnerable coastal areas, particularly those susceptible to erosion, and assess the effects of climate change, specifically focusing on rising sea levels. This study's findings shed light on the dynamic coastal landscape and provide valuable insights for sustainable coastal management in the face of environmental change. Our study shows that the studied region suffers from significant losses in the surface area of sand on some beaches due to the phenomenon of erosion. At the same time, some beaches knew a set back the shoreline by several metres, and others knew to advance the shoreline by several metres. In this way, it constitutes a continuation of a development that began several centuries ago, and which has been observed in the Mediterranean coast between Tangier and Ksar Sghir coastlines in the context of a rapid rise in sea level.

Using geographic rescue time contours, point-of-care strategies, and spatial care paths to prepare island communities for global warming, rising oceans, and weather disasters

ObjectivesTo perform geographic contour analysis of sea and land ambulance rescue times in an archipelago subject to super typhoons; to design point-of-care testing strategies for medical emergencies and weather disasters made more intense by global warming and rising oceans; and to assess needs for prehospital testing on spatial care paths that accelerate decision making, increase efficiency, improve outcomes, and enhance standards of care in island nations.MethodsWe performed needs assessments, inspected healthcare facilities, and collected ambulance rescue times from professionals in the Bantayan Archipelago, Philippines. We mapped sea/land ambulance rescue routes and time contours. To reveal gaps, we statistically compared the fastest and slowest patient rescue times from islands/islets and barangays to the District Hospital on Bantayan Island. We developed spatial care paths (the fastest routes to care) for acute myocardial infarction, community care, and infectious diseases. We generated a compendium of prehospital diagnostic testing and integrated outcomes evidence, diagnostic needs, and public health goals to recommend point-of-care strategies that build geographic health resilience.ResultsWe observed limited access to COVID-19 assays, absence of blood gas/pH testing for critical care support, and spatial gaps in land and airborne rescues that worsened during inclement weather and sea swells. Mean paired differences (slowest-fastest) in ambulance rescue times to the District Hospital for both islands and barangays were significant (P < 0.0001). Spatial care path analysis showed where point-of-care cardiac troponin testing should be implemented for expedited care of acute myocardial infarction. Geospatial strengths comprised distributed primary care that can be facilitated by point-of-care testing, logical interisland transfers for which decision making and triage could be accelerated with onboard diagnostics, and healthcare networks amenable to medical advances in prehospital testing that accelerate treatment.ConclusionsPoint-of-care testing should be positioned upstream close to homes and island populations that have prolonged rescue time contours. Geospatially optimized point-of-need diagnostics and distributed prehospital testing have high potential to improve outcomes. These improvements will potentially decrease disparities in mortality among archipelago versus urban dwellers, help improve island public health, and enhance resilience for increasingly adverse and frequent climate change weather disasters that impact vulnerable coastal areas. [350 words].

How just is the low-carbon transition in coastal areas? Development of a composite vulnerability index for coastal low-carbon transition

The transition toward a carbon–neutral society requires social and economic sacrifices in certain regions, and the vulnerability of specific areas to low-carbon transitions may be particularly pronounced in coastal regions. This study focuses on the development and application of a composite vulnerability index that can assess climate justice in coastal areas from a low-carbon transition perspective. Facilitated by the developed indices, this study, focuses on investigating regional disparities stemming from the transition and exploring various policy options for alleviating the resulting burdens or damages associated with these inequalities.The initial step in developing indicators involved creating a scoping diagram to define the scope of vulnerability and to identify specific indicators for coastal low-carbon transition vulnerability. Subsequently, based on the parameters, dimensions, and measurement factors presented in the diagram, composite vulnerability indices were formulated. In the process of calculating the vulnerability index, weights were assigned to the indicators at both quantitative and qualitative levels, reflecting vulnerability factors and dimensions. Finally, the Coastal Low-Carbon Transition Vulnerability Index (CLCTVI) was established for three sectors: marine fisheries, carbon sink, and energy development. The CLCTVI was then applied to coastal regions in South Korea, and its regional and sectoral patterns were analyzed using basic statistics, scatter plots, parallel coordinate plots, and the geodetector method.The findings of this study highlight the following key points: the degree of vulnerability in coastal areas to low-carbon transitions varies across regions; the main factors contributing to high or low vulnerability in low-carbon transitions differ for each sector; only a few regions are simultaneously vulnerable across all sectors. In particular, various interactive effects among factors were identified in each sector, underscoring the need for considering the interactions among factors alongside dominant factors for sector-specific vulnerabilities in policy support for regions exhibiting low-carbon transition vulnerabilities. This study showcases how CLCTVI can effectively capture interregional disparities resulting from low-carbon transitions in coastal areas, thus providing insight to decision-makers regarding previously unaddressed regional disparities associated with low-carbon transitions.

