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Review

The Need for an Environmental Notification System in the Lithuanian Coastal Area

Marine Research Institute, Klaipėda University, H. Manto Str. 84, LT–92294 Klaipėda, Lithuania
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2023, 11(8), 1561; https://doi.org/10.3390/jmse11081561
Submission received: 30 June 2023 / Revised: 26 July 2023 / Accepted: 5 August 2023 / Published: 7 August 2023

Abstract

:
The Lithuanian coastal area is divided by the jetties of the Port of Klaipėda and represents two geomorphologically distinct parts. Local companies and institutions contribute to shaping the coastal area through infrastructure development. Awareness of the changes in the coastal zone can play an important role in the planning and economic feasibility of activities in the Klaipėda coastal region. Therefore, developing a notification system that provides long– and short–term monitoring data for the Lithuanian coastal zone is necessary. In order to do so, the authors intend to create a system that should provide a link between long– and short–term observation and monitoring data for stakeholders, such as wind speed and direction, wave direction and significant height, water and air temperature, atmospheric pressure, sediment size, and distribution, height above sea level, shoreline position, beach width, change in beach protection measures, beach wreckage, and marine debris management, in order to provide timely notifications to end users.

1. Introduction

Sandy beaches are coastal environments that change in time and space depending on the depositional morphology and hydrodynamic behavior of the region in which they are located [1,2,3]. A detailed understanding of nearshore physical processes is critical to the planning and implementation of coastal development programs. Coastal geomorphology can be significantly affected by the longshore and cross–shore sediment transport in the surf zone, shoreline position changes, hydrometeorological conditions, and various human activities in the coastal area [4,5,6,7].
Hydrometeorological conditions and various human activities significantly alter the morphological characteristics of the coastal area [7,8,9]. The cross–shore profile is an important tool for equilibrium beach assessment, coastal structure design and construction, and coastal protection strategy planning. It is also needed in coastal models for predicting beach dynamics [10,11]. Shoreline movement is the most commonly used indicator for assessing coastal erosion or accumulation processes. It could indicate various causes, such as storms, changes in wave–wind regimes, and human activities [12,13,14]. Monitoring the latter features could help predict changes in morphodynamics in the coastal area. Therefore, a detailed plan for monitoring coastal morphological features, hydrometeorological conditions, and human activities is critical to establishing an environmental notification system. In addition, the forecast and early notification system also serve as a long–term management tool, as it can simulate the response to future scenarios related to changing environments, such as mean sea level rise and/or storm intensity [15].
Since local businesses and institutions are the actors that contribute to the development and planning of the study area, they are also the ones that contribute to shaping the coastal zone [16]. Timely knowledge of the changes can play an important role in the planning and economic feasibility of the activities in the coastal area of the Klaipėda region. To address this issue, the authors attempted to develop an environmental alert system for timely maintenance solutions of the coastal zone—EASTMOC. To ensure the sustainability and optimal functioning of the EASTMOC system, local stakeholders—businesses, public institutions, and NGOs operating in the study area—were approached. Interviews helped identify the data (wind, waves, currents) that stakeholders use in their day–to–day operations, data sharing practices, data gaps (depth of a slope, monitoring, and other scientific data), and relevant thresholds for different sectors. Hydrometeorological thresholds place short–term limits on daily activities in the harbor area for port authorities, passenger ferries, and commercial fishermen. They can also have long–term implications that lead to changes in strategic plans at the municipal and national levels.
As noted in previous studies by authors [17,18,19,20], air temperature and wind direction were more important than other natural factors based on Bayesian networks because their conditional probability was higher than other variables. The most influential predictors of natural factors were the temperature and the temperature of the bathing water, which were acceptable and preferable for bathing according to the recreational needs of the inhabitants of Klaipėda [17]. Hydrometeorological conditions and anthropogenic factors are the main driving force for coastal development trends [21,22,23]. Coastal profile assessment shows a tendency for the underwater profile to steepen near the jetties, causing waves to reach the shore with higher energy [20]. Recreational activities in the coastal zone are not among the factors contributing to the changes. However, the changes directly influence them and depend on planners’ decisions to adjust and mitigate the influencing factors [20].
According to previous findings [18,19], a comparison of the shoreline changes in 1993–2003 and 2003–2022 revealed that the area of the eroded coast increased 4.4 times, from 2.73 km to 11.90 km. Significant coastal erosion extends north from the port jetties of Klaipėda with a net shoreline movement (NSM) value of −51.95 m [18,19]. Depending on the hydrometeorological and litho–geomorphological characteristics and the impact of the port, erosion processes should prevail [19,24]. Long–term changes in erosion might immediately impact society, influencing sectors such as coastal protection and shipping, among others [9,25].
The current phase of developing this concept includes creating a network of data sources to ensure the availability and accessibility of data among stakeholders. These sources are essential to the design of the overall notification system, as thresholds will be established based on these data. The aim of the EASTMOC concept is to bridge the gap in access to up–to–date data, serve as a hub for knowledge sharing, and provide early notification to various stakeholders according to thresholds established in accordance with the specifics of their activities.
The lack of a systemic approach to knowledge and data sharing is the main problem of this study. The authors of the paper operate under the premise that the shoreline, coastal evolution, and hydrometeorological data are the basis of the solution and a systemic approach to address the problem; EASTMOC being the delivery method.
This paper aims to demonstrate a proof of concept for EASTMOC and its practical potential for stakeholders operating in the study area. In addition, create an architecture for the system, address the knowledge gaps and create a knowledge–sharing platform, and determine thresholds that could limit activities or change the course of short– and long–term strategies. A pilot study was performed, and the results confirmed the feasibility of the system’s idea [18].

