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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, 2025, V. 22, No. 4, pp. 302-314

Remote microwave solonchak water content indicator

A.N. Romanov 1 
1 Institute for Water and Environmental Problems SB RAS, Barnaul, Russia
Accepted: 04.07.2025
DOI: 10.21046/2070-7401-2025-22-4-302-314
Hydrological changes associated with global warming and occurring in different regions of the globe with varying intensity lead to disruption of established ecosystems and significantly complicate socio-economic problems of the population. In arid and semi-arid zones of Northern Eurasia, negative consequences of these changes include climate aridization, reduced water availability in the territories, intensification of soil and hydrological droughts, partial or complete drying up of salt lakes and formation of salt marshes in their place. The paper describes the results of in situ and laboratory measurements of dielectric characteristics of soil taken from the surface of a soda gleyic solonchak formed on the drained part of a hypersaline soda lake. To be able to model the dielectric properties of a natural salt marsh, dielectric parameters of a chemically pure sample of mineral salt Na2CO3 and its aqueous solution were measured. The ability of a solonchak whose surface is salt crust when dry to change emissivity and brightness temperature is shown. A difference in brightness temperatures, reaching 100 K during one day, can be detected by remote microwave probing of the underlying surface. An algorithm for remote microwave monitoring of solonchaks by their radio-emitting parameters is proposed. A remote microwave indicator of solonchak water content is developed that can be used to detect solonchaks by remote microwave monitoring from unmanned aerial vehicles, small aircraft, and satellites.
Keywords: drying hypersaline lakes, salt marshes, radio-emitting characteristics, microwave range
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References:

  1. Bazilevich N. I., Geokhimiya pochv sodovogo zasoleniya (Geochemistry of soda brining soils), Moscow: Nauka, 1965, 349 p. (in Russian).
  2. Glushkova N. V., Chupina D. A., Pchel’nikov D. V., Boldyrev I. I., Selyatitskaya N. A., Mapping and monitoring of aridization processes in the south of the West Siberian Plain, Geografiya i prirodnye resursy, 2016, No. 1, pp. 133–140.
  3. Kovda V. A., Solonchaki i solontsy (Solonchaks and solonetz), Leningrad: Izd. AN SSSR, 1937, 246 p. (in Russian)
  4. Kovda V. A., Proiskhozhdenie i rezhim zasolennykh pochv (Origin and regime of saline soils), Iss. 1, Moscow; Leningrad: Izd. AN SSSR, 1946, 574 p. (in Russian).
  5. Kovda V. A., Problemy bor’by s opustynivaniem i zasoleniem oroshaemykh pochv (Problems of combating desertification and salinization of irrigated soils), Moscow: Kolos, 1984, 304 p. (in Russian).
  6. Komarov S. A., Mironov V. L., Romanov A. N., Aerokosmicheskoe zondirovanie gidrologicheskogo sostoyaniya pochv radiofizicheskimi metodami (Aerospace sounding of the hydrological state of soils by radiophysical methods), Barnaul: Izd. Altaiskogo gosudarstvennogo universiteta, 1997, 104 p. (in Russian).
  7. Lebedeva (Verba) M. P., Lopukhina O. V., Kalinina N. V., Features of the chemical and mineralogical composition of salts in sor solonchaks and lakes of the Kulunda steppe, Pochvovedenie, 2008, No. 4, pp. 467–480 (in Russian).
  8. Lyamina V. A., Glushkova N. V., Smolentseva E. N., Zol’nikov I. D., Use of GIS and remote sensing methods for monitoring the area of lakes and solonchaks in the south of Western Siberia, Interehkspo GEO-Sibir’, 2010, V. 4, No. 2, pp. 3–7 (in Russian).
  9. Pankova E. I., Saline soils of Russia: Solved and unsolved problems, Pochvovedenie, 2015, No. 2, pp. 131–144 (in Russian).
  10. Pankova E. I., Gorokhova I. N., Analysis of data on the area of saline soils in Russia at the end of the 20th and beginning of the 21st centuries, Byulleten’ Pochvennogo instituta im. V. V. Dokuchaeva, 2020, No. 103, pp. 5–33 (in Russian).
  11. Rabinovich V. A., Khavin Z. Ya., Kratkii khimicheskii spravochnik (Brief Chemical Handbook), 3rd ed., Leningrad: Khimiya, 1978, 392 p. (in Russian).
  12. Romanov A. N., Dielectric and radio-emitting properties of saline soils, Barnaul, Izd. Altaiskogo gosudarstvennogo universiteta, 2002, 118 p. (in Russian).
  13. Romanov A. N., The influence of mass concentration of mineral salts on the dielectric characteristics of their aqueous solutions in the microwave range, Radiotekhnika i ehlektronika, 2004, V. 49, No. 9, pp. 1157–1163 (in Russian).
