Remote monitoring of nature restoration at a mouth of a small river after cessation of industrial wastewater inflow

Estimation of natural restoration of aquatic ecosystems stricken with an intense manmade pressure and deprived of their natural functions is the ecological objective of paramount importance. The analysis of land self-restoration after cessation of industrial wastewater inflow at a mouth of a small river being a bay of the Kama Reservoir in the Perm Krai uses the data of Earth Remote Sensing. The spectral indexes are calculated: NDWI, NDVI, AMWI and NDTI. The mapping and analysis of the river mouth involved the Sentinel-2 data with a spatial resolution of 10 m from the period between 2016 and 2024, and the ultra-high spatial resolution images in the natural color range from 2016 up to the present day. The analysis results enable finding that the area of the vegetation restoration at the mouth of the old course of the river changes within an interval of 2.5–20.2 ha (2.5–60.5% of the whole area) depending on the flooding of the area. Evaluation of NDVI values reveals the grass and crown covers with the dominance of hydrophytic association. NDWI is an efficient tool of the spatiotemporal analysis and visualization of the water level dynamics and processes of natural invasion of waters. The calculated values of NDTI and AMWI are reflective of silting of the test area in the time of shallow waters. AMWI also points at the increased iron content of water. The accomplished research has a practical value for setting up monitoring of water for the operational control, protection and restoration of ecosystems within the limits of the upper Kama Reservoir. 

Drobinina Е. V., Ushakova Е. S., Perevoshchikova А. А. Remote monitoring of nature restoration at a mouth of a small river after cessation of industrial wastewater inflow. MIAB. Mining Inf. Anal. Bull. 2026;(4):74-90. [In Russ]. DOI: 10.25018/0236_1493_2026_4_0_74.

The study was supported by the Perm Krai, Agreement No. C-26/1872.

Е.V. Drobinina¹, Cand. Sci. (Geol. Mineral.), Assistant Professor, e-mail: alenadrobinina@yandex.ru, ORCID ID: 0000-0002-6756-7947,
Е.S. Ushakova¹, Cand. Sci. (Geol. Mineral.), Junior Researcher, e-mail: ushakova.evgeniya@gmail.com, ORCID ID: 0000-0002-2016-7356,
А.А. Perevoshchikova¹, Junior Researcher; Perm National Research Polytechnic University, 614990, Perm, Russia, e-mail: aaperevoshchikova@yandex.ru, ORCID ID: 0000-0003-1769-7740,
¹ Perm State National Research University, 614068, Perm, Russia.

Е.V. Drobinina, e-mail: alenadrobinina@yandex.ru.

1. Lepikhin A. P., Vozniak A. A., Lyubimova T. P., Parshakova Y. N., Lyakhin Y. S., Bogomolov A. V. Study of the formation features and scale of diff use pollution formed by large industrial com plexes, with the Solikamsk-Bereznikovsk industrial center as an example. Water Resources. 2020, vol. 47, no. 5, pp. 560—566. [In Russ]. DOI: 10.31857/S0321059620050120.

2. Belkin P. A. Chemical composition of spring discharge in the area of mining waste storage and potassium salt enrichment. Bulletin of Perm university. Geology. 2020, vol. 19, no. 3, pp. 232—240. [In Russ]. DOI: 10.17072/psu.geol.19.3.232.

3. Ushakova E. S., Belkin P. A., Baklanov M. A., Drobinina E. V., Puzik A. Yu. Ecological-geochemical and bioindication assessment of the small rivers pollution at the city of Berezniki. Bulletin of Perm university. Geology. 2022, vol. 21, no. 4, pp. 384—393. [In Russ]. DOI: 10.17072/psu.geol.21.4.375.

4. Ushakova E. S. Ekogeokhimiya vodnykh ekosistem urbanizirovannykh territoriy Severnogo Prikam'ya [Ecogeochemistry of Water Ecosystems in Urbanized Areas of the Northern Kama Region], Candidate’s thesis, Perm, 2024, 24 p.

5. Hauer F. R., Lorang M. S., Gonser T. Remote sensing to characterize river floodplain structure and function. Remote Sensing. 2022, vol. 14, article 1132. DOI: 10.3390/rs14051132.

6. Khavanskaya N. M., Novochadova A. V. Revegation analysis within the shurupov quarries based on remote sensing data. Natural systems and resources. 2023, vol. 13, no. 2, pp. 58—66. [In Russ]. DOI: 10.15688/nsr.jvolsu.2023.2.6.

7. Ozaryan Yu. A. Remote sensing of vegetation restoration in mining areas in the south of Russia’s Far East. Gornyi Zhurnal. 2024, no. 6, pp. 105—109. [In Russ]. DOI: 10.17580/gzh.2024.06.17. 

8. Mikov L. S., Schastlivcev E. L., Androkhanov V. A. Reclamation efficiency assessment at Nazarovo open pit mine using remote sensing. MIAB. Mining Inf. Anal. Bull. 2023, no. 1, pp. 70—83. [In Russ]. DOI: 10.25018/0236_1493_2023_1_0_70.