2. Materials and Methods

2.1. Study Site

Lithuanian nearshore is a part of the Baltic Sea and has a short sandy shoreline of approximately 90.6 km [26]. The country’s main harbor is located in the Klaipėda Strait on the eastern coast of the Baltic Sea, which connects it with the Curonian Lagoon [27,28] (Figure 1). During the last decade, the seaport rapidly developed and required several significant reconstructions. The last one was accomplished in 2002, including the construction of new quays and a fairway dredging [28]. These works have notably altered sediment transport processes in the Klaipėda Strait and nearshore [19,28,29]. Changes in the coastal processes are also presumed to be associated with natural factors such as regime shifts in the wind direction [19,20].
The angular distribution of winds and the geometry of the coast is such that the wave–induced longshore sediment transport is, on average, to the north over the entire Curonian Spit and the mainland coast of Lithuania [30,31,32]. This prevailing pattern of sediment flux means that variations in sediment availability or transport patterns along with these areas significantly affect the sediment budget north of Klaipėda [19,20]. Although sediment flows in the spit mainly occur under natural conditions, the further transport of sediments to the mainland coast of Lithuania is hindered by the jetties of the Klaipėda port, the currents coming out of the Klaipėda Strait, the deepening of the port inlet channel and other factors [19,20].
The study area is important for recreation [17,33]. Official beaches, accommodations, restaurants, and various tourist infrastructures are located near the shoreline. Tourism is a growing sector in the region, supported by a cruise terminal that opened in 2003 [17] and increasing passenger numbers on ferry connections to Germany and Scandinavian countries. The study area is located between two national resorts—Neringa and Palanga—and has characteristics of a resort in many respects. Although Klaipėda has no status granted by law, it is a residential area that contains scientifically studied and recognized natural healing factors. It has infrastructure for the use of these factors for wellness, tourism, and recreation purposes [34]. The vegetation consists mainly of pine trees [35]. The area offers a large concentration of resources important for health tourism and health promotion, such as the coastal microclimate, the therapeutic sapropel of the lagoon, amber, coastal algae, and many others [36].
The Port of Klaipėda, located on the Baltic Sea’s south–eastern shore, splits the Lithuanian coast into two geologically and geomorphologically distinct parts: southern—the Curonian Spit coast—and northern—the mainland coast. The port jetties disrupt the primary sediment movement and substantially impact the northern area of the Lithuanian coast [19,37]. Only Quaternary sediments are discovered on the Baltic Sea coast of Lithuania. Geologically, the mainland shore and the Curonian Spit coast are not homogeneous. The sediments produced during the past several glaciations largely impacted the geological structure of the continental coast [26]. The Curonian Spit coast’s sediments developed in the Baltic Sea basin, beginning with the Baltic Ice Lake and ending with the present Baltic Sea stage [26]. Sandy sediments form the Curonian Spit coast: this Lithuanian coastal region is distinguished by accumulation processes. The Lithuanian mainland coast is more geologically diverse: the northern section is dominated by fine–grained sand (0.25–0.1 mm), and the southern and central parts are dominated by medium–grained (0.5–0.25 mm) and coarse–grained (1–2.5 mm) sand (Table 1) [19,38]. Since longshore sediment transport along the Lithuanian coast is directed from south to north, the mainland coast is affected by erosion, which explains the diversity of the sediment distribution [19,20,26].
The two parts of the case study differ in more than geomorphological features alone (Table 1). Differences between the two areas are recognized and utilized differently by the users of the Klaipėda municipality, the district, and tourists. Both parts are held in high regard; however, their value is not equal. The entire Lithuanian coast is part of Natura 2000 sites and contains national nature–protected areas. However, only the Curonian Spit is inscribed in UNESCO World Heritage sites as a unique, vulnerable sandy wooded cultural landscape with documented Outstanding Universal Value.
Coastal areas are among the most developed and populated land areas in the world, as the majority of the world’s population lives near the coast [39,40,41,42]. The same is true for tourists [43]. Beach tourism is an important pillar of the tourism industry due to the inevitable attraction of the beach [44,45]; proximity to the water and the world’s oceans attracts tourists. Therefore, their preferences are the best determinant of the value of a particular destination [46]. The beaches on both sides have been used as recreational areas for many years [47]. Currently, there is a 3400 m stretch for official beaches in study area A and a 4420 m stretch in area B [17]. The larger part of the Lithuanian part of the Curonian Spit is located in the municipality of Neringa, which is a resort town. In connection with the state–recognized status of Neringa, the municipality of Klaipėda and inhabitants of Smiltynės settlement are driving a process to grant this part of the Spit the status of a resort area.
Since 2001, the Klaipėda Port entrance channel of Klaipėda harbour has been dredged, and the clean dredged sand, meeting sanitary requirements, is used to restore the sediment budget of the mainland and replenish the coast [19,29,37]. These sand replenishment campaigns have significantly impacted the Melnragė–Giruliai section of area B, where a decrease in the erosion process can be observed [19].
Since 2002, the beaches of the Curonian Spit in the municipality of Neringa have been awarded the Blue Flag. Since 2017 (Smiltynės I) and 2018 (Melnaragės II), the beaches in the study area have also received this recognition.
The Curonian Spit has a land connection via the Russian Federation, as the two neighboring countries share the Spit. However, this access is restricted by the visa regime in the usual circumstances. Currently, access is completely closed due to the closed border between the two countries, leaving locals and tourists to predominantly rely on the regular ferry connection and continue by road. Meanwhile, anyone wishing to visit the mainland coast has much easier access through various land transport options.
The construction of a bridge between Klaipėda and the Curonian Spit has been debated for decades. This highlights another significant difference between the two areas—building restrictions and development limitations that come with the exceptional value of the Curonian Spit [48].