  14. Trofimov I. A., Trofimova L. S., Yakovleva E. P., Remote indicators of land desertification, Aridnye ehkosistemy, 2015, V. 21, No. 1 (62), pp. 36–40 (in Russian).
  15. Sharkov E. A., Radioteplovoe distantsionnoe zondirovanie Zemli: fizicheskie osnovy. V 2 t., V. 1 (Radiothermal remote sensing of the Earth: Physical foundations, in 2 v., V. 1), Moscow: IKI RAN, 2014, 548 p. (in Russian).
  16. Shutko A. M., SVCh-radiometriya vodnoi poverkhnosti i pochvogruntov (Microwave radiometry of water surface and soil), Moscow: Nauka, 1986, 190 p. (in Russian).
  17. Aihaiti A., Nurmemet I., Yu X. et al., An enhanced soil salinity estimation method for arid regions using multisource remote sensing data and advanced feature selection, Catena, 2025, V. 256, Article 109116, https://doi.org/10.1016/j.catena.2025.109116.
  18. Alizade Govarchin Ghale Y., Baykara M., Unal A., Investigating the interaction between agricultural lands and Urmia Lake ecosystem using remote sensing techniques and hydro-climatic data analysis, Agricultural Water Management, 2019, V. 221, pp. 566–579, https://doi.org/10.1016/j.agwat.2019.05.028.
  19. Alizade Govarchin Ghale Y., Tayanc M., Unal A., Dried bottom of Urmia Lake as a new source of dust in the northwestern Iran: Understanding the impacts on local and regional air quality, Atmospheric Environment, 2021, V. 262, Article 118635, https://doi.org/10.1016/j.atmosenv.2021.118635.
  20. Bouaziz M., Matschullat J., Gloaguen R., Improved remote sensing detection of soil salinity from a semi-arid climate in Northeast Brazil, Comptes Rendus Géoscience, 2011, V. 343, No. 11–12, pp. 795–803, https://doi.org/10.1016/j.crte.2011.09.003.
  21. Gao Z., Li X., Zuo L. et al., Unveiling soil salinity patterns in soda saline-alkali regions using Sentinel-2 and SDGSAT-1 thermal infrared data, Remote Sensing of Environment, 2025, V. 322, Article 114708, https://doi.org/10.1016/j.rse.2025.114708.
  22. Ghasempour R., Aalami M. T., Saghebian S. M., Ozgur Kirca V. S., Analysis of spatiotemporal variations of drought and soil salinity via integrated multiscale and remote sensing-based techniques (Case study: Urmia Lake basin), Ecological Informatics, 2024, V. 81, Article 102560, https://doi.org/10.1016/j.ecoinf.2024.102560.
  23. Gopi N. M., Annadurai R., A statistical approach to map saline and fluoride (F) affected areas using optical and microwave remote sensing data simulations: A case study in Palacode Taluk, Tamil Nadu, India, Remote Sensing Applications: Society and Environment, 2024, V. 35, Article 101207, https://doi.org/10.1016/j.rsase.2024.101207.
  24. Guo Y., Shi Z., Zhou L.-Q. et al., Integrating remote sensing and proximal sensors for the detection of soil moisture and salinity variability in coastal areas, J. Integrative Agriculture, 2013, V. 12, No. 4, pp. 723–731, https://doi.org/10.1016/S2095-3119(13)60290-7.
  25. Hall D. K., O’Leary D. S., DiGirolamo N. E. et al., The role of declining snow cover in the desiccation of the Great Salt Lake, Utah, using MODIS data, Remote Sensing of Environment, 2021, V. 252, Article 112106, https://doi.org/10.1016/j.rse.2020.112106.
  26. IUSS Working Group WRB, World reference base for soil resources 2006. A framework for international classification, correlation and communication, 2nd ed., World Soil Resources Reports No. 103, Food and Agriculture Organization of the United Nations (FAO), Rome, Italy, 2006, 145 p.
  27. IUSS Working Group WRB, World Reference Base for Soil Resources. International soil classification system for naming soils and creating legends for soil maps, 4th ed., International Union of Soil Sciences (IUSS), Vienna, Austria, 2022, 236 p.
  28. Kazemi M., Asadi A., Feiznia S. et al., Transformations in a hypersaline lake: Examining the linkages between water level changes and Aeolian dust generation, Environmental Research, 2025, V. 271, Article 121090, https://doi.org/10.1016/j.envres.2025.121090.
  29. Lopes C. L., Mendes R., Caçador I., Dias J. M., Assessing salt marsh extent and condition changes with 35 years of Landsat imagery: Tagus Estuary case study, Remote Sensing of Environment, 2020, V. 247, Article 111939, https://doi.org/10.1016/j.rse.2020.111939.
