The paper proposes a methodology for transforming an arbitrary cartographic representation of hydrographic networks to the tree graph form. This methodology is designed to semi-automatically convert hydrographic layers from cartographic databases into a format suitable for hydrologic modeling and geomorphometric analysis from topological perspective. In the resulting dataset, hydrography polygons are replaced by their centerlines, planarity and tree-like structure of the hydrographic network is ensured, while the orientations of the lines are aligned with directions of the corresponding watercourses. The transformation of hydrography layers is achieved with polygon skeletonization, followed by the path routing along the hydrographic network graph from sources to outlets within first-order drainage basins. After the first iteration of routing, a significant number of discontinuities in the original hydrographic network are typically identified. These discontinuities must be corrected manually and iteratively. When the manual correction of the original graph and the final routing iteration is completed, hydrographic network tree representation is extracted from the route lines. The resulting vector dataset meets the requirements for use in hydrological modeling. However, when examining the orientations of the lines within some individual river basins, errors can be found, caused by the presence of connecting links between sub-basins. As a result of these errors, the lines of some rivers adopt orientations opposite to the actual flow direction.

Mikhail V. Uzhegov
Graduate student
Department of Geography, Lomonosov Moscow State University
GSP-1, 1 Leninskiye Gory, MSU, Faculty of Geography, Moscow, 119991, Russia
e-mail: uzhegovmv@my.msu.ru
ORCID ID: 0009-0009-0812-2751
ResearcherID: LFS-0719-2024
SPIN: 6844-9687

Andrey L. Entin
Candidate of Geographical Sciences (PhD in Cartography)
Senior Researcher
Department of Geography, Lomonosov Moscow State University
GSP-1, 1 Leninskiye Gory, MSU, Faculty of Geography, Moscow, 119991, Russia
e-mail: aentin@geogr.msu.ru
ORCID ID: 0000-0002-0350-5587
SCOPUS ID: 57202589652
ResearcherID: V-3775-2017
SPIN: 2012-3433

1. Lehner B., Grill G. Global river hydrography and network routing: Baseline data and new approaches to study the world’s large river systems. Hydrological Process. 2013;27(15):2171–2186. DOI: 10.1002/hyp.9740.
2. Lin P., Pan M., Beck H.E., Yang Y., Yamazaki D., Frasson R., David C.H., Durand M., Pavelski T.M., Allen G.H., Gleason C.J., Wood E.F. Global Reconstruction of Naturalized River Flows at 2.94 Million Reaches. Water Resources Research. 2019;55(8):6499–6516. DOI: 10.1029/2019WR025287.
3. Mizukami N., Clark M.P., Gharari Sh., Kluzek E., Pan M., Lin P., Beck H.E., Yamazaki D. A Vector-Based River Routing Model for Earth System Models: Parallelization and Global Applications. Journal of Advances in Modeling Earth Systems. 2021;13(6):e2020MS002434. DOI: 10.1029/2020MS002434.
4. Graham S.T., Famiglietti J.S., Maidment D.R. Five-minute, 1/2 °, and 1° data sets of continental watersheds and river networks for use in regional and global hydrologic and climate system modeling studies. Water Resources Research. 1999;35(2):583–587. DOI: 10.1029/1998WR900068.
5. Samsonov T.E. Automated conflation of digital elevation model with reference hydrographic lines. ISPRS International Journal of Geo-Information. 2020;9(5):334. DOI: 10.3390/ijgi9050334.
6. Mayorga E., Logsdon M.G., Ballester M.V.R., Richey J.E. Estimating cell-to-cell land surface drainage paths from digital channel networks, with an application to the Amazon basin. Journal of Hydrology. 2005;315(1–4):167–182. DOI: 10.1016/j.jhydrol.2005.03.023.
7. Olivera F., Raina R. Development of large scale gridded river networks from vector stream data. Journal of the American Water Resources Association. 2003;39(5):1235–1248. DOI: 10.1111/j.1752-1688.2003.tb03705.x.
8. O’Callaghan J.F., Mark D.M. The extraction of drainage networks from digital elevation data. Computer Vision, Graphics, and Image Processing. 1984;28:323–344. DOI: 10.1016/S0734-189X(84)80047-X.
9. Lehner B., Roth A., Huber M., Anand M., Grill G., Osterkamp N., Tubbesing R., Warmedinger L., Thieme M. HydroSHEDS v2.0 – Refined global river network and catchment delineations from TanDEM-X elevation data. In: vEGU21, the 23rd EGU General Assembly. 2021. EGU21-9277. Available at: https://ui.adsabs.harvard.edu/abs/2021EGUGA..23.9277L/abstract (accessed 03.40.2026). DOI: 10.5194/egusphere-egu21-9277.
10. USGS EROS Archive – Digital Elevation – HYDRO1K. 2018. Available at: https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-hydro1k (accessed 30.05.2025). DOI: 10.5066/F77P8WN0.
11. Yamazaki D., Ikeshima D., Sosa J., Bates P.D., Allen G.H., Pavelsky T.M. MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset. Water Resources Research. 2019;55(6):5053–5073. DOI: 10.1029/2019WR024873.
12. Bhandari P. Digital Chart of the World. Geos. 1993;20(1):22–25.
13. World Shapefiles, Vector Map Level 0 (VMAP0). 2000. Available at: https://lib.msu.edu/map/findingaids/VMAP0 (accessed 30.05.2025).
14. Vector Digital Topographic Map – VMap1, 1945 -1996. 2003. Available at: https://open.canada.ca/data/en/dataset/7fa46d41-2d69-47e8-b66b-51ce178b9983 (accessed 30.05.2025).
15. Karpinsky Institute. Digital topographic bases [Electronic resource]. – 2005. – URL: https://karpinskyinstitute.ru/ru/info/topo (accessed 30.05.2023).
16. Polygon To Centerline (Topographic Production). ArcGIS Pro. 2025. Available at: https://pro.arcgis.com/ru/pro-app/latest/tool-reference/topographic-production/polygon-to-centerline.htm (accessed 18.08.2025).
17. Schwenk J., Piliouras A., Rowland J.C. Determining flow directions in river channel networks using planform morphology and topology. Earth Surface Dynamics. 2020;8(1):87–102. DOI: 10.5194/esurf-8-87-2020.
18. Motovilov Yu.G. Sistema fiziko-matematicheskikh modelei formirovaniya rechnogo stoka i ee primenenie v zadachakh gidrologicheskikh raschetov i prognozov [System of Physically-Based Models of River Runoff Formation and Its Application in Hydrological Calculations and Forecasts]: Doctor of Geogr. Sciences diss. Moscow, 2019. 368 p.
19. Ogniewicz R., Ilg M. Voronoi skeletons: Theory and applications. In: Proceedings of the 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) (Champaign, Illinois, June 1992). 1992. pp. 63–69.