2.2. Data Sources

Shoreline: aerial maps, orthophotos, and survey datasets from GPS determined shoreline positions from 1993 to 2022. A dual–band “Leica 900” GPS receiver measured the shoreline position in the swash zone’s middle. Historical shoreline positions were measured every 25 m along the shoreline in 800 transects. Shoreline position changes were analyzed with the ArcGIS extension DSAS v. 5.0 (Digital Shoreline Analysis System) package [49], developed by the United States Geological Survey (USGS).
Coastal elevation: the analysis of coastal geomorphology and underwater elevation changes was calculated from bathymetry data from 1993–2022 using Global Mapper software [50]. It indicated that reconstruction works and continuous dredging of Klaipėda harbor affected the sediment budget along the study area. Bathymetry data were obtained from the Klaipėda Port Administration with a grid resolution of 0.5 m and from the Lithuanian Geological Survey with a grid resolution of 1.5 m. The data provided were obtained using a Kongsberg EM2040C multibeam echo sounder in accordance with the International Hydrographic Organization’s Standards for Hydrographic Surveys S–44 [51].
Hydrometeorological: the hydrometeorological data used for this study were obtained from the Marine Environment Assessment Division of the Environmental Protection Agency, the Lithuanian Hydrometeorological Service, which is under the Ministry of Environment, the Palanga Aviation Meteorological Station, and the National Oceanic and Atmospheric Administration. Data were initially collected at the Klaipėda meteorological station on the Lithuanian Baltic coast and processed by the authors. The Klaipėda meteorological station is located near the Klaipėda Sea port jetties.

2.3. Methods

Analysis of long–term trends in shoreline changes showed that the stable operating processes of shoreline formation, which determine and form the balance of shoreline change, have intensified due to the anthropogenic impact of port reconstruction.
Shoreline positions were determined from aerial photo charts, orthophotos, and GPS survey data sets. The shoreline position was measured in the middle of the swash zone by a dual–band GPS receiver, “Leica 900”. Historical coastline positions are measured every 25 m along the coastline. Three coastline positioning and detection errors were calculated [52]:
(1)
for the aerial photo charts
Ut = ±(Es2+ Ed2 + Ep2+ Etc2 + Ec2)1/2,
(2)
for the orthophotos
Ut = ±(Es2+ Ed2 + Ep2 + Er2 + Ec2)1/2,
(3)
for the GPS survey data
Ut = Ut = ±(Es2 + Ec2)1/2
where Es—sea–level fluctuation error, Ed—digitization error, Ep—pixel error, Ec—shoreline line detection or resolution errors, Etc—T–sheets plotting errors, and Er—rectification error. Shoreline position changes were analyzed with the ArcGIS extension DSAS v. 5.0 (Digital Shoreline Analysis System) package [49], developed by the United States Geological Survey (USGS).
Analysis of the coastal geomorphology and underwater slope changes were calculated from the bathymetry data using Global Mapper software [50] and helped identify that the reconstruction works and the continuous dredging of the Klaipėda port influenced the sediment budget along the study area. In the period of 2003–2022, about 2.5 km north of the port jetties, a bottom sediment deficit was observed, where the coastal elevation has lowered about 5–7 m. The sediment loss during seaport reconstruction corresponds to hydro–technical constructions and changes in their configuration. The Port of Klaipėda’s north jetty site has been altered, and the entry channel has narrowed, creating changes in nearshore hydrodynamics and sediment movement [20]. Throughout the study period from 1993 to 2022, a steepening of the undersea bottom profile was detected in close proximity to the Port of Klaipėda jetties; as a result, waves reached the beach with more intensity [20].

3. Results and Discussion

3.1. Background for EASTMOC

The location of the Port of Klaipėda jetties interrupts, at this point of the south–eastern Baltic Sea, the natural path of longshore sediment transport from south to north [19,20,29,31,53]. This should create favorable conditions for two different processes: accumulation on the Curonian Spit south of the jetties and erosion north of the jetties. Although the long–term analysis of shoreline changes in the whole study area indicates a total positive shoreline shift towards the sea, at an average velocity of 0.43 ± 0.03 m/yr, over the 35 years, the shoreline had different trends in both geomorphological and temporal changes [19]. In the long term, the accumulated coastal stretch includes the 10 km shoreline of the Curonian Spit south of the southern Klaipėda seaport jetties [19]. The mainland coast, which comprises the northern part of the study area, is affected by erosive processes [19,20].
The grain size distribution of sediments is a natural result of sediment transport processes, mainly related to erosion and accumulation [54,55,56]. During the study period from 2003 to 2022, the grain size of sediments on the mainland coast became finer and more evenly distributed in the profiles. This could be due to the beach replenishment works carried out by the authorities of the Port of Klaipėda. On the other hand, sediments became coarser on the Curonian Spit coast between 2003 and 2022. This observation confirms the authors’ statement of previous works, in which the coastal erosion on both coasts was determined [19,20].
Hydrometeorological data alone could not explain current changes. It is a common understanding that there should be a holistic approach to the question and use of modeling. This is to ensure that decision–makers operating in the Klaipėda coastal zone are well–informed about the causation of coastal dynamics. The authors of the study attempt to do so in a timely manner so that needed decisions can be made and implemented in due time. Development of the EASTMOC system results from this collaboration, where stakeholders are the initiators.
Net shoreline movement analysis for the entire study period 1993–2022 confirmed that 39.05% of the shoreline was erosive, 34.04% accumulative, and 26.53% was stable or within the range of uncertainty ±5.02 m (Figure 2). The Curonian Spit coast’s net volume was −2,615,669.7 m3, whereas the mainland coast’s net volume was −429,631.47 m3, according to Global Mapper’s (Figure 2) calculations for 1993 to 2022. Net sediment volume on the mainland coast was −348,070.61 m3, and on the Curonian Spit was −4,633,217.1 m3 in 1993–2003, before the reconstruction of Klaipėda seaport, which took place in 2002. Sediment loss on the mainland coast increased to −1,520,535.2 m3 in the years following reconstruction, from 2003 to 2022, compared to the prior years. In contrast, the Curonian Spit experienced a decrease in sediment loss to −553,413.63 m3 [20].
Endpoint rate shoreline change for 1993–2022 confirmed that accumulation processes dominate the Curonian Spit coast while the mainland coast is eroded (Figure 3). The most significant erosion occurrence was observed in the nearest proximity to the northern port jetty. In the period after the Port of Klaipėda reconstruction, erosion processes intensified on both the Curonian Spit and mainland coasts (Figure 3) [19]. During 1993–2022 on average, the shoreline changed by –0.01 ± 0.04 m/yr, meaning that the shoreline moved landward on both coasts. In the period before the Port of Klaipėda reconstruction, 1993–2003, the endpoint rate on average was 0.67 ± 0.07 m/yr, and in the period after reconstruction, 2003–2022, the erosion rate increased on average to –0.35 ± 0.04 m/yr (Figure 3).
The need for the alert system occurred after several meetings with stakeholders concerning the research the team is currently carrying out. In 2022 it was especially true when the planned coastal protective measures were carried out—the beach enrichment campaign in the northern part of the Klaipėda coast in Spring. Even though the weather conditions were stable, coastal erosion was prominent and raised the concern of the Municipality and port authorities. The Port of Kaipėda is also highly affected by the Curonian Lagoon processes [57,58], and the annual dredging campaign is essential to ensuring its activities’ stability [59,60]. More context is needed to operate in the area and make informed, sustainable decisions. A knowledge gap exists regarding long and cross–shore sediment transport in the Curonian Lagoon and the Baltic Sea. Those processes are evaluated based on the literature [31,61,62,63], as no actual data or research has been done in this area. Researching long– and cross–shore sediment transport in the study area would require funding and technical solutions.

3.2. Pilot Study

Stakeholder mapping was performed in the first step of the pilot study, and all actors in the Klaipėda Port impact area were identified alongside possibly affected institutions and organizations. The pilot study was performed in cooperation with ten selected stakeholders that provided the following data: relevant information on natural factors that is essential to their continuous operations, information gaps, and main thresholds limiting their day–to–day operations and/or planning strategies. Selected stakeholders include the main actors operating in the area: Klaipėda State Sea Port Authority, the biggest operator acting on the national level, SC “Smiltynės perkėla” provides regular passenger ferry connections to the Curonian Spit; Lithuanian Transport Safety Administration and others.
The most relevant data on natural factors used for day–to–day operations and future plans were indicated as follows: beach width and length, underwater slope (depth), shoreline position, significant wave height and direction, wind speed and direction, and current speed and direction, ice cover, and visibility. First, important gaps were identified as nearshore bathymetry (0–6 m depth), hydrological data of rivers and the Curonian lagoon, and easy access to real–time hydrometeorological data.
Various stakeholders act in a small area, and their activities depend on different variables and the nature and scale of their operations. For example, the need to limit operations of passenger ferries occurs at the following conditions (to name a few): wind speed 14 m/s; southwest 240°, west 270° turning north 300°; long waves—southwest/west direction. Monitoring operations and shipping of small vessels in the nearshore area can be limited at a wind speed of 7 m/s and above a wave height of 1.5 m.
Stakeholders also identified that shoreline position is the most commonly used indicator for assessing coastal erosion or accumulation processes and is important for the long–term planning of their activities. Port reconstruction, planning, and beach nourishment depend on the long–term changes as they could serve as a prediction model.
The gathered data supports the need for sharing knowledge in a timely manner. The team concluded that, for the moment, it is possible to cater to several select stakeholders and provide monitoring data and personalized alerts. However, the datasets need to be continuously updated daily. This creates a need for an automated system and timely data input in order to support the idea of the study—to provide access to the database to every interested institution or possibly on a personal level.

3.3. EASTMOC System

In order to provide timely notifications to end users, the EASTMOC system (Figure 4) is intended to create a link between long– and short–term observation and monitoring data to stakeholders, such as wind speed and direction, wave direction and significant height, water and air temperature, atmospheric pressure, sediment size and distribution, cross–shore elevation, shoreline position, beach width, change in beach protection measures, beach wreck, and marine debris management.
Local businesses and institutions contribute to shaping the coastal area through infrastructure development. Awareness of the changes in the coastal zone can play an essential role in the planning and economic feasibility of activities in the Klaipėda coastal region. Therefore, to ensure the sustainability and optimal functioning of EASTMOC, local stakeholders—businesses, public institutions, and non–governmental organizations operating in the study area—were consulted. Discussions with stakeholders helped identify the data (e.g., wind, waves, currents) they use in their day–to–day operations, data sharing practices, data gaps (slope depth, monitoring, and other scientific data), and relevant thresholds for various industries that form the basis for the EASTMOC notification system (Figure 5).
To identify and predict trends in various processes, looking at long–term data spanning years, decades, or even centuries is necessary. Such time scales reveal how the system under study behaves under different processes or conditions. For example, how changing wind directions and velocities alter certain sections of the beach (erosion or accumulation). Such long–term data are important to companies and institutions operating in the coastal zone because they determine their long–term strategic plans, coastal zone infrastructure development, and beach replenishment needs. In the short–term, coastal zone changes may interest local residents, transportation companies, port operations, tourists, and extreme sports enthusiasts.
The chosen tool for implementing the EASTMOC system is Bayesian Networks (BNs). The Bayesian Network’s approach is particularly useful in complex systems where multiple factors interact to produce outcomes [64]. By incorporating a wide range of variables, the model can capture the distinctions and interdependencies of the system, leading to more accurate predictions and better–informed decision–making. Additionally, the iterative nature of the modeling process allows for ongoing alteration and improvement as new data and insights emerge. This can lead to a more robust and adaptable model that can respond to changing conditions over time. Overall, the use of systems thinking and integrated modeling approaches has the potential to revolutionize our understanding of complex systems and inform more effective strategies for sustainably managing them.
As previous research from the authors shows [17], the Bayesian Networks application will provide a continuous evaluation of understanding as new information occurs, each time updating the probability that something is true. The BN modeling methodology helps to represent the causal relationships of a system in the context of variability, uncertainty, and subjectivity; elicits subjective expert opinion; and provides a framework for model improvement as new data and knowledge become available [64].
The pilot study results demonstrate a proof of concept for the EASTMOC and its potential value for stakeholders operating in the study area. The architecture of the system addresses the knowledge gaps. It has the potential to provide a knowledge–sharing platform as well as determine thresholds that could limit activities or change the course of short and long–term strategies in the study area or could be applied in other areas in the future.

4. Conclusions

The development of EASTMOC drew the research team’s attention to the distinctions between two different sides of the study area. In addition to geomorphological differences, the two parts also differ regarding access, social and economic values, and use. Therefore, their evaluation in the system should be done separately and comprise unique data sets.
The pilot study and the identified thresholds proved the need for a notification system. Moreover, the stakeholder initiative has identified the features and characteristics of the coastal area that need to be monitored more closely. Their participation underpins the feasibility of a functioning system.
Further steps are needed to advance the development of the EASTMOC into a fully functional system. It is expected that stakeholders and various actors in the Klaipėda Port impact area will initially use the system. Additional funding will be required to make the system available to the general public.

Author Contributions

Conceptualization, I.Š. and V.K.; methodology, I.Š. and V.K.; software, V.K.; validation, I.Š., V.K. and E.B.; formal analysis, I.Š.; investigation, V.K.; resources, E.B. and V.G.; data curation, V.G.; writing—original draft preparation, I.Š.; writing—review and editing, E.B.; visualization, V.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Quadrado, G.P.; Goulart, E.S. Longshore sediment transport: Predicting rates in dissipative sandy beaches at southern Brazil. SN Appl. Sci. 2020, 2, 1421. [Google Scholar] [CrossRef]
  2. Eelsalu, M.; Parnell, K.E.; Soomere, T. Sandy beach evolution in the low–energy microtidal Baltic Sea: Attribution of changes to hydrometerological forcing. Geomorphology 2022, 414, 108383. [Google Scholar] [CrossRef]
  3. George, J.; Sanil Kumar, V.; Victor, G.; Gowthaman, R. Variability of the local wave regime and the wave–induced sediment transport along the Ganpatipule coast, eastern Arabian Sea. Reg. Stud. Mar. Sci. 2019, 31, 100759. [Google Scholar] [CrossRef]
  4. Sundar, V.; Sannasiraj, S.A. Longshore sediment transport rate from the field measured wave and sediment characteristics along the coast of Karaikal, India. ISH J. Hydraul. Eng. 2022. [Google Scholar] [CrossRef]
  5. Belibassakis, K.A.; Karathanasi, F.E. Modelling nearshore hydrodynamics and circulation under the impact of high waves at the coast of Varkiza in Saronic–Athens Gulf. Oceanologia 2017, 59, 350–364. [Google Scholar] [CrossRef]
  6. Karathanasi, F.E.; Belibassakis, K.A. A cost–effective method for estimating long–term effects of waves on beach erosion with application to Sitia Bay, Crete. Oceanologia 2019, 61, 276–290. [Google Scholar] [CrossRef]
  7. Hapke, C.J.; Kratzmann, M.G.; Himmelstoss, E.A. Geomorphic and human influence on large–scale coastal change. Geomorphology 2013, 199, 160–170. [Google Scholar] [CrossRef]
  8. Anderson, D.; Ruggiero, P.; Antolínez, J.A.A.; Méndez, F.J.; Allan, J. A Climate Index Optimized for Longshore Sediment Transport Reveals Interannual and Multidecadal Littoral Cell Rotations. J. Geophys. Res. Earth Surf. 2018, 123, 1958–1981. [Google Scholar] [CrossRef]
  9. Weisse, R.; Dailidiene, I.; Hünicke, B.; Kahma, K.; Madsen, K.; Omstedt, A.; Parnell, K.; Schöne, T.; Soomere, T.; Zhang, W.; et al. Sea level dynamics and coastal erosion in the Baltic Sea region. Earth Syst. Dyn. 2021, 12, 871–898. [Google Scholar] [CrossRef]
  10. Gong, Z.; Jin, C.; Zhang, C.; Zhou, Z.; Zhang, Q.; Li, H. Temporal and spatial morphological variations along a cross–shore intertidal profile, Jiangsu, China. Cont. Shelf Res. 2017, 144, 1–9. [Google Scholar] [CrossRef]
  11. Reeve, D.E.; Horrillo–Caraballo, J.; Karunarathna, H.; Pan, S. A new perspective on meso–scale shoreline dynamics through data–driven analysis. Geomorphology 2019, 341, 169–191. [Google Scholar] [CrossRef]
  12. Almonacid–Caballer, J.; Sánchez–García, E.; Pardo–Pascual, J.E.; Balaguer–Beser, A.A.; Palomar–Vázquez, J. Evaluation of annual mean shoreline position deduced from Landsat imagery as a mid–term coastal evolution indicator. Mar. Geol. 2016, 372, 79–88. [Google Scholar] [CrossRef]
  13. Benkhattab, F.Z.; Hakkou, M.; Bagdanavičiūtė, I.; Mrini, A.E.; Zagaoui, H.; Rhinane, H.; Maanan, M. Spatial–temporal analysis of the shoreline change rate using automatic computation and geospatial tools along the Tetouan coast in Morocco. Nat. Hazards 2020, 104, 519–536. [Google Scholar] [CrossRef]
  14. Hanslow, D.J. Beach erosion trend measurement: A comparison of trend indicators. J. Coast. Res. 2007, 588–593. [Google Scholar]
  15. Fortes, C.J.E.M.; Reis, M.T.; Poseiro, P.; Santos, J.A.; Pinheiro, L.; Craveiro, J.; Rodrigues, A.; Sabino, A.; Silva, S.F.; Ferreira, J.C.; et al. HIDRALERTA Project: A Flood Forecast and Alert System in Coastal and Port Areas. IWA World Water Congr. Exhib. 2014, 21–26. [Google Scholar] [CrossRef]
  16. Phillips, M.R.; Jones, A.L. Erosion and tourism infrastructure in the coastal zone: Problems, consequences and management. Tour. Manag. 2006, 27, 517–524. [Google Scholar] [CrossRef] [Green Version]
  17. Baltranaitė, E.; Kelpšaitė-rimkienė, L.; Povilanskas, R.; Šakurova, I.; Kondrat, V. Measuring the impact of physical geographical factors on the use of coastal zones based on bayesian networks. Sustainability 2021, 13, 7173. [Google Scholar] [CrossRef]
  18. Kondrat, V.; Šakurova, I.; Baltranaitė, E.; Kelpšaitė–Rimkienė, L. EASTMOC: Environmental Alert System for Timely Maintenance of the Coastal Zone. Oceanography 2023, 36, 8. [Google Scholar] [CrossRef]
  19. Kondrat, V.; Šakurova, I.; Baltranaitė, E.; Kelpšaitė–Rimkienė, L. Natural and anthropogenic factors shaping the shoreline of klaipėda, Lithuania. J. Mar. Sci. Eng. 2021, 9, 1456. [Google Scholar] [CrossRef]
  20. Šakurova, I.; Kondrat, V.; Baltranaitė, E.; Vasiliauskienė, E.; Kelpšaitė–Rimkienė, L. Assessment of Coastal Morphology on the South–Eastern Baltic Sea Coast: The Case of Lithuania. Water 2023, 15, 79. [Google Scholar] [CrossRef]
  21. Ouillon, S. Why and how do we study sediment transport? Focus on coastal zones and ongoing methods. Water 2018, 10, 390. [Google Scholar]
  22. Keevallik, S.; Soomere, T. Regime shifts in the surface–level average air flow over the gulf of Finland during 1981–2010. Proc. Est. Acad. Sci. 2014, 63, 428–437. [Google Scholar] [CrossRef]
  23. Keevallik, S.; Soomere, T. Shifts in early spring wind regime in North–East Europe (1955–2007). Clim. Past 2008, 4, 147–152. [Google Scholar] [CrossRef] [Green Version]
  24. Cuevas Jiménez, A.; Euán Ávila, J.I.; Villatoro Lacouture, M.M.; Silva Casarín, R. Classification of Beach Erosion Vulnerability on the Yucatan Coast. Coast. Manag. 2016, 44, 333–349. [Google Scholar] [CrossRef]
  25. Weisse, R.; Bisling, P.; Gaslikova, L.; Geyer, B.; Groll, N.; Hortamani, M.; Matthias, V.; Maneke, M.; Meinke, I.; Meyer, E.M.; et al. Climate services for marine applications in Europe. Earth Perspect. 2015, 2, 3. [Google Scholar] [CrossRef] [Green Version]
  26. Bitinas, A.; Žaromskis, R.; Gulbinskas, S.; Damušyte, A.; Žilinskas, G.; Jarmalavičius, D. The results of integrated investigations of the Lithuanian coast of the Baltic Sea: Geology, geomorphology, dynamics and human impact. Geol. Q. 2005, 49, 355–362. [Google Scholar]
  27. Jakimavičius, D.; Kriaučiūnienė, J.; Šarauskienė, D. Impact of climate change on the Curonian Lagoon water balance components, salinity and water temperature in the 21st century. Oceanologia 2018, 60, 378–389. [Google Scholar] [CrossRef]
  28. Kriaučiūnienė, J.; Gailiušis, B.; Rimavičiūtė, E. Modelling of shoreface nourishment in the Lithuanian nearshore of the Baltic Sea. Geologija 2006, 53, 28–37. [Google Scholar]
  29. Žilinskas, G.; Janušaitė, R.; Jarmalavičius, D.; Pupienis, D. The impact of Klaipėda Port entrance channel dredging on the dynamics of coastal zone, Lithuania. Oceanologia 2020, 62, 489–500. [Google Scholar] [CrossRef]
  30. Kelpšaitė, L.; Dailidiene, I. Influence of wind wave climate change on coastal processes in the eastern Baltic Sea. J. Coast. Res. 2011, 220–224. [Google Scholar]
  31. Viška, M.; Soomere, T. Simulated and observed reversals of wave–driven alongshore sediment transport at the eastern baltic sea coast. Baltica 2013, 26, 145–156. [Google Scholar] [CrossRef] [Green Version]
  32. Soomere, T.; Bishop, S.R.; Viška, M.; Räämet, A. An abrupt change in winds that may radically affect the coasts and deep sections of the Baltic Sea. Clim. Res. 2015, 62, 163–171. [Google Scholar] [CrossRef] [Green Version]
  33. Inácio, M.; Gomes, E.; Bogdzevič, K.; Kalinauskas, M.; Zhao, W.; Pereira, P. Mapping and assessing coastal recreation cultural ecosystem services supply, flow, and demand in Lithuania. J. Environ. Manag. 2022, 323, 116175. [Google Scholar] [CrossRef]
  34. Tourism Law of the Republic of Lithuania. 2018. Available online: https://e-seimas.lrs.lt/portal/legalAct/lt/TAD/3c3504d2804011e89188e16a6495e98c (accessed on 29 June 2023).
  35. Kutorga, E.; Adamonyte, G.; Iršenaite, R.; Juzenas, S.; Kasparavičius, J.; Markovskaja, S.; Motiejunaite, J.; Treigiene, A. Wildfire and post–fire management effects on early fungal succession in Pinus mugo plantations, located in Curonian Spit (Lithuania). Geoderma 2012, 191, 70–79. [Google Scholar] [CrossRef]
  36. Armaitiene, A.; Bertuzyte, R.; Vaskaitis, E. Conceptual Framework for Rethinking of Nature Heritage Management and Health Tourism in National Parks. Procedia—Soc. Behav. Sci. 2014, 148, 330–337. [Google Scholar] [CrossRef] [Green Version]
  37. Jarmalavičius, D.; Žilinskas, G.; Pupienis, D. Impact of Klaipda port jetties reconstruction on adjacent sea coast dynamics. J. Environ. Eng. Landsc. Manag. 2012, 20, 240–247. [Google Scholar] [CrossRef]
  38. Bagdanavičiūtė, I.; Kelpšaitė–Rimkienė, L.; Galinienė, J.; Soomere, T. Index based multi–criteria approach to coastal risk assesment. J. Coast. Conserv. 2019, 23, 785–800. [Google Scholar] [CrossRef]
  39. Luijendijk, A.; Hagenaars, G.; Ranasinghe, R.; Baart, F.; Donchyts, G.; Aarninkhof, S. The State of the World’s Beaches. Sci. Rep. 2018, 8, 6641. [Google Scholar] [CrossRef] [PubMed]
  40. Small, C.; Nicholls, R.J. A global analysis of human settlement in coastal zones. J. Coast. Res. 2003, 19, 584–599. [Google Scholar]
  41. Hallegatte, S.; Green, C.; Nicholls, R.J.; Corfee–Morlot, J. Future flood losses in major coastal cities. Nat. Clim. Chang. 2013, 3, 802–806. [Google Scholar] [CrossRef]
  42. Hinkel, J.; Nicholls, R.J.; Tol, R.S.J.; Wang, Z.B.; Hamilton, J.M.; Boot, G.; Vafeidis, A.T.; McFadden, L.; Ganopolski, A.; Klein, R.J.T. A global analysis of erosion of sandy beaches and sea–level rise: An application of DIVA. Glob. Planet. Change 2013, 111, 150–158. [Google Scholar] [CrossRef]
  43. Hasan, K.; Abdullah, S.K. Determining factors of tourists’ loyalty to beach tourism destinations: A structural model. Asia Pacific J. Mark. Logist. 2020, 32, 169–187. [Google Scholar] [CrossRef]
  44. Picken, F. The SAGE International Encyclopedia of Travel and Tourism 2017; SAGE: Newcastle upon Tyne, UK.
  45. Baltranaitė, E.; Jurkus, E.; Povilanskas, R. Impact of physical geographical factors on sustainable planning of South Baltic seaside resorts. Baltica 2017, 30, 119–131. [Google Scholar] [CrossRef]
  46. Azizah, F.N.; Kausar, D.R.K.; Gunadi, I.M.A.; Yuan, Y. The Preferences of Indonesian Outbound Tourists Toward Travel Types and Tourism Attributes. In Proceedings of the First International Conference on Global Innovation and Trends in Economy, InCoGITE, Java, Indonesia, 7 November 2019. [Google Scholar]
  47. Abromas, J.; Grecevičius, P.; Jankauskaitė, A.; Piekienė, N. Trends of Lithuanian Cultural Landscapes in the Recreational Territorial System of the Southeast Baltic Sea Region. Rural Sustain. Res. 2018, 39, 8–18. [Google Scholar] [CrossRef] [Green Version]
  48. Šimanauskienė, R.; Linkevičienė, R.; Povilanskas, R.; Satkūnas, J.; Veteikis, D.; Baubinienė, A.; Taminskas, J. Curonian Spit Coastal Dunes Landscape: Climate Driven Change Calls for the Management Optimization. Land 2022, 11, 877. [Google Scholar] [CrossRef]
  49. Himmelstoss, E.A.; Henderson, R.E.; Kratzmann, M.G.; Farris, A.S. Digital Shoreline Analysis System (DSAS) Version 5.0 User Guide; Open-File Report 2018-1179; US Geological Survey: Reston, VA, USA, 2018. [Google Scholar] [CrossRef] [Green Version]
  50. Marbel, B. GLobal Mapper Getting Started Guide; Blue Marble Geographics: Hallowell, ME, USA, 2019. [Google Scholar]
  51. Mills, G.B. International Hydrographic Organization Standards for Hydrographic Surveys. Int. Hydrogr. Rev. 2020, 6, 5–13. [Google Scholar]
  52. Crowell, M.; Leatherman, S.P.; Buckley, M.K. Shoreline Change Rate Analysis: Long Term Versus Short Term Data. Shore and Beach 1993, 61, 13–20. [Google Scholar]
  53. Soomere, T.; Viška, M. Simulated wave–driven sediment transport along the eastern coast of the Baltic Sea. J. Mar. Syst. 2014, 129, 96–105. [Google Scholar] [CrossRef]
  54. Le Roux, J.P.; Rojas, E.M. Sediment transport patterns determined from grain size parameters: Overview and state of the art. Sediment. Geol. 2007, 202, 473–488. [Google Scholar] [CrossRef]
  55. Prodger, S.; Russell, P.; Davidson, M. Grain–size distributions on high–energy sandy beaches and their relation to wave dissipation. Sedimentology 2017, 64, 1289–1302. [Google Scholar] [CrossRef] [Green Version]
  56. Yu, X.; Zhan, C.; Liu, Y.; Bi, J.; Li, G.; Cui, B.; Wang, L.; Liu, X.; Wang, Q. Retrieval of Remotely Sensed Sediment Grain Size Evolution Characteristics along the Southwest Coast of Laizhou Bay Based on Support Vector Machine Learning. J. Mar. Sci. Eng. 2022, 10, 968. [Google Scholar] [CrossRef]
  57. Čerkasova, N.; Ertürk, A.; Zemlys, P.; Denisov, V.; Umgiesser, G. Curonian Lagoon drainage basin modelling and assessment of climate change impact. Oceanologia 2016, 58, 90–102. [Google Scholar] [CrossRef] [Green Version]
  58. Umgiesser, G.; Zemlys, P.; Erturk, A.; Razinkova–Baziukas, A.; Mezine, J.; Ferrarin, C. Seasonal renewal time variability in the Curonian Lagoon caused by atmospheric and hydrographical forcing. Ocean Sci. 2016, 12, 391–402. [Google Scholar] [CrossRef] [Green Version]
  59. Mežine, J.; Ferrarin, C.; Vaičiute, D.; Idzelyte, R.; Zemlys, P.; Umgiesser, G. Sediment transport mechanisms in a lagoon with high river discharge and sediment loading. Water 2019, 11, 1970. [Google Scholar] [CrossRef] [Green Version]
  60. Viška, M. Sediment Transport Patterns Along the Eastern Coasts of the Baltic Sea; Tallin University of Technology: Tallin, Estonia, 2014; ISBN 9789949236381. [Google Scholar]
