Inventory and functional classification of ponds based on Sentinel-2 NDWI data in the Sovytsia Kitsmanska River basin (Ukraine)
DOI:
https://doi.org/10.31861/geo.2025.854.150-169Keywords:
Sovytsia Kitsmanska River, basin,, ponds,, small water bodies,, QGIS,, NDWI,, Sentinel-2,, geoinformation analysis, water surface area,, pond classification.Abstract
The article presents a methodology for creating a unified digital database of ponds in the Sovytsia Kitsmanska River basin and their classification by area and degree of current utilisation using open geospatial data and the desktop GIS QGIS 3.34. Within a single GIS project, Sentinel-2 L2A satellite images, Google orthophotos, OpenStreetMap and Visicom cartographic basemaps, as well as the Copernicus DEM were integrated, which ensured full coverage of the basin and made it possible to reliably visually identify pond basins and associated waterlogged areas. Based on the NDWI index calculated in the QGIS raster calculator, the contours of open water surfaces and waterlogged areas were delineated, digitised as polygons and merged into a GeoPackage database, followed by reprojection to the metric coordinate system WGS 84 / UTM zone 35N for correct area determination. For each pond, the area of the water surface was calculated in square metres, hectares and square kilometres, and a two-level classification scheme was implemented: by functional status (actively exploited, abandoned, under reclamation) and by five area classes (<0.5; 0.5–1; 1–5; 5–10; >10 ha). In total, 397 ponds were identified in the basin, of which 259 are actively exploited, 81 are abandoned and 57 are under reclamation. It is shown that the most numerous are the smallest water bodies (with an area of up to 0.5 ha), which account for about two fifths of the total number but provide only a small share of the total water surface area. In contrast, the largest ponds (>10 ha), being relatively few in number, accumulate most of the area of regulated waters. The proposed methodology demonstrates that combining open satellite data, index analysis (NDWI), manual vectorisation and the statistical tools of QGIS makes it possible to obtain a simple, reproducible and scalable scheme for the inventory of small water bodies. The resulting database and pond classification can be used for quantitative assessment of flow regulation, identification of priority areas for reclamation and support of decision-making in the field of local water use and spatial planning in agricultural landscapes.
Ponds are an important element of agricultural landscapes and local water systems, yet small water bodies often remain “invisible” to conventional statistics and large-scale inventories, which complicates the assessment of their contribution to flow regulation and the provision of ecosystem services. In the Sovytsia Kitsmanska River basin, over a long period a dense network of ponds of various purposes and conditions has formed, and the information about them in available sources is fragmented and unsystematic. In such a situation, methods that make it possible, on the basis of open geospatial sources and GIS tools, to carry out a complete inventory of ponds, accurately determine their area and consistently describe the degree of their current use become particularly relevant. The aim of this study is to create a unified digital database of ponds in the Sovytsia Kitsmanska basin in the QGIS environment and to develop a two-level classification that combines a division by water surface area with the functional status of ponds. The proposed scheme is intended to provide a simple and reproducible basis for further analysis of the structure of the pond network, monitoring of changes and support of practical decisions in the field of local water use and spatial planning
References
1. Amoah, M. K. M. (2022). Mapping wetlands using GIS and remote sensing [Master’s thesis, Bowling Green State University]. BGSU ScholarWorks.
2. Bespalko, R., & Hutsul, T. (2021). Technological features of distribution between river basins using GIS technologies (based on the example of r. Brusnytsya). Visnyk of V. N. Karazin Kharkiv National University, Series “Geology. Geography. Ecology”, 55, 117–127. https://doi.org/10.26565/2410-7360-2021-55-09
3. Buzey, O. V., & Pasichnyk, M. D. (2025). Comparative evaluation of spectral indices for semi-automatic extraction of river surface. Natural Sciences Education and Research, 2025(3), Article 17. https://doi.org/10.32782/NSER/2025-3.17
4. Chaskovskyi, O., Andreichuk, Yu., & Yamelynets, T. (2021). Застосування ГІС у природоохоронній справі на прикладі відкритої програми QGIS [Application of GIS in environmental protection using the open-source QGIS program]. Простір-М. (in Ukrainian).
5. Dahal, K. (2020). Open source GIS-based lake basin delineation procedure: A tutorial (ILBM training materials). International Lake Environment Committee. Retrieved from https://www.ilec.or.jp
6. Dumalag, J. B. L. C., Blanco, A. C., & Tamondong, A. M. (2024). Fishpond status mapping using radar remote sensing. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-4/W8-2023, 195–202. https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-195-2024
7. Enriquez, M. D. (2022). Catchment delineation of Pandurucan River using quantum geographical information system (QGIS). AIP Conference Proceedings, 2472(1), 040005. https://doi.org/10.1063/5.0092766
8. Falasy, A., & Cooke, R. (2025). QGIS-based support tools to simplify the complex design challenges of subsurface drainage systems. Irrigation and Drainage, 74(1), 199–215. https://doi.org/10.1002/ird.3011
9. Hrebin, V. V., Khilchevskyi, V. K., Stashuk, V. A., Chunariov, O. V., & Yaroshevych, O. Ye. (2014). Vodnyi fond Ukrainy. Shtuchni vodoimy. Vodoskhovyshcha i stavky: Dovidnyk [Water fund of Ukraine. Artificial reservoirs. Reservoirs and ponds: A reference book] (V. K. Khilchevskyi & V. V. Grebin, Eds.). Kyiv: Interpres LTD (in Ukr.).
10. Pasichnyk, M., Yushchenko, Y., Palanychko, O., Melnyk, A. and Darchuk, K. (2025). Remote Sensing and GIS in the Research of Young River Landscape. Grassroots Journal of Natural Resources, 8(1): 163-189. https://doi.org/10.33002/nr2581.6853.080106
11. Hopchak, I. V. (2021). Naukovi zasady zberezhennia ta vidrodzhennia malykh richok Zakhidnoho Polissia Ukrainy [Scientific principles of conservation and revival of small rivers of Western Polissya of Ukraine]. Avtoreferat doktorskoi dysertatsii [Abstract of thesis doctoral dissertation]. Kyiv: Instytut vodnykh problem i melioratsii Natsionalnoi akademii ahrarnykh nauk Ukrainy (in Ukr.).
12. Hopchak, I. V., & Basyuk, T. O. (2014). Uporiadkuvannia vodookhoronnykh zon Bratslavskoho vodoskhovyshcha za umovy pidvyshchennia rivnia vody [Arrangement of water protection zones of the Bratslav reservoir under the condition of water level increase]. Visnyk Natsionalnoho universytetu vodnoho hospodarstva ta pryrodokorystuvannia. Tekhnichni nauky [Bulletin of the National University of Water Management and Nature Management. Technical Sciences], 4, 66–73 (in Ukr.).
13. Jamroen, C., Sritrakul, N., Nuchprayoon, P., Noppakun, A., Phonratanasoontorn, W., & Siritaratiwat, A. (2024). A geographic information system-assisted techno-economic assessment framework for aquavoltaic systems in shrimp farming. Energy Reports, 12, 881–891. doi:10.1016/j.egyr.2024.06.059
14. Kim, B., Lee, J., & Park, J. (2022). Role of small wetlands on the regime shift of ecological network in a wetlandscape. Environmental Research Communications, 4(4), 041006. doi:10.1088/2515-7620/ac5e46
15. Kovalchuk, I., Kovalchuk, A., Kovalchuk, I., Tsaryk, L., Pavlovska, T., & Pylypovych, O. (2023). Kontseptualni zasady doslidzhen heoekolohichnoho stanu richkovo-baseinovykh system ta yikh tsyfrovoho atlasnoho kartohrafuvannia [Conceptual foundations of research on the geo-ecological state of river-basin systems and their digital atlas mapping]. Naukovi zapysky Ternopilskoho natsionalnoho pedahohichnoho universytetu imeni Volodymyra Hnatiuka. Seriia: Heohrafiia [Scientific Notes of Ternopil Volodymyr Hnatiuk National Pedagogical University. Series: Geography], 55(2). doi:10.25128/2519-4577.23.2.1 (in Ukr.).
16. Kozmuk, P. F., Kulish, V. I., & Chernyavsky, O. A. (2007). Zemelni resursy Bukovyny: Stan, monitorynh, vykorystannia [Land resources of Bukovina: State, monitoring, use]. Chernivtsi: Bukrek (in Ukr.).
17. Nielsen, K., Stenseng, L., Andersen, O. B., & Knudsen, P. (2017). The performance and potentials of the CryoSat-2 SAR and SARIn modes for lake level estimation. Water, 9(6), Article 374. https://doi.org/10.3390/w9060374
18. Palamarchuk, M. M., & Zakorchevna, N. B. (2001). Vodnyi fond Ukrainy: Dovidkovyi posibnyk [Water fund of Ukraine: Reference manual] (V. M. Khorsov & K. A. Aliiev, Eds.). Kyiv: Nika-Tsentr (in Ukr.).
