Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2025, V. 22, No. 5, pp. 346-356
Remote sensing and analytical modeling of temperature regime of the Yenisei River in the lower pool of Krasnoyarsk HPP
A.K. Matuzko
1 , N.Ya. Shaparev
1 , O.E. Yakubailik
2 1 Institute of Computational Modelling SB RAS, Krasnoyarsk, Russia
2 Krasnoyarsk Science Center SB RAS, Krasnoyarsk, Russia
Accepted: 03.09.2025
DOI: 10.21046/2070-7401-2025-22-5-346-356
Regulation of the Yenisei River flow by the Krasnoyarsk Hydroelectric Power Plant has led to significant changes in the hydrothermal regime in the lower pool. The existing water temperature monitoring system based on discrete measurements at gauging stations does not provide sufficient spatiotemporal detailing to address current tasks of socio-economic development of the Yenisei basin and the Arctic territories of the Krasnoyarsk Krai. The paper proposes an integrated approach combining remote sensing and analytical modeling methods to assess the river temperature regime. The remote sensing data were obtained from thermal infrared surveys of Landsat-8/-9 (Collection 2 Level 2 Science Product) that provide high accuracy data due to the inclusion of atmospheric parameters. The analytical modeling of the hydrothermal regime was performed based on solution of the heat conduction equation, taking into account solar and thermal infrared radiation, convection and evaporation. Morphometric characteristics of the riverbed were obtained from high-resolution QuickBird satellite images. The results showed a high degree of consistency between the calculated temperatures and the data from the hydrographic posts, as well as the results of water temperature calculations based on Landsat satellite data. The proposed approach allows for a significant improvement in the spatial and temporal resolution of river temperature monitoring. However, a number of limitations related to the frequency of satellite imaging, cloudiness, and spatial resolution of Landsat thermal channels were identified.
Keywords: water temperature, Yenisei, Landsat-8/-9, remote sensing, hydroposts, analytical modeling
Full textReferences:
- Belolipetsky V. M., Genova S. N., Tugovikov V. B., Shokin Yu. I., Chislennoe modelirovanie zadach gidroledotermiki vodotokov (Numerical modeling of problems of hydro-ice thermals of watercourses), Novosibirsk: Izd. SO RAN, 1993, 138 p. (in Russian).
- Kosmakov I. V., Termicheskii i ledovyi rezhim v verkhnikh i nizhnikh b’efakh vysokonapornykh gidroehlektrostantsii na Enisee (Thermal and ice regime in the upper and lower pools of high-pressure hydroelectric power stations on the Yenisei), Krasnoyarsk: Claretianum, 2001, 143 p. (in Russian).
- Lozhkin D. M., Shevchenko G. V., Comparative analysis of Okhotsk Sea surface temperature from satellite observations and ERA5 reanalysis, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, V. 19, No. 2, pp. 183–192 (in Russian), DOI: 10.21046/2070-7401-2022-19-2-183-192.
- Parmuzin E. I., Lezina N. R., Agoshkov V. I., Investigation of the effect of assimilation of instantaneous satellite data on the reproduction of sea surface temperature in the Black and Azov Seas dynamics model, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 2, pp. 61–69 (in Russian), DOI: 10.21046/2070-7401-2024-21-2-61-69.
- Rice W. G., Osnovy distantsionnogo zondirovaniya (Fundamentals of Remote Sensing), Moscow: Tekhnosfera, 2006, 338 p. (in Russian).
- Stepanenko V. M., Repina I. A., Medvedev A. I., Romanenko V. A., Reproduction of the largest Earth lakes surface temperature by the LAKE model: Automatic calibration system based on MODIS data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 6, pp. 267–283 (in Russian), DOI: 10.21046/2070-7401-2024-21-6-267-283.
- Shaparev N. Ya., Andrianova A. V., Indicators of sustainable water use of the Yenisei River, Geography and natural resources, 2018, No. 4, pp. 47–56 (in Russian), DOI: 10.21782/GIPR0206-1619-2018-4(47-56).
- Shaparev N. Ya., Shokin Yu. I., Modeling of summertime hydrothermal regime in the downstream pool of Krasnoyarsk hydroelectric power station, Computational technologies, 2018, V. 23, No. 6, pp. 107–114 (in Russian), DOI: 10.25743/ICT.2018.23.6.0010.
- Caissie D., The thermal regime of rivers: A review, Freshwater Biology, 2006, V. 51, pp. 1389–1406, DOI: 10.1111/j.1365-2427.2006.01615.x.
- Dingman S. L., Physical Hydrology, 3rd ed., Long Grove: Waveland Press, 2015, 670 p.
- Handcock R. N., Gillespie A. R., Cherkauer K. A. et al., Accuracy and uncertainty of thermal-infrared remote sensing of stream temperatures at multiple spatial scales, Remote Sensing of Environment, 2006, V. 100, pp. 427–440, DOI: 10.1016/j.rse.2006.01.007.
