Earth Sciences

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Monthly Variations of Rainfall Erosivity (R factor) in Shida Kartli, Georgia

Received: 28 June 2017    Accepted: 29 June 2017    Published: 21 August 2017
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Abstract

Soil erosion is a global problem that tends to become more extreme on the background of climate change. Rainfall is one the main drivers of soil erosion. One of the best indicators of the potential erosion risks is the rainfall-runoff erosivity factor (R) of the revised universal soil loss equation (RUSLE). Shida Kartli is one of the main agrarian regions in the country and research on soil erosion has the great importance. The purpose of this study is to assess monthly variations of rainfall erosivity in Shida Kartli region from the RUSLE R-factor, based on the best available datasets. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 min intensity of individual events. However, these data are unavailable in study region since 1990. Alternative approaches are used for the calculation of EI30 in this paper. Soil erosion rate is sufficiently high in eastern Georgia. According to the results of previous studies, two maximums of R-factor are calibrated in May and July in Shida Kartli. A set of equations is presented for calculating monthly and annual R factor values based on daily precipitation data for Shida Kartli in the current study. Data have been collected from 2 meteorological stations for the period from January 1990 through December 2016. Precipitation time series for both stations included 27 years. Rainfall-runoff factor (R) for each month (Rmonth) of study period has been determined and seasons with high rainfall erosivity were established for both stations.

DOI 10.11648/j.earth.s.2017060501.23
Published in Earth Sciences (Volume 6, Issue 5-1, October 2017)

This article belongs to the Special Issue New Challenge for Geography: Landscape Dimensions of Sustainable Development

Page(s) 87-92
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Soil Erosion, Precipitation, Rainfall, Erosivity, Monthly Time Step

References
[1] Sholagberu, A. T., Mustafa, M. R., Yusof, K. W., & Ahmad, M. H. (2016). Evaluation oF Rainfall-Runoff Erosivity Factor. Journal of Ecological Engineering, Volume 17, Issue 3, 1-8.
[2] Norton, D. L., Chaudhari, K., & Flanagan, D. (2002). Erosion Control Using Soil Amendments and Other Low Cost Methods Prior to Establishment of Vegetation. 12th ISCO Conference, (P. 133-137). Beijing.
[3] Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva, S., Hrabalíková, M. (2015). Rainfall erosivity in Europe. Science of the Total Environment 511, 801-814.
[4] Lopes-Vicente, M., Navas, A., & Machin, J. (2008). Identifying Erosive Periods by Using RUSLE Factors in Mountain fields of the Central Spanish Pyrenees. Hydrology and Earth System Sciences, 523-535.
[5] Ghorjomeladze, O., Turmanidze, N., & Gogichaishvili, G. (2012). Norms of Soil Erosion. Annals of Georgian Academy of Agrarian Science, 30, 200-207.
[6] Oliveira, P. T., Wendland, E., & Nearing, M. A. (2012). Rainfall erosivity in Brazil: A review. Catena 100, 139-147.
[7] Diodato, N. (2005). Predicting RUSLE (Revised Universal Soil Loss Equation) Monthly Erosivity Index from Readily Available Rainfall Data in Mediterranean Area. The Environmentalist, 25, 63-70.
[8] Nearing, M. A., Pruski, F. F., & O'Neal, M. R. (2004). Expected climate change impacts on soil erosion rates: A review. Journal of Soil and Water Conservation, 59 (1), 43-50.
[9] Diodato, N., Borrelli, P., Fiener, P., Bellocchi, G., & Romano, N. (2017). Discovering historical rainfall erosivity with a parsimonious approach: A. Journal of Hydrology 544, 1-9.
[10] Angulo-Martinez, M., & Begueria, S. (2009). Estimating rainfall erosivity from daily precipitation records: A comparison among methods using data from the Ebro Basin (NE Spain). Journal of Hydrology, Vol. 379, Issues 1-2, 111-121.
[11] Wishmeier, W. H., & Smith, D. D. (1978). Predicting Rainfall Erosion Losses-a guide to conservation planning. U. S Department of Agriculture, Agriculture Handbook. No. 537.
[12] Renard, K. G., Foster, G. R., & Weesies, G. A. (1997). Predicting Soil Erosion by Water; a Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). Agriculture Handbook No. 703, USDA-ARS, 404.
[13] Foster, G. R. (2004). User’s Reference Guide: Revised Universal Soil Loss Equation (RUSLE 2). Washington, D. C.: US Department of Agriculture, Agricultural Research Service.
[14] Liu, B. Y., Guo, S. Y., Li, Z. G., Xie, Y., Zhang, K. L., & Liu, X. C. (2013). Water erosion sample survey 30 in China. Soil and Water Conservation, 10, 26-34.
[15] Yin, S., Xie, Y., Liu, B., & Nearing, M. A. (2015). Rainfall Erosivity Estimation Based on Rainfall Data Collected over a Range of Temporal Resolutions. Hydrology and Earth System Science, 19, 4113-4126.
[16] de Santos Loureiro, N., & de Azavedo Coutinho, M. (2001). A New Procedure to Estimate the RUSLE EI30 Index Based on Monthly Rainfall Data and Applied to the Algarve Region, Portugal. Journal of Hydrology, 250, 12-18.
[17] Renard, K. G., Foster, G. R., Weesies, G. A., & Porter, J. P. (1991). RUSLE-revised universal soil loss equation. Journal of Soil and Water Conservation 46 (1), 30-33.
[18] Diodato, N., & Bellocchi, G. (2007). Estimating monthly (R)USLE climate input in a Mediterranean region using limited data. Journal of Hydrology, 345 (3-4), 224-236.
[19] (2013). Shida Kartli Regional Development Strategy 2014-2021. Tbilisi.
[20] Kordzakhia, M., & Kavakhishvili, S. (1971). Climate of Georgia. Tbilisi: Ganatleba. (in Georgian).
[21] Gogichaishvili, G. (2002). Assessement and Prediction of the Rainfall Erosivity Riks on the Soils of Georgia. Tbilisi. (in Georgian).
[22] Bregvazde, M. (1952). Soil Erosin In Zestaphoni Municipality. Tbilisi: Science Academi of Soviet Georgia. (in Georgian).
Author Information
  • Department of Geomorphology and Geoecology, Vakhushti Bagrationi Institute of Geography, Ivane Javakhishvili Tbilisi State University, Tbilisi, Georgia

