Back to search

Assessment of change of water level in the Burluk River using digital terrain models

The study assesses the change of the water level in the Burluk River using a digital terrain model and satellite images from OGIS. The interest in this topic is connected with the recent and frequent observations of changing hydrological regime of rivers, which can lead to underflooding and other adverse consequences for the river-adjacent mining operations and population clusters. The research used the data from a digital terrain model and different-time  satellite images for processing and definition of the water surface of rivers with the help of the water indexes. The riverbed was digitalized, and the terrain relief was analyzed. That allowed following the change in the water plane area in different periods of time, and identifying land sites most exposed to flooding. The results show that the Burluk River is highly sensitive to seasonal changes: the riverbed expands during the flood season and narrows in the dry weather season. GIS technologies appear to be a convenient and demonstrative tool for the analysis of such processes and for the prompt decision-making on prevention of their adverse effects. 

Keywords: Burluk River, digital terrain model, earth remote sensing, QGIS, NDWI, MNDWI, hydrological monitoring, flood seasons.
For citation:

Bessimbayeva O. G., Khmyrova E. N., Bakhaeva S. P., Kaltaeva A. A. Assessment of change of water level in the Burluk River using digital terrain models. MIAB. Mining Inf. Anal. Bull. 2026;(10-1):140-151. [In Russ]. DOI: 10.25018/0236_1493_2026_101_0_140.

Acknowledgements:
Issue number: 10-1
Year: 2026
Page number: 140-151
ISBN: 0236-1493
UDK: 551.444
DOI: 10.25018/0236_1493_2026_101_0_140
Article receipt date: 10.06.2026
Date of review receipt: 25.08.2026
Date of the editorial board′s decision on the article′s publishing: 20.09.2026
About authors:

O.G. Bessimbayeva1, Cand. Sci. (Eng.), Associate Professor, Associate Professor, e-mail: bog250456@mail.ru, ORCID ID: 0000-0002-8132-1505,
E.N. Khmyrova1, Cand. Sci. (Eng.), Associate Professor, e-mail: alena.khmyrova.rodina@mail.ru, ORCID ID: 0000-0001-5763-327X,
S.P. Bakhaeva, Dr. Sci. (Eng.), Professor, Kuzbass State University named after Gorbachev, Kemerovo, Russia, e-mail: bsp.mdg@kuzstu.ru, ORCID ID: 0009-0003-1764-2341, 
A.A. Kaltaeva1, Master's Student of the EP «Geodesy», e-mail: asyltas.kaltaeva@mail.ru,
1 Karaganda Technical University named after Abylkas Saginov, 100008, Karaganda, Republic of Kazakhstan. 

 

For contacts:

E.N. Khmyrova, e-mail: alena.khmyrova.rodina@mail.ru.

Bibliography:

1. Karpik A. P., Ganagina I. G., Opritova O. A. Assessment of the accuracy of global digital terrain models on the territory of the Russian Federation. Geodesy and Cartography. 2025, no. 10, pp. 2—11. [In Russ]. DOI: 10.22389/0016-7126-2025-1024-10-2-11.

2. Pekel J., Cottam A., Gorelik N., Belward A. High-resolution mapping of global surface water and its long-term changes. Nature. 2016, vol. 540 (7633), pp. 418—422. DOI: 10.1038/nature20584.

3. Zelalem Demissie, Prashant Rimal, Wondwosen M., Atri Dutta, Glen Rimmington Flood susceptibility mapping: Integrating machine learning and GIS for enhanced risk assessment. Applied Computing and Geosciences. 2024, vol. 23, article 100183. DOI: 10.1016/j.acags.2024.100183.

4. Orlov P. Y. Analysis of the experience of geoinformation modeling of karst-suffusion processes. Izvestia vuzov. Geodesy and Aerophotosurveying. 2022, vol. 66, no. 5, pp. 14—27. [In Russ]. DOI: 10.30533/0536-101Х-2022-66-5-14-27.

5. Kharazmi R. S., Chaban L. N. Analysis of ecosystem dynamics in the Sistan basin based on the results of automated processing of multispectral satellite images. Izvestia vuzov. Geodesy and Aerophotosurveying. 2015, no. 4, pp. 94—100. [In Russ].

