Coastal Locations Research Articles

Preserving History: Assessments and Climate Adaptations at the House of the Seven Gables in Salem, Massachusetts, USA

Salem, Massachusetts, is one of the oldest cities in the United States (1629) and its coastal location on the Atlantic helped create one of the wealthiest cities in America during the late 18th century, but today its coastal location threatens many of its buildings due to sea level rise and increased storm activity. The House of the Seven Gables, a National Historic Landmark District, consists of five important historic buildings, the most famous being The Turner Ingersoll Mansion (1668), more commonly known as The House of the Seven Gables. Considered one of the most important houses in America, it is also one of the most threatened historic buildings due to its location on Salem’s harbor. The House of the Seven Gables conducted a two-year study funded by Massachusetts Coastal Zone Management to evaluate the risks posed by climate change. This process included the use of data from groundwater monitoring wells and a tidal gauge installed on-site, along with soil samples and a detailed survey base plan including topography and subsurface infrastructure. The project team then used the Massachusetts Coastal Flood Risk Model (MC-FRM) to assess climate change impacts on the site in 2030, 2050, and 2070, and then created a plan for adaptations that should be implemented before those risks materialize. Strategies for adapting to storm surges, increasing groundwater, and intense surface water runoff were evaluated for their effectiveness and appropriateness for the historic site. The conclusion of the study resulted in a five-phase plan ending in the managed retreat of the historic buildings to higher ground on the existing site. This article goes beyond other research that suggests coastal retreats by demonstrating how to quantitatively evaluate current and future coastal issues with predictive models and how to set viable dates for adaptive solutions and a managed retreat.

Design and Construction of the Real Felipe Fortress of Callao: Analysis of the Military Treatise and Layout Using Photogrammetry and GIS

Peru constituted the most important Viceroyalty of the Spanish Empire in South America, with the Port of Callao controlling the South Pacific trade routes. Although it was safe in its infancy, Callao suffered coastal attacks leading to its fortification. However, on 28 October 1746, an earthquake and tidal wave devastated the port, leading to its relocation and the construction of the Real Felipe Fortress of Callao, the South Pacific’s most significant fortification. The fortress was based on 18th century military conceptions adapted to the specific conditions of the coastal lands of the Peruvian Viceroyalty, such as the lack of stone, the use of adobe, and the frequent earthquakes. This research sought to identify the architectural theories influencing its design, the adaptations necessary for its coastal location, and the underlying mathematical and military concepts. Photogrammetry based techniques and a geographic information system (GIS) were used for georeferencing historical planimetry, along with the analysis of historical documents. This allowed us to reconstruct the original design and make evident how European ideas were adjusted to the particularities of the American territory, thus contributing to the improvement of knowledge about Spanish military architecture in America.

Feasibility analysis of solar and wind energy-powered irrigation pumping systems using reanalysis data–A case of Thiruvananthapuram district in Kerala, southwest region of India

This study presents a feasibility assessment of solar photovoltaic and wind energy systems for irrigation at three locations (a coastal lowland location named A, a midland location B, and a highland location C) in Thiruvananthapuram district, Kerala, in India’s southwest region. The solar and wind potentials are determined using the National Solar Radiation Database and Modern-Era Retrospective Analysis for Research and Applications, Version 2 reanalysis data sets, respectively. The technical analyses suggest that site B has the most solar energy potential, while site C has the highest wind energy potential. However, the economic feasibility study reveals that the only suitable location is site B, which has a 10-year simple payback time (SPT). The site has an annual solar energy potential of 1633.85 kWh/kWp, which is enough to pump 3921.24 kL of water to irrigate the majority of crops in one acre.

First Report of 'Soft Flesh' Induced by the Parasite Kudoa thyrsites (Myxosporea) in Commercial Codfish From Norway.

Kudoa thyrsites is a myxosporean parasite that infects the skeletal muscle of various teleost fish species globally. Severe infections lead to 'soft flesh' in fish fillets, resulting in food spoilage and subsequent discard. While K. thyrsites has previously been identified in migratory Atlantic mackerel in the northern Northeast Atlantic Ocean, it has not been observed in resident or farmed fish species in Norwegian waters until now. This study presents the first evidence of K. thyrsites infection and the associated 'soft flesh' condition in resident commercially important gadoid species from Norwegian waters, including Norwegian coastal cod (NCC), Northeast Arctic cod (NEA) and tusk. Molecular analyses confirmed the parasitic infection in 'soft flesh'-affected fish sampled from multiple coastal locations in Norway. The life cycle of Kudoa remains unknown but likely involves an alternating annelid host as in other myxosporeans. These findings in resident hosts suggest that the parasite completes its life cycle also at higher latitudes, in northern Norway. Consequently, there is a risk for the Norwegian fishing industry, as the effect of the parasite on fish fillet texture can occasionally occur and impact both consumer acceptance and industry revenues.

