Articles | Volume 17, issue 7
https://doi.org/10.5194/essd-17-3125-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-3125-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
02 Jul 2025
Data description paper |
| 02 Jul 2025
| 02 Jul 2025
An integrated high-resolution bathymetric model for the Danube Delta system
Lauranne Alaerts
CORRESPONDING AUTHOR
Department of Astrophysics, Geophysics and Oceanography (AGO), ULiège, Liège, Belgium
Earth and Life Institute (ELI), UCLouvain, Louvain-la-Neuve, Belgium
Jonathan Lambrechts
Institute of Mechanics, Materials and Civil Engineering (IMMC), UCLouvain, Louvain-la-Neuve, Belgium
Ny Riana Randresihaja
Department of Astrophysics, Geophysics and Oceanography (AGO), ULiège, Liège, Belgium
Earth and Life Institute (ELI), UCLouvain, Louvain-la-Neuve, Belgium
Luc Vandenbulcke
Department of Astrophysics, Geophysics and Oceanography (AGO), ULiège, Liège, Belgium
Olivier Gourgue
Operational Directorate Natural Environment (OD Nature), Royal Belgian Institute of Natural Sciences (RBINS), Brussels, Belgium
Emmanuel Hanert
Earth and Life Institute (ELI), UCLouvain, Louvain-la-Neuve, Belgium
Institute of Mechanics, Materials and Civil Engineering (IMMC), UCLouvain, Louvain-la-Neuve, Belgium
Marilaure Grégoire
Department of Astrophysics, Geophysics and Oceanography (AGO), ULiège, Liège, Belgium
Related authors
Marilaure Grégoire, Luc Vandenbulcke, Séverine Chevalier, Mathurin Choblet, Ilya Drozd, Jean-François Grailet, Evgeny Ivanov, Loïc Macé, Polina Verezemskaya, Haolin Yu, Lauranne Alaerts, Ny Riana Randresihaja, Victor Mangeleer, Guillaume Maertens de Noordhout, Arthur Capet, Catherine Meulders, Anne Mouchet, Guy Munhoven, and Karline Soetaert
EGUsphere, https://doi.org/10.5194/egusphere-2025-4196, https://doi.org/10.5194/egusphere-2025-4196, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This paper describes the ocean BiogeochemicAl Model for Hypoxic and Benthic Influenced areas (BAMHBI). BAMHBI is a moderate complexity marine biogeochemical model that describes the cycling of carbon, nitrogen, phosphorus, silicon and oxygen through the marine foodweb. BAMHBI is a stand-alone biogeochemical model that can be coupled to any hydrodynamical model and is particularly appropriate for modelling low oxygen environments and the generation of sulfidic waters.
Ny Riana Randresihaja, Olivier Gourgue, Lauranne Alaerts, Xavier Fettweis, Jonathan Lambrechts, Miguel De Le Court, Marilaure Grégoire, and Emmanuel Hanert
EGUsphere, https://doi.org/10.5194/egusphere-2025-634, https://doi.org/10.5194/egusphere-2025-634, 2025
Preprint archived
Short summary
Short summary
Coastal areas face rising flood threats as storms intensifies with climate change. With an advanced model of the Scheldt Estuary-North Sea, we studied how detailed atmospheric data must be to predict storm surge peaks in estuaries. We found that high-resolution atmospheric data gives the best results, and coarser data with same resolution as current global climate models give poorer results. We show that investing in localized, high-resolution atmospheric data can significantly improve results.
Marilaure Grégoire, Luc Vandenbulcke, Séverine Chevalier, Mathurin Choblet, Ilya Drozd, Jean-François Grailet, Evgeny Ivanov, Loïc Macé, Polina Verezemskaya, Haolin Yu, Lauranne Alaerts, Ny Riana Randresihaja, Victor Mangeleer, Guillaume Maertens de Noordhout, Arthur Capet, Catherine Meulders, Anne Mouchet, Guy Munhoven, and Karline Soetaert
EGUsphere, https://doi.org/10.5194/egusphere-2025-4196, https://doi.org/10.5194/egusphere-2025-4196, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This paper describes the ocean BiogeochemicAl Model for Hypoxic and Benthic Influenced areas (BAMHBI). BAMHBI is a moderate complexity marine biogeochemical model that describes the cycling of carbon, nitrogen, phosphorus, silicon and oxygen through the marine foodweb. BAMHBI is a stand-alone biogeochemical model that can be coupled to any hydrodynamical model and is particularly appropriate for modelling low oxygen environments and the generation of sulfidic waters.
Loïc Macé, Luc Vandenbulcke, Jean-Michel Brankart, Pierre Brasseur, and Marilaure Grégoire
Biogeosciences, 22, 3747–3768, https://doi.org/10.5194/bg-22-3747-2025, https://doi.org/10.5194/bg-22-3747-2025, 2025
Short summary
Short summary
The representation of light propagation in seawater is critical for modelling marine biogeochemistry. We analyse results from a radiative transfer model that accounts for the absorption and scattering of light in the ocean with their respective uncertainties. We compare these results with in situ and remote-sensed data. Our analysis highlights the benefits of accounting for model uncertainties while using advanced representations of light in modelling frameworks.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Ny Riana Randresihaja, Olivier Gourgue, Lauranne Alaerts, Xavier Fettweis, Jonathan Lambrechts, Miguel De Le Court, Marilaure Grégoire, and Emmanuel Hanert
EGUsphere, https://doi.org/10.5194/egusphere-2025-634, https://doi.org/10.5194/egusphere-2025-634, 2025
Preprint archived
Short summary
Short summary
Coastal areas face rising flood threats as storms intensifies with climate change. With an advanced model of the Scheldt Estuary-North Sea, we studied how detailed atmospheric data must be to predict storm surge peaks in estuaries. We found that high-resolution atmospheric data gives the best results, and coarser data with same resolution as current global climate models give poorer results. We show that investing in localized, high-resolution atmospheric data can significantly improve results.
Sarah Hautekiet, Jan-Eike Rossius, Olivier Gourgue, Maarten Kleinhans, and Stijn Temmerman
Earth Surf. Dynam., 12, 601–619, https://doi.org/10.5194/esurf-12-601-2024, https://doi.org/10.5194/esurf-12-601-2024, 2024
Short summary
Short summary
This study examined how vegetation growing in marshes affects the formation of tidal channel networks. Experiments were conducted to imitate marsh development, both with and without vegetation. The results show interdependency between biotic and abiotic factors in channel development. They mainly play a role when the landscape changes from bare to vegetated. Overall, the study suggests that abiotic factors are more important near the sea, while vegetation plays a larger role closer to the land.
Ignace Pelckmans, Jean-Philippe Belliard, Olivier Gourgue, Luis Elvin Dominguez-Granda, and Stijn Temmerman
Hydrol. Earth Syst. Sci., 28, 1463–1476, https://doi.org/10.5194/hess-28-1463-2024, https://doi.org/10.5194/hess-28-1463-2024, 2024
Short summary
Short summary
The combination of extreme sea levels with increased river flow typically can lead to so-called compound floods. Often these are caused by storms (< 1 d), but climatic events such as El Niño could trigger compound floods over a period of months. We show that the combination of increased sea level and river discharge causes extreme water levels to amplify upstream. Mangrove forests, however, can act as a nature-based flood protection by lowering the extreme water levels coming from the sea.
Ignace Pelckmans, Jean-Philippe Belliard, Luis E. Dominguez-Granda, Cornelis Slobbe, Stijn Temmerman, and Olivier Gourgue
Nat. Hazards Earth Syst. Sci., 23, 3169–3183, https://doi.org/10.5194/nhess-23-3169-2023, https://doi.org/10.5194/nhess-23-3169-2023, 2023
Short summary
Short summary
Mangroves are increasingly recognized as a coastal protection against extreme sea levels. Their effectiveness in doing so, however, is still poorly understood, as mangroves are typically located in tropical countries where data on mangrove vegetation and topography properties are often scarce. Through a modelling study, we identified the degree of channelization and the mangrove forest floor topography as the key properties for regulating high water levels in a tropical delta.
Joko Sampurno, Valentin Vallaeys, Randy Ardianto, and Emmanuel Hanert
Nonlin. Processes Geophys., 29, 301–315, https://doi.org/10.5194/npg-29-301-2022, https://doi.org/10.5194/npg-29-301-2022, 2022
Short summary
Short summary
In this study, we successfully built and evaluated machine learning models for predicting water level dynamics as a proxy for compound flooding hazards in a data-scarce delta. The issues that we tackled here are data scarcity and low computational resources for building flood forecasting models. The proposed approach is suitable for use by local water management agencies in developing countries that encounter these issues.