19. Passy, P., & Selles, A. (2018). Reservoir hydrological monitoring by satellite image analysis. In N. Baghdadi, C. Mallet, & M. Zribi (Eds.), QGIS and applications in water and risks (pp. 77–103). ISTE / John Wiley & Sons. https://doi.org/10.1002/9781119476726.ch3
20. Pasichnyk, M. D. (2024). GІS-modeliuvannia vodozbirnoho baseinu ta richkovoi merezhi: analiz hidrologichnykh protsesiv na prykladi baseinu richky Brusnytsia [GIS modelling of the drainage basin and river network: Analysis of hydrological processes using the Brusnytsia River basin as a case study]. Hidrologiia, hidrokhimiia i hidroekolohiia, 4(74), 30–44. https://doi.org/10.17721/2306-5680.2024.4.3
21. Primavera, J. H., Savaris, J. P., Bajoyo, B. E., Coching, J. D., Curnick, D. J., Golbeque, R. L., Guzman, A. T., Henderin, J. Q., Joven, R. V., Loma, R. A., & Koldewey, H. J. (2012). Manual on community-based mangrove rehabilitation (Mangrove Manual Series No. 1). Zoological Society of London. https://cms.zsl.org/sites/default/files/2023-02/1%20Manual%20-%20Community-based%20Mangrove%20Rehabilitation.pdf ZSL+1
22. Rapinel, S., Fabre, E., Dufour, S., Arvor, D., Garbey, C., & Hubert-Moy, L. (2019). Mapping potential, existing and efficient wetlands using free remote sensing data. Journal of Environmental Management, 247, 829–839. https://doi.org/10.1016/j.jenvman.2019.06.098
23. Rapinel, S., Hubert-Moy, L., Clément, B., Nabucet, J., & Sellin, V. (2019). Mapping potential, existing and efficient wetlands using remote-sensing-derived data. Journal of Environmental Management, 247, 829–839.
24. Rapinel, S., Panhelleux, L., Gayet, G., Vanacker, R., Lemercier, B., Laroche, B., Chambaud, F., Guelmami, A., & Hubert-Moy, L. (2023). National wetland mapping using remote-sensing-derived environmental variables, archive field data, and artificial intelligence. Heliyon, 9(2), e13482. https://doi.org/10.1016/j.heliyon.2023.e13482
25. Smith, L. P., Clarke, L. E., Weldon, L., & Robson, H. J. (2022). An evidence-based study mapping the decline in freshwater ponds in the Severn Vale catchment in the UK between 1900 and 2019. Hydrobiologia, 849, 4637–4649. doi:10.1007/s10750-022-05000-w
26. Van der Kwast, H., & Menke, K. (2022). QGIS for hydrological applications: Recipes for catchment hydrology and water management (2nd ed.). Locate Press. Locate Press page for the book
27. Velychko, S., & Dupliak, O. (2025). Calculation of an elevation-volume curve of the water reservoir using GIS. Problems of Water Supply, Sewerage and Hydraulic Engineering. Retrieved from https://wateruse.org.ua/article/view/334067
28. Vodna ramkova dyrektyva YeS 2000/60/ES. Osnovni terminy ta yikh vyznachennia [Water Framework Directive 2000/60/EC: Basic terms and their definitions]. (2006). Kyiv: N.p. (in Ukr.).
29. Vudvud, M., Pasichnyk, M., Yushchenko, Yu. (2024). Analiz stanu pryberezhnykh smuh vzdlovzh richok Sovytsia Stavchanska i Sovytsia Kitsmanska ta yikh roli u zberezhenni yakosti vodnykh ob’iektiv [Analysis of the condition of riparian strips along the Sovytsia Stavchanska and Sovytsia Kitsmanska rivers and their role in maintaining the quality of water bodies]. Naukovyi visnyk Chernivetskoho universytetu. Seriia: Heohrafiia [Scientific Bulletin of Chernivtsi University. Series: Geography], 847, 135–143. doi:10.31861/geo.2024.847.135-143 (in Ukr.).
30. Vyshnevsky, V. I. (2000). Richky i vodoimy Ukrainy. Stan i vykorystannia [Rivers and reservoirs of Ukraine: The state and use]. Kyiv: Vipol (in Ukr.).
31. Wachholz, A., Schmidt, S. I., Arle, J., & Völker, J. (2025). The German small lake and pond inventory [Preprint]. Earth System Science Data Discussions. https://doi.org/10.5194/essd-2024-563
32. Yu, Z., Di, L., Rahman, M. S., & Tang, J. (2020). Fishpond mapping by spectral and spatial-based filtering on Google Earth Engine: A case study in Singra Upazila of Bangladesh. Remote Sensing, 12(17), 2692. doi:10.3390/rs12172692
33. Yushchenko, Yu. S. (2019). Vodookhoronni zemli [Water protection lands]. In Problemy hidrolohii, hidrokhimii, hidroekolohii [Problems of hydrology, hydrochemistry, hydroecology] (pp. 32–39). Kyiv: Nika-Tsentr (in Ukr.).
34. Zoological Society of London (ZSL). (2023). Digitizing fishpond survey plans (resources within project “Mangroves”). Retrieved from https://www.zsl.org/what-we-do/projects/mangroves
35. QGIS Development Team. (2024). QGIS user guide (Release 3.34). QGIS Association. (Джерело)
