Digital Bathymetric Model Research Articles

Bathymetric analysis using multifrequency multibeam echosounder

Making a nautical chart for safe navigation is a bathymetric survey’s primary goal. Multifrequency MBES have been developed over the last few decades, and their introduction has dramatically improved the efficiency, accuracy, and spatial resolution of coastal and ocean mapping. The goal of multifrequency MBES is to increase the subsurface’s detection resolution. To obtain an accurate picture of the seabed, the user can lessen the impact of this subsidence by running surveys in three different modes at once. With the help of multifrequency MBES, this study will analyze bathymetry in shallow coastal waters. The digital bathymetric model’s (DBM) frequencies are remarkably close. The depth value of the study site ranges from –20 m to–70 m with reference to lowest water surface (LWS) based on the produced DBM. Generally, the difference between 100 kHz, 200 kHz, and 400 kHz is as small as 0–30 cm, and a small part is 30–60 cm. The volume between frequencies for an area of 1 ha is between 90 m3 to 440 m3. If the thickness of the dredged sediment is 1 m, then the difference in volume between frequencies is less than 5%. The bathymetry difference between 100 kHz and 400 kHz frequencies to –10 cm is dominated by the region of 0 cm. Dredging volume inter frequency ranges from 0.042 m3/m2 to 0.068 m3/m2.

Exploring Ancillary Parameters for Quantifying Interpolation Uncertainty in Digital Bathymetric Models

The oceans remain one of Earth’s most enigmatic frontiers, with approximately 75% of the world’s oceans still unmapped. To create a seamless digital bathymetric model (DBM) from sparse bathymetric datasets, interpolation is employed, but this introduces uncertainties of unknown nature. This study aims to estimate and characterize these uncertainties, which is important in many fields, particularly nautical charting, and navigational safety. Complete seafloor coverage sonar depth data for five testbeds that varied in slope and roughness are sampled at a range of densities (1% to 50%) and interpolated across an entire area using Spline, Inverse Distance Weighting (IDW), and Linear interpolation. The resulting uncertainties are evaluated from both scientific and operational perspectives. Employing linear regression and machine learning techniques, the relationships between these uncertainties and ancillary parameters (distance to the nearest measurement, seabed roughness, and slope) are examined for quantifying and characterizing the interpolation uncertainty. Results indicate insignificant operational differences among the three interpolators in depth estimation, as well as the statistical significance of the examined uncertainty predictors. Additionally, findings suggest the potential presence of unaccounted-for factors shaping uncertainty, yet this work lays a foundational understanding for improving the estimate of uncertainty in DBMs.

A regional digital bathymetric model fusion method based on topographic slope: A case study of the south China sea and surrounding waters

High-resolution seafloor topography is important in scientific research and marine engineering in regard to marine resource development and environmental protection monitoring. In this study, multi-dimensional comparisons were made between GEBCO_2022, SRTM15_V2.5.5, SRTM30_PLUS, SYNBATH_V1.0, ETOPO_2022, and topo_25.1 in the South China Sea and surrounding waters (SCS). This study has found that ETOPO_2022 had the best overall accuracy and reliability. Based on the results of the model accuracy analysis and by considering the topographic slope, ETOPO_2022, GEBCO_2022, and SRTM15_V2.5.5 were weighted and fused to form a fusion model. The error of the fusion model was 94.80% concentrated in (−100–100 m). When compared with GEBCO_2022, SRTM15_V2.5.5, SRTM30_PLUS, SYNBATH_V1.0, ETOPO_2022, and topo_25.1, the RMSE was reduced by 2%, 9%, 62%, 15%, 1%, and 73%, respectively. The slope-based weighted fusion method has been shown that it can overcome the limitations of a single data source and provide a reference for timely reconstruction and updating of large-scale seafloor topography.