Olivier Gourgue, Jim van Belzen, Christian Schwarz, Wouter Vandenbruwaene, Joris Vanlede, Jean-Philippe Belliard, Sergio Fagherazzi, Tjeerd J. Bouma, Johan van de Koppel, and Stijn Temmerman
Earth Surf. Dynam., 10, 531–553, https://doi.org/10.5194/esurf-10-531-2022, https://doi.org/10.5194/esurf-10-531-2022, 2022
Short summary
Short summary
There is an increasing demand for tidal-marsh restoration around the world. We have developed a new modeling approach to reduce the uncertainty associated with this development. Its application to a real tidal-marsh restoration project in northwestern Europe illustrates how the rate of landscape development can be steered by restoration design, with important consequences for restored tidal-marsh resilience to increasing sea level rise and decreasing sediment supply.
Joko Sampurno, Valentin Vallaeys, Randy Ardianto, and Emmanuel Hanert
Biogeosciences, 19, 2741–2757, https://doi.org/10.5194/bg-19-2741-2022, https://doi.org/10.5194/bg-19-2741-2022, 2022
Short summary
Short summary
This study is the first assessment to evaluate the interactions between river discharges, tides, and storm surges and how they can drive compound flooding in the Kapuas River delta. We successfully created a realistic hydrodynamic model whose domain covers the land–sea continuum using a wetting–drying algorithm in a data-scarce environment. We then proposed a new method to delineate compound flooding hazard zones along the river channels based on the maximum water level profiles.
Estrella Olmedo, Verónica González-Gambau, Antonio Turiel, Cristina González-Haro, Aina García-Espriu, Marilaure Gregoire, Aida Álvera-Azcárate, Luminita Buga, and Marie-Hélène Rio
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-364, https://doi.org/10.5194/essd-2021-364, 2021
Revised manuscript not accepted
Short summary
Short summary
We present the first dedicated satellite salinity product in the Black Sea. We use the measurements provided by the European Soil Moisture and Ocean Salinity mission. We introduce enhanced algorithms for dealing with the contamination produced by the Radio Frequency Interferences that strongly affect this basin. We also provide a complete quality assessment of the new product and give an estimated accuracy of it.
Florian Ricour, Arthur Capet, Fabrizio D'Ortenzio, Bruno Delille, and Marilaure Grégoire
Biogeosciences, 18, 755–774, https://doi.org/10.5194/bg-18-755-2021, https://doi.org/10.5194/bg-18-755-2021, 2021
Short summary
Short summary
This paper addresses the phenology of the deep chlorophyll maximum (DCM) in the Black Sea (BS). We show that the DCM forms in March at a density level set by the winter mixed layer. It maintains this location until June, suggesting an influence of the DCM on light and nutrient profiles rather than mere adaptation to external factors. In summer, the DCM concentrates ~55 % of the chlorophyll in a 10 m layer at ~35 m depth and should be considered a major feature of the BS phytoplankton dynamics.
Arthur Capet, Luc Vandenbulcke, and Marilaure Grégoire
Biogeosciences, 17, 6507–6525, https://doi.org/10.5194/bg-17-6507-2020, https://doi.org/10.5194/bg-17-6507-2020, 2020
Short summary
Short summary
The Black Sea is 2000 m deep, but, due to limited ventilation, only about the upper 100 m contains enough oxygen to support marine life such as fish. This oxygenation depth has been shown to be decreasing (1955–2019). Here, we evidence that atmospheric warming induced a clear shift in an important ventilation mechanism. We highlight the impact of this shift on oxygenation. There are important implications for marine life and carbon and nutrient cycling if this new ventilation regime persists.
