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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, 2024, Vol. 21, No. 3, pp. 145-154

Modeling water erosion using the RUSLE equation at the land use scale

A.S. Kuznetsova 1 , K.V. Krasnoshchekov 1 , A.V. Dergunov 1 , M.G. Erunova 1 , D.S. Makarov 1 , D.V. Kharlamov 1 , O.E. Yakubailik 2 
1 Krasnoyarsk Science Center SB RAS, Krasnoyarsk, Russia
2 Institute of Computational Modeling SB RAS, Krasnoyarsk, Russia
Accepted: 15.05.2024
DOI: 10.21046/2070-7401-2024-21-3-145-154
This study models water erosion of soil cover and assesses it at the land use scale. The Mikhailovskoye experimental production farm (EPF) was chosen as the object of study. The RUSLE equation, together with ground and remote sensing data, was used to calculate the average annual soil loss rate and the spatial distribution of water erosion. The input data included the FABDEM digital elevation model, Sentinel-2 satellite data, ground-based weather station data and digital maps which represent the results of ground-based land use surveys. In this study, an algorithm for calculating the factors of the RUSLE equation was developed. For the first time, QGIS and ArcGIS software have created digital maps showing practice of supporting and saving soil cover, soil erodibility, the influence of topography on soil erosion by water and soil loss due to land cover type. As a result of modeling water erosion of the soil cover of the Mikhailovskoye EPF, a digital map of the average annual soil loss rate was obtained. Based on the analysis of the resulting map, it was established that the soils of the study area are generally characterized by an insignificant erosion hazard.
Keywords: soil erosion, agriculture, RUSLE, modeling of water erosion, remote sensing
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References:

  1. Erunova M. G., Simakina A. S., Yakubailik O. E., Database for precision farming at the Kuraginskoye agricultural experimental production facility, Bulletin KrasSAU, 2022, No. 1(178), pp. 13–20 (in Russian), DOI: 10.36718/1819-4036-2022-1-13-20.
  2. Ivanov M. A., Yermolaev O. P., Geomorphometric analysis of river basins of the Volga Federal District using SRTM and Aster GDEM data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2017, Vol. 14, No. 2, pp. 98–109 (in Russian), DOI: 10.21046/2070-7401-2017-14-2-98-109.
  3. Shinkarenko S. S., Bodrova V. N., Sidorova N. V., Influence of the exhibition of the slopes on the seasonal dynamics of the vegetation industry NDVI index of area planted, Izvestiya Nizhnevolzhskogo agrouniversitetskogo kompleksa: nauka i vysshee professional’noe obrazovanie, 2019, No. 1, pp. 96–105 (in Russian), DOI: 10.32786/2071-9485-2019-01-12.
  4. Bircher P., Liniger H. P., Prasuhn V., Comparison of long-term field-measured and RUSLE-based modelled soil loss in Switzerland, Geoderma Regional, 2022, Vol. 31, Article e00595, DOI: 10.1016/j.geodrs.2022.e00595.
  5. Durigon V. L., Carvalho D. F., Antunes M. A. H. et al., NDVI time series for monitoring RUSLE cover management factor in a tropical watershed, Intern. J. Remote Sensing, 2014, Vol. 35, Issue 2, pp. 441–453, DOI: 10.1080/01431161.2013.871081.
  6. Haregeweyn N., Tsunekawa A., Poesen J. et al., Comprehensive assessment of soil erosion risk for better land use planning in river basins: Case study of the Upper Blue Nile River, Science of the Total Environment, 2017, Vol. 574, pp. 95–108, DOI: 10.1016/j.scitotenv.2016.09.019.
  7. Hawker L., Uhe P., Paulo L. et al., A 30 m global map of elevation with forests and buildings removed, Environmental Research Letters, 2022, Vol. 17, No. 2, Article 024016, DOI: 10.1088/1748-9326/ac4d4f.
  8. la Cecilia D., Tom M., Stamm C., Odermatt D., Pixel-based mapping of open field and protected agriculture using constrained Sentinel-2 data, ISPRS Open J. Photogrammetry and Remote Sensing, 2023, Vol. 8, Article 100033, DOI: 10.1016/j.ophoto.2023.100033.
  9. Laflen J. M., Lane L. J., Foster G. R., WEPP: a new generation of erosion prediction technology, J. Soil and Water Conservation January, 1991, Vol. 46, No. 1, pp. 34–38.
  10. Liu J., Yang K., Tariq A. et al., Interaction of climate, topography and soil properties with cropland and cropping pattern using remote sensing data and machine learning methods, The Egyptian J. Remote Sensing and Space Sciences, 2023, Vol. 26, Issue 3, pp. 415–426, DOI: 10.1016/j.ejrs.2023.05.005.
  11. Marino S., Understanding the spatio-temporal behavior of crop yield, yield components and weed pressure using time series Sentinel-2-data in an organic farming system, European J. Agronomy, 2023, Vol. 145, Article 126785, DOI: 10.1016/j.eja.2023.126785.
  12. Moore I. D., Grayson R. B., Ladson A. R., Digital terrain modelling: A review of hydrological, geomorphological, and biological applications, Hydrological Processes, 1991, Vol. 5, Issue 1, pp. 3–30, DOI: 10.1002/HYP.3360050103.
  13. Nguyen Q.-V., Liou Y.-A., Nguyen K.-A., Tran D.-P., Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-making, Ecological Indicators, 2023, Vol. 155, Article 110993, DOI: 10.1016/j.ecolind.2023.110993.
  14. Pandey A., Himanshu S. K., Mishra S. K., Singh V. P., Physically based soil erosion and sediment yield models revisited, CATENA, 2016, Vol. 147, pp. 595–620, DOI: 10.1016/j.catena.2016.08.002.
  15. Petito M., Cantalamessa S., Pagnani G. et al., Impact of Conservation Agriculture on Soil Erosion in the Annual Cropland of the Apulia Region (Southern Italy) Based on the RUSLE-GIS-GEE Framework, Agronomy, 2022, Vol. 12, Issue 2, Article 281, DOI: 10.3390/agronomy12020281.
  16. Räsänen T. A., Tähtikarhu M., Uusi-Kämppä J. et al., Evaluation of RUSLE and spatial assessment of agricultural soil erosion in Finland, Geoderma Regional, 2023, Vol. 32, Article e00610, DOI: 10.1016/j.geodrs.2023.e00610.
  17. Renard K. G., Freimund J. R., Using monthly precipitation data to estimate the R-factor in the revised USLE, J. Hydrology, 1994, Vol. 157, Issues 1–4, pp. 287–306, DOI: 10.1016/0022-1694(94)90110-4.
  18. Renard K. G., Foster G. R., Weesies G. et al., Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE), U. S. Department of Agriculture, 1997, 404 p.
  19. Sharply A. N., Williams J. R., EPIC-Erosion/Productivity Impact Calculator: 1. Model Documentation, U. S. Department of Agriculture Technical Bulletin, 1990, 235 p.
  20. Uuemaa E., Ahi S., Montibeller B. et al., Vertical accuracy of freely available global digital elevation models (ASTER, AW3D30, MERIT, TanDEM-X, SRTM, and NASADEM), Remote Sensing, 2020, Vol. 12, Issue 21, Article 3482, DOI: 10.3390/rs12213482.
  21. Wang L., Zhang F., Fu S. et al., Assessment of soil erosion risk and its response to climate change in the mid-Yarlung Tsangpo River region, Environmental Science and Pollution Research, 2020, Vol. 27, Issue 12, pp. 607–621, DOI: 10.1007/s11356-019-06738-y.
  22. Wischmeier W. H., Smith D. D., Predicting rainfall erosion losses: A Guide to Conservation Planning, U. S. Department of Agriculture, 1978, 67 p.