- Jimenez-Munoz J. C., Cristobal J., Sobrino J. A. et al., Revision of the single-channel algorithm for land surface temperature retrieval from Landsat thermal-infrared data, IEEE Trans. Geoscience and Remote Sensing, 2009, V. 47, Iss. 1, pp. 339–349, DOI: 10.1109/TGRS.2008.2007125.
- Kirner D., Laska K., Stachon Z., Assessment and validation of Land Surface Temperature retrieval algorithms using Landsat 8 TIRS data in Antarctic ice-free areas, Polar Science, 2024, V. 42, Article 101127, DOI: 10.1016/j.polar.2024.101127.
- Li Z.-L., Tang B.-H., Wu H. et al., Satellite-derived land surface temperature: Current status and perspectives, Remote Sensing of Environment, 2013, V. 131, pp. 14–37, DOI: 10.1016/j.rse.2012.12.008.
- Ling F., Foody G. M., Du H. et al., Monitoring thermal pollution in rivers downstream of dams with Landsat ETM+ thermal infrared images, Remote Sensing, 2017, V. 9, Iss. 11, Article 1175, DOI: 10.3390/rs9111175.
- Lyapustin A., Wang Y., Korkin S., Huang D., MODIS Collection 6 MAIAC algorithm, Atmospheric Measurement Techniques, 2018, V. 11, Iss. 10, pp. 5741–5765, DOI: 10.5194/amt-11-5741-2018.
- Malakar N. K., Hulley G. C., Hook S. J. et al., An operational land surface temperature product for Landsat thermal data: Methodology and validation, IEEE Trans. Geoscience and Remote Sensing, 2018, V. 56, Iss. 10, pp. 5717–5735, DOI: 10.1109/TGRS.2018.2824828.
- Matuzko A. K., Yakubailik O. E., Monitoring of land surface temperature in Krasnoyarsk and its suburban area based on Landsat 8 satellite data, J. Siberian Federal University. Engineering and Technologies, 2018, V. 11, No. 8, pp. 934–945, DOI: 10.17516/1999-494X-0115.
- Montanaro M., Levy R., Markham B., On-orbit radiometric performance of the Landsat 8 Thermal Infrared Sensor, Remote Sensing, 2014, V. 6, Iss. 12, pp. 11753–11769, DOI: 10.3390/rs61211753.
- Parastatidis D., Mitraka Z., Chrysoulakis N., Abrams M., Online global land surface temperature estimation from Landsat, Remote Sensing, 2017, V. 9, Iss. 12, Article 1208, DOI: 10.3390/rs9121208.
- Sekertekin A., Validation of physical radiative transfer equation-based land surface temperature using Landsat 8 satellite imagery and SURFRAD in-situ measurements, J. Atmospheric and Solar-Terrestrial Physics, 2019, V. 196, Article 105161, DOI: 10.1016/j.jastp.2019.105161.
- Shaparev N., Modelling summer water temperature on the Yenisei River, Thermal Science, 2019, V. 23, pp. 607–614.
- Shaparev N., Shokin Y., Yakubailik O., Modelling and remote sensing of water temperature of the Yenisei River, IOP Conf. Series: Earth and Environmental Science, 2018, V. 211, Article 012022.
- Simon R. N., Tormos T., Danis P.-A., Retrieving water surface temperature from archive Landsat thermal infrared data: Application of the mono-channel atmospheric correction algorithm over two freshwater reservoirs, Intern. J. Applied Earth Observation and Geoinformation, 2014, V. 30, pp. 247–250, DOI: 10.1016/j.jag.2014.01.005.
- Sinokrot B. A., Stefan H. G., Stream temperature dynamics: Measurements and modeling, Water Resources Research, 1993, V. 29, Iss. 7, pp. 2299–2312.
- Vanhellemont Q., Automated water surface temperature retrieval from Landsat 8/TIRS, Remote Sensing of Environment, 2020, V. 237, Article 111518, DOI: 10.1016/j.rse.2019.111518.
- Wang F., Qin Z., Song C. et al., An improved mono-window algorithm for land surface temperature retrieval from Landsat 8 Thermal Infrared Sensor data, Remote Sensing, 2015, V. 7, Iss. 4, pp. 4268–4289, DOI: 10.3390/rs70404268.
- Wawrzyniak V., Piégay H., Poirel A., Longitudinal and temporal thermal patterns of the French Rhône River using Landsat ETM+ thermal infrared images, Aquatic Sciences, 2012, V. 74, pp. 405–414.
- Webb B. W., Hannah D. M., Moore R. D., Brown L. E., Nobilis F., Recent advances in stream and river temperature research, Hydrological Processes, 2008, V. 22, Iss. 7, pp. 902–918.
- Yang D., Liu B., Ye B., Stream temperature changes over Lena River basin in Siberia, Geophysical Research Letters, 2005, V. 32, Iss. 5, Article L05401, DOI: 10.1029/2004GL021568.
- Yu X., Guo X., Wu Z., Land surface temperature retrieval from Landsat 8 TIRS — Comparison between radiative transfer equation-based method, split window algorithm and single channel method, Remote Sensing, 2014, V. 6, Iss. 10, pp. 9829–9852, DOI: 10.3390/rs6109829.