Cited articles
Alaerts, L., Lambrechts, J., Randresihaja, N. R., Vandenbulcke, L., Gourgue, O., Hanert, E., and Grégoire, M.: Comprehensive Bathymetry of the Danube Delta Three Branches, Zenodo [data set], https://doi.org/10.5281/zenodo.14055741, 2024. a, b
Anastasiu, M. C.: Evoluţia Sistemelor de Altitudini Utilizate În România Şi Europa, PhD thesis, Universitatea Tehnică de Construcţii Bucureşti, Facultatea de Geodezie. With the Ministerul Educaţiei, Certcetării, Tineretului şi Sportului, https://pdfcoffee.com/disertatie-anastasiupdf-pdf-free.html (last access: 21 September 2022), 2014. a, b
Bakhtyar, R., Maitaria, K., Velissariou, P., Trimble, B., Mashriqui, H., Moghimi, S., Abdolali, A., Van der Westhuysen, A. J., Ma, Z., Clark, E. P., and Flowers, T.: A New 1D/2D Coupled Modeling Approach for a Riverine-Estuarine System Under Storm Events: Application to Delaware River Basin, J. Geophys. Res.-Oceans, 125, e2019JC015822, https://doi.org/10.1029/2019JC015822, 2020. a
Bănăduc, D., Rey, S., Trichkova, T., Lenhardt, M., and Curtean-Bănăduc, A.: The Lower Danube River–Danube Delta–North West Black Sea: A Pivotal Area of Major Interest for the Past, Present and Future of Its Fish Fauna – A Short Review, Sci. Total Environ., 545–546, 137–151, https://doi.org/10.1016/j.scitotenv.2015.12.058, 2016. a
Bănăduc, D., Afanasyev, S., Akeroyd, J. R., Năstase, A., Năvodaru, I., Tofan, L., and Curtean-Bănăduc, A.: The Danube Delta: The Achilles Heel of Danube River–Danube Delta–Black Sea Region Fish Diversity under a Black Sea Impact Scenario Due to Sea Level Rise – A Prospective Review, Fishes, 8, 355, https://doi.org/10.3390/fishes8070355, 2023. a, b, c
Beckers, J. M., Gregoire, M., Nihoul, J. C. J., Stanev, E., Staneva, J., and Lancelot, C.: Modelling the Danube-influenced North-western Continental Shelf of the Black Sea. I: Hydrodynamical Processes Simulated by 3-D and Box Models, Estuar. Coast. Shelf Sci., 54, 453–472, https://doi.org/10.1006/ecss.2000.0658, 2002. a
Bomers, A., Schielen, R. M. J., and Hulscher, S. J. M. H.: The Influence of Grid Shape and Grid Size on Hydraulic River Modelling Performance, Environ. Fluid Mech., 19, 1273–1294, https://doi.org/10.1007/s10652-019-09670-4, 2019. a, b
Bonamano, S., Federico, I., Causio, S., Piermattei, V., Piazzolla, D., Scanu, S., Madonia, A., Madonia, N., De Cillis, G., Jansen, E., Fersini, G., Coppini, G., and Marcelli, M.: River–Coastal–Ocean Continuum Modeling along the Lazio Coast (Tyrrhenian Sea, Italy): Assessment of near River Dynamics in the Tiber Delta, Estuar. Coast. Shelf Sci., 297, 108618, https://doi.org/10.1016/j.ecss.2024.108618, 2024. a
Breitburg, D., Levin, L. A., Oschlies, A., Grégoire, M., Chavez, F. P., Conley, D. J., Garçon, V., Gilbert, D., Gutiérrez, D., Isensee, K., Jacinto, G. S., Limburg, K. E., Montes, I., Naqvi, S. W. A., Pitcher, G. C., Rabalais, N. N., Roman, M. R., Rose, K. A., Seibel, B. A., Telszewski, M., Yasuhara, M., and Zhang, J.: Declining Oxygen in the Global Ocean and Coastal Waters, Science, 359, eaam7240, https://doi.org/10.1126/science.aam7240, 2018. a
Bridge, J. S.: Rivers and Floodplains: Forms, Processes, and Sedimentary Record, Wiley-Blackwell, ISBN 978-0-632-06489-2, 2003. a
Bunya, S., Dietrich, J. C., Westerink, J. J., Ebersole, B. A., Smith, J. M., Atkinson, J. H., Jensen, R., Resio, D. T., Luettich, R. A., Dawson, C., Cardone, V. J., Cox, A. T., Powell, M. D., Westerink, H. J., and Roberts, H. J.: A High-Resolution Coupled Riverine Flow, Tide, Wind, Wind Wave, and Storm Surge Model for Southern Louisiana and Mississippi. Part I: Model Development and Validation, Mon. Weather Rev., 138, 345–377, https://doi.org/10.1175/2009MWR2906.1, 2010. a
