[
Abdi O., Uusitalo J., Pietarinen J., Lajunen A. 2022. Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet. Remote Sensing, 14: 2856.
]Search in Google Scholar
[
Absalon D. 2008. Application of GIS in hydrographic and environmental maps of Poland. Kartografické listy, 16: 40–47.
]Search in Google Scholar
[
Absalon D., Matysik M., Woźnica A., Janczewska N. 2023. Detection of changes in the hydrobiological parameters of the Oder River during the ecological disaster in July 2022 based on multi-parameter probe tests and remote sensing methods. Ecological Indicators, 148: 110103.
]Search in Google Scholar
[
Acharya B.S., Bhandari M., Bandini F., Pizarro A., Perks M. … Sharma S. 2021. Unmanned aerial vehicles in hydrology and water management: Applications, challenges, and perspectives. Water Resources Research, 57, 11: e2021WR029925.
]Search in Google Scholar
[
Albertini C., Gioia A., Iacobellis V., Manfreda S. 2022. Detection of Surface Water and Floods with Multispectral Satellites. Remote Sensing, 14: 6005.
]Search in Google Scholar
[
Albiac J., Calvo E., Esteban E. 2014. Chapter 9 River Basin Governance and Water Policies in Spain. [in:] D.E. Garrick, G.R.M. Anderson, D. Connell, J. Pittock (eds.), Managing Water in Multi-Layered Political Systems. Elgaronline: 141–157.
]Search in Google Scholar
[
Amatulli G., Garcia Marquez J., Sethi T., Kiesel J., Grigoropoulou A., Üblacker M.M., Shen L.Q., Domisch S. 2022. Hydrography 90 m: a new high-resolution global hydrographic dataset. Earth System Science Data, 14: 4525–4550.
]Search in Google Scholar
[
Australian Government - Bureau of Meteorology. 2023. [Online] Available: http://www.bom.gov.au/ (accessed on 18 January 2024).
]Search in Google Scholar
[
Australian Government. Australian Hydrological Geospatial Fabric (Geofabric). [Online] Available: http://www.bom.gov.au/water/geofabric/ (accessed on 02 August 2024).
]Search in Google Scholar
[
Autorità di Bacino Distrettuale delle Alpi Orientali. 2023. [Online] Available: https://sigma.distrettoalpiorientali.it/portal/index.php/cartografie/ (accessed on 06 January 2024).
]Search in Google Scholar
[
Barczyńska M., Borzuchowski J., Kubacka D., Piórkowski P., Rataj C., Walczykiewicz T., Woźniak Ł. 2013. Mapa Podziału Hydrograficznego Polski w skali 1:10 000 - nowe hydrograficzne dane referencyjne. Roczniki Geomatyki, 11, 3: 15–28.
]Search in Google Scholar
[
Barker L.J., Fry M., Hannaford J., Nash G., Tanguy M., Swain O. 2022. Dynamic High Resolution Hydrological Status Monitoring in Real-Time: The UK Water Resources Portal. Frontiers in Environmental Science, 10, 752201.
]Search in Google Scholar
[
Barović G., Vujacic D., Spalevic V. 2017. The River Network of Montenegro in the GIS Database. Kartografija i Geoinformacije, 27, 16: 44–60.
]Search in Google Scholar
[
Bayerisches Landesamt für Umwelt. [Online] Available: https://www.gkd.bayern.de/ (accessed on 04 August 2024).
]Search in Google Scholar
[
Bayerisches Landesamt für Umwelt. 2018. Gewässerkundlicher Dienst: Nutzerhandbuch. Bayerisches Landesamt für Umwelt (LfU), Augsburg, p. 9.
]Search in Google Scholar
[
Bieda A. 2012. Weryfikacja granicy matematycznej prowadzonej środkiem koryta rzecznego. Roczniki Geomatyki, X, 4(54): 17–27.
]Search in Google Scholar
[
Borges M.C.P., Abreu S.B., Lima C.H.R., Cardoso T., Yonamine S.M., Araujo W.D.V., Silva P.R.S., Machado V.B., Moraes V., Silva T.J.B., Reis V.A., Santos J.V.R., Reis M.L., Canamary É.A., Vieira G.C., Meireles S. 2022. The Brazilian National System for Water and Sanitation Data (SNIS): Providing information on a municipal level on water and sanitation services. Journal of Urban Management, 11, 4: 530–542.
]Search in Google Scholar
[
Brauman K. 2016. Global Water Data: We’ll Show You the World, Sort Of. [in:] P. Nunnally (ed.), Open Rivers: Rethinking The Mississippi. 2nd ed. University of Minnesota, Northrop.