  61. Žaromskis, R.; Gulbinskas, S. Main patterns of coastal zone development of the Curonian Spit, Lithuania. Baltica 2010, 23, 146–156. [Google Scholar]
  62. Lampe, R.; Nordstrom, K.F.; Jackson, N.L. Cross–shore Distribution of Longshore Sediment Transport Rates on a Barred Non–Tidal Beach. Estuaries 2003, 26, 1426–1436. [Google Scholar] [CrossRef]
  63. Marcot, B.G.; Penman, T.D. Advances in Bayesian network modelling: Integration of modelling technologies. Environ. Model. Softw. 2019, 111, 386–393. [Google Scholar] [CrossRef]
  64. Geurts, L. An Overview of the B Programming Language or B without Tears. ACM SIGPLAN Not. 1982, 17, 49–58. [Google Scholar] [CrossRef] [Green Version]
Figure 1. Overview of the study site, where I—Klaipėda, II—Klaipėda district, III—Municipality of Neringa, D1—distant dumping area, D2—near dumping area, and D3—nearshore dumping area, A—the Curonian Spit coast, B—the mainland coast.
Figure 1. Overview of the study site, where I—Klaipėda, II—Klaipėda district, III—Municipality of Neringa, D1—distant dumping area, D2—near dumping area, and D3—nearshore dumping area, A—the Curonian Spit coast, B—the mainland coast.
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Figure 2. (a) Transect positions along the study area, (b) net shoreline movement (m) during 1993–2003 and 2003–2022 along the study area, and (c) elevation change for 1993–2003 and 2003–2022, including underwater and onshore parts on both the Curonian Spit (A) and mainland (B) coasts (Adapted from Kondrat et al. 2023 [18] and Šakurova et al. 2023 [20] ).
Figure 2. (a) Transect positions along the study area, (b) net shoreline movement (m) during 1993–2003 and 2003–2022 along the study area, and (c) elevation change for 1993–2003 and 2003–2022, including underwater and onshore parts on both the Curonian Spit (A) and mainland (B) coasts (Adapted from Kondrat et al. 2023 [18] and Šakurova et al. 2023 [20] ).
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Figure 3. Endpoint rate shoreline change (m/yr) for periods 1993–2022, 1993–2003, and 2003–2022 on the Curonian Spit (A) and mainland (B) coasts.
Figure 3. Endpoint rate shoreline change (m/yr) for periods 1993–2022, 1993–2003, and 2003–2022 on the Curonian Spit (A) and mainland (B) coasts.
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Figure 4. Conceptual diagram of the EASTMOC system.
Figure 4. Conceptual diagram of the EASTMOC system.
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Figure 5. EASTMOC database structure, where the personal level is planned as a further study step.
Figure 5. EASTMOC database structure, where the personal level is planned as a further study step.
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Table 1. Key characteristics of the study site.
Table 1. Key characteristics of the study site.
A: The Curonian Spit CoastB: The Mainland Coast
Nature protected areasKuršių Nerija (Curonian Spit) National ParkBaltic Sea Thalassological Reserve, Pajūris Regional Park
Natura 2000 sitesCoastal area, nearshore, and coastal zone’s terrestrial areasCoastal area, nearshore, and coastal zone’s terrestrial areas
UNESCO World Heritage sitesCuronian Spit
Designated resortsNeringa
Official beachSmiltynės I, Smiltynės IIMelnragės I, Melnragės II, Handicapt, Girulių
Blue Flag sites Smiltynės I Melnragės II
State of shorelineMostly accumulativeMostly erosive
Granulometry Very well and moderately sorted fine sand prevails S orting of the sediments differs in a cross–shore profile
DumpingD1—distant dumping areaD2—near dumping area, D3—nearshore dumping area
2014932,711 m3114,571 m3 in a nearshore dumping area
2015779,645 m3581,820 m3 in near dumping area, 112,603 m3 in nearshore dumping area
2016672,778 m347,772 m3 in near dumping area, 29,548 m3 in nearshore dumping area
2017458,065 m328,273 m3 in near dumping area, 46,727 m3 in nearshore dumping area
2018945,482 m348,898 m3 in a nearshore dumping area
AccessibilityWaterway onlyOn land transportation
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Šakurova, I.; Kondrat, V.; Baltranaitė, E.; Gardauskė, V. The Need for an Environmental Notification System in the Lithuanian Coastal Area. J. Mar. Sci. Eng. 2023, 11, 1561. https://doi.org/10.3390/jmse11081561

AMA Style

Šakurova I, Kondrat V, Baltranaitė E, Gardauskė V. The Need for an Environmental Notification System in the Lithuanian Coastal Area. Journal of Marine Science and Engineering. 2023; 11(8):1561. https://doi.org/10.3390/jmse11081561

Chicago/Turabian Style

Šakurova, Ilona, Vitalijus Kondrat, Eglė Baltranaitė, and Vita Gardauskė. 2023. "The Need for an Environmental Notification System in the Lithuanian Coastal Area" Journal of Marine Science and Engineering 11, no. 8: 1561. https://doi.org/10.3390/jmse11081561

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