Caviedes-Voullième, D., Morales-Hernández, M., López-Marijuan, I., and García-Navarro, P.: Reconstruction of 2D River Beds by Appropriate Interpolation of 1D Cross-Sectional Information for Flood Simulation, Environ. Model. Softw., 61, 206–228, https://doi.org/10.1016/j.envsoft.2014.07.016, 2014. a
Cristofor, S., Vadineanu, A., and Ignat, G.: Importance of Flood Zones for Nitrogen and Phosphorus Dynamics in the Danube Delta, Hydrobiologia, 251, 143–148, https://doi.org/10.1007/BF00007174, 1993. a
Dey, S., Saksena, S., Winter, D., Merwade, V., and McMillan, S.: Incorporating Network Scale River Bathymetry to Improve Characterization of Fluvial Processes in Flood Modeling, Water Resour. Res., 58, e2020WR029521, https://doi.org/10.1029/2020WR029521, 2022. a, b
Diaconu, D. C., Bretcan, P., Peptenatu, D., Tanislav, D., and Mailat, E.: The Importance of the Number of Points, Transect Location and Interpolation Techniques in the Analysis of Bathymetric Measurements, J. Hydrol., 570, 774–785, https://doi.org/10.1016/j.jhydrol.2018.12.070, 2019. a, b, c
Dragićević, S.: The Potential of Web-based GIS, J. Geogr. Syst., 6, 79–81, https://doi.org/10.1007/s10109-004-0133-4, 2004. a
Dresback, K., Szpilka, C., Kolar, R., Moghimi, S., and Myers, E.: Development and Validation of Accumulation Term (Distributed and/or Point Source) in a Finite Element Hydrodynamic Model, J. Mar. Sci. Eng., 11, 248, https://doi.org/10.3390/jmse11020248, 2023. a
Duţu, F., Panin, N., Ion, G., and Tiron Duţu, L.: Multibeam Bathymetric Investigations of the Morphology and Associated Bedforms, Sulina Channel, Danube Delta, Geosciences, 8, 7, https://doi.org/10.3390/geosciences8010007, 2018. a, b
Dysarz, T.: Development of RiverBox – An ArcGIS Toolbox for River Bathymetry Reconstruction, Water, 10, 1266, https://doi.org/10.3390/w10091266, 2018. a
Esri: Ocean Basemap, https://www.arcgis.com/home/item.html?id=67ab7f7c535c4687b6518e6d2343e8a2 (last access: 18 March 2025), 2018. a
European Space Agency: Copernicus Global Digital Elevation Model, European Space Agency [data set], https://doi.org/10.5270/ESA-c5d3d65, 2021. a
FAIRway Danube: Fairway Rehabilitation and Maintenance Master Plan for the Danube and Its Navigable Tributaries: National action plans update May 2021, Tech. Rep. v. 16.11.2021, Connecting Europe Facility of the European Union, https://navigation.danube-region.eu/wp-content/uploads/sites/10/sites/10/2022/01/FRMMP_national_action_plans_May-2021.pdf (last access: 27 June 2024), 2021. a
Foglini, F., Rovere, M., Tonielli, R., Castellan, G., Prampolini, M., Budillon, F., Cuffaro, M., Di Martino, G., Grande, V., Innangi, S., Loreto, M. F., Langone, L., Madricardo, F., Mercorella, A., Montagna, P., Palmiotto, C., Pellegrini, C., Petrizzo, A., Petracchini, L., Remia, A., Sacchi, M., Sanchez Galvez, D., Tassetti, A. N., and Trincardi, F.: A New Multi-Grid Bathymetric Dataset of the Gulf of Naples (Italy) from Complementary Multi-Beam Echo Sounders, Earth Syst. Sci. Data, 17, 181–203, https://doi.org/10.5194/essd-17-181-2025, 2025. a
Fuchs, M., Palmtag, J., Juhls, B., Overduin, P. P., Grosse, G., Abdelwahab, A., Bedington, M., Sanders, T., Ogneva, O., Fedorova, I. V., Zimov, N. S., Mann, P. J., and Strauss, J.: High-Resolution Bathymetry Models for the Lena Delta and Kolyma Gulf Coastal Zones, Earth Syst. Sci. Data, 14, 2279–2301, https://doi.org/10.5194/essd-14-2279-2022, 2022. a
GEBCO Bathymetric Compilation Group: The GEBCO_2024 Grid – a continuous terrain model of the global oceans and land, NERC EDS British Oceanographic Data Centre NOC [data set], https://doi.org/10.5285/1c44ce99-0a0d-5f4f-e063-7086abc0ea0f, 2024. a, b
Geuzaine, C. and Remacle, J.-F.: Gmsh: A 3-D Finite Element Mesh Generator with Built-in Pre- and Post-Processing Facilities, Int. J. Numer. Meth. Eng., 79, 1309–1331, https://doi.org/10.1002/nme.2579, 2009. a
Goff, J. A. and Nordfjord, S.: Interpolation of Fluvial Morphology Using Channel-Oriented Coordinate Transformation: A Case Study from the New Jersey Shelf, Math. Geol., 36, 643–658, https://doi.org/10.1023/B:MATG.0000039539.84158.cd, 2004. a, b, c
Grégoire, M. and Friedrich, J.: Nitrogen Budget of the Northwestern Black Sea Shelf Inferred from Modeling Studies and in Situ Benthic Measurements, Mar. Ecol. Prog. Ser., 270, 15–39, https://doi.org/10.3354/meps270015, 2004. a
Habersack, H., Hein, T., Stanica, A., Liska, I., Mair, R., Jäger, E., Hauer, C., and Bradley, C.: Challenges of River Basin Management: Current Status of, and Prospects for, the River Danube from a River Engineering Perspective, Sci. Total Environ., 543, 828–845, https://doi.org/10.1016/j.scitotenv.2015.10.123, 2016. a
Hilton, J. E., Grimaldi, S., Cohen, R. C. Z., Garg, N., Li, Y., Marvanek, S., Pauwels, V. R. N., and Walker, J. P.: River Reconstruction Using a Conformal Mapping Method, Environ. Model. Softw., 119, 197–213, https://doi.org/10.1016/j.envsoft.2019.06.006, 2019. a
Ivanov, E., Capet, A., Barth, A., Delhez, E. J. M., Soetaert, K., and Grégoire, M.: Hydrodynamic Variability in the Southern Bight of the North Sea in Response to Typical Atmospheric and Tidal Regimes. Benefit of Using a High Resolution Model, Ocean Model., 154, 101682, https://doi.org/10.1016/j.ocemod.2020.101682, 2020. a
Jugaru Tiron, L., Le Coz, J., Provansal, M., Panin, N., Raccasi, G., Dramais, G., and Dussouillez, P.: Flow and Sediment Processes in a Cutoff Meander of the Danube Delta during Episodic Flooding, Geomorphology, 106, 186–197, https://doi.org/10.1016/j.geomorph.2008.10.016, 2009. a, b
Kara, A. B., Wallcraft, A. J., Hurlburt, H. E., and Stanev, E. V.: Air–Sea Fluxes and River Discharges in the Black Sea with a Focus on the Danube and Bosphorus, J. Mar. Syst., 74, 74–95, https://doi.org/10.1016/j.jmarsys.2007.11.010, 2008. a
Kubryakov, A. A., Stanichny, S. V., and Zatsepin, A. G.: Interannual Variability of Danube Waters Propagation in Summer Period of 1992–2015 and Its Influence on the Black Sea Ecosystem, J. Mar. Syst., 179, 10–30, https://doi.org/10.1016/j.jmarsys.2017.11.001, 2018. a
Lai, R., Wang, M., Zhang, X., Huang, L., Zhang, F., Yang, M., and Wang, M.: Streamline-Based Method for Reconstruction of Complex Braided River Bathymetry, J. Hydrol. Eng., 26, 04021012, https://doi.org/10.1061/(ASCE)HE.1943-5584.0002080, 2021. a
Lai, Y. G.: Two-Dimensional Depth-Averaged Flow Modeling with an Unstructured Hybrid Mesh, J. Hydraul. Eng., 136, 12–23, https://doi.org/10.1061/(ASCE)HY.1943-7900.0000134, 2010. a, b
Lazar, L., Rodino, S., Pop, R., Tiller, R., D'Haese, N., Viaene, P., and De Kok, J.-L.: Sustainable Development Scenarios in the Danube Delta – A Pilot Methodology for Decision Makers, Water, 14, 3484, https://doi.org/10.3390/w14213484, 2022. a
Legleiter, C. J. and Kyriakidis, P. C.: Spatial Prediction of River Channel Topography by Kriging, Earth Surf. Proc. Land., 33, 841–867, https://doi.org/10.1002/esp.1579, 2008. a, b, c, d
Lima, L., Aydogdu, A., Escudier, R., Masina, S., Cilibert, S., Azevedo, D., Peneva, E., Causio, S., Cipollone, A., Clementi, E., Cretí, S., Stefanizzi, L., Lecci, R., Palermo, F., Coppini, G., Pinardi, N., and Palazov, A.: Black Sea Physical Reanalysis (CMEMS BS-Currents) (Version 1), CMCC, https://doi.org/10.25423/CMCC/BLKSEA_MULTIYEAR_PHY, 2020. a
Merwade, V. M., Maidment, D. R., and Hodges, B. R.: Geospatial Representation of River Channels, J. Hydrol. Eng., 10, 243–251, https://doi.org/10.1061/(ASCE)1084-0699(2005)10:3(243), 2005. a, b, c
Merwade, V. M., Maidment, D. R., and Goff, J. A.: Anisotropic Considerations While Interpolating River Channel Bathymetry, J. Hydrol., 331, 731–741, https://doi.org/10.1016/j.jhydrol.2006.06.018, 2006. a, b, c, d
Merwade, V. M., Cook, A., and Coonrod, J.: GIS Techniques for Creating River Terrain Models for Hydrodynamic Modeling and Flood Inundation Mapping, Environ. Model. Softw., 23, 1300–1311, https://doi.org/10.1016/j.envsoft.2008.03.005, 2008. a
Nelson, J. M., Bennett, J. P., and Wiele, S. M.: Flow and Sediment-Transport Modeling, in: Tools in Fluvial Geomorphology, 1st Edn.,edited by: Kondolf, G. M. and Piégay, H., Wiley, 539–576, ISBN 978-0-471-49142-2 978-0-470-86833-1, https://doi.org/10.1002/0470868333.ch18, 2003. a
Niculescu, S., Lardeux, C., Hanganu, J., Mercier, G., and David, L.: Change Detection in Floodable Areas of the Danube Delta Using Radar Images, Nat. Hazards, 78, 1899–1916, https://doi.org/10.1007/s11069-015-1809-4, 2015. a
NOAA National Centers for Environmental Information: ETOPO 2022 15 Arc-Second Global Relief Model, NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/fd45-gt74, 2022. a, b
Panin, N. and Jipa, D.: Danube River Sediment Input and Its Interaction with the North-western Black Sea, Estuar. Coast. Shelf Sci., 54, 551–562, https://doi.org/10.1006/ecss.2000.0664, 2002. a, b
Pasquaré Mariotto, F., Antoniou, V., Drymoni, K., Bonali, F. L., Nomikou, P., Fallati, L., Karatzaferis, O., and Vlasopoulos, O.: Virtual Geosite Communication through a WebGIS Platform: A Case Study from Santorini Island (Greece), Appl. Sci., 11, 5466, https://doi.org/10.3390/app11125466, 2021. a
Pelckmans, I., Gourgue, O., Belliard, J.-P., Dominguez-Granda, L. E., Slobbe, C., and Temmerman, S.: Hydrodynamic Modelling of the Tide Propagation in a Tropical Delta: Overcoming the Challenges of Data Scarcity, in: 2020 TELEMAC-MASCARET User Conference October 2021, 14 and 15 October 2021, Antwerp, https://hdl.handle.net/20.500.11970/108312 (last access: 30 June 2025), 2021. a, b
Pham Van, C., de Brye, B., Deleersnijder, E., Hoitink, A. J. F., Sassi, M., Spinewine, B., Hidayat, H., and Soares-Frazão, S.: Simulations of the Flow in the Mahakam River–Lake–Delta System, Indonesia, Environ. Fluid Mech., 16, 603–633, https://doi.org/10.1007/s10652-016-9445-4, 2016. a
Romanescu, G.: Alluvial Transport Processes and the Impact of Anthropogenic Intervention on the Romanian Littoral of the Danube Delta, Ocean Coast. Manage., 73, 31–43, https://doi.org/10.1016/j.ocecoaman.2012.11.010, 2013. a, b
Rose, K. A., Justic, D., Fennel, K., and Hetland, R. D.: Numerical Modeling of Hypoxia and Its Effects: Synthesis and Going Forward, in: Modeling Coastal Hypoxia: Numerical Simulations of Patterns, Controls and Effects of Dissolved Oxygen Dynamics, edited by: Justic, D., Rose, K. A., Hetland, R. D., and Fennel, K., Springer International Publishing, Cham, 401–421, ISBN 978-3-319-54571-4, https://doi.org/10.1007/978-3-319-54571-4_15, 2017. a