]Search in Google Scholar
[
Brunsdon C., Comber A. 2020. Big issues for big data: challenges for critical spatial data analytics. Journal of Spatial Information Science, 21, JOSIS’ 10th Anniversary: Part Two and Special Feature on GeoComputation: 89–98.
]Search in Google Scholar
[
Cantemir A., Visan A., Parvulescu N., Dogaru M. 2016. The Use of Multiple Data Sources in the Process of Topographic Maps Updating. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic.
]Search in Google Scholar
[
Chatterjee R., Sinha S.K. 2014. Water Resources Database – Development and Management. Proceedings of the Indian National Science Academy, 80, 3: 713–730.
]Search in Google Scholar
[
Chowdhury S. 2023. Modelling hydrological factors from DEM using GIS. MethodsX: 10102062.
]Search in Google Scholar
[
Copernicus. 2019. EU-Hydro River Network Database 2006-2012 (vector), Europe - version 1.3, Nov. 2020. WWW: https://sdi.eea.europa.eu/catalogue/copernicus/api/records/393359a7-7ebd-4a52-80ac-1a18d5f3db9c?language=all (accessed on 22 July 2024).
]Search in Google Scholar
[
Curran K., Crumlish J., Fisher G. 2012. OpenStreetMap. International Journal of Interactive Communication Systems and Technologies (IJICST), 2, 1: 69–78.
]Search in Google Scholar
[
Eldrandaly K.A. 2010. GIS and spatial decision making. [in:] C.J. Dowesn (ed.), Geographic Information Systems. Nova Science Publishers, Inc.
]Search in Google Scholar
[
Esri. 2024. Collaborate with colleagues. Available at: https://www.esri.com/en-us/arcgis/products/arcgis-online/capabilities/collaborate (accessed on 22 June 2024).
]Search in Google Scholar
[
EU-Hydro River Network Database 2006-2012 (vector), Europe. Available at: https://land.copernicus.eu/en/products/eu-hydro/eu-hydro-river-network-database (accessed on 18 July 2024).
]Search in Google Scholar
[
European Commission. 2007. Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 Establishing an Infrastructure for Spatial Information in the European Community (INSPIRE). Available at: http://eurlex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32007L0002 (accessed on 5 February 2023).
]Search in Google Scholar
[
Executive Order 12906: Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure. 1994. Federal Register, 59, 71.
]Search in Google Scholar
[
Farhadi H., Esmaeily A., Najafzadeh M. 2022. Flood monitoring by integration of Remote Sensing technique and Multi-Criteria Decision Making method. Computers & Geosciences, 160: 105045.
]Search in Google Scholar
[
Feyisa G.L., Meilby H., Fensholt R., Proud S.R. 2014. Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery. Remote Sensing of Environment, 140, 23–35.
]Search in Google Scholar
[
Fryirs K.A., Brierley G.J. 2018. What’s in a Name? A Naming Convention for Geomorphic River Types Using the River Styles Framework. PLoS ONE, 13, 9: e0201909.
]Search in Google Scholar
[
Generalitat de Catalunya Departament d’Acció Climàtica. Available at: https://sig.gencat.cat/visors/VISOR_ACA.html (accessed on 02 August 2024).
]Search in Google Scholar
[
Geological Survey of Japan, Water Environment Map Hydrogeological Maps of Japan. Available at: https://www.gsj.jp/Map/EN/environment.html (accessed on 04 August 2024).
]Search in Google Scholar
[
Golub Medvešek I., Šoda J., Karin I., Maljković M. 2023. The State of the Hydrographic Survey and Assessment of the Potentially Risky Region for Navigation Safety. Journal of Marine Science and Engineering. 11, 8:1498.
]Search in Google Scholar
[
Gotway C.A., Young L.J. 2002. Combining Incompatible Spatial Data. Journal of the American Statistical Association, 97(458), 632–648.
]Search in Google Scholar
[
Government of Canada, National Hydro Network - NHN - GeoBase Series. Available at: https://open.canada.ca/data/en/dataset/a4b190fe-e090-4e6d-881e-b87956c07977 (accessed on 03 August 2024).
]Search in Google Scholar
[
Government of Canada. 2023. Available at: https://open.canada.ca/data/en/dataset/a4b190fe-e090-4e6d-881e-b87956c07977 (accessed on 05 January 2024).