New digital bathymetric model of Lake Onego (Verhne-Svirskoe reservoir): development, verification, application

A new digital bathymetric model of Lake Onego (Verhne-Svirskoe Reservoir) has been developed based on navigation charts. Verification of the model was carried out by comparing the modeled bathymetry with the cartographic materials, echo sounder measurements, and previous bathymetric models. Spatial resolution of the developed model is 50 m in plane and 2 m in depth. Despite these identified deviations in depth, the model has a good agreement between raster values and measured depth, which can be considered sufficient to calculate the main morphometric characteristics of the lake and solve other applied tasks. Morphometric characteristics of the water body (within the boundaries of the lake and reservoir separately) and its limnic regions were updated based on the developed digital model. In particular, values of the water area, water volume, average and maximum depth, littoral area (up to isobaths 2, 5, and 10 m) of limnic regions were specified for the first time based on the developed bathymetric model. The Central and South Onego are the largest regions by water area, while the Large Onego, the Central part of the lake and the Povenets Bay are the deepest. The largest areas of the lake in terms of the littoral area value are the Central part and the South Onego, while the maximum percentage of the littoral area was observed in the Kizhi skerriesand for most of thenorthern bays of the lake. The digital bathymetric model was applied to reconstruct the lake development in the post-glacial period, as well as in mapping the Quaternary deposits of the lake basin. The digital model can also be used as a basis for 3D modeling of geomorphologic, thermo-hydrodynamic and sedimentation processes.

High-Resolution Digital Bathymetric Model (DBM) With Uncertainty Reconstructed by Deep Learning With Dropout

High-Resolution Digital Bathymetric Model (DBM) With Uncertainty Reconstructed by Deep Learning With Dropout

Methodology for Creating a Digital Bathymetric Model Using Neural Networks for Combined Hydroacoustic and Photogrammetric Data in Shallow Water Areas.

This study uses a neural network to propose a methodology for creating digital bathymetric models for shallow water areas that are partially covered by a mix of hydroacoustic and photogrammetric data. A key challenge of this approach is the preparation of the training dataset from such data. Focusing on cases in which the training dataset covers only part of the measured depths, the approach employs generalized linear regression for data optimization followed by multilayer perceptron neural networks for bathymetric model creation. The research assessed the impact of data reduction, outlier elimination, and regression surface-based filtering on neural network learning. The average values of the root mean square (RMS) error were successively obtained for the studied nearshore, middle, and deep water areas, which were 0.12 m, 0.03 m, and 0.06 m, respectively; moreover, the values of the mean absolute error (MAE) were 0.11 m, 0.02 m, and 0.04 m, respectively. Following detailed quantitative and qualitative error analyses, the results indicate variable accuracy across different study areas. Nonetheless, the methodology demonstrated effectiveness in depth calculations for water bodies, although it faces challenges with respect to accuracy, especially in preserving nearshore values in shallow areas.

A Seabed Terrain Feature Extraction Transformer for the Super-Resolution of the Digital Bathymetric Model

The acquisition of high-resolution (HR) digital bathymetric models (DBMs) is crucial for oceanic research activities. However, obtaining HR DBM data is challenging, which has led to the use of super-resolution (SR) methods to improve the DBM’s resolution, as, unfortunately, existing interpolation methods for DBMs suffer from low precision, which limits their practicality. To address this issue, we propose a seabed terrain feature extraction transform model that combines the seabed terrain feature extraction module with the efficient transform module, focusing on the terrain characteristics of DBMs. By taking advantage of these two modules, we improved the efficient extraction of seabed terrain features both locally and globally, and as a result, we obtained a highly accurate SR reconstruction of DBM data within the study area, including the Mariana Trench in the Pacific Ocean and the adjacent sea. A comparative analysis with bicubic interpolation, SRCNN, SRGAN, and SRResNet shows that the proposed method decreases the root mean square error (RMSE) by 16%, 10%, 13%, and 12%, respectively. These experimental results confirm the high accuracy of the proposed method in terms of reconstructing HR DBMs.

The formation and growth mechanisms of young back-arc spreading ridges from high-resolution bathymetry: The Marsili Seamount (Tyrrhenian Sea, Italy)