Temporal Assessment of the Effect of Flooding Vulnerability on Agricultural Land Use in the Gambia

Flooding is a significant environmental problem, projected to intensify from 2010 to 2030. This natural disaster has affected several regions globally, leading to loss of life and property, community disruption, economic loss, injuries, and deaths. Factors contributing to flooding include heavy rainfall, rising sea levels, lowlands, waterways, climatic variations, wetlands, soil types, and unplanned urban settlements. The most severe case in the history of the Gambia struck in 2022. Therefore, this study aimed to identify areas vulnerable to flooding and the effect on agricultural land in the Gambia, as well as suggest preventive measures. The method adopted included the collection of secondary data from Landsat ETM imagery, Digital Elevation Model, rainfall data, Copernicus Global Land Services (CGLS), and Food Agricultural Organisation soil maps. The satellite imageries were processed and classified using ArcGIS 10.7.1, generating land use and land cover, slope, drainage density, rainfall, and soil maps. ArcGIS, combined with the Analytic Hierarchy Process (AHP), was used to integrate these maps to produce a vulnerability map for the study. The results showed areas with very high, high, moderate, low, and very low vulnerability. Based on the classification, coastal and lowland regions were in the high category. Therefore, this study recommended the construction of water barricades in vulnerable coastal areas to mitigate the disaster.

Tidal Flood Hazard Assessment in Pekalongan City, Central Java

Climate change has had a significant impact on regional climate in many countries, including Indonesia. The coastal sector is one of the most vulnerable to climate change. Pekalongan City is one of the most vulnerable coastal areas in Indonesia to the effects of climate change. Tidal flooding is a disaster that occurs in coastal areas due to rising sea levels, which average 6-10 mm per year on Java’s northern coast. Tidal flood hazard analysis was performed using indicators of sea-level rise, distance to the sea, distance to the river, slope, topography, land cover, and land subsidence. The results of the field validation were consistent with those of the tidal flood hazard analysis. Areas covered by the tidal flood hazard modeling include Pasirkratonkramat, Bandengan, Kandang Panjang, Panjang Baru, Panjang Wetan, Krapyak, and Degayu. Pekalongan City experienced an increase in hazard area of 6.18% of the total area of Pekalongan City based on the results of the CSIRO modeling RCP 4.5 scenario. In comparison, the other three models show a decrease of up to 3.13% in the total area of Pekalongan City. However, when viewed at the site scale (per urban village), Podosugih Village experienced the highest increase in hazard area, up to 20.5% of the total area for the CSIRO-modeled RCP 4.5. The highest decrease in the area occurred in Klego Village, at 8.94% of the area for the RCP 4.5 scenario of the MIROC model. Future changes in rainfall, sea level, and land subsidence will cause these changes.

Adaptive response for climate change challenges for small and vulnerable coastal area (SVCA) countries: Qatar perspective

Climate change has already been affecting the entire globe in all aspects of life. Along with mitigation efforts, adaptive response actions are gaining increasingly urgent importance for many regions to considerably reduce the most severe impacts of climate change on social and physical infrastructure. As the severity and frequency of climate change impacts and consequences grow fast and highly alarming, particularly for small and vulnerable coastal area (SVCA) countries, the urgency and magnitude of the crises call for immediate and more adaptive responses. This study proposes that SVCA countries, being on the frontline of climate change vulnerabilities, impacts, and risks, should prioritize their resources and capacity and focus on developing and implementing immediate, tailored, adaptive response policies, plans, and actions. Long-term mitigation efforts would not help them reduce their current or immediate vulnerability in the short-term, as long as large countries with comparably huge populations, economies, heavy industrial dependences, and extreme consumption levels do not change their courses significantly. Therefore, this study presents a framework of climate change, sustainability, resilience, risk reduction, and adaptive response as a nexus to conceptualize the problem and solutions properly. Such a framework is needed to develop synergies between climate change and immediate adaptive response for such countries. The study analyzes Qatar, a typical SVCA country, assessing its current vulnerabilities & risks and potential physical, social, and economic challenges. Finally, it concludes with a discussion on recommended adaptive responses proposed for Qatar.