  30. Mohamed S. A., Metwaly M. M., Metwalli M. R. et al., Integrating active and passive remote sensing data for mapping soil salinity using machine learning and feature selection approaches in arid regions, Remote Sensing, 2023, V. 15, Article 1751, https://doi.org/10.3390/rs15071751.
  31. Mulder V. L., de Bruin S., Schaepman M. E., Mayr T. R., The use of remote sensing in soil and terrain mapping — A review, Geoderma, 2011, V. 162, No. 1–2, pp. 1–19, https://doi.org/10.1016/j.geoderma.2010.12.018.
  32. Pouladi P., Nazemi A. R., Pouladi M. et al., Desiccation of a saline lake as a lock-in phenomenon: A socio-hydrological perspective, Science of the Total Environment, 2022, V. 811, Article 152347, https://doi.org/10.1016/j.scitotenv.2021.152347.
  33. Romanov A. N. (2019a), Dielectric behavior of sodic solonchak at 1.41 GHz in the south of Western Siberia, IEEE Trans. Geoscience and Remote Sensing, 2019, V. 57, No. 12, pp. 9517–9523, https://doi.org/10.1109/TGRS.2019.2927243.
  34. Romanov A. N. (2019b), Influence of water content and temperature on the dielectric and radio-emitting properties of the salt crust of puffy solonchak, Eurasian Soil Science, 2019, V. 52, No. 2, pp. 171–179, https://doi.org/10.1134/S1064229319020121.
  35. Romanov A. N., Khvostov I. V., Emissivity peculiarities of the inland salt marshes in the south of Western Siberia, Intern. J. Remote Sensing, 2018, V. 39, No. 2, pp. 418–431, http://dx.doi.org/10.1080/01431161.2017.1385105.
  36. Romanov A. N., Bordonskiy G. S., Gurulev A. A. et al., On some features of diurnal dynamics of solonchak emissivity in summer, Intern. J. Remote Sensing, 2025, V. 46, No. 3, pp. 1248–1256, https://doi.org/10.1080/01431161.2024.2429780.
  37. Shinkarenko S. S., Bartalev S. A., Mapping of sor depressions and solonchaks in the northern Caspian region based on long-term Landsat data, Cosmic Research, 2024, V. 62, Suppl. 1, pp. S115–S123, https://doi.org/10.1134/S0010952524601300.
  38. Stückemann K.-J., Waske B., Mapping Lower Saxony’s salt marshes using temporal metrics of multi-sensor satellite data, Intern. J. Applied Earth Observation and Geoinformation, 2022, V. 115, Article 103123, https://doi.org/10.1016/j.jag.2022.103123.
  39. Sun C., Liu Y., Zhao S. et al., Classification mapping and species identification of salt marshes based on a short-time interval NDVI time-series from HJ-1 optical imagery, Intern. J. Applied Earth Observation and Geoinformation, 2016, V. 45, Pt. A, pp. 27–41, https://doi.org/10.1016/j.jag.2015.10.008.
  40. Tebbs E. J., Remedios J. J., Avery S. T. et al., Regional assessment of lake ecological states using Landsat: A classification scheme for alkaline–saline, flamingo lakes in the East African Rift Valley, Intern. J. Applied Earth Observation and Geoinformation, 2015, V. 40, pp. 100–108, https://doi.org/10.1016/j.jag.2015.03.010.
  41. Wang Z., Zhang F., Zhang X. et al., Regional suitability prediction of soil salinization based on remote-sensing derivatives and optimal spectral index, Science of the Total Environment, 2021, V. 775, Article 145807, https://doi.org/10.1016/j.scitotenv.2021.145807.
  42. Wang N., Peng J., Chen S. et al., Improving remote sensing of salinity on topsoil with crop residues using novel indices of optical and microwave bands, Geoderma, 2022, V. 422, Article 115935, https://doi.org/10.1016/j.geoderma.2022.115935.
  43. Wang J., Yang T., Zhu K. et al., A novel retrieval model for soil salinity from CYGNSS: Algorithm and test in the Yellow River Delta, Geoderma, 2023, V. 432, Article 116417, https://doi.org/10.1016/j.geoderma.2023.116417.
  44. Xiao Y., Hu W., Zhang Y. et al., Spatiotemporal variation and driving forces of soil salinization in the lower reach of arid endorheic basins: Critical role of lake system and groundwater overflow, Agricultural Water Management, 2025, V. 315, Article 109568, https://doi.org/10.1016/j.agwat.2025.109568.
  45. Zhang C., Gong Z., Qiu H. et al., Mapping typical salt-marsh species in the Yellow River Delta wetland supported by temporal-spatial-spectral multidimensional features, Science of the Total Environment, 2021, V. 783, Article 147061, https://doi.org/10.1016/j.scitotenv.2021.147061.