Skip to main content

Advertisement

Log in

Assessing the potential of soil erosion in Kyrgyzstan based on RUSLE, integrated with remote sensing

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

Soil erosion is a serious ecological and economic issue occurring in all regions across the biosphere. Soil erosion contributes to land degradation, endangering both the pastoral and natural environments in Kyrgyzstan. This study objective is to identify the potential of soil erosion in Kyrgyzstan and estimate the total soil loss rate. The revised universal soil loss equation (RUSLE) model with remote sensing (RS) was used to show the distribution of risk zones of soil erosion and soil loss. Variables were obtained from Kyrgyz Hydro-Meteorological agency, Harmonized World Soil Data (HWSD), Moderate Resolution Imaging Spectroradiometer-Normalized Difference Vegetation Index (MOD13Q1-MODIS/Terra), Shuttle Radar Topography Mission (SRTM), and Global Land Cover Map (GlobeLand30). The study results display that the average annual soil erosion amount in Kyrgyzstan was 5.95 t ha−1 year−1, with an annual soil loss of 113.7 × 106 t year−1. The entire area was separated into seven erosion risk classes. More than 28% of the territory of Kyrgyzstan is affected by limited soil erosion; the average volume of potential erosion is around 1.0 t ha−1 year−1. The northeastern and central parts of the country mainly experienced low soil erosion, whereas the west and southwestern parts were subject to high-to-extremely high soil erosion rates. This is the first time this method has been used to estimate the potential of soil loss throughout the country; it provides suitable tools for identifying priority areas for considering measures to decrease soil erosion risk. Our findings give valuable implementations for assessing soil loss and protecting the environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. http://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v12/en/

  2. https://cgiarcsi.community/data/srtm-90m-digital-elevation-database-v4-1/

  3. https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD13Q1/

  4. http://www.globeland30.org

References

  • Adyshev M et al. (1987) Atlas of Kyrgyz SSR: natural conditions and resources. vol. 1 Central Administrative Board of Geodetics and Cartography, Council of Ministers, Moscow, p 157

  • Alamanov S, Sakiev K, Akhmedov S (2013) Physical geography of Kyrgyzstan Bishkek. p.259 (in Russia)

  • Almagro A, Thomé TC, Colman CB, Pereira RB, Marcato Junior J, Rodrigues DBB, Oliveira PTS (2019) Improving cover and management factor (C-factor) estimation using remote sensing approaches for tropical regions. Int Soil Water Conserv Res 7:325–334. https://doi.org/10.1016/j.iswcr.2019.08.005

    Article  Google Scholar 

  • Angima S, Stott D, O’neill M, Ong C, Weesies G (2003) Soil erosion prediction using RUSLE for central Kenyan highland conditions. Agric Ecosyst Environ 97:295–308

    Article  Google Scholar 

  • Azimi Sardari MR, Bazrafshan O, Panagopoulos T, Sardooi ER (2019) Modeling the impact of climate change and land use change scenarios on soil erosion at the Minab Dam Watershed. Sustainability 11:3353

    Article  Google Scholar 

  • Barataliev O (2010) Geography of Kyrgyzstan. Ministry of Education of the Kyrgyz Republic, Bishkek

    Google Scholar 

  • Borrelli P et al (2017) An assessment of the global impact of 21st century land use change on soil erosion. Nat Commun 8:2013. https://doi.org/10.1038/s41467-017-02142-7

    Article  Google Scholar 

  • Borrelli P et al. (2020) Land use and climate change impacts on global soil erosion by water (2015–2070). Proceedings of the National Academy of Sciences, p. 202001403. Doi:https://doi.org/10.1073/pnas.2001403117

  • Desmet P, Govers G (1996) A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units. J Soil Water Conserv 51:427–433

    Google Scholar 

  • Didan K (2015) MOD13Q1 MODIS/Terra vegetation indices 16-day L3 global 250m SIN grid V006 NASA EOSDIS land processes DAAC

  • Dobrovolsky GV (2002) Degradation and protection of soils. Moscow State University publishing house, Moscow

    Google Scholar 

  • Duulatov E, Chen X, Amanambu AC, Ochege FU, Orozbaev R, Issanova G, Omurakunova G (2019) Projected rainfall erosivity over Central Asia based on CMIP5. Clim Models Water 11:897

    Google Scholar 

  • Duulatov E, Chen X, Issanova G, Orozbaev R, Mukanov Y, Amanambu AC (2021) Current and future trends of rainfall erosivity and soil erosion in Central Asia, 1st edn. Springer, Cham. https://doi.org/10.1007/978-3-030-63509-1

    Book  Google Scholar 

  • Dzhunushbaev AD (1958) Soils of the Suusamyr Valley. Kirgosizdat, Frunze

  • Dzhunushbaev A (1990) Eroded soils of Kyrgyzstan and ways to increase their fertility. Kyrgyzstan, Frunze

  • Gafforov KS et al (2020) The assessment of climate change on rainfall-runoff erosivity in the Chirchik-Akhangaran Basin. Uzbekistan Sustain 12:3369

    Article  Google Scholar 

  • Gupta S, Kumar S (2017) Simulating climate change impact on soil erosion using RUSLE model—a case study in a watershed of mid-Himalayan landscape. J Earth Syst Sci 126:43

    Article  Google Scholar 

  • Haregeweyn N et al (2017) Comprehensive assessment of soil erosion risk for better land use planning in river basins: case study of the Upper Blue Nile River. Sci Total Environ 574:95–108

    Article  Google Scholar 

  • Jarvis A, Reuter HI, Nelson A, Guevara E (2008) Hole-filled SRTM for the globe Version 4

  • Jiang B, Bamutaze Y, Pilesjö P (2014) Climