The coast and the nearshore is a resource of extremely high value to the Baltic States and a location of major conflict of interests by different user groups. It is an important ecosystem that supports human wellbeing, incl. providing food and recreational opportunities. It also has an important commercial function, supporting trade, the movement of people, and recreation through the beaches, ports and marinas. It is the buffer between land and sea, with coastal erosion and integrity of the nearshore ecosystem being a particular concern.
The project SOLIDSHORE titled in Estonian: Läänemere idaranniku looduslike randade ja rannikuehitiste jätkusuutlik tulevik and in English Solutions to current and future problems on natural and constructed shorelines, eastern Baltic Sea is financed from the European Economic Area (EEA) Financial Instrument 2014–2021 Baltic Research Programme (project EMP480).
This research brings together specialists from four partners:
Tallinn University of Technology (Partner 1, team leader Tarmo Soomere, firstname.lastname@example.org),
Klaipėda University (Partner 2, team leader Loreta Kelpšaitė-Rimkienė, email@example.com),
Norwegian University of Science and Technology (Partner 4, team leader Hans Bihs, firstname.lastname@example.org).
Each team brings into the consortium its own internationally recognized expertise, to provide solutions to the current and future problems that already and will affect how we use coastal resources.
The major source of energy to the nearshore are waves. Many of the problems we experience (such as erosion and port siltation) relate to how sediment (mainly gravel, sand and mud) is moved. Much current knowledge comes from open ocean and cannot be directly applied to very different conditions of the Baltic Sea.
We aim at providing environmentally friendly solutions to coastal problems in ways that very specifically account for the wave, water level and sediment conditions in the eastern Baltic Sea and are transferable for all similar water bodies. This is accomplished using i) data and knowledge that we currently have to provide much better and higher resolution knowledge about waves than are presently available, ii) by measuring sediment transport using novel sensors developed at TalTech, iii) by applying the new knowledge to examine how the interactions of waves and sediment impact the natural shores and coastal structures, and iv) provide tools so that coastal managers can make use of the knowledge produced to estimate how vulnerable are single coastal sections.
PROGRESS IN 2020
The first half-year of the project (June–December 2020) has already led to several publications about our progress in reputable journals (see below). Technically, it covered seven months from the formal Project Year 1 (01.06.2020–31.05.2021), with the following major tasks:
Wave and extreme water level model refinement. Simulation of the nearshore wave climate in high resolution for at least 45 years. Verification of the results against measured wave data. Field experiments towards quantification of variability of bottom loads and entrainment rates in short and short-crested wave fields.
Particular achievements (Partners 1–3 together; Partner 4 (Norway) will start from Project Year 2)
(1) [Extreme water levels] We have demonstrated that modelled extreme water levels in the eastern Baltic Sea have increased much faster than the global sea level rise in 1961–2005. The increase rates of water level maxima vary from about 1.5 to 10 mm/yr. The fastest increase in water level maxima occurred in the eastern Gulf of Finland (8–10 mm/yr), Gulf of Riga (6–9 mm/yr) and near Klaipėda (6–8 mm/yr). Most of the increase stems from stronger local storm surges. The upsurge of the water level maxima on the shores of Sweden and in the eastern Gulf of Bothnia is typically 3–4 mm/yr and is almost fully governed by the increase in the maximum water volume of the entire sea [Publication 1].
(2) [Refinement of water level regime in the study area] We analysed water level measurements from all 10 currently functioning coastal tide gauges on the Latvian shores for 1961–2018. The empirical probability distributions of different water levels have become narrower in 1991–2018 compared to 1961–1990. Very low water levels are now less frequent. The amplitude of the seasonal course of water level has greatly decreased. The annual mean and maxima of water level have increased in 1961–2018. This rate of increase is smaller than the rate of increase in the sea level in the North Atlantic suggesting that changes in the local drivers of water level mitigate the sea level rise in Latvian waters. Variations in the NAO index can explain 1/3 of the annual variability of the main properties of water level and up to 2/3 of this variability in wintertime .
(3) [Contribution of wave set-up into total water level] We have analysed in detail the appearance and properties of empirical probability of the occurrence of different set-up heights on an approximately 80 km long section of coastline near Tallinn. This phenomenon may substantially contribute to the formation of devastating coastal flooding in certain coastal areas that are open to predominant strong wind directions.
We have shown the probability distribution of wave set-up heights substantially deviates from a Rayleigh or Weibull distribution (that usually reflect the distribution of different wave heights). This distribution is usually fairly well approximated by a standard exponential distribution. However, in about 25% of the coastal segments, it matches a Wald (inverse Gaussian) distribution. This distribution systematically better matches the empirical probability distributions of set-up heights than the Weibull, exponential, or Gaussian distributions. In such segments, relatively high set-up events are likely .