]Search in Google Scholar
[
Greer M. 2021. Guidance Note How to Determine Whether a Watercourse is a River, Ephemeral Watercourse, Highly Modified River or Stream or Artificial Watercourse. Wellington Regional Council.
]Search in Google Scholar
[
Gusman T., Naeemullah M., Qasim A.M. 2022. Big Data Processing: A review. Mesopotamian Journal of Big Data, 2022: 23–30.
]Search in Google Scholar
[
Haining R.P. 2009. The Special Nature of Spatial Data. [in:] S. Fotheringham, D.W.S. Wong (eds.), Spatial Analysis Handbook. SAGE Publications Inc: 4–21.
]Search in Google Scholar
[
Hamal S. 2020. GIS Technology and its Applications in Water Resources and Environmental Engineering. Journal of Hydrogeology and Hydrologic Engineering, 9, 3.
]Search in Google Scholar
[
Hammam N., Abdulwahab K., Sidahmed Mohamed A. 2022. Flood Monitoring Using Remote Sensing And GIS Techniques: A Case Study Of Kampala District, Uganda. Journal of Multidisciplinary Engineering Science and Technology (JMEST), 9, 10: 15540–15545.
]Search in Google Scholar
[
Hecht H. 2000. Hydrographic GIS. The International Hydrographic Review, 1, 2:71–76.
]Search in Google Scholar
[
Holland M., Hoggarth A., Nicholson J. 2016. IOP Conference Series: Earth and Environmental Science, 34: 012016.
]Search in Google Scholar
[
Husain T., Caselton W.F. 1980. Hydrologic Network Design Methods and Shannon’s Information Theory. IFAC Proceedings Volumes, 13, 3: 259–267.
]Search in Google Scholar
[
Hydroportal. Available at: https://isok.gov.pl/hydroportal.html (accessed on 01 August 2024).
]Search in Google Scholar
[
HydroSHEDS Core Layers (version 1). Available at: https://www.hydrosheds.org/products/hydrosheds (accessed on 20 July 2024).
]Search in Google Scholar
[
IGB Freshwater Research and Environmental Database. Available at: https://fred.igb-berlin.de/data/allpackages/ (accessed on 18 July 2024).
]Search in Google Scholar
[
India Water Resources Information System. 2018. Available at: https://indiawris.gov.in/wris (accessed on 04 August 2024).
]Search in Google Scholar
[
International Hydrographic Organization Online. Available at: https://iho.int/en/iho-online-catalogues (accessed on 22 July 2024).
]Search in Google Scholar
[
Janczewska N., Matysik M., Absalon D. 2023. Verification of the consistency of surface water spatial databases and their importance for water management in Poland. Journal of Hydrology: Regional Studies, 49: 101486.
]Search in Google Scholar
[
Japan International Cooperation Agency 2022. [Online] Available: https://openjicareport.jica.go.jp/pdf/1000047169_01.pdf (accessed on 06 January 2024).
]Search in Google Scholar
[
Jiang H., Feng M., Zhu Y., Lu N., Huang J., Xiao T. 2014. An Automated Method for Extracting Rivers and Lakes from Landsat Imagery. Remote Sensing, 6: 5067–5089.
]Search in Google Scholar
[
Koski C., Kettunen P., Poutanen J., Zhu L., Oksanen J. 2023. Mapping Small Watercourses from DEMs with Deep Learning—Exploring the Causes of False Predictions. Remote Sensing, 15: 2776.
]Search in Google Scholar
[
Kumar P.C. 2018. Water Resources Issues and Management in India. Journal of Scientific and Engineering Research, 5, 9: 137–147.
]Search in Google Scholar
[
Kwartnik-Pruc A., Mączyńska A. 2023. Methodology of assessing quality of spatial data describing course of shoreline as tool supporting water resource management process. Journal of Water and Land Development, 57: 167–180.
]Search in Google Scholar
[
Lantmäteriet 2023. Hydrography Download Service. Ver. 2.3. Lantmäteriet, Stockholm.
]Search in Google Scholar
[
Lantmäteriet. Hydrography Download Service. [Online] Available: https://www.lantmateriet.se/en/geodata/geodata-products/product-list/hydrography-download-service/ (accessed on 02 August 2024).
]Search in Google Scholar
[
Larsen S., Hamilton S., Lucido J., Garner B., Young D. 2016. Supporting Diverse Data Providers in the Open Water Data Initiative: Communicating Water Data Quality and Fitness of Use. Journal of the American Water Resources Association (JAWRA), 52, 4: 859–872.