The formation and growth mechanisms of Mid-Ocean Ridges (MOR) are relatively well known, whereas those of back-arc spreading ridges are comparatively less known because geophysical, geochemical, and morphological data are scarce and of low density. Here we present a high-resolution bathymetry of the Marsili Seamount (MS; 1 Ma − 3 ka), which represents the inflated spreading ridge of the 2 Ma old Marsili back-arc basin associated to the subduction of the Ionian Sea below the Calabrian Arc and Tyrrhenian Sea. MS is 70 km long, 30 km wide, and its height reaches about 3000 m from surrounding seafloor. Our new digital bathymetric model has a 5 m grid cell size resolution and covers the MS bathymetry from −1670 mbsl to the top at −491 mbsl. We conduct morphometric and morphological analyses of the bathymetry and recognize landforms due to volcanic, tectonic, hydrothermal and gravity processes. MS consists of volcanoes related to fissural and central-type activity, this latter located at the northern and southern tips of the main dike swarms. Dike swarms represent the surface expression of different ridge segments whose strikes are controlled by the larger scale back-arc spreading processes and by the local occurrence of an active hydrothermal field. This latter develops in a flat area between two partly overlapping ridge segments where historical volcanism and extensional processes concentrate. Such ridges represent the embryonic stage of the formation of transform-like faults. Central volcanoes, the northern of which is characterized by a caldera, form at the tips of MS because the decrease in width of the major volcanic fissures promotes vent localization associated with the formation of sill-like reservoirs from which central-type vents may develop. Gravity processes affecting the MS flanks are due to shallow seafloor sliding. Caldera collapses affecting the northernmost central-type polygenic volcano must be included in the evaluation of the hazard related to potential tsunami. Inward dipping faults characterize the MS eastern flank suggesting a moderately asymmetric growth of the spreading ridge possibly associated with the eastward opening of the Marsili back-arc.The Marsili back-arc spreading rate is similar to those of MOR slow spreading ridges. However, the MS morphology resembles that of fast spreading ridges. These two features also characterize more extended back-arc spreading ridges (e.g. the Mariana in Western Pacific). We conclude that, independently from the spatial scale, the increase in the ridge accretion rate is related to the progressive addition of a subduction-related component to a pure spreading mantle source.

RELIEF STRUCTURE OF THE LAKE LADOGA BOTTOM BASED ON SEISMIC-ACOUSTIC AND BATHYMETRIC DATA<a href="#FN2"><sup>2</sup></a>

A large amount of data on geological structure, quaternary deposits and bottom sediments of Lake Ladoga was obtained during the last 70 years. Meanwhile, bottom geomorphology of the lake is poorly studied. In most of cases geomorphological description includes only short morphometric characteristics and large-scale bottom elements description. In the present study new materials on Lake Ladoga bottom geomorphology is presented. Ultrahigh-resolution seismic data of 2014 and 2015 expeditions on research vessel “Ekolog” (Organizers: Saint-Petersburg State University, Marine Research Center of MSU, and Karelian Scientific Center of RAS), as well as digital bathymetric model of the basin, developed in the Institute of Limnology of SPB FRC RAS were used as original data. As a result of geomorphological interpretation 6 geomorphological genetic types were characterized: denudative constructive, erosional subequal, lacustrine, glacial, fluvioglacial marginal, and glacial lacustrine. Meso- and macroscale forms such as plains, ridges, hollows, valleys were distinguished. Signs of neotectonic movements north of Vallaam archipelago were approved. Terminal glacial landforms produced during the Neva stage of the Ostashkov glaciation were traced in the central part of the lake. Conditions and forms of the postglacial landscape development were characterized. These data were used to construct 1:1 000 000 scale geomorphological scheme applying the morphogenetic approach of analytical geomorphological mapping.

Application of Filtering Techniques to Smooth a Surface of Hybrid Digital Bathymetric Model

The aim of the research is to identify the optimal method for smoothing the surface of a hybrid digital bathymetric model (HDBM). The initiation of this research is justified by the fact that a model created from diverse types of data may have different surface textures and outliers. This diversity may cause problems in subsequent data processing stages, such as generating depth contours. As part of the adopted research methodology, fifteen filters were analysed. Filtering techniques were examined for filter type, the number of iterations, weights, and window size. The result is the adopted research methodology, which enabled the selection of the optimal filtering method. The research undertaken in this work is an extension of the methodology for developing an HDBM. An important aspect of the research is the approach to elaborating on such kinds of models in shallow and ultra-shallow waters adjacent to the land, as well as the use of data obtained by modern measurement platforms, such as unmanned surface vehicles (USV) and unmanned aerial vehicles (UAV). The studies fit into the general context of works related to the development of this type of model and undoubtedly provide a solid reference for further development or improvement of similar methods.