  • Faculty of Exact and Natural Sciences, Ivane Javakhishvili Tbilisi State University, Tbilisi, Georgia

  • Department of Geomorphology and Geoecology, Vakhushti Bagrationi Institute of Geography, Ivane Javakhishvili Tbilisi State University, Tbilisi, Georgia

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  • APA Style

    Mariam Tsitsagi, Ana Berdzenishvili, Ketevan Gogidze. (2017). Monthly Variations of Rainfall Erosivity (R factor) in Shida Kartli, Georgia. Earth Sciences, 6(5-1), 87-92. https://doi.org/10.11648/j.earth.s.2017060501.23

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    ACS Style

    Mariam Tsitsagi; Ana Berdzenishvili; Ketevan Gogidze. Monthly Variations of Rainfall Erosivity (R factor) in Shida Kartli, Georgia. Earth Sci. 2017, 6(5-1), 87-92. doi: 10.11648/j.earth.s.2017060501.23

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    AMA Style

    Mariam Tsitsagi, Ana Berdzenishvili, Ketevan Gogidze. Monthly Variations of Rainfall Erosivity (R factor) in Shida Kartli, Georgia. Earth Sci. 2017;6(5-1):87-92. doi: 10.11648/j.earth.s.2017060501.23

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  • @article{10.11648/j.earth.s.2017060501.23,
      author = {Mariam Tsitsagi and Ana Berdzenishvili and Ketevan Gogidze},
      title = {Monthly Variations of Rainfall Erosivity (R factor) in Shida Kartli, Georgia},
      journal = {Earth Sciences},
      volume = {6},
      number = {5-1},
      pages = {87-92},
      doi = {10.11648/j.earth.s.2017060501.23},
      url = {https://doi.org/10.11648/j.earth.s.2017060501.23},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.earth.s.2017060501.23},
      abstract = {Soil erosion is a global problem that tends to become more extreme on the background of climate change. Rainfall is one the main drivers of soil erosion. One of the best indicators of the potential erosion risks is the rainfall-runoff erosivity factor (R) of the revised universal soil loss equation (RUSLE). Shida Kartli is one of the main agrarian regions in the country and research on soil erosion has the great importance. The purpose of this study is to assess monthly variations of rainfall erosivity in Shida Kartli region from the RUSLE R-factor, based on the best available datasets. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 min intensity of individual events. However, these data are unavailable in study region since 1990. Alternative approaches are used for the calculation of EI30 in this paper. Soil erosion rate is sufficiently high in eastern Georgia. According to the results of previous studies, two maximums of R-factor are calibrated in May and July in Shida Kartli. A set of equations is presented for calculating monthly and annual R factor values based on daily precipitation data for Shida Kartli in the current study. Data have been collected from 2 meteorological stations for the period from January 1990 through December 2016. Precipitation time series for both stations included 27 years. Rainfall-runoff factor (R) for each month (Rmonth) of study period has been determined and seasons with high rainfall erosivity were established for both stations.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Monthly Variations of Rainfall Erosivity (R factor) in Shida Kartli, Georgia
    AU  - Mariam Tsitsagi
    AU  - Ana Berdzenishvili
    AU  - Ketevan Gogidze
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    JO  - Earth Sciences
    SP  - 87
    EP  - 92
    PB  - Science Publishing Group
    SN  - 2328-5982
    UR  - https://doi.org/10.11648/j.earth.s.2017060501.23
    AB  - Soil erosion is a global problem that tends to become more extreme on the background of climate change. Rainfall is one the main drivers of soil erosion. One of the best indicators of the potential erosion risks is the rainfall-runoff erosivity factor (R) of the revised universal soil loss equation (RUSLE). Shida Kartli is one of the main agrarian regions in the country and research on soil erosion has the great importance. The purpose of this study is to assess monthly variations of rainfall erosivity in Shida Kartli region from the RUSLE R-factor, based on the best available datasets. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 min intensity of individual events. However, these data are unavailable in study region since 1990. Alternative approaches are used for the calculation of EI30 in this paper. Soil erosion rate is sufficiently high in eastern Georgia. According to the results of previous studies, two maximums of R-factor are calibrated in May and July in Shida Kartli. A set of equations is presented for calculating monthly and annual R factor values based on daily precipitation data for Shida Kartli in the current study. Data have been collected from 2 meteorological stations for the period from January 1990 through December 2016. Precipitation time series for both stations included 27 years. Rainfall-runoff factor (R) for each month (Rmonth) of study period has been determined and seasons with high rainfall erosivity were established for both stations.
    VL  - 6
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