Optimizing Wind Speed Predictions in Bangladesh: Unveiling the Power of Machine Learning Approaches

Wind speed is a naturally occurring phenomenon that arises from the intricate interplay of various atmospheric processes. Wind speed prediction is pivotal in various sectors worldwide, and Bangladesh is no exception. Beyond its impact on agriculture, water management, and disaster preparedness, wind speed also plays a crucial role in urban planning and construction projects. Architects and engineers rely on accurate wind speed forecasts to design buildings and infrastructure that can withstand local wind conditions. Furthermore, the aviation and maritime industries heavily depend on wind speed predictions to ensure the safety of flights and shipping routes. Predicting wind speeds in Bangladesh poses a significant challenge due to the region's susceptibility to frequent seasonal changes influenced by its coastal location and complex, nonlinear climate patterns. To address this important aspect, we leverage Machine Learning (ML) algorithms, including Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), Random Forest (RF), K Nearest Neighbors (K-NN), and Support Vector Machine (SVM) to forecast wind speeds at various weather stations in Bangladesh. We utilized various accuracy metrics, including precision, sensitivity, specificity, F-measure, and overall accuracy, to evaluate the performances of the algorithms. The RF model outperformed the other models with an overall accuracy of 94.73% for predicting wind speed conditions in Bangladesh. On the other hand, the LDA model exhibited the lowest performance, achieving an accuracy of 93.27% in comparison to the other models. It is noticeable that the aforementioned five models showed more than 90% accuracy for windspeed prediction. Additionally, we complement our analysis with visual representations such as box plots, density plots, dot plots, parallel plots, and scatterplot matrix plots. These empirical results also highlighted the RF as the most suitable method for predicting contemporary wind speed patterns in Bangladesh. International Journal of Statistical Sciences, Vol. 24(2), November, 2024, pp 137-154

Regional modelling of extreme sea levels induced by hurricanes

Abstract. Coastal zones are increasingly threatened by extreme sea level events, with storm surges being among the most hazardous components, especially in regions prone to tropical cyclones. This study aims to explore the factors influencing the performance of numerical models in simulating storm surges in the tropical Atlantic region. The maxima, durations, and time evolutions of extreme storm surge events are evaluated for four historical hurricanes against tide gauge records. The Advanced Circulation (ADCIRC) and Nucleus for European Modelling of the Ocean (NEMO) ocean models are compared using similar configurations in terms of domain, bathymetry, and spatial resolution. These models are then used to perform sensitivity experiments on oceanic and atmospheric forcings, physical parameterizations of wind stress, and baroclinic/barotropic modes. NEMO and ADCIRC demonstrate similar abilities in simulating storm surges induced by hurricanes. Storm surges simulated with ERA5 atmospheric reanalysis forcing are generally more accurate than those simulated with parametric wind models for the simulated hurricanes. The inclusion of baroclinic processes improves storm surge amplitudes at some coastal locations, such as along the southeastern Florida peninsula (USA). However, experiments exploring different implementations of wind stress and interactions among storm surges, tides, and mean sea level have shown minimal impacts on hurricane-induced storm surges.

Application Of Remote Sensing Technology And Geographic Information Systems For Tsunami Vulnerability Analysis In Mamuju District

This research aims to analyze the vulnerability to tsunami disasters in Mamuju District, West Sulawesi, using remote sensing technology and Geographic Information Systems (GIS). Mamuju District is at high risk of tsunamis due to its coastal location and its position between active tectonic plates. The analysis utilizes five main parameters: elevation, slope gradient, distance from rivers, distance from the coastline, and land cover. The GIS overlay analysis method is applied to map tsunami hazard zones, combining weighting and scoring for each parameter. The results indicate that 3% of the area has very high vulnerability, 7% of the area has high vulnerability, while 82% of the area has low to very low vulnerability. Areas with very high vulnerability include the coastal zone directly adjacent to the shoreline and residential areas. This study is expected to serve as a reference for local governments and disaster management agencies in efforts to mitigate and plan safer spatial arrangements against tsunami threats. Mitigation strategy recommendations include the construction of evacuation routes, safe shelters, and the regular enhancement of disaster education and simulations for the community. Furthermore, this research encourages the use of mountainous areas as primary evacuation zones and collaboration with research institutions for the development of more innovative mitigation technologies.

A Hedonic Approach to Coastal Resilience in Post-Hurricane Maria’s Puerto Rico

Hurricane Maria devastated Puerto Rico in 2017, resulting in reduced beach width and dune flattening in certain coastal areas. Economic development activity observed in coastal regions of Puerto Rico after Hurricane Maria has partly focused on commercial and housing construction projects. The following study seeks to estimate the implicit value attributed by coastal homeowners to natural infrastructure attributes that may serve not only for recreation, but also as protection from future extreme weather events. We estimated a hedonic valuation model to assess the implicit value attributed by coastal homeowners to key natural attributes, emphasizing beach width and property elevation. Property owners sufficiently close to the coastline (1,000 m or less) implicitly assigned a positive value to beach width at their closest coastal location. An unexpected result was that elevation, when interacted with beach and human-made coastal types, was negatively associated with property prices, an indication of the importance of closeness to sea level. Given the impact of extreme weather events in coastal regions, hedonic valuation data on natural coastal attributes such as beach width can provide valuable information not currently considered in coastline development permitting.

Characteristics, symptoms, and outcomes of patients with Vibrio vulnificus infection in Hainan, China: A retrospective study.

With global temperatures on the rise and an expanding seafood trade, infections by Vibrio vulnificus, particularly in warm coastal areas like Hainan, China, are increasingly prevalent. These bacteria are notorious for causing grave infections with a high fatality rate. This study aims to dissect the clinical features, laboratory findings, treatment modalities, and patient outcomes associated with V vulnificus infections in Hainan Province. The medical records and clinical data of intensive care unit patients from Hainan General Hospital were retrospectively analyzed. Conventional sequencing and metagenomic sequencing were used to identify V vulnificus. The study involved 10 patients (9 males and 1 female) with a median age of 60.5 years, predominantly fishermen, with infections mainly occurring between May and October. Of note, 2 cases were linked to plant-related injuries. The typical manifestations included fever, pain, swelling, hemorrhagic vesicles, septic shock, and multi-organ dysfunction. It was found that delayed hospital admissions were associated with elevated Sequential Organ Failure Assessment and Acute Physiology and Chronic Health Evaluation II scores and increased mortality. Laboratory results indicated a robust inflammatory response, and interventions comprised antibiotic therapy and surgical procedures. A mortality rate of 50% was recorded. Vigilance for V vulnificus infections is crucial in coastal locales. The study endorses immediate and assertive treatment strategies, including the use of targeted antibiotics and surgical interventions, to enhance patient survival rates. A call for heightened awareness, intensified surveillance, and expanded research is essential to combat this life-threatening condition.

Influence of terrestrial and marine air mass on the constituents and intermixing of bioaerosols over a coastal atmosphere

Abstract. Coastal environments provide an ideal setting for investigating the intermixing processes between terrestrial and marine aerosols. In this study, fine particulate matter (PM2.5) samples categorized into terrestrial, marine, and mixed air masses were collected from a coastal location in northern China. The chemical and biological constituents, including water-soluble ions (WSIs), metallic elements, and bacterial and fungal aerosols, were investigated from January to March 2018, encompassing both the winter heating and spring dust seasons. Terrestrial air masses constituted 59.94 % of the total air masses throughout the sampling period, with a significant increase during severe haze pollution (up to 90 %). These air masses exhibited a higher concentration of PM2.5 (240 µg m−3) and carried more water-soluble ions and metal elements. The terrestrial air mass also contained a larger number of animal parasites or symbionts, as well as human pathogens from anthropogenic emissions, such as Staphylococcus, Deinococcus, Sphingomonas, Lactobacillus, Cladosporium, and Malassezia. Conversely, a significant quantity of saprophytic bacteria such as hydrocarbon-degrading and gut bacteria from the genera Comamonas, Streptococcus, Novosphingobium, and Aerococcus and the saprophytic fungus Aspergillus were the most abundant species in the marine air mass samples. The mixed air mass elucidates the intermixing process of terrestrial and marine sources, a result of microorganisms originating from both anthropogenic and terrestrial emissions, which includes pathogenic microorganisms from hospitals and sewage treatment plants, and a multitude of soil bacteria. A stronger correlation was noted between microorganisms and continental elements in both terrestrial and mixed air mass samples, specifically K+, Mg2+, and Ca2+ derived from soil dust. Marine air masses exhibited a significant correlation with sea salt ions, specifically Na+. In the mixed air mass sample, a fusion of marine and terrestrial microorganisms is characterized by alterations in the ratio of pathogenic to saprophytic microorganisms when compared to samples derived from either terrestrial or marine sources. This study on the constituents and amalgamation of bioaerosols over the coastal atmosphere encompassing distinct air masses is crucial to understand the transport, intermixing processes, and health implications of terrestrial and marine air masses.

