Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 23, 2026
Number 1 Number 2 Number 3
Volume 22, 2025
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 21, 2024
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 20, 2023
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 19, 2022
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 18, 2021
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 17, 2020
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 16, 2019
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 15, 2018
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 14, 2017
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 13, 2016
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 12, 2015
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 11, 2014
Number 1 Number 2 Number 3 Number 4
Volume 10, 2013
Number 1 Number 2 Number 3 Number 4
Volume 9, 2012
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 8, 2011
Number 1 Number 2 Number 3 Number 4
Volume 7, 2010
Number 1 Number 2 Number 3 Number 4
Issue 6, 2009
Volume 1 Volume 2
Issue 5, 2008
Volume 1 Volume 2
Issue 4, 2007
Volume 1 Volume 2
Issue 3, 2006
Volume 1 Volume 2
Issue 2, 2005
Volume 1 Volume 2
Issue 1, 2004
Volume 1
Search
Find:
русский
ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2026. Т. 23. № 3. С. 371-377

On importance of satellite information in the task of reservoir storage monitoring

A.G. Terekhov 1 , G.N. Sagatdinova 1 , R.I. Mukhamediev 2 
1 Institute of Information and Computational Technologies, Almaty, Kazakhstan
2 K.I. Satbayev Kazakh National Research University, Almaty, Kazakhstan
Accepted: 17.04.2026
DOI: 10.21046/2070-7401-2026-23-3-371-377
Some small reservoirs have convenient parameters for conducting remote monitoring of reservoir storage using the most popular satellite systems, such as Sentinel-2 (resolution 10 m) and Landsat (resolution 30 m). Due to small size of a reservoir, wind surge of water that distorts satellite estimates is negligible and the coastline position and mirror area can change significantly as a result of reservoir operation. Satellite estimates are particularly relevant in the case of transboundary rivers, where key reservoirs are located in neighboring countries. This research examines the Kirov Reservoir (550 million m3) located in Kyrgyzstan at the border with Kazakhstan on the transboundary Talas River (0.9 km3). The lower part of the Talas River valley belongs to Kazakhstan, so monitoring the resources of the Kirov Reservoir is very important for Kazakhstan water users. During operation, the water surface area of the reservoir varies between 0.6 and 26 km2 and the water edge can shift by more than 8 km. This significant spatial variability of the water objects allows for high-resolution satellite monitoring using Sentinel-2 and Landsat-8, -9 data. In this study, based on 80 Sentinel-2 satellite images from 2019 to 2023 and synchronous average daily ground-based data from the Water Resources Service of the Kyrgyz Republic, an empirical model was developed to determine the water reserve storage based on the position of the water edge. The results of satellite monitoring in March–June 2024 showed that the data published by the relevant organization in Kyrgyzstan on its online resource systematically underestimated water reserves by up to 40 million m3. Also, an assessment of water reserves in the 2025 season was carried out, which was not promptly presented on this Internet resource. Thus, high-detail satellite monitoring of the state of small reservoirs using Sentinel-2 and Landsat-8, -9 appears to be an important part of hydrological monitoring, ensuring the reliability and robustness of the obtained data on water reserves in the reservoir, especially true when there is no access to ground-based information or it is distorted.
Keywords: remote sensing, satellite monitoring, reservoir, reservoir storage, water edge, Sentinel-2, Landsat-9
Full text

References:

  1. Artikova F. Ya., Kalabaev S. B., Prospects for using satellite data to determine water levels in large lakes, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 4, pp. 251–259 (in Russian), DOI: 10.21046/2070-7401-2024-21-4-251-259.
  2. Tertychnaya A. S., Tertychniy K. S., Khoperskov A. V., Method for determining the coastlines of water bodies based on processing Landsat ETM+ remote sensing data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, V. 20, No. 5, pp. 28–38 (in Russian), DOI: 10.21046/2070-7401-2023-20-5-28-38.
  3. Khamedov V. A., Fratya D. A., Analysis of spatial and temporal dynamics of lake landscapes near Urengoyskaya power plant, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 2, pp. 261–270 (in Russian), DOI: 10.21046/2070-7401-2024-21-2-261-270.
  4. Avisse N., Tilmant A., Müller M. F., Zhang H., Monitoring small reservoirs’ storage with satellite remote sensing in inaccessible areas, Hydrology and Earth System Sciences, 2017, V. 21, pp. 6445–6459, DOI: 10.5194/hess-21-6445-2017.
  5. Codjia A. K. D., Akpoti K., Dembélé M. et al., Estimating water levels in reservoirs using Sentinel-2 derived time series of surface water areas: A case study of 20 reservoirs in Burkina Faso, Intern. J. Applied Earth Observation and Geoinformation, 2025, V. 139, Article 104523, DOI: 10.1016/j.jag.2025.104523.
  6. Codjia A. K. D., Akpoti K., Dembélé M. et al., Satellite remote sensing for estimating reservoir physical characteristics: A global review of existing methodologies for operational monitoring, Science of Remote Sensing, 2026, V. 13, Article 100383, DOI: 10.1016/j.srs.2026.100383.
  7. Li J., Ma R., Cao Z et al., Satellite detection of surface water extent: A review of methodology, Water, 2022, V. 14, Iss. 7, Article 1148, DOI: 10.3390/w14071148.
  8. McFeeters S. K., The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features, Intern. J. Remote Sensing, 1996, V. 17, Iss. 7, pp. 1425–1432, DOI: 10.1080/01431169608948714.
  9. Xu H., Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery, Intern. J. Remote Sensing, 2006, V. 27, Iss. 14, P. 3025–3033, DOI: 10.1080/01431160600589179.