]Search in Google Scholar
[
Lin P., Pan M., Wood E.F., Yamazaki D., Allen G.H. 2021. A new vector-based global river network dataset accounting for variable drainage density. Scientific Data, 8: 28.
]Search in Google Scholar
[
Liu Z., Cheng L. 2020. Review of GIS Technology and Its Applications in Different Areas. [in:]IOP Conference Series: Materials Science and Engineering, 735, 1: 012066.
]Search in Google Scholar
[
Masetti G., Faulkes T., Wilson M., Wallace J. 2022. Effective Automated Procedures for Hydrographic Data Review. Geomatics, 2: 338–354.
]Search in Google Scholar
[
MERIT Hydro. [Online] Available: https://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro/ (accessed on [Date]).
]Search in Google Scholar
[
Ministerio para la Transición Ecológica y el Reto Demogr|fico (MITERD), 2023: Global water strategy of the Kingdom of Spain. Madrid. P. 24.
]Search in Google Scholar
[
Mitani K., Kashiwagi K., Umakoshi K., Inoue T., Saito Y., Fujino T., Saisho O. 2020. A Global Data Infrastructure for Data Sharing Between Businesses. NTT Software Innovation Center.
]Search in Google Scholar
[
Mullen A.L., Watts J.D., Rogers B.M., Carroll M.L., Elder C.D., Noomah J.… Kyzivat E.D. 2023. Using high-resolution satellite imagery and deep learning to track dynamic seasonality in small water bodies. Geophysical Research Letters, 50: e2022GL102327.
]Search in Google Scholar
[
Munier S., Decharme B. 2022. River network and hydro-geomorphological parameters at 1∕12° resolution for global hydrological and climate studies. Earth System Science Data, 14, 5: 2239–2258.
]Search in Google Scholar
[
National State of Water. [Online] Available: https://www.dws.gov.za/niwis2 (accessed on 08 August 2024).
]Search in Google Scholar
[
National Water Agency Open Data Portal. [Online] Available: https://storymaps.arcgis.com/stories/d4991710873845d688cea101c6149856 (accessed on 04 August 2024).
]Search in Google Scholar
[
Nkeki N.F., Asikhia M. 2014. Mapping and Geovisualizing Topographical Data Using Geographic Information System (GIS). Journal of Geography and Geology, 6, 1: 1–13.
]Search in Google Scholar
[
Normandin C., Frappart F., Bourrel L., Diepkilé A.T., Mougin E., Zwarts L., … Wigneron J.P. 2024. Quantification of surface water extent and volume in the Inner Niger Delta (IND) over 2000–2022 using multispectral imagery and radar altimetry. Geocarto International, 39, 1: 2311203.
]Search in Google Scholar
[
Nunes P., Vicente J., Veiga A.L., Monteiro C., Dias T., Palma C., Neto M. 2023. Datos hidrogr|ficos abertos para a sociedade. Revista Internacional Mapping, 32, 211: 34–48.
]Search in Google Scholar
[
Ordnance Survey. 2024. OS Open Rivers. [Online] Available: https://www.data.gov.uk/dataset/dc29160b-b163-4c6e-8817-f313229bcc23/os-open-rivers (accessed on 03 August 2024).
]Search in Google Scholar
[
Ozdemir S., Akbulut Z., Karsli F., Kavzoglu T. 2024. Extraction of Water Bodies from High-Resolution Aerial and Satellite Images Using Visual Foundation Models. Sustainability, 16: 2995.
]Search in Google Scholar
[
Panamaldeniya L. 2021. Importance of GIS, GPS, and RS. Conference: Importance GIS, GPS and RS, Kandy, Sri Lanka.
]Search in Google Scholar
[
River Network Routes. [Online] Available: https://data.gov.ie/dataset/river-network-routes (accessed on 05 August 2024).
]Search in Google Scholar
[
Safarov E., Mamanazarova D. 2023. Development of Irrigation and Hydrography Networks of the Fergana Region on the Basis of GIS Technologies. E3S Web of Conferences, 452: 02014.
]Search in Google Scholar
[
Sambo A., Pott A., Kime D., Strydom C.J. 2015. The National Integrated Water Information System (NIWIS) for South Africa. [in:] 36th Hydrology and Water Resources Symposium: The Art and Science of Water. Engineers Australia.
]Search in Google Scholar
[
Sampaio T.V.M., Rocha J. 2022. On the Quality of the Drainage Network Cartographic Representation. Ecological Indicators, 143: 109350.
