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Observations and Models for End-User Services in Coastal Marine Systems

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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Oceans and Coastal Zones".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 23512

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Special Issue Editors

Prof. Dr. Georgios Sylaios

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Guest Editor

Department of Environmental Engineering, Democritus University of Thrace, 67100 Xanthi, Greece
Interests: water quality; oceanography; effluent quality; environmental stressors
Special Issues, Collections and Topics in MDPI journals

Dr. Ghada El Serafy

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Guest Editor

Delft Institute of Applied Mathematics, Delft University of Technology, Mekelweg 5, 2628 CD Delft, The Netherlands
Interests: data assimilation; data sciences; ecosystem modeling; ecosystem services; marine environmental quality; ecosystem health; integrated monitoring and assessment
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Special Issue Information

Dear Colleagues,

Presently, existing earth observing facilities and networks (such as Copernicus, GEOSS, GOOS, and EMODNet) provide a ‘wealth of marine data’ collected by satellites, on-site static and mobile sensors, and produced by operational numerical models, stored in repositories in the form of big databases. The coupling and downscaling of these coarse resolution numerical models of global coverage, the deployment of local online sensors, and the combined use of remote sensing and the data post-processing and assimilation enables the generation of high-quality services that could be offered to a wide range of end-users, such as ports, aquaculture, navigation, marine renewables, oil and gas, tourism, marine surveillance, public authorities, and more. Such core, on-demand derived data services lie at the heart of Blue Economy and Growth, the central EU policy for marine sustainability and jobs creation.

Through this Special Issue, we invite authors to submit their work related to integrated observational/modeling systems, data platforms, and data post-processing techniques to derive services for the multiple end-users spectrum, operating in the coastal to continental shelf zones.

Prof. Georgios Sylaios
Dr. Ghada El Serafy
Guest Editors

Manuscript Submission Information

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Keywords

coastal systems
integrated monitoring and modeling
short-term forecasting
climate services
data platforms and repositories
end-user data services
blue growth

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Published Papers (7 papers)

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Research

20 pages, 6004 KiB

Open AccessFeature PaperArticle

The Northern Adriatic Forecasting System for Circulation and Biogeochemistry: Implementation and Preliminary Results

by Isabella Scroccaro, Marco Zavatarelli, Tomas Lovato, Piero Lanucara and Andrea Valentini

Water 2022, 14(17), 2729; https://doi.org/10.3390/w14172729 - 1 Sep 2022

Cited by 1 | Viewed by 1666

Abstract

This paper described the implementation of a forecasting system of the coupled physical and biogeochemical state of the northern Adriatic Sea and discussed the preliminary results. The forecasting system is composed of two components: the NEMO general circulation model and the BFM biogeochemical model. The BFM component includes an explicit benthic pelagic coupling providing fluxes at the sediment–water interface and the dynamic of the major benthic state variables. The system is forced by atmospheric forcing from a limited-area model and by available land-based (river runoff and nutrient load) data. The preliminary results were validated against available remote and in situ observations. The validation effort indicated a good performance of the system in defining the basin scale characteristics, while locally the forecasting model performance seemed mostly impaired by the uncertainties in the definition of the land-based forcing. Full article

(This article belongs to the Special Issue Observations and Models for End-User Services in Coastal Marine Systems)

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17 pages, 6595 KiB

Open AccessArticle

Automatic Recognition of Oil Spills Using Neural Networks and Classic Image Processing

by Rotem Rousso, Neta Katz, Gull Sharon, Yehuda Glizerin, Eitan Kosman and Assaf Shuster

Water 2022, 14(7), 1127; https://doi.org/10.3390/w14071127 - 1 Apr 2022

Cited by 12 | Viewed by 5325

Abstract

Oil spill events are one of the major risks to marine and coastal ecosystems and, therefore, early detection is crucial for minimizing environmental contamination. Oil spill events have a unique appearance in satellite images created by Synthetic Aperture Radar (SAR) technology, because they are byproducts of the oil’s influence on the surface capillary, causing short gravity waves that change the radar’s backscatter intensity and result in unique dark formations in the SAR images. This signature’s appearance can be utilized to monitor and automatically detect oil spills in SAR images. Although SAR sensors capture these dark formations, which are likely connected to oil spills, it is hard to distinguish them from ships, ocean, land, and other oil-like formations. Most of the approaches for automatic detection and classification of oil spill events employ semantic segmentation with convolutional neural networks (CNNs), using a custom-made dataset. However, these approaches struggle to distinguish between oil spills and spots that resemble them. Therefore, developing a tailor-made sequence of methods for the oil spill recognition challenge is an essential need, and should include examination and choice of the most effective preprocessing tools, CNN models, and datasets that are specifically effective for the oil spill detection challenge. This paper suggests a new sequence of methods for accurate oil spill detection. First, a SAR image filtering technique was used for emphasizing the unique physical characteristics and appearance of oil spills. Each filter’s impact on leading CNN architectures performances was examined. Then, a method of a model ensemble was used, aiming to reduce the generalization error. All experiments demonstrated in this paper confirm that using the sequence suggested, in comparison to the common formula, leads to a 4.2% of improvement in the intersection over union score (IoU) for oil spill detection, and a 9.3% of improvement in the mean IoU among several relevant classes. Full article

(This article belongs to the Special Issue Observations and Models for End-User Services in Coastal Marine Systems)

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11 pages, 5537 KiB

Open AccessFeature PaperArticle

Multi-Band Bathymetry Mapping with Spiking Neuron Anomaly Detection

by J. Lawen, K. Lawen, G. Salman and A. Schuster

Water 2022, 14(5), 810; https://doi.org/10.3390/w14050810 - 4 Mar 2022

Viewed by 2698

Abstract

The developed method extracts bathymetry distributions from multiple satellite image bands. The automated remote sensing function is sparsely coded and combines spiking neural net anomaly filtration, spline, and multi-band fittings. Survey data were used to identify an activation threshold, decay rate, spline fittings, and multi-band weighting factors. Errors were computed for remotely sensed Landsat satellite images. Multi-band fittings achieved an average error of 25.3 cm. This proved sufficiently accurate to automatically extract shorelines to eliminate land areas in bathymetry mapping. Full article

(This article belongs to the Special Issue Observations and Models for End-User Services in Coastal Marine Systems)

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14 pages, 1472 KiB

Open AccessArticle

Fish Assemblages in Seagrass (Zostera marina L.) Meadows and Mussel Reefs (Mytilus edulis): Implications for Coastal Fisheries, Restoration and Marine Spatial Planning

by Georgios A. Orfanidis, Konstantinos Touloumis, Claus Stenberg, Patrizio Mariani, Josianne Gatt Støttrup and Jon C. Svendsen

Water 2021, 13(22), 3268; https://doi.org/10.3390/w13223268 - 17 Nov 2021

Cited by 5 | Viewed by 3993

Abstract

Seagrass meadows and mussel reefs provide favorable habitats for many fish species, but few studies have compared the associated fish assemblages directly and examined the influence of environmental variables. Knowledge of fish assemblages associated with disparate habitats is needed for the conservation of coastal fisheries and marine spatial planning. Catch per unit effort data derived from fyke nets showed similar species richness and diversity in seagrass meadows and mussel reefs, suggesting that both habitats support elevated marine biodiversity of mobile fauna. However, it was shown that fish assemblage structure differed between those habitats, and also fish abundance in seagrass meadows was significantly higher than in mussel reefs by comparing the data with a multivariate extension of Generalized Linear Models (GLM). Furthermore, employing underwater video recordings to compare fish abundances in high and low water current speed mussel reefs with a Generalized Linear Mixed Model with negative binomial distribution, data revealed similar fish abundances (in terms of the MaxN metric) despite the variation in current speed, probably because the mussel formations provide sufficient shelter, even from high water currents. The commercially important species Atlantic cod (G. morhua), however, was significantly more abundant in the low water current mussel reef. Therefore, restoration efforts targeting G. morhua could benefit from restoring low current mussel reefs. Our study provides input for the conservation of coastal recreational and commercial fisheries, habitat restoration and marine spatial planning where certain habitats may be prioritized. Full article

(This article belongs to the Special Issue Observations and Models for End-User Services in Coastal Marine Systems)

