The Danube River Water Discharge According to Satellite Optical Data of the Landsat Series

V. V. Suslin, S. A. Sholar, Е. A. Podgibailov*, O. V. Martynov

Marine Hydrophysical Institute of RAS, Sevastopol, Russia

* e-mail: e.podgibailov@yandex.ru

Abstract

The paper aims to find the correlation relationship between the land–water area ratio for a fixed area of the Danube Delta and the total river discharge using Landsat series satellite products and SMHI Hypeweb hydrological model. The study period covered 1984–2010. We used a total of 132 satellite images in one band in the near-infrared spectral range with a spatial resolution of 30 m. Two study areas were selected: the delta area with channel and land (44.9–45.4°N, 29.55–29.60°E) and the control area of the mouth seashore (44.9–45.4°N and 29.80–29.85°E). For each of them a histogram was plotted which characterised the reflected light in relative units and their corresponding numbers of pixels. The signal from the first area was found to be in the range of 7000–26,000 r. u., whereas from the second one it was 7000–8000 r. u. This distinction allowed us to separate the delta areas occupied by river water from those of land. For this purpose, we calculated the ratio between the number of pixels corresponding to a value of 7000–8000 r. u. to all pixels in the area. Then we found the correlation between the river discharge from the SMHI Hypeweb hydrological model and the proportion of pixels corresponding to areas occupied by water. The regression y = 7.78∙10–4∙x 0.09 – 5.98∙10–4 was obtained. The analysis of seasonal variability showed that in the studied delta area, the share of pixels related to water-occupied areas > 0.5 corresponds to the months from March to May, and the minimum values < 0.3 correspond to July–September. All this is consistent with the period of intensity of precipitation and snowmelt in the Danube River basin area. The data from this work may be useful to researchers assessing the impact of this river discharge on the hydrological regime and condition of the Black Sea.

Keywords

remote sensing, Danube River, river discharge, Landsat TM, SMHI Hypeweb, hydrological model, Black Sea

Acknowledgments

The work was carried out under state assignment of MHI RAS FNNN-2024-0012 “Analysis, diagnosis and operational forecast of the state of hydrophysical and hydrochemical fields of marine areas based on mathematical modeling using data from remote and contact measurement methods”.

For citation

Suslin, V.V., Sholar, S.A., Podgibailov, Е.A. and Martynov, O.V., 2025. The Danube River Water Discharge According to Satellite Optical Data of the Landsat Series. Ecological Safety of Coastal and Shelf Zones of Sea, (1), pp. 42–50.

References

  1. Tsyganova, M.V., Lemeshko, E.M. and Ryabtsev, Yu.N., 2023. Influence of Upwelling on River Plume Development in the Coastal Zone of the North-Western Black Sea Shelf Based on Numerical Modelling. Ecological Safety of Coastal and Shelf Zones of Sea, (1), pp. 20–30.
  2. Kondratev, S.I., 2019. Three Typical Hydrological-Hydrochemical Situations near the Danube River Mouth Based on the Marine Hydrophysical Institute Research Expeditions in 1997–2013. Physical Oceanography, 26(4), pp. 326–340. https://doi.org/10.22449/1573-160X-2019-4-326-340
  3. Goryachkin, Yu.N. and Ivanov, V.A., 2006. [Black Sea Level: Past, Present and Future]. Sevastopol: MHI NAS of Ukraine, 210 p. (in Russian).
  4. Terekhov, A.G., Dolgikh, S.A., Pak, I.T. and Makarenko, N.G., 2015. [Satellite-Based Diagnostics of Water Discharge in Snow-Ice Fed Rivers Using the Kash River as an Example (PRC)]. In: IKI, 2015. [Proceedings of the 13th All-Russian Open Conference “Current Problems of Remote Sensing of Earth from Space”]. Moscow: IKI RAS, p. 140 (in Russian).
  5. Mukhamedjanov, I.D., Konstantinova, A.M., Loupian, E.A. and Umirzakov, G.U., 2022. Evaluation of Satellite Monitoring Capabilities of Stream Runoff Based on the Amu Darya River State Analysis. Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa, 19(1), pp. 87–103. https://doi.org/10.21046/2070-7401-2022-19-1-87-103 (in Russian).
  6. Gleason, C.J. and Durand, M.T., 2020. Remote Sensing of River Discharge: A Review and a Framing for the Discipline. Remote Sensing, 12(7), 1107. https://doi.org/10.3390/rs12071107
  7. Bjerklie, D.M., Birkett, C.M., Jones, J.W., Carabajal, C., Rover, J.A., Fulton, J.W. and Garambois, P.-A., 2018. Satellite Remote Sensing Estimation of River Discharge: Application to the Yukon River Alaska. Journal of Hydrology, 561, pp. 1000–1018. https://doi.org/10.1016/j.jhydrol.2018.04.005
  8. Bjerklie, D.M., Dingman, S.L., Vorosmarty, C.J., Bolster, C.H. and Congalton, R.G., 2003. Evaluating the Potential for Measuring River Discharge from Space. Journal of Hydrology, 278(1–4), pp. 17–38. https://doi.org/10.1016/S0022-1694(03)00129-X
  9. Sichangi, A.W., Wang, L., Yang, K., Chen, D., Wang, Z., Li, X., Zhou, J., Liu, W. and Kuria, D., 2016. Estimating Continental River Basin Discharges Using Multiple Remote Sensing Datasets. Remote Sensing of Environment, 179, pp. 36–53. https://doi.org/10.1016/j.rse.2016.03.019
  10. Filippucci, P., Brocca, L., Bonafoni, S., Saltalippi, C., Wagner, W. and Tarpanelli, A., 2022. Sentinel-2 High-Resolution Data for River Discharge Monitoring. Remote Sensing of Environment, 281, 113255. https://doi.org/10.1016/j.rse.2022.113255
  11. Mukhamediev, R.I., Terekhov, A., Sagatdinova, G., Amirgaliyev, Y., Gopejenko, V., Abayev, N., Kuchin, Y., Popova, Y. and Symagulov, A., 2023. Estimation of the Water Level in the Ili River from Sentinel-2 Optical Data Using Ensemble Machine Learning. Remote Sensing, 15(23), 5544. https://doi.org/10.3390/rs15235544
  12. Mukhamedjanov, I.D., Konstantinova, A.M. and Loupian, E.A., 2020. The Use of Satellite Data for Monitoring Rivers in the Amu Darya Basin. Regional Problems of Earth Remote Sensing, 223, 03008. https://doi.org/10.1051/e3sconf/202022303008
  13. Terekhov, A.G., Abayev, N.N., Sagatdinova, G.N., Mukhamediev, R.I. and Amirgaliyev, E.N., 2023. Satellite Estimation of River Water Level from Shoal Monitoring Data: The Case of the Transboundary Ili River (Central Asia). Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa, 20(4), pp. 227–238. https://doi.org/10.21046/2070-7401-2023-20-4-227-238 (in Russian).
  14. Suslin, V.V., Podgibailov, E.A., Martynov, O.V. and Sholar, S.A., 2023. Water Discharge of the Danube River According to Medium-Resolution Optical Satellite Data. In: IO RAS, 2023. Proceedings of the XII All-Russian Conference with International Participation “Current Problems in Optics of Natural Waters”. 25–27 October 2023, Saint Petersburg. Vol. 13. Moscow: Shirshov Institute Publishing House, pp. 240–245 (in Russian).

Full text

English version (PDF)

Russian version (PDF)

We use Yandex Metrics. Read more.

Мы используем Яндекс Метрику. Подробнее.