Habitat suitability modeling of loggerhead sea turtles in the Central-Eastern Mediterranean Sea: a machine learning approach using satellite tracking data

Understanding how sea turtle species move through the environment and respond to environmental features is fundamental for sustainable ecosystem management and effective conservation. This study investigates the habitat suitability of the loggerhead sea turtle (Caretta caretta) in the Adriatic and Northern Ionian Seas (Central-Eastern Mediterranean) by developing and validating a multidisciplinary framework that leverages machine learning to investigate movement patterns collected by satellite tags Argos satellite tags. Satellite tracking data, enriched with sixteen environmental variables from the Copernicus Marine Service and EMODnet-bathymetry, were analyzed using Random Forest models, obtaining an accuracy of 80.9% when classifying presence versus pseudo-absence of loggerhead sea turtles. As main findings, sea bottom depth, surface chlorophyll (chl-a), and mixed layer depth (MLD) were identified as the most influential features in the habitat suitability of these specimens. Moreover, statistically significant differences, evaluated using t-test statistics, were found between coastal and pelagic locations, for the different seasons, in mixed layer depth, chl-a, 3D-clorophyll, salinity and phosphate. Although based on a limited sample of tagged animals, this study demonstrates that the distribution patterns of loggerhead sea turtles in Mediterranean coastal and pelagic areas are primarily influenced by sea water features linked to productivity and, consequently, to potential prey abundance. Additionally, this multidisciplinary framework presents a replicable approach that can be adapted for various species and regions.

A potential tool for marine biogeography: eDNA-dominant fish species differ among coastal habitats and by season concordant with gear-based assessments.

Effective ocean management asks for up-to-date knowledge of marine biogeography. Here we compare eDNA and gear-based assessments of marine fish populations using an approach that focuses on the commonest species. The protocol takes advantage of the "hollow curve" of species abundance distributions, with a minority of species comprising the great majority of individuals or biomass. We analyzed new and published teleost eDNA metabarcoding surveys from three neighboring northwest Atlantic coastal locations representing sandy, rocky, or estuary habitat. Fish eDNA followed a hollow curve species abundance distribution at each location-the 10 commonest taxa accounted for more than 90% of eDNA copies. Top ten taxa were designated eDNA-dominant species (eDDS) and categorized as habitat-associated (top 10 in one study) or as shared. eDDS by category were similarly abundant in concurrent bottom trawl and seine surveys. eDDS habitat category profiles correctly classified most (94%-100%) individual eDNA and capture measurements within surveys and recognized estuarine sites in other regional eDNA and seine studies. Using a category metric like that for habitats, eDDS demonstrated strong seasonal turnover concordant with trawl catch weights. eDNA seasonal profiles applied to historical trawl and seine records highlighted known long-term trends in mid-Atlantic fish populations. This study provides evidence that eDNA-abundant fish species differ among coastal habitats and by season consistent with gear-based assessments. Grouping abundant species by category facilitated comparisons among habitats and integration with established surveys. eDNA metabarcoding of dominant fish species potentially offers a useful tool for marine biogeography and ocean monitoring.