9. Pace B., Gutiérrez-Cánovas C., Henriques R., Carvalho-Santos C., Cássio F., Pascoal C. Remote sensing indicators to assess riparian vegetation and river ecosystem health. Ecological Indicators. 2022, vol. 144, article 109519. DOI: 10.1016/j.ecolind.2022.109519.

10. Caroppi G., Järvelä J. Shear layer over floodplain vegetation with a view on bending and streamlining effects. Environmental Fluid Mechanics. 2022, vol. 22, pp. 587—618. DOI: 10.1007/s10652-022-09841-w.

11. Iskin E. P., Wohl E. Quantifying floodplain heterogeneity with field observation, remote sensing, and landscape ecology: Methods and metrics. River Research and Applications. 2023, vol. 39, no. 5, pp. 911—929. DOI: 10.1002/rra.4109.

12. Berezina О. А., Shikhov А. N., Abdullin R. К. The use of multi-temporal satellite images for environmental assessment in coal mining areas (by example of closed Kizel coal basin). Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa. 2018, vol. 15, no. 2, pp. 144—158. [In Russ]. DOI: 10.21046/2070-7401-2018-15-2-144-158.

13. Demenev А. D., Berezina О. А., Maksimovich N. G., Mizev А. А. Applying remote sensing data to assess water quality in a mining area. Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa. 2024, vol. 21, no. 2, pp. 271—285. [In Russ]. DOI: 10.21046/2070-7401-2024-21-2-271-285.

14. Elhag M., Gitas I., Othman A., Bahrawi J., Gikas P. Assessment of water quality parameters using temporal remote sensing spectral reflectance in arid environments, Saudi Arabia. Water. 2019, vol. 11, no. 3, article 556. DOI: 10.3390/w11030556.

15. Lizcano-Sandoval L., Anastasiou Ch., Montes E., Raulerson G., Sherwood E., Muller-Karger F. Seagrass distribution, areal cover, and changes (1990—2021) in coastal waters off West-Central Florida, USA. Estuarine Coastal and Shelf Science. 2022, vol. 279, article 108134. DOI: 10.1016/j.ecss.2022.108134.

16. Laonamsai J., Julphunthong P., Saprathet T., Kimmany B., Ganchanasuragit T., Chomcheawchan P., Tomun N. Utilizing NDWI, MNDWI, SAVI, WRI, and AWEI for estimating erosion and deposition in Ping river in Thailand. Hydrology. 2023, vol. 10, article 70. DOI: 10.3390/hydrology10030070. 

17. McFeeters S. К. The use of the normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing. 1996, vol. 17, no. 7, pp. 1425—1432. DOI: 10.1080/01431169608948714.

18. Rouse J. W., Haas R. H., Scheel J. A., Deering D. W. Monitoring vegetation systems in the great plains with ERTS. Proceedings 3rd Earth Resource Technology Satellite (ERTS) Symposium. 1974, vol. 1, pp. 48—62, DOI: l0.l007/sl0230-021-00761-7.

19. Mou X., Chai H., Duan C., Feng Y., Wang X. An assessment of vegetation changes in the three-river headwaters region, China: Integrating NDVI and its spatial heterogeneity. Plants. 2024, vol. 13, article 2814. DOI: 10.3390/plants13192814.

20. Vierira F. R., Christofaro C. Contributions of the vegetation index (NDVI) in water quality prediction models in a semi-arid tropical watershed. Journal of Arid Environments. 2024, vol. 220, article 105122. DOI: 10.1016/j.jaridenv.2024.105122.

21. Batina A., Krtalić A. Integrating remote sensing methods for monitoring lake water quality: A comprehensive review. Hydrology. 2024, vol. 11, article 92. DOI: 10.3390/hydrology11070092

22. Powers S. M., Barnard M. A., Macleod M. S., Miller L. A., Wagner N. D. Spatially intensive patterns of water clarity in reservoirs determined rapidly with sensor-equipped boats and satellites. Journal of Geophysical Research: Biogeosciences. 2023, vol. 128, article e2023JG007650. DOI: 10.1029/2023JG007650.

23. Li C., Rousta I., Olafsson H., Zhang H. Lake water quality and dynamics assessment during 1990—2020 (A case study: Chao Lake, China). Atmosphere. 2023, vol. 14, article 382. DOI: 10.3390/ atmos14020382.

24. Huang S., Xia J., Wang G., Lei J. The impact of flood regime on river floodplain vegetation coverage: Insights from a 30-year Landsat record. Journal of Hydrology. 2023, vol. 626, article 130355. DOI: 10.1016/j.jhydrol.2023.130355.

25. Venitsianov E. V., Miroshnichenko S. A., Lepikhin A. P., Gubernatorova T. N. Development and sub stantiation of regional indicators of water quality in terms of the content of heavy metals for water bodies of the Upper Kama basin. Water Sector of Russia: Problems, Technologies, Management. 2015, no. 3, pp. 50—64. [In Russ].