Assessing Social Vulnerability to Climate Change in a Fishery-Dependent Village in South Central Vietnam

Fishery-dependent communities are highly susceptible to the impacts of climate change due to their proximity to vulnerable coastal areas and reliance on ecosystem services for their livelihoods. The study assessed the effects of climate change on the socioeconomic livelihoods and adaptive capacity of Xuan Tu, a community located in South Central Vietnam. The assessment employed the social vulnerability index (SVI) and adaptive capacity index (ACI). A hybrid data collection approach was utilized to gather information from households, and a composite method was employed to aggregate the data, enabling an assessment of community vulnerability. The findings indicated exposure, sensitivity, and adaptive capacity index values of 0.16, 0.34, and 0.26, respectively. The community exhibited a moderate vulnerability to climate change, with a social vulnerability index of 0.43. Notably, economic sufficiency, access to social groups, and level of education emerged as significant factors in reducing social vulnerability. To adapt to climate change, the community modified their fish feeding practices, fish culture methods, increased technology usage, and diversified their sources of income. However, the study identified a lack of institutional support as a significant obstacle to the community's autonomous adaptation. Based on these results, the study recommends livelihood diversification and the implementation of planned adaptation strategies to enhance preparedness for climate emergencies in South Central Vietnam.

Macrophyte removal affects nutrient uptake and metabolism in lowland streams

Macrophytes provide essential ecosystem services in lowland streams, including nutrient uptake that can reduce downstream transport to vulnerable coastal areas. Despite that, to ensure water conveyance and effective run off from agricultural fields, aquatic plant biomass is removed regularly in many European streams (i.e. weed cutting practices). However, the impacts of weed cutting on stream ecosystem processes are not yet well documented. Here, we studied the effect of weed cutting on nutrient retention and ecosystem metabolism in three lowland streams with contrasting dominant vegetation communities (submergent and emergent plants) during summer in Denmark. Our results showed a decrease in nutrient retention; uptake velocity of ammonium decreased 34–77 % and of phosphate decreased 50–77 %. Ecosystem metabolic rates also decreased after weed cutting, both in gross primary production (9 %, 60 % and 85 %) and respiration (47 %, 69 % and 76 %). The effects of weed cutting on these ecosystem processes prevailed three weeks after the cutting occurred. Understanding the effects of weed cutting on stream ecosystem functioning can improve nature-based management strategies to control eutrophication of downstream coastal areas.

An Integrated Bayesian Risk Model for Coastal Flow Slides Using 3-D Hydrodynamic Transport and Monte Carlo Simulation

The literature suggests two forms of flow slides: breaching and liquefaction. Both forms of failure have comparable ultimate circumstances, but the progression and sand movement mechanisms of breaching failure diverge from those of liquefaction. The first type, breaching, occurs in densely packed sand and is characterized by slow sand grain discharge throughout the dilation of the failing soil particles and negative excess pore pressures. The latter form, known as liquefaction, is the process by which a mass of soil abruptly begins to behave like a flowing liquid, and as a result, it can flow out across overly mild slopes. The process begins in compacted sand and is linked to positive surplus pore water pressures that are caused by the compaction of the sand. Despite the available literature on flow slide failures, our understanding of the mechanisms involved remains limited. Since flow slides often begin below the water surface, they can go undetected until the collapse reaches the bank above ground. The complexity of flow slides requires the use of cutting-edge technological instruments, diving equipment, advanced risk assessment, and a variety of noteworthy probabilistic and sensitivity analyses. Hence, we developed a new sensitivity index to identify the risk of breach failure and vulnerable coastal areas to this risk. In addition, we developed a sophisticated hybrid model that allows for all possibilities of flow slides in sync with random variables used in this new sensitivity index. In this new hybrid model, three distinctive models exist. The 3D Hydrodynamic Model addresses waves, wind, current, climate change, and sediment transport. The Monte Carlo Simulation is responsible for sensitivity analysis, and the Bayesian Network focuses on joint probabilities of coastal flow slide parameters of this new index that incorporates all environmental parameters, including climate change. With the assistance of these three models, researchers aim to: (a) expand the application scope by presenting a method on coastal flow slides; (b) consider different particle diameters corresponding to critical angle slope failure; (c) analyze variables that can play a pivotal role in the flow slides; and (d) present a methodology for coupling coastal flow slide projections with reliable outcomes. The hybrid model incorporates random variables of retrogressive breach failures, and the new risk index considers their ranges to control the simulation. The use of such a hybrid model and risk index offers a robust and computationally efficient approach to evaluating coastal flow slides.