6. Bondur V. G., Zakharova L. N., Zakharov A. I., Chimitdorzhiev T. N., Dmitriev A. V., Dagurov P. N. Long-term monitoring of the landslide process on Bureya riverbank based on interferometric L-band radar data. Current Problems in Remote Sensing of the Earth from Space. 2019, vol. 16, no. 5, pp. 113—119. [In Russ]. DOI: 10.21046/2070-7401-2019-16-5-113-119.

7. Kurbatova I. E. Space monitoring negative situations in coastal zones of large reservoirs. Current Problems in Remote Sensing of the Earth from Space. 2012, vol. 9, no. 2, pp. 52—59. [In Russ].

8. Akpambetova K. M., Abieva G. B. Geographical factors of the location of river valleys in Central Kazakhstan. Eurasian Union of Scientists (EUU). 2019, no. 4(61), pp. 26—31. [In Russ].

9. Abegeja D. The application of satellite sensors, current state of utilization, and sources of remote sensing dataset in hydrology for water resource management. Journal of Water and Health. 2024, vol. 22, no. 7, pp. 1162—1179.

10. Abd El-sadek E., Elbeih S., Negm A. Coastal and landuse changes of Burullus Lake, Egypt: A comparison using Landsat and Sentinel-2 satellite images. The Egyptian Journal of Remote Sensing and Space Science. 2022, vol. 25, no. 3, pp. 815—829.

11. Kuzmin K. A., Bukovskiy M. E., Voronkov A. V. Calculation of the morphometric characteristics of the river basin relief of high and low plains based on a digital elevation model. The Bulletin of Irkutsk State University Series «Earth Sciences». 2025, vol. 53, pp. 70—83. [In Russ]. DOI: 10.26516/2073-3402.2025.53.70.

12. Bezgodova O. V. Structural and morphometric analysis of the ihe-ukhgun small river basin (Irkut river basin). The Bulletin of Irkutsk State University Series «Earth Sciences». 2021, vol. 37, pp. 3—16. [In Russ]. DOI: 10.26516/2073-3402.2021.37.3.

13. Yang V., Harshadip N. R. Managing water resources in large river basins. Water. 2020, vol. 12, no. 12, article 3486. DOI: 10.3390/w12123486.

14. Volkova N. A. Improving the quality of hydrological forecasting based on reducing the criticality of information-based fuzzy estimates of river flow indicators. Russian water industry: problems, technologies, management. 2025, no. 5, pp. 97—118. [In Russ]. DOI: 10.35567/1999-4508-2025-5-97-118.

15. Andreevich P. P. Hydrological risks and their prevention in Kazakhstan. International Journal of Hydraulic Engineering. 2019, no. 3(1), pp. 3—4. [In Russ]. DOI: 10.15406/ijh.2019.03.00154.

16. Nada Kadhim Assessment of water level changes based on the analysis of optical satellite images. ISPRS Annals of Photogrammetry, Remote Sensing of the Earth and Spatial Information Sciences. 2025, pp. 445—452. DOI: 10.5194/isprs-annals-XG-2025-445.

17. MacFerrin M., Amante C., Carignan K., Love M., Lim E. The Earth Topography 2022 (ETOPO 2022) Global DEM dataset. Earth System Science Data. 2024, vol. 17, no. 5, pp. 1835—1849. DOI: 10.5194/essd-17-1835-2025.

18. Zhurkin I. G., Sychev G. G. Method of determining the coordinates of digital images of photogrammetric reference signs: development and evaluation of accuracy. Measuring equipment. 2021, no. 11, pp. 19—23. [In Russ]. DOI: 10.32446/0368-1025it.2021-11-19-23.

19. Chaban L. N., Berezina K. V. Information analysis of spectral and textural features in the classification of vegetation by hyperspectral aerial photographs. News of higher educational institutions. Izvestia vuzov. Geodesy and Aerophotosurveying. 2018, vol. 62, no. 1, pp. 85—95. [In Russ]. DOI: 10.30533/0536-101X-2018-62-1-85-95.

20. Svobodova K. Integrating cultural and spiritual restoration into mine closure: The case of wayside shrines and crosses. Energy Research & Social Science. 2025, vol. 127, article 104289. 

Подписка на рассылку

Подпишитесь на рассылку, чтобы получать важную информацию для авторов и рецензентов.