Tectonics of the Iberian continental margins and abyssal plains

ABSTRACT The tectonic map at scale 1:1,750,000 presented in this work shows an update of the existing knowledge of the main tectonic and volcanic structures along the Iberian continental margins and abyssal plains. The morphotectonic trends around Iberia recorded superposed geodynamic processes linked to the opening of the North Atlantic Ocean since the Mesozoic and the evolution of the Mediterranean Sea during the Cenozoic, as well as the reactivation of Hercynian faults and the formation of new tectonic structures during the Alpine orogeny. This map is based on the interpretation of the digital bathymetric model and other geophysical data from our own studies, and those from other authors. The morphotectonic features in this map provides a basis for the recognition of the tectonic control at lithospheric plate scale and the establishment of potential tectonic and volcanic risk zones.

Dredging Volume Analysis Using Bathymetric Multifrequency

Making a nautical chart for safe navigation is a bathymetric survey's primary goal. Multifrequency MBES, developed during the last few decades, has dramatically improved the efficiency, accuracy, and spatial resolution of coastal and ocean mapping. The goal of multifrequency MBES is to increase the sub surface’s detection resolution. In order to obtain an accurate picture of the seabed, the user can lessen the impact of this subsidence by running surveys in five different modes at once. With the help of multifrequency MBES, this study will analyze bathymetry in shallow coastal waters. According to this study, each frequency's density equals one-fifth of the raw data. The digital bathymetric model (DBM) has identical frequencies. According to the produced DBM, the study site's depth value ranges from -2.5 m to -23.5 m LWS. Between 200 kHz and other depths, a bathymetric variation of little more than 50 cm. Between 200 kHz and other frequencies to -10 cm, the bathymetry range of 0 cm predominates. Dredging volume inter frequencies falls between 0.042 m3/m2 and 0.068 m3/m2. This amount is negligible compared to the overall dredging volume with a thickness of more than 1 m inside 1 hectare.

Bathymetric data integration approach to study bedforms in the estuary of the Saint‐Lawrence River

The identification of bedforms has an important role in the study of seafloor morphology. The presence of these dynamic structures on the seafloor represents a hazard for navigation. They also influence the hydrodynamic simulation models used in the context, for example, of coastal flooding. Generally, MultiBeam EchoSounders (MBES) are used to survey these bedforms. Unfortunately, the coverage of the MBES is limited to small areas per survey. Therefore, the analysis of large areas of interest (like navigation channels) requires the integration of different datasets acquired over overlapping areas at different times. The presence of spatial and temporal inconsistencies between these datasets may significantly affect the study of bedforms, which are subject to many natural processes (e.g., Tides; flow). This paper proposes a novel approach to integrate multisource bathymetric datasets to study bedforms. The proposed approach is based on consolidating multisource datasets and applying the Empirical Bayesian Kriging interpolation for the creation of a multisource Digital Bathymetric Model (DBM). It has been designed to be adapted for estuarine areas with a high dynamism of the seafloor, characteristic of the fluvio-marine regime of the Estuary of the Saint-Lawrence River. This area is distinguished by a high tidal cycle and the presence of fields of dunes. The study involves MBES data that was acquired daily over a field of dunes in this area over the span of 4 days for the purpose of monitoring the morphology and migration of dunes. The proposed approach performs well with a resulting surface with a reduced error relative to the original data compared to existing approaches and the conservation of the dune shape through the integration of the data sets despite the highly dynamic fluvio-marine environments.

Geomorphometric Methods Application for Lake Ladoga Bottom Morphology Investigation

Abstract—In present research results of Lake Ladoga bottom morphology analysis are presented. Semi-automated instrumental classification of digital bathymetric model with application of geomorphometric parameters was executed to achieve the goal. Bathymetric position index and slope were used as classifiers. As a result, 8 types of surfaces were distinguished, which were mapped on the morphological scheme. Plains, slopes and linear top (ridges, heights) and bottom (hollows, depressions) were distinguished. Combinations of such elements allow to contour 3 zones which correlate to morphostructural areas: South-Ladoga, Central-Ladoga, North-Ladoga. Differences of these zones depend on both lake’s basin geological structure and exogenous factors of Late-Pleistocene-Holocene (glacial, glacial lacustrine processes). The suggested approach proves high efficiency for Lake Ladoga greatly variable morphology study.