(4) [Field experiments towards quantification of properties wave fields of different type] As an important step towards reaching the goals of the project, we tested and calibrated the spectrogram technique for the identification of single components of wave fields and for quantification of their properties and timing. This was done by in situ measurements of ship-generates waves in Tallinn Bay.
The structure of wakes is revealed using a Short Time Fourier Transform. Single wakes are detected based on Gabor multipliers. The results are compared with vessel passages retrieved from the Automatic Identification System (AIS) data. The algorithm detects the majority of ship wakes that can be visually recognized in spectrograms. As an interesting application, we made an attempt to calculate speed and distance of the detected ships. The method provides an option for mitigation of the impact of ship wakes in semi-enclosed water bodies.
This work was further developed using multisensor devices called hydromasts that track both pressure and near-bed current velocities. As above, the main tool for the analysis is a windowed Fourier transform that produces a spectrogram of the wave field. It is shown that time series from the pressure sensors, measured at a frequency of 100 Hz, 0.2 m above the seabed are a valid source of input data for the spectrogram technique. The use of several time series from synchronized multisensor systems substantially suppresses noise and improves the quality of the outcome compared to one-point measurements. As a side result, the obtained information about variations in the water flow in ship wakes provides a simple and reaso
nably accurate tool for rapid detection of ship passages. [3, 4].
We also addressed part of targets of Year 2 namely: Development and verification of express models for local sediment transport and related analytical techniques.
In particular, we analysed the possibilities to employ spatial statistical methods for the use in problems of coastal zone management in the conditions of the south-eastern Baltic Sea . This type of models are easy to apply as express models for rapid evaluation of the nature and magnitude of changes of the coast but they generally need some backup by dynamical models to provide functional input for decision-making.
Publications in 2020 of the research supported by the project SOLIDSHORE
1. Pindsoo, K., Soomere, T. 2020. Spatial variability in trends in water level extremes in the Baltic Sea. Continental Shelf Research, 193, art. no. 104029, doi: 10.1016/j.csr.2019.104029.
Extreme water levels in the Baltic Sea have increased much faster than the global sea level rise. We employ long-term simulations with the Rossby Centre Ocean (RCO) circulation model in 1961–2005 for the quantification of (i) spatial variability of the increase rate of water level maxima in this water body and (ii) the contribution from different water level components to this increase. The increase rates of water level maxima vary from about 1.5 to 10 mm/yr. These values do not involve the vertical crust movements. The fastest increase in water level maxima occurred in the eastern Gulf of Finland (8–10 mm/yr), Gulf of Riga (6–9 mm/yr), near Klaipėda (6–8 mm/yr) and in the south-western Baltic Sea (5–7 mm/yr). Most of the increase in these locations stems from stronger local storm surges. The upsurge of the water level maxima on the shores of Sweden and in the eastern Gulf of Bothnia is typically 3–4 mm/yr and is almost fully governed by the joint impact of global sea level rise and increase in the maximum water volume of the entire sea.
2. Rätsep, M., Parnell, K.E., Soomere, T. 2020. Detecting ship wakes for the study of coastal processes. Journal of Coastal Research, Special Issue No. 95, 1258–1262, doi: 10.2112/SI95-243.1.
Wakes from contemporary vessels may affect, and in some places dominate, coastal processes in the vicinity of major shipping lanes. The analysis of the properties and impact of wakes has generally been restricted to wakes that can be visually observed in raw data. In this work, spectral analysis of the time series of single-point measurements of water surface elevation from Tallinn Bay is used to highlight the structure of ship wakes using a Short Time Fourier Transform. This method makes it possible to determine the speed and distance of a vessel from the measurement site. Wakes are detected using an algorithm based on Gabor multipliers. The results are compared with vessel passages retrieved from the Automatic Identification System (AIS) data. The algorithm detects the majority of ship wakes that can be visually recognized in spectrograms and misses only those with low signal to noise ratio or those in close proximity to another vessel wake. The calculated speed and distance are consistent with the AIS data except for high-speed vessels sailing at ≥30 knots. The results indicate that by using these techniques the detection of vessel wakes from a single-point wave record is achievable under favorable weather conditions. The methods provide an option for mitigation of the impact of ship wakes in semi-enclosed water bodies.
3. Rätsep, M., Parnell, K.E., Soomere, T., Kruusmaa, M., Ristolainen, A., Tuhtan, J.A. 2020. Using spectrograms from underwater total pressure sensors to detect passing vessels in a coastal environment. Journal of Oceanic and Atmospheric Technology, 37(8), 1353–1363, doi: 10.1175/JTECH-D-19-0192.1.
Monitoring vessel traffic in coastal regions is a key element of maritime security. For this reason, additional ways of detecting moving vessels are explored by using the unique structure of their wake waves based on pressure measurements at the seabed. The experiments are performed at a distance of about 2 km from the sailing line using novel multisensor devices called ‘‘hydromasts’’ that track both pressure and near-bed water flow current velocities. The main tool for the analysis is a windowed Fourier transform that produces a spectrogram of the wake structure. It is shown that time series from the pressure sensors, measured at a frequency of 100 Hz, 0.2m above the seabed are a valid source of input data for the spectrogram technique. This technique portrays the properties of both divergent and transverse waves with an accuracy and resolution that is sufficient for the evaluation of the speed and distance of the detected vessels from the measurement device. All the detected passings are matched with vessels using automatic identification system (AIS) data. The use of several time series from synchronized multisensor systems substantially suppresses noise and improves the quality of the outcome compared to one-point measurements. Additional information about variations in the water flow in wakes provides a simple and reasonably accurate tool for rapid detection of ship passages.
4. Soomere, T., Pindsoo, K., Kudryavtseva, N., Eelsalu, M. 2020. Variability of distributions of wave set-up heights along a shoreline with complicated geometry. Ocean Science, 16, 1047–1065, doi: 10.5194/os-16-1-2020.
The phenomenon of wave set-up may substantially contribute to the formation of devastating coastal flooding in certain coastal areas. We study the appearance and properties of empirical probability density distributions of the occurrence of different set-up heights on an approximately 80 km long section of coastline near Tallinn in the Gulf of Finland, eastern Baltic Sea. The study area is often attacked by high waves propagating from various directions, and the typical approach angle of high waves varies considerably along the shore. The distributions in question are approximated by an exponential distribution with a quadratic polynomial as the exponent. Even though different segments of the study area have substantially different wave regimes, the leading term of this polynomial is usually small (between –0:005 and 0.005) and varies insignificantly along the study area. Consequently, the distribution of wave set-up heights substantially deviates from a Rayleigh or Weibull distribution (that usually reflect the distribution of different wave heights). In about three-quarters of the occasions, it is fairly well approximated by a standard exponential distribution. In about 25% of the coastal segments, it qualitatively matches a Wald (inverse Gaussian) distribution. The Kolmogorov–Smirnov test (D value) indicates that the inverse Gaussian distribution systematically better matches the empirical probability distributions of set-up heights than the Weibull, exponential, or Gaussian distributions.
5. [Joint publication of Estonian and Latvian teams] Männikus, R., Soomere, T., Viška, M. 2020. Variations in the mean, seasonal and extreme water level on the Latvian coast, the eastern Baltic Sea, during 1961–2018. Estuarine Coastal and Shelf Science, 245, art. no. 106827, doI: 10.1016/j.ecss.2020.106827.
High-resolution in situ water level data is one of the core sources for the identification and understanding the reaction of the sea to climate change. We analyse digitised recordings of water level measurements from all 10 currently functioning coastal tide gauges on the Latvian shores of the Baltic proper and in the Gulf of Riga for the period of 1961–2018. The frequency and temporal coverage of measurements vary greatly for these stations. The most complete hourly data are available from Liepaja on the Baltic proper coast and from Daugavgriva in the south-eastern bayhead of the Gulf of Riga. The water level regime is analysed from the viewpoint of (i) the entire range of w
ater level variations, (ii) empirical probability distributions of different water levels, (iii) the seasonal course of water level, (iv) trends in the annual, seasonal, and monthly means and extremes of water level (in terms of the relative and uplift corrected absolute values), and (v) correlations of the main properties of water level with the North Atlantic Oscillation (NAO Gibraltar) index. The empirical probability distributions of different water levels have become narrower in 1991–2018 compared to 1961–1990 whereas very low water levels are now less frequent. The amplitude of the seasonal course has greatly decreased over these time intervals. The annual mean and maxima of water level have increased in 1961–2018. The rate of increase is smaller than the rate of increase in the sea level in the North Atlantic suggesting that changes in the local drivers of water level mitigate the sea level rise in Latvian waters. Variations in the NAO index can explain 1/3 of the annual variability of the main properties of water level and up to 2/3 of this variability in wintertime (December–March). The changes in the statistical properties of water level are consistent with alterations to the directional structure of strong winds.
6. Borisenko, I., Kondrat, V., Valaitis, E., Kelpsaite-Rimkiene, L., Urboniene, R.O. 2020. Application of the spatial statistic methods to coastal zone management: SE Baltic Sea coast case. Journal of Coastal Research, Special Issue 95, 753-758, doi: 10.2112/SI95-147.1.
The coastal zone is one of the most dynamic environments in the world. Climate change is having an undeniable influence on coastal areas. The main climatic factors driving change in the Baltic Sea coastal zone are wind, waves, storm surges and flooding. Shoreline change is affected by a multitude of complex processes operating at various time- and length-scales.
The presented work aims at clarification of the effects of different hydro meteorological factor to the short-term shoreline evolution at the Palanga beach. The analysis of the hydrometeorological factors, in order to assess the dependence of the beach response on the wind, sea level and wave characteristics with the focus on short term effects of the coastal protection structures in the rapid transition stage immediately after beach nourishment activities.
PROGRESS IN 2021
The research targets in 2021 involved tasks from the formal Project Year 1 (01.06.2020–31.05.2021) and Project Year 2 (01.06.2021–31.05.2022):
Year 1: Wave and extreme water level model refinement. Simulation of the nearshore wave climate in high resolution for at least 45 years. Verification of the results against measured wave data. Field experiments towards quantification of variability of bottom loads and entrainment rates in short and short-crested wave fields.
Year 2: Refinement of sediment transport models and phase-resolving wave models, verification of models using targeted field experiments, development of new parameterisations of entrainment and their integration into sediment transport and morphological development models, development and verification of express models for local sediment transport and related analytical techniques.
As the organization of field work was complicated in 2020 because of COVID-19 pandemic, we decided to gather progress in single items scheduled to Year 3 (e.g., analysis of wave-induced dangers in terms of wave set-up) and to start preparations, wherever possible, for development of solutions that are scheduled to be finished in Year 4.
Particular achievements (Partners 1–3 together; Partner 4 (Norway) will start from the second half of Project Year 2):
(1) [Extreme water levels: further progress; see results in year 2020 above] We showed that the extreme water level regime is substantially non-stationary on the Latvian shores. While the parameters of the relevant extreme value distributions vary smoothly on the shores of the Baltic proper, the temporal variations in these parameters systematically contain regime shifts in the interior of the Gulf of Finland [Publication 4(10)].
(4) [Field experiments towards quantification of properties wave fields of different type: further progress; see results in year 2020 above] Further analysis made it possible to much more exactly solve the problem of localisation of ships based on certain asymptotic properties of specific features of the time-frequency diagrams of the wave recording [5(11)]. The use of multiple sensors makes it possible to adequately evaluate also the sailing direction [5(11)].
(5) [Observations of coastal processes] Assessment of the dependence of the beach response on the wind, sea level and wave characteristics with the focus on short term effects of the coastal protection structures in the rapid transition stage immediately after beach nourishment activities . Development of detailed understanding of cross-shore profile evolution at Palanga, eastern Baltic Sea, where short period waves dominate. This first involves observations a significant coastal erosion event caused in December 1999, complemented by further measurements 16 years later. The profile evolution was strongly influenced by the depth of closure which is constrained by a moraine layer, and the presence of a groyne [1(7)].
Coastal development near Klaipėda in Lithuania has adversely changed in the long-term perspective (1984–2019), possibly because of the Port of Klaipėda reconstruction in 2002. The eroded coast length increased from 1.5 to 4.2 km. However, accumulation has been mainly restored after the Port of Klaipėda peformed the coastal zone nourishment in 2014 [10(16)].
(6) [Nearshore wave climate] Wave simulations over 37 years using geostrophic winds underestimated wave heights whereas the hindcast using COSMO winds tended to overestimate wave heights. The hindcast forced with geostrophic winds is only adequate at the latitudes of the Gulf of Finland [2(8)].
The linear trends in the winter wave heights exhibit a prominent meridional pattern. Using the technique of Empirical Orthogonal Functions (EOF) applied to multi-mission satellite altimetry data, we explain a large part of this increase with the Scandinavia pattern, North Atlantic Oscillation and Arctic Oscillation climatic indices [9(15)].
(7) [Hot spots of accumulation of current-driven floating items] We developed the ability to predict hotspots of accumulation of current-drive debris on the shore. This capacity has a strong socio-economic importance in both efficient debris clean-up operations and in understanding of the long-term impact of current-driven sediment transport on certain accumulation areas.
(8) [Tools for decision-making] We present an approach to identify the social, economic, and environmental factors influencing the sustainability of coastal resorts. The results may be used to advise local governments on many Integrated Coastal Management matters: planning the development of the beaches and addressing the seasonality of use, directing investments to improve the quality of the beaches and protect them from storm erosion, and maintaining the sand quality and beach infrastructure [6(12)].
A detailed overview is provided of the construction and use of decision support systems as combinations of decision support tools, such as the commonly used multi-criteria decision analysis (MCDA) methods and an artificial neural network (ANN), integrated with a geographical information system (GIS) [7(13)]
A thorough overview of main known aspects of sea level dynamics and coastal erosion in the Baltic Sea region is provided in cooperation with 9 leading scientist in the region. For large parts of the sedimentary shores of the Baltic Sea, the wave climate and the angle at which the waves approach the nearshore region are the dominant factors, and coastline changes are highly sensitive to ev
en small variations in these driving forces. Processes contributing to Baltic sea level dynamics and coastline change are expected to vary and to change in the future, leaving their imprint on future Baltic sea level and coastline change and variability [8(14)].
(9) [From science to management] Most importantly, we reached the level of knowledge that was sufficient for providing concrete recommendations for management of the entire coastal zone and of its specific parts (Klooga-Rand, Narva-Jõesuu) in Estonia.
These recommendations were formulated as opinion papers in the leading daily newspaper Postimees (The Postman):
A description of three challenges in Narva-Jõesuu: reconstruction of a groin/jetty, pumping part of sand from the river mouth to the eastern part of the beach, and catching part of aeolian sand drift:
Soomere T. Kolm ülesannet Narva-Jõesuus. – Postimees, 211(7548), 08.10.2021, 12, https://arvamus.postimees.ee/7356411/tarmo-soomere-kolm-ulesannet-narva-joesuus.
An opinion paper about options for management of Estonian coasts: Soomere, T. Ranniku õiguste nõidus. – Postimees Nädal, 32(7603), 11.12.2021, 8, https://arvamus.postimees.ee/7405805/tarmo-soomere-ranniku-oiguste-noidus.
A description of the core properties of coastal processes on Estonian shores: Soomere, T., Parnell, K. Rannad tahavad vabalt hingata. – Postimees, 34(7605), 14.12.2021, https://arvamus.postimees.ee/7407785/tarmo-soomere-kevin-parnell-rannad-tahavad-vabalt-hingata.
On top of that, the knowledge developed and tested within the project was use in the Court case 4-20-351/47 (ECLI:EE:HMK:2020:4.20.351.14546, published in Riigi Teataja: https://www.riigiteataja.ee/kohtulahendid/detailid.html?id=270812696) where T. Soomere acted as an expert.
Publications in 2020 of the research supported by the project SOLIDSHORE
1(7). [Joint publication of Lithuanian and Estonian teams] Kelpšaitė-Rimkienė, L., Parnell, K.E., Žaromskis, R., Kondrat, V. 2021. Cross-shore profile evolution after an extreme erosion event—Palanga, Lithuania. Journal of Marine Science and Engineering, 9, art. no. 38, https://doi.org/10.3390/jmse9010038
We report cross-shore profile evolution at Palanga, eastern Baltic Sea, where short period waves dominate. Cross-shore profile studies began directly after a significant coastal erosion event caused by storm “Anatol”, in December of 1999, and continued for a year. Further measurements were undertaken sixteen years later. Cross-shore profile changes were described, and cross-shore transport rates were calculated. A K-means clustering technique was applied to determine sections of the profile with the same development tendencies. Profile evolution was strongly influenced by the depth of closure which is constrained by a moraine layer, and the presence of a groyne. The method used divided the profile into four clusters: the first cluster in the deepest water represents profile evolution limited by the depth of closure, and the second and third are mainly affected by processes induced by wind, wave and water level changes. The most intensive sediment volume changes were observed directly after the coastal erosion event. The largest sand accumulation was in the fourth profile cluster, which includes the upper beach and dunes. Seaward extension of the dune system caused a narrowing of the visible beach, which has led to an increased sand volume
2(8). Räämet, A., Soomere, T. 2021. Spatial pattern of quality of historical wave climate reconstructions for the Baltic Sea. Boreal Environment Research, 26, 29–41.
We address the accuracy of replication of wave properties of the Baltic Sea in two simulations of wave climate for the period of 1970–2007. Both are based on the spectral wave model WAM with a resolution of 3 nautical miles in hypothetic ice-free conditions. One of them used adjusted geostrophic wind fields from the Swedish Meteorological and Hydrological Institute database and the other applied high-resolution COSMO-CLM 4.8 winds. The outcome of both simulations is compared with available instrumentally measured wave heights. Simulations using geostrophic winds systematically underestimated wave heights whereas the hindcast using COSMO winds tended to overestimate wave heights. The run with COSMO winds provides an acceptable match with measured data in the entire sea. The hindcast forced with geostrophic winds is only adequate at the latitudes of the Gulf of Finland.
3(9). Ghosh, S., Suara, K., McCue, S.W., Yu, Y., Soomere, T., Brown, R.J. 2021. Persistency of debris accumulation in tidal estuaries using Lagrangian coherent structures. Science of the Total Environment, 781, art. no. 146808, https://doi.org/10.1016/j.scitotenv.2021.146808.
Coastal and estuarine ecosystems are heavily influenced through floating debris pollution. This often leads to low-quality coastal water and a negative impact on ecosystem health. The fate of debris, mostly originating from land is impacted by factors including river/tidal currents, winds, waves, and density gradients. The ability to predict hotspots of accumulation of debris has a strong socio-economic importance particularly in efficient debris clean-up operations. We show this can be done using Lagrangian coherent structures (LCSs), a technique highly robust to hydrodynamic model uncertainties. Here we present a comprehensive study showing the utility of this approach to predict areas of spontaneous material accumulation in Moreton Bay, a semi-enclosed subtropical embayment on the southeast Queensland of Australia. The backward finite-time Lyapunov exponent (FTLE) is used as a diagnostic for attracting LCSs, which identifies 11 debris accumulation hotspots. The material accumulation in these identified areas is asymmetric with most events occurring during the ebb tide and most pronounced in the spring tidal cycle, indicating a strong role of outflow in debris accumulation. The impact of wind enhances a high concentration of material accumulation in 8 identified areas of Moreton Bay. Importantly, the identified hotspots, mostly in the vicinity of islands and headland, match the areas in which there is a high level of historical debris collection. This approach thus provides a useful tool for effective clean-up management of vulnerable regions and marine protected areas.
4(10). Kudryavtseva, N., Soomere, T., Männikus, R. 2021. Non-stationary analysis of water level extremes in Latvian waters, Baltic Sea, during 1961–2018. Natural Hazards and Earth Systems Sciences, 21(4), 1279–1296, https://doi.org/10.5194/nhess-21-1279-2021.
Analysis and prediction of water level extremes in the eastern Baltic Sea are difficult tasks because of the contribution of various drivers to the water level, the presence of outliers in time series, and possibly non-stationarity of the extremes. Non-stationary modeling of extremes was performed to the block maxima of water level derived from the time series at six locations in the Gulf of Riga and one location in the Baltic proper, Baltic Sea, during 1961–2018. Several parameters of the generalized-extreme-value (GEV) distribution of the measured water level maxima both in the Baltic proper and in the interior of the Gulf of Riga exhibit statistically significant changes over these years. The most considerable changes occur to the shape parameter . All stations in the interior of the Gulf of Riga experienced a regime shift: a drastic abrupt drop in the shape parameter from
about 0.03+/-0.02 to -0.36+/-0.04 around 1986 followed by an increase of a similar magnitude around 1990. This means a sudden switch from a Fréchet distribution to a three-parameter Weibull distribution and back. The period of an abrupt shift (1986–1990) in the shape parameters of GEV distribution in the interior of the Gulf of Riga coincides with the significant weakening of correlation between the water level extremes and the North Atlantic Oscillation (NAO). The water level extremes at Kolka at the entrance to the Gulf of Riga reveal a significant linear trend in shape parameter following the -0.04+0.01(t-1961) relation. There is evidence of a different course of the water level extremes in the Baltic proper and the interior of the Gulf of Riga. The described changes may lead to greatly different projections for long-term behavior of water level extremes and their return periods based on data from different intervals.
5(11). Rätsep, M., Parnell, K.E., Soomere, T., Kruusmaa, M., Ristolainen, A., Tuhtan, J.A. 2021. Surface vessel localization from wake measurements using an array of pressure sensors in the littoral zone. Ocean Engineering, 233, 109156, https://doi.org/10.1016/j.oceaneng.2021.109156.
Vessel detection and localization based on wake measurements have been used extensively in aerial and satellite reconnaissance. Here, a wake-based approach for vessel localization and speed estimation is developed using a grid of pressure sensors on the seabed. The sensor array consisted of 9 devices in a 3 × 3 rectangular grid with 2.5 m spacing between the instruments. The array was deployed at a depth of 3 m approximately 2.5 km from the fairway. The pressure time series from all sensors were used to estimate vessel speed and the travelling distance of the wake by interpreting the geometry of its time-frequency representation. The wake direction and an estimate of the vessel course are calculated from the delays of the incoming wake between the sensor locations, equivalently, based on cross-correlations of the signal at neighbouring sensors. Results for single events are compared with data collected from the vessels self-reporting systems (AIS). It is concluded that a grid of pressure sensors can provide a reliable estimation of the vessel location and its speed. The presented technique makes it possible to locate ships, and their speed and course, as the next step towards a vessel traffic monitoring system based on wake recordings.
6(12). Baltranaitė, E., Kelpšaitė-Rimkienė, L., Povilanskas, R., Šakurova, I., Kondrat, V. 2021. Measuring the impact of physical geographical factors on the use of coastal zones based on Bayesian networks. Sustainability, 13, art. no. 7173, https://doi.org/10.3390/su13137173
Coastal regions of the Baltic Sea are among the most intensively used worldwide, resulting in a need for a holistic management approach. Therefore, there is a need for strategies that even out the seasonality, which would ensure a better utilization of natural resources and infrastructure and improve the social and economic conditions. To assess the effectiveness of coastal zone planning processes concerning sustainable tourism and to identify and substantiate significant physical geographical factors impacting the sustainability of South Baltic seaside resorts, several data sets from previous studies were compiled. Seeking to improve the coastal zone’s ecological sustainability, economic efficiency, and social equality, a qualitative study (content analysis of planning documents) and a quantitative survey of tourists’ needs expressed on a social media platform and in the form of a survey, as well as long-term hydrometeorological data, were used. Furthermore, a Bayesian Network framework was used to combine knowledge from these different sources. We present an approach to identifying the social, economic, and environmental factors influencing the sustainability of coastal resorts. The results of this study may be used to advise local governments on a broad spectrum of Integrated Coastal Management matters: planning the development of the beaches and addressing the seasonality of use, directing investments to improve the quality of the beaches and protect them from storm erosion, and maintaining the sand quality and beach infrastructure. The lessons learned can be applied to further coastal zone management research by utilizing stakeholders and expert opinion in quantified current beliefs.
7(13). Barzehkar, M., Parnell, K.E., Soomere, T., Dragovich, D., Engstrom, J. 2021. Decision support tools, systems, and indices for sustainable coastal planning and management: A review. Ocean & Coastal Management, 212, 105813, https://doi.org/10.1016/j.ocecoaman.2021.105813
Coasts worldwide are facing enormous challenges relating to extreme water levels, inundation and coastal erosion. These challenges need to be addressed with consideration given to the need for infrastructure such as for ports and other socio-economic developments, especially for coastal tourism. Choosing the optimal decision support tools (DSTs) for coastal vulnerability and resilience assessment is a major challenge for decision-makers and coastal planners. The robustness and flexibility of coastal decision-making can be improved by using effective DSTs, particularly for the management of coastal hazards. This study provides an overview of the construction and use of decision support systems (DSSs) as combinations of DSTs, such as the commonly used multi-criteria decision analysis (MCDA) methods and an artificial neural network (ANN), integrated with a geographical information system (GIS). The experience of many researchers is that the combination of MCDA techniques based on fuzzy logic, analytical hierarchy process (AHP) and weighted linear combination (WLC), with GIS, and possibly also incorporating ANN, provides decision-makers with a comprehensive tool for efficiently calculating decision support indices (DSIs). Hybrid tools are becoming more popular and relevant among experts due to their multiple functionalities that facilitate decision-making. An integration of DSTs in a DSS and further development of DSIs provides a path for the integration of quantitative and qualitative parameters into the decision-making process, and providing materials to be used in consultation processes. An integrated DSS is more likely to produce high-quality results for decision-makers, handle the uncertainty of analysis, and extend the long-term applicability of tools employed by coastal managers.
8(14). Weisse, R., Dailidienė, I., Hünicke, B., Kahma, K., Madsen, K., Omstedt, A., Parnell, K., Schöne, T., Soomere, T., Zhang, W., Zorita, E. 2021. Sea level dynamics and coastal erosion in the Baltic Sea region. Earth Systems Dynamics, 12, 871–898, https://doi.org/10.5194/esd-12-871-2021.
There are a large number of geophysical processes affecting sea level dynamics and coastal erosion in the Baltic Sea region. These processes operate on a large range of spatial and temporal scales and are observed in many other coastal regions worldwide. This, along with the outstanding number of long data records, makes the Baltic Sea a unique laboratory for advancing our knowledge on interactions between processes steering sea level and erosion in a climate change context. Processes contributing to sea level dynamics and coastal erosion in the Baltic Sea include the still ongoing viscoelastic response of the Earth to the last deglaciation, contributions from global and North Atlantic mean sea level changes, or contributions from wind waves affecting erosion and sediment transport along the subsiding southern Baltic Sea coast. Other examples are storm surges, seiches, or meteotsunamis which primarily contribute to sea level extremes. Such processes have undergone considerable variation and change in the past. For example, over approximately the past 50 years, the Baltic absolute (geocentric) mean sea level has risen at a rate
slightly larger than the global average. In the northern parts of the Baltic Sea, due to vertical land movements, relative mean sea level has decreased. Sea level extremes are strongly linked to variability and changes in large-scale atmospheric circulation. The patterns and mechanisms contributing to erosion and accretion strongly depend on hydrodynamic conditions and their variability. For large parts of the sedimentary shores of the Baltic Sea, the wave climate and the angle at which the waves approach the nearshore region are the dominant factors, and coastline changes are highly sensitive to even small variations in these driving forces. Consequently, processes contributing to Baltic sea level dynamics and coastline change are expected to vary and to change in the future, leaving their imprint on future Baltic sea level and coastline change and variability. Because of the large number of contributing processes, their relevance for understanding global figures, and the outstanding data availability, global sea level research and research on coastline changes may greatly benefit from research undertaken in the Baltic Sea.
9(15). Najafzadeh, F., Kudryavtseva, N., Soomere, T. 2021. Effects of large-scale atmospheric circulation on the Baltic Sea wave climate: application of EOF method on multi-mission satellite altimetry data. Climate Dynamics, 57(11–12), 3465–3478, https://doi.org/10.1007/s00382-021-05874-x.
Wave heights in the Baltic Sea in the period 1992–2015 have mainly increased in the sea’s western parts. The linear trends in the winter wave heights exhibit a prominent meridional pattern. Using the technique of Empirical Orthogonal Functions (EOF) applied to multi-mission satellite altimetry data, we explain a large part of this increase with the Scandinavia pattern, North Atlantic Oscillation and Arctic Oscillation climatic indices. The winter trends show a statistically significant negative correlation (correlation coefficient –0.47 ± 0.19) with the Scandinavia pattern and a positive correlation with the North Atlantic Oscillation (0.31 ± 0.22) and Arctic Oscillation (0.42 ± 0.20). The meridional pattern is associated with more dominant north-westerly and westerly winds driven by the Scandinavia pattern and North Atlantic Oscillation, respectively. All three climatic indices show a statistically significant time-variable correlation with Baltic Sea wave heights during the winter season. When the Scandinavia pattern’s influence is strong, the North Atlantic and Arctic Oscillation effects are low and vice versa. The results are backed up by simulations using synthetic data that demonstrate that the percentage of variance explained using EOF analysis from the satellite-derived wave measurements is directly related to the percentage of noise in the data and that the retrieved spatial patterns are insensitive to the level of noise.
10(16). Kondrat, V., Šakurova, I., Baltranaitė, E., Kelpšaitė-Rimkienė, L. 2021. Natural and anthropogenic factors shaping the shoreline of Klaipėda, Lithuania. Journal of Marine Science and Engineering, 9, art. no. 1456, https://doi.org/10.3390/jmse9121456.
Port of Klaipėda is situated in a complex hydrological system, between the Curonian Lagoon and the Baltic Sea, at the Klaipėda strait in the south-eastern part of the Baltic Sea. It has almost 300 m of jetties separating the Curonian Spit and the mainland coast, interrupting the main path of sediment transport through the South-Eastern coast of the Baltic Sea. Due to the Port of Klaipėda reconstruction in 2002 and the beach nourishment project, which was started in 2014, the shoreline position change tendency was observed. Shoreline position measurements of various periods can be used to derive quantitative estimates of coastal process directions and intensities. These data can be used to further our understanding of the scale and timing of shoreline changes in a geological and socio-economic context. This study analyzes long- and short-term shoreline position changes before and after the Port of Klaipėda reconstruction in 2002. Positions of historical shorelines from various sources were used, and the rates (EPR, NSM, and SCE) of shoreline changes have been assessed using the Digital Shoreline Analysis System (DSAS). An extension of ArcGIS K-means clustering was applied for shoreline classification into different coastal dynamic stretches. Coastal development has changed in the long-term (1984–2019) perspective: the eroded coast length increased from 1.5 to 4.2 km in the last decades. Coastal accumulation processes have been restored by the Port of Klaipėda executing the coastal zone nourishment project in 2014.