CURRENT STATE AND DIRECTIONS OF THE USAGE OF REMOTE TOOLS FOR INVENTORY AUDITING OF IRRIGATION SYSTEMS
Keywords:
inventory audit, irrigation systems, remote sensing, GIS, UAV, satellite data
Abstract
The paper examines modern approaches to conducting an inventory audit of irrigation systems using remote tools. The traditional methods of irrigation systems inventory audit require significant financial and labor costs, which complicates large-scale audit and planning of measures for the reconstruction and modernization of irrigation systems. According to the results of the research, it was found that remote technologies are the most appropriate for inventorying such basic elements of irrigation systems as pumping stations, antechambers, open earth and concrete canals, pipelines, hydrants, water distribution facilities, and other components of engineering infrastructure. Based on the analysis, a list of remote tools that can be used to assess the technical condition of irrigation facilities was determined. It includes satellite remote sensing of the Earth, namely the use of optical, multispectral, and hyperspectral images, aerial photography using unmanned aerial vehicles, geophysical research methods, in particular ground penetrating radar (GPR) and electromagnetic methods for tracing underground communications, as well as geographic information systems for integrating, analyzing, modeling, and visualizing the obtained results.
Our research has shown that a comprehensive approach that combines modern remote sensing, geophysical, and geoinformation methods creates additional opportunities for conducting an effective inventory audit of irrigation systems in Ukraine, increases the efficiency of surveys, the accuracy of determining the technical condition of facilities, and the objectivity of the obtained results. The results of the performed analytical studies can be used to justify the choice of tools and develop recommendations for conducting an inventory audit of irrigation systems by remote means.
References
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15. Vlasova, O., Savchuk, D., Shevchenko, I., Shevchenko, A., & Kozytskyi, O. (2025). Spatial and temporal changes in the ecological and reclamation state of drainless areas. Land Reclamation and Water Management, (1), 17 - 27. https://doi.org/10.31073/mivg202501-417
16. Voytovych, I., Shevchuk, Y., KozytskyiO., Ignatova, O., Boyko, G., & Limachov, Y. (2025). Assessment of the technical condition of the krasnopavlivsk reservoir earth dam. Land Reclamation and Water Management, (1), 98 - 108. https://doi.org/10.31073/mivg202501-412
17. Vlasova, O., Shevchenko, I., Kozytskyi, O., Shevchenko, A., & Voitovych, O. (2024). Assessment of the current ecological state of the fastiv reservoir using ground and satellite data. Land Reclamation and Water Management, (2), 11 - 18. https://doi.org/10.31073/mivg202402-399
18. Vlasova, O., Shevchenko, A., Shevchenko, I., & Kozytsky, O. (2023). Monitoring of water bodies and reclaimed lands affected by warfare using satellite data. Land Reclamation and Water Management, (2), 59 - 68. https://doi.org/10.31073/mivg202302-371
19. Matiash, T., Romashchenko, M., Bogaenko, V., Shevchuk, S., Kruchenyuk, A., & Butenko, Y. (2022). Monitoring and irrigation regime formation when growing crops using the "Irrigation Online" system. Land Reclamation and Water Management, (1), 29 - 39. https://doi.org/10.31073/mivg202201-321
20. Lykhovyd, P. (2025). Geospatial Intelligence and Remote Sensing for Climate-Smart and Sustainable Agriculture. Deep Science Publishing. https://doi.org/10.70593/978-93-7185-854-0
21. Lykhovyd, P. (2025, October 22–24). An evaluation of machine learning algorithm performance in crop recognition using remote sensing: A case study in Southern Ukraine [Paper presentation]. 3rd International Online Conference on Agriculture: Smart Farming: From Sensor to Artificial Intelligence. https://sciforum.net/paper/view/24734
22. Lykhovyd, P., Vozhehova, R., Hranovska, L., Yuziuk, S., & Bidnyna, I. (2024). Fenolohichnyi monitorynh silskohospodarskykh kultur iz vykorystanniam danykh dystantsiinoho zonduvannia zemli [Phenological monitoring of agricultural crops using remote sensing data]. Tekhniko-Tekhnolohichni Aspekty Rozvytku ta Vyprobuvannia Novoi Tekhniky i Tekhnolohii dlia Silskoho Hospodarstva Ukrainy, 35(49), 98–106. https://doi.org/10.31473/2305-5987-2024-2-35(49)-9
23. Kuzmych, L.V., Voropai, H.V., Kuzmych, A.A, Polishchuk, V.V., & Kuzmych, S.A. (2021). Kontseptsiia pobudovy avtomatyzovanoi systemy dystantsiinoho monitorynhu ta kontroliu tekhnichnoho stanu ob’iektiv inzhenernoi infrastruktury vodohospodarsko-melioratyvnoho kompleksu [Concept of building an automated system for remote monitoring and control of the technical condition of engineering infrastructure facilities of the water management and land reclamation complex]. Visnyk Natsionalnoho universytetu vodnoho hospodarstva ta pryrodokorystuvannia:zbirnyk naukovykh prats, 1, 215-222. [in Ukrainian].
24. Shevchuk, S., Vyshnevskyi, V., & Bilous, O. (2022). The use of remote sensing data for investigation of environmental consequences of russia-ukraine war. Journal of Landscape Ecology, Vol. 15 (3). DOI: 10.2478/jlecol-2022-0017
25. Shevchuk, S., Matiash, T., & Krucheniuk, A. (2025). Assessment of Water Resources Needs for Irrigation Development under Climate Change in Ukraine. 18th International Conference Monitoring of Geological Processes and Ecological Condition of the Environment, Apr 2025, Vol. 2025, 1 – 5 https://doi.org/10.3997/2214-4609.2025510141
26. Polishchuk, V., Zhovtonog, O., Saliuk, A., Butenko, Y., & Chorna, K. (2021). Model Complex of Information System “GIS Poliv” and Remote Sensing Data use to Adjust Model Parameters. In 2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) (pp. 211-214). IEEE. ISBN 978-166543845-2 DOI: 10.1109/ Atit54053.2021.9678578
27. U.S. Geological Survey. (n.d.). EarthExplorer. https://earthexplorer.usgs.gov
28. U.S. National Archives. (n.d.). Satellite photography (CORONA collection). https://www.archives.gov/research/cartographic/aerial-photography/satellite-photography
29. U.S. Geological Survey. (n.d.). EROS: Earth Resources Observation and Science Center. https://www.usgs.gov/centers/eros
30. Google. (n.d.). Google Earth Engine. https://earthengine.google.com/
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Published
2026-06-30
How to Cite
Romashchenko, M., Usatyi, S., Polishchuk, V., Usata, L., Kolomiets, S., KovalenkoІ., & Sardak, A. (2026). CURRENT STATE AND DIRECTIONS OF THE USAGE OF REMOTE TOOLS FOR INVENTORY AUDITING OF IRRIGATION SYSTEMS. Land Reclamation and Water Management, (1), 16 - 27. https://doi.org/10.31073/mivg202601-441
Section
Articles