What types of nature exposure are associated with hedonic, eudaimonic and evaluative wellbeing? An 18-country study

Although spending time in nature can improve subjective wellbeing (SWB), little is known about how different types of nature exposure are associated with different dimensions of SWB or the consistency of associations across national/cultural contexts. Using data from 18 countries, associations between green, coastal and freshwater blue space exposures (including residential availability, visits ‘yesterday’ and visits in the previous four weeks) and hedonic, eudaimonic, and evaluative wellbeing were estimated. Overall, residential nature availability showed little association with any wellbeing outcome, whereas visiting green and coastal locations ‘yesterday’ was associated with better hedonic wellbeing. Although frequently visiting green, coastal and freshwater spaces were all associated with greater evaluative wellbeing, greater eudaimonic wellbeing was only associated with frequent visits to green and freshwater spaces. Variations existed across countries. Results suggest that different types of nature exposure vary in their association with different dimensions of SWB. Understanding these differences may help us maximise the potential of natural environments as SWB-promoting resources.

Scrub Typhus Outbreak among Soldiers in Coastal Training Area, Australia, 2022.

A scrub typhus outbreak occurred among 24 soldiers from 2 Australian Defence Force infantry units following separate training events conducted in the same coastal location in tropical North Queensland, Australia, in June 2022. Seven soldiers visited a hospital, 5 requiring admission. Outbreak recognition was hampered by the geographic dispersion of soldiers after the exercise and delayed case identification resulting from such factors as prolonged incubation, cross-reactive serologic responses to other pathogens, the nonspecific symptoms of scrub typhus, and the illness's nonnotifiable status in the state of Queensland. Our investigation focused on personal protective measures in a subanalysis of 41 soldiers, revealing an association between scrub typhus infection and the use of doxycycline chemoprophylaxis and permethrin uniform dipping.

Extremely Rare Finding of a Chiton (Mollusca, Polyplacophora) in a Rocky Intertidal Habitat in Nova Scotia (Canada)

Chitons are a group of mollusks (polyplacophores) that differ from the mollusks that are most often found on marine rocky shores (bivalves and gastropods). On the Atlantic coast of North America, chitons have been reported in subtidal habitats from Newfoundland (Canada) to New England (USA). Here, we report the finding of Boreochiton ruber in an intertidal habitat in Nova Scotia (Canada). After surveying various coastal locations across Nova Scotia for 20 years (2004 to 2024), this was the only intertidal chiton we ever found, making this an extremely rare occurrence. Rare species may contribute in unique ways to community functioning, making their reports valuable for biodiversity and ecosystem research.

Pengembangan Potensi Wisata dan Kesesuaian Lahan Wisata terhadap Resiko Tsunami di Kawasan Teluk Pacitan

The southern coastal region of Pacitan Regency, particularly in six districts, namely Ngadirejo, Sudimoro, Kebonagung, Donorojo, Pringkuku, and Pacitan District, is classified as a high-risk tsunami red zone. Based on the research findings, the Pacitan Bay area consists of two villages, namely Sidoarjo Village and Ploso Village in Pacitan Distict. Sidoarjo Village covers an area of 8.36 km², while Ploso Village covers 3.66 km², making the total area 12.02 km² or 1202 hectares. The analysis of land suitability for tourism in relation to tsunami risk aims to assess the level of compatibility of a tourist area located in a tsunami-prone region. The environmental vulnerability parameters include elevation, land slope, coastal morphology, land use, distance from the coastline, and distance from rivers. Additionally, bathymetric data and tsunami run-up based on historical tsunami events in the southern coastal areas of Java Island are utilized to assess the extent and depth of tsunami inundation. In the analysis of tourism suitability based on tsunami disaster mitigation, the suitable tourism area is located in the eastern part of Sidoarjo Village and the entire Ploso Village. These areas fall into the high tsunami risk zone, but their tourism potential is also high due to the coastal location of tourist attractions

How to use efficiently airborne criteria pollutants and radon-222 in source apportionment: A self-organizing maps approach

Pollutant source apportionment represents one of the fundamental activities in environmental science. Several efficient chemometric tools are available to the scope, mostly based on multivariate techniques and usually applied to aerosol chemical speciation data. In the present work, an alternative source profiling method is proposed, based on the self-organizing maps (SOM) algorithm. Moreover, the dataset used includes typical criteria pollutants and physical parameters related to airborne particulate matter widely used as a complement of aerosol source apportionment and largely available at a higher time resolution than bulk aerosol samplings, allowing the information on the dynamic behavior of the local airshed to be extended. In this work, data was collected at a coastal location in NW Italy, between January and July 2012. Hourly concentrations of typical gaseous pollutants (SO2, NO, NO2, benzene, toluene, (m-p)-xylene, o-xylene), black-carbon and particle number concentrations by an optical particle sizer (OPS) were collected. The dataset was integrated with radon-222 activity concentration and meteorological parameters to enrich and refine the information obtained by SOM computation as well as to improve the air pollution source localization. Despite the lower specificity of criteria pollutants, the approach developed was capable of revealing distinct pollution sources such as the urban background traffic, the coal-fired power plant active at the time of the study, and the harbor, in agreement with previous PM-based source apportionment studies carried out locally, while enlightening peculiar dynamical conditions detectable at the sub-daily time scale. The application of the SOM algorithm, with the integration of meteorological parameters and atmospheric radon, proved to be very efficient in unveiling the air pollution sources.

A Climatology of the Comprehensive Climate Index and Input Values for Türkiye, 1985–2014

Spatial and temporal variations and trends in the Comprehensive Climate Index (CCI) and relevant input values are presented and discussed for fifteen locations across Türkiye. Environmental conditions that are stressful to livestock are captured in the CCI model metrics, which are determined using input of temperature, humidity, wind speed, and solar radiation data. The period from 1985 to 2014 is used to characterize the climatology of CCI across Türkiye. Given its midlatitude location, pronounced seasonality exists in the individual input values and in CCI index values. Differences across Türkiye in CCI are strongly influenced by elevation and moderated for coastal locations. Warming temperature trends and declining levels of humidity combine to create a pattern where CCI has increased at some locations and declined at other places since 1985.

Integrated coastal vulnerability index for coastal flooding: A case study of the Croatian coast

The combination of accelerated urbanization and tourism-related activities, along with frequent coastal flooding, has generated pressure on the coastline of the Republic of Croatia (RH). In this paper, an integrated coastal vulnerability model (ICVI) for coastal flooding was developed. The ICVI was generated using a GIS multicriteria approach and derived from two sub-indices: the physical vulnerability index (CVIN) and the socio-economic vulnerability index (CVIS). In total, 30 criteria were used in the derivation of the ICVI, with twelve contributing to CVIS and eighteen to CVIN. The ICVI model is represented as a line divided into smaller segments, each segment indicating ICVI vulnerability levels ranging from 1 (very low) to 5 (very high). The accuracy of CVIN was evaluated using 159 geocoded coastal flood locations obtained from various websites and the official register of Hrvatske Vode flood events from 2008 to 2023. More than 80% of geocoded flood locations are situated in areas with very high (5) or high (4) CVIN. Furthermore, out of 32 settlements with officially registered flood events, 90.6% of them are located in areas with very high or high ICVI. Since all data used in the ICVI derivation were acquired from open-source databases and a user-friendly GIS-MCDA toolbox was utilized, this paper presents a cost-effective approach to modeling integrated coastal vulnerability. This model can guide decision-makers and provide them with new insights for implementing an effective integrated coastal zone management strategy.

2D nonlinear inversion of DC resistivity measurements, a case study; southeastern part of Ras El Dabaa, Northwestern coast, Egypt

The southern Mediterranean coast suffers from limited water resources as a result of exploitation of water supply, population growth, and climate change. Spatial lineaments and Seawater Intrusion (SWI) were detected at the southeast portion of Ras El Dabaa, on Egypt’s northwest coast, using the direct current resistivity (DCR) method. The Vertical Electrical Sounding (VES) data were acquired using Schlumberger array along four profiles and inverted both independently and jointly, aiming to obtain Two Dimensional (2D) geoelectrical images. The results of the one Dimensional (1D) inversion of VES data at each profile were stitched to form pseudo-2D sections on which the resistivity values and aquifer thickness in the southwest of the region appeared to be generally increasing, indicating a potential improvement in water quality.However, the results did not fully image the lateral variation but focused on the horizontal boundaries of the subsurface. On the contrary, the results of 2D inversion of the same data sets successfully managed to provide images that depicted resistivity distribution in both lateral and vertical directions. The detected sets of lineaments and fractured zones within the oolitic limestone and fossiliferous limestone units control the occurrence of groundwater in the region. The 2D inversion scheme revealed a low resistivity zone that indicated the presence of SWI and/or the dissolution of marine salts from the marine limestone bedrock of these aquifers in the northern portions of the studied area. Additionally, analysis of the 2D apparent porosity section shows how aquifers are connected by secondary porosity, which is defined by structures that resemble channels. The current approach offers valuable structural information for future planning and development of such complex geological coastal locations, taking into consideration the vulnerability of the groundwater system.