SPLINE MODEL OF GRIDDED DATA OPERATION AS A PRINCIPLE OF ELECTRONIC MAPPING SEABED TOPOGRAPHY

The influence of technologies of automated processing of hydrographic survey results on the potential of the human factor in the transformation of polygraphic cartographic products into digital ones is analyzed. When configuring the digital bathymetric model, the concept of the navigation surface is used as a perspective principle of automated mapping. The approach to the problem of generating bathymetric contours from measurement results in the navigation surface paradigm is construed on continuous spline interpolation of geospatial data for reasonable cartographic generalization when creating electronic cartographic products. From the theoretical positions of the spline approach, the subjectivity of the method of artificial displacement of generalized isobaths to deep-water areas is excluded when creating a safe digital model of the bottom relief, interpreted in a mathematical sense as a navigational isosurface. The principle of electronic mapping based on the use of a spline in tension as an effective approach for the process of generalizing isobaths in order to obtain a wide range of morphometric characteristics of underwater topography has been developed. The generalized line of the active depth contour is estimated in the form of algorithmic reproduction on electronic charts of the safe convexity of the isobate towards the deep-sea area due to the practical implementation of the B-spline “snake model” by analogy with the serpentine configuration of the bathymetric isoline in the form of a piecewise polynomial function. When using the spline approach, an innovative principle of electronic mapping of the underwater landscape based on operating with a set of gridded data is implemented. The latter are interpreted as the results of depth measurements with the formalization of a two-dimensional frame of fixed values of bathymetric measurements for their representation as a navigational isosurface in three-dimensional Euclidean space. The actual synthesis of the seabed topography is implemented on the basis of a proven hybrid spline model for a specific indicative test case based on the processing of experimental gridded data. Hypothetically, the possibility of intellectual assistance to the watch officer in the strategy of instant orientation in conditions of a minimum depth reserve under the keel is organized when using computer three-dimensional visualization of the topography of the underwater relief in an unaffiliated graphic environment with foreign software.

Denmark’s Depth Model: Compilation of Bathymetric Data within the Danish Waters

Denmark’s Depth Model (DDM) is a Digital Bathymetric Model based on hundreds of bathymetric survey datasets and historical sources within the Danish Exclusive Economic Zone. The DDM represents the first publicly released model covering the Danish waters with a grid resolution of 50 m. When modern datasets are not available for a given area, historical sources are used, or, as the last resort, interpolation is applied. The model is generated by averaging depths values from validated sources, thus, not targeted for safety of navigation. The model is available by download from the Danish Geodata Agency website. DDM is also made available by means of Open Geospatial Consortium web services (i.e., Web Map Service). The original datasets—not distributed with the model—are described in the auxiliary layers to provide information about the bathymetric sources used during the compilation.

An Approach for the Automatic Characterization of Underwater Dunes in Fluviomarine Context

The identification of underwater landforms represents an important role in the study of the seafloor morphology. In this context, the segmentation and characterization of underwater dunes allow a better understanding of the dynamism of the seafloor, since the formation of these structures is directly related to environmental conditions, such as current, tide, grain size, etc. In addition, it helps to ensure safe navigation, especially in the context of navigation channels requiring periodic maintenance. This paper proposes a novel method to automatically characterize the underwater dunes. Its originality relies on the extraction of morphological descriptors not only related to the dune itself, but also to the fields where the dunes are located. Furthermore, the proposed approach involves the entire surface of the dunes, rather than profiles or group of pixels as generally found in previous works. Considering the surface modelled by a digital bathymetric model (DBM), the salient features of the dunes (i.e., crest line, stoss trough, and lee trough) are first identified using a geomorphometric analysis of the DBM. The individual dunes are built by matching the crest lines with their respective troughs according to an object-oriented approach. Then, a series of morphological descriptors, selected through a literature review, are computed by taking advantage of the dune salient features, surface representation, and spatial distribution in the fields where they are located. The validation of the proposed method has been conducted using more than 1200 dunes in the fluvio-marine context of the Northern Traverse of the Saint Lawrence River.