]Search in Google Scholar
[
Schürz M., Grigoropoulou A., García M|rquez J., Torres-Cambas Y., Tomiczek T., Floury M., Bremerich V., Schürz C., Amatulli G., Grossart H.-P., Domisch S. 2023. hydrographr: An R package for scalable hydrographic data processing. Methods in Ecology and Evolution, 14: 2953–2963. https://doi.org/10.1111/2041-210X.14226.
]Search in Google Scholar
[
SIGMA, Autorità di Bacino Distrettuale delle Alpi Orientali. [Online] Available: https://sigma.distrettoalpiorientali.it/portal/index.php/cartografie/ (accessed on 04 August 2024).
]Search in Google Scholar
[
Silalahi F.E.S., Hidayat F. 2020. Model builder and Unit Hydrograph for Flood Prediction and Watershed Flow Direction Determination at The West Branch of The Little River, Stowe, Lamoille County, Vermont, USA. Geoplanning: Journal of Geomatics and Planning, 6, 2: 89–98.
]Search in Google Scholar
[
State Cartographer’s Office. Rivers, Lakes, and Streams Data. https://www.sco.wisc.edu/data/rivers-lakes-streams/ (accessed on 18 July 2024).
]Search in Google Scholar
[
Strack M. 2018. Natural Boundaries, Legal Definitions: Making room for rivers. Riverscapes, 6: 65–80.
]Search in Google Scholar
[
Strobl J. 2010. Status of GIS in Europe: Opportunities and Challenges. Geospatial World 2010. Available online: http://mmm-gi.geo-see.org/wp-content/uploads/MMMGI_10/Cetl_Kotsev_Dusart.pdf (accessed on 3 March 2024).
]Search in Google Scholar
[
Szypuła B. 2020. Digital adaptation of the Geomorphological Map of Upper Silesian Industrial Region, Poland (1:50,000) – old map new possibilities. Journal of Maps, 16, 2: 614–624.
]Search in Google Scholar
[
Thakur R., Manekar V.L. 2021. Artificial Intelligence-Based Image Classification Techniques for Hydrologic Applications. Applied Artificial Intelligence, 36, 1.
]Search in Google Scholar
[
The National Hydrography Dataset (NHD). [Online] Available: https://www.usgs.gov/national-hydrography/ (accessed on 03 August 2024).
]Search in Google Scholar
[
Tymków P., Jóźków G., Walicka A., Karpina M., Borkowski A. 2019. Identification of Water Body Extent Based on Remote Sensing Data Collected with Unmanned Aerial Vehicle. Water, 11: 338.
]Search in Google Scholar
[
U.S. Geological Survey. 2014. USGS Water Use Data for the Nation - National Water Information System (NWIS): U.S. Geological Survey data release.
]Search in Google Scholar
[
UK Water Resources Portal. [Online] Available: https://nrfa.ceh.ac.uk/content/uk-water-resources-portal (accessed on 04 August 2024).
]Search in Google Scholar
[
United States Agency for International Development. 2020. Data for Water Security: Improving Water Data Access and Use. United States Agency for International Development, Washington DC, USA.
]Search in Google Scholar
[
USGS EROS Archive - Digital Elevation - HYDRO1K. https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-hydro1k (accessed on 20 July 2024).
]Search in Google Scholar
[
USGS EROS Archive. 2018. USGS EROS Archive – Digital Elevation – HYDRO1K, HYDRO1k Elevation Derivative Database.
]Search in Google Scholar
[
USGS Water Data for the Nation. [Online] Available: https://waterdata.usgs.gov/nwis (accessed on 03 August 2024).
]Search in Google Scholar
[
Yamazaki D., Ikeshima D., Sosa J., Bates P.D., Allen G.H., Pavelsky T.M. 2019. MERIT Hydro: a high-resolution global hydrography map based on latest topography dataset. Water Resources Research, 55: 5053–5073.
]Search in Google Scholar
[
Young D. 2018. Integrating Data Using Open Standards. Proceedings of the Water Environment Federation, 3218–3221.
]Search in Google Scholar
[
Zhao R., Chen J., Wang D., Shang Y., Wang Z., Li X., Ai T. 2012. Updating Geospatial Data from Large Scale Data Sources. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVIII-4/W25: 68–72.
]Search in Google Scholar
[
Zhao Z., Wang H., Zhang Y., Deng C., Xie Q., Wang C. 2020. Problems and Countermeasures of River Management in the Process of Rapid Urbanization in China. Water, 12: 2260.
]Search in Google Scholar
Profilo Orcid