Roşu, A., Arseni, M., Roşu, B., Petrea, Ş.-M., Iticescu, C., and Georgescu, P. L.: Study of the Influence of Manning Parameter Variation for Waterflow Simulation in Danube Delta, Romania, Scientific Papers, Series E, Land Reclamation, Earth Observation & Surveying, Environmental Engineering, XI, 374–381, https://landreclamationjournal.usamv.ro/index.php/scientific-papers/current?id=548 (last access: 3 June 2024), 2022. a
Sommerwerk, N., Bloesch, J., Baumgartner, C., Bittl, T., Čerba, D., Csányi, B., Davideanu, G., Dokulil, M., Frank, G., Grecu, I., Hein, T., Kováč, V., Nichersu, I., Mikuska, T., Pall, K., Paunović, M., Postolache, C., Raković, M., Sandu, C., Schneider-Jacoby, M., Stefke, K., Tockner, K., Toderaş, I., and Ungureanu, L.: Chapter 3 – The Danube River Basin, in: Rivers of Europe, 2nd Edn., edited by: Tockner, K., Zarfl, C., and Robinson, C. T., Elsevier, 81–180, https://doi.org/10.1016/B978-0-08-102612-0.00003-1, 2022. a, b
Simon, T. and Andrei, M.-T.: The Danube Delta and Its Tourism Development between 1989 and 2022, in: 6th International Hybrid Conference Water resources and wetlands, 13–17 September 2023, 237–247, https://www.limnology.ro/wrw2023/20_Andrei.pdf (last access: 26 October 2024), 2023. a
Suciu, R., Constantinescu, A., and David, C.: The Danube Delta: Filter or Bypass for the Nutrient Input into the Black Sea?, Large Rivers, 13, 165–173, https://doi.org/10.1127/lr/13/2002/165, 2002. a
Sultanov, E.: The Glossy Ibis Plegadis Falcinellus in Azerbaijan, SIS Conservation, 1, 10–15, 2019. a
Tiron Duţu, L., Provansal, M., Le Coz, J., and Duţu, F.: Contrasted Sediment Processes and Morphological Adjustments in Three Successive Cutoff Meanders of the Danube Delta, Geomorphology, 204, 154–164, https://doi.org/10.1016/j.geomorph.2013.07.035, 2014. a, b
Wu, C.-Y., Mossa, J., Mao, L., and Almulla, M.: Comparison of Different Spatial Interpolation Methods for Historical Hydrographic Data of the Lowermost Mississippi River, Ann. GIS, 25, 133–151, https://doi.org/10.1080/19475683.2019.1588781, 2019. a, b
Zhang, Y., Yaak, W. B., Wang, N., Li, Z., Wu, X., Wang, Q., Wang, Y., and Yao, W.: Evaluation of the Highly Sinuous Bend Sequences Using an Ecohydraulic Model to Ascertain the Suitability of Fish Habitats for River Ecological Conservation, J. Nat. Conserv., 82, 126750, https://doi.org/10.1016/j.jnc.2024.126750, 2024. a
Zigler, S. J., Newton, T. J., Steuer, J. J., Bartsch, M. R., and Sauer, J. S.: Importance of Physical and Hydraulic Characteristics to Unionid Mussels: A Retrospective Analysis in a Reach of Large River, Hydrobiologia, 598, 343–360, https://doi.org/10.1007/s10750-007-9167-1, 2008. a
Short summary
We created the first comprehensive, high-resolution, and easily accessible bathymetry dataset for the three main branches of the Danube Delta. By combining four data sources, we obtained a detailed representation of the riverbed, with resolutions ranging from 2 to 100 m. This dataset will support future studies on water and nutrient exchanges between the Danube and the Black Sea and provide insights into the delta's buffer role within the understudied Danube–Black Sea continuum.
We created the first comprehensive, high-resolution, and easily accessible bathymetry dataset...
Altmetrics
Final-revised paper
Preprint