Palaeoshoreline reconstruction and underwater archaeological potential of Liman Tepe: A long-occupied coastal prehistoric settlement in western Anatolia, Turkey

Rising post-glacial sea levels had a major influence on the prehistoric settlement of the Aegean coastal zone. At Liman Tepe, an important Chalcolithic-Bronze Age coastal settlement on the south coast of the Bay of Izmir, archaeological evidence suggests a Neolithic (ca. 9600-5500 BCE) presence, but no settlement has been discovered on land. Sea levels during the Neolithic period were between 6 and >20 m below present and there is high potential for discovery of submerged prehistoric sites. Marine sediment coring and geophysical investigations (bathymetry, sub-bottom seismic profiling; >600 line-km) were conducted over a 4-km2 inshore area to assess the underwater archaeological potential. Multi-proxy sediment analysis (sedimentary facies, micropalaeontology, micro-XRF geochemistry) was conducted on 20 cores to reconstruct the relative sea level (RSL) history and coastal palaeogeography. Palaeoshoreline positions were estimated by back-stripping of the decompacted sediment thickness from a digital bathymetric model (DBM).The DBM reveals a drowned middle Holocene coastal plain with well-preserved relict river channels, palaeoshorelines and coastal headlands. The inshore stratigraphy consists of shoreface, foreshore and lagoonal deposits overlying terrestrial clay and palaeosols, defining a marine transgressive surface (MTS). The MTS records the inundation of the coastal plain prior to ca. 4000 BCE (transgressive systems tract; TST) and is marked in cores by an increasing abundance of foraminifera and a rise in Ca/Ti. During the Early Neolithic (ca. 6700 BCE), the shoreline was >500 m seaward (RSL ∼ −14 to −16 m) and Karantina Island was a broad coastal headland with a sheltered western embayment. By the Middle Chalcolithic (ca. 4800 BCE), the coastline had transgressed ∼800 m inland of the present shoreline and the Liman Tepe headland was separated from the mainland by a shallow coastal wetland. The maximum transgression (∼1 km inland at ca. 4000 BCE) was followed by a shift to a high-stand systems tract (HST) and rapid coastline progradation by barrier accretion and lagoon development. Palaeogeographic maps identify areas with high underwater archaeological potential: 1) palaeoriver channels and lowland riverine habitats formed during the TST, prior to 4000 BCE, 2) submerged palaeoshorelines and coastal promontories (water depths 10–14 mbsl) with high potential for Neolithic sites, and 3) protected coastal embayments and lagoons representing possible prehistoric anchorage sites.

A Segmentation Approach to Identify Underwater Dunes from Digital Bathymetric Models

The recognition of underwater dunes has a central role to ensure safe navigation. Indeed, the presence of these dynamic landforms on the seafloor represents a hazard for navigation, especially in navigation channels, and should be at least highlighted to avoid collision with vessels. This paper proposes a novel method dedicated to the segmentation of these landforms in the fluvio-marine context. Its originality relies on the use of a conceptual model in which dunes are characterized by three salient features, namely the crest line, the stoss trough, and the lee trough. The proposed segmentation implements the conceptual model by considering the DBM (digital bathymetric model) as the seafloor surface from which the dunes shall be segmented. A geomorphometric analysis of the seabed is conducted to identify the salient features of the dunes. It is followed by an OBIA (object-based image analysis) approach aiming to eliminate the pixel-based analysis of the seabed surface, forming objects to better describe the dunes present in the seafloor. To validate the segmentation method, more than 850 dunes were segmented in the fluvio-marine context of the Northern Traverse of the Saint-Lawrence river. A performance rate of nearly 92% of well segmented dunes (i.e., true positive) was achieved.

BATHYMETRIC AND GEOLOGICAL PROPERTIES OF THE ADRIATIC SEA

Advance in the visualization of the bathymetric and geological data from charted to digital maps and models opened the possibility to analyse data within Geographic Information System (GIS) functionalities. In this paper, bathymetric and geological properties of the Adriatic Sea were analysed using the General Bathymetric Chart of the Ocean (GEBCO) 2020 digital bathymetric model (DBM) and data from the European Marine Observation and Data Network (EMODnet). The bathymetric analysis includes depth statistics, area and volume calculation, hypsometry, and analysis of the heterogeneity of bathymetric data from the GEBCO 2020 DBM within the limits of the Adriatic defined by the International Hydrographic Organization (IHO) and 3 sub-basins delineated according to the bathymetry. The geological analysis includes seabed substrate map from EMODnet data and kilometre-scale seabed variability in the Adriatic. The GEBCO 2020 DBM shows that the Adriatic Sea is a shallow sea with a mean depth of -253 metres and over 50% of area shallower than 100 metres. The area of the Adriatic Sea is 138 516 km2 with a total volume of 35 521 km3. Patterns describing morphological variability coincide with the heterogeneity of the underlying source data of the GEBCO 2020 digital bathymetry model and major structures in the Adriatic Sea.