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12 pages, 791 KiB

Open AccessArticle

Development of a Fish-Based Multimetric Index for the Assessment of Lagoons’ Ecological Quality in Northern Greece

by Argyrios S. Sapounidis and Emmanuil T. Koutrakis

Water 2021, 13(21), 3008; https://doi.org/10.3390/w13213008 - 27 Oct 2021

Cited by 6 | Viewed by 2194

Abstract

Maintaining and improving the aquatic ecosystems in the community is the aim of the Water Framework Directive (WFD) 2000/60/EC. The WFD requires the water quality to be classified into five categories. Lagoons are dynamic ecosystems. The fish communities inhabiting them are highly affected by the environmental conditions prevailing both in the freshwater systems and in the marine environment. The current paper presented the first effort to develop a fish-based index (Lagoon Fish-based Index—LFI) for the assessment of the Mediterranean shallow lagoons, as almost all indices produced to date refer to freshwater or estuarine systems. For the development and calibration of the index, data were collected from nine lagoons situated in three estuarine systems in the East Macedonia and Thrace regions. The development of the LFI was based on the principles of the Indices of Biological Integrity (IBIs) that were primary used for the assessment of aquatic ecosystems in the USA. A total number of 25 metrics were selected as potential metrics for the LFI. These metrics describe attributes such as the abundance and composition of the fish fauna, the feeding strategies of the species, and the presence of sentinel species. Finally, eight metrics were included in the LFI. Full article

(This article belongs to the Special Issue Observations and Models for End-User Services in Coastal Marine Systems)

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10 pages, 1619 KiB

Open AccessFeature PaperArticle

Ecotrophic Effects of Fishing across the Mediterranean Sea

by Donna Dimarchopoulou, Ioannis Keramidas, Georgios Sylaios and Athanassios C. Tsikliras

Water 2021, 13(4), 482; https://doi.org/10.3390/w13040482 - 12 Feb 2021

Cited by 7 | Viewed by 3206

Abstract

The status of the Mediterranean Sea fisheries was evaluated across the seven subdivisions of the General Fisheries Commission for the Mediterranean (GFCM), using ecotrophic and catch-based indicators for the period 1970–2017. All indicators confirmed that the fishery resources across the Mediterranean Sea are no longer sustainably exploited and that the structure and function of marine ecosystems has been altered as a result of overexploitation. Although declining catches were a common feature across the Mediterranean Sea, the pattern of exploitation and the state of stocks differed among the subdivisions, with the Levantine Sea and Sardinia having a better status. Although they only include the exploited biological resources of marine ecosystems, catch and ecotrophic indicators can provide insight on ecosystem status and fishing pressure. In the case of southern Mediterranean countries, catch and trophic levels are the only information available, which is extremely valuable in data-poor ecosystems. Full article

(This article belongs to the Special Issue Observations and Models for End-User Services in Coastal Marine Systems)

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17 pages, 4118 KiB

Open AccessFeature PaperArticle

A Fuzzy Inference System for Seagrass Distribution Modeling in the Mediterranean Sea: A First Approach

by Dimitra Papaki, Nikolaos Kokkos and Georgios Sylaios

Water 2020, 12(10), 2949; https://doi.org/10.3390/w12102949 - 21 Oct 2020

Cited by 1 | Viewed by 3074

Abstract

A Mamdani-type fuzzy-logic model was developed to link Mediterranean seagrass presence to the prevailing environmental conditions. UNEP-WCMC (seagrass presence), CMEMS, and EMODnet (oceanographic/environmental) datasets, along with human-impact parameters were utilized for this expert system. The model structure and input parameters were tested according to their capacity to accurately predict the presence of seagrass families at specific locations. The optimum Fuzzy Inference System (FIS) comprised four input variables: water depth, sea surface temperature, nitrates, and bottom chlorophyll-a concentration, exhibiting reasonable precision (76%). Results illustrated that Posidoniaceae prefers cooler water (16–18 °C) with low chlorophyll-a levels (<0.2 mg/m³); Zosteraceae favors similarly cooler (16–18 °C) and mesotrophic waters (Chl-a > 0.2 mg/m³), but also slightly warmer (18–19.5 °C) with lower Chl-a levels (<0.2 mg/m³); Cymodoceaceae lives in warm, oligotrophic (19.5–21.0 °C, Chl-a < 0.3 mg/m³) to moderately warm mesotrophic sites (18–21.3 °C, 0.3–0.4 mg/m³ Chl-a). Finally, Hydrocharitaceae thrives in the warm Mediterranean waters (21–23 °C) of low chlorophyll-a content (<0.25 mg/m³). Climate change scenarios show that Posidoniaceae and Zosteraceae tolerate bathymetric changes, and Posidoniaceae and Zosteraceae are mostly affected by sea temperature rise, while Hydrocharitaceae exhibits tolerance at higher sea temperatures. This FIS could aid the protection of vulnerable seagrass ecosystems by national and regional policy-makers and public authorities. Full article

(This article belongs to the Special Issue Observations and Models for End-User Services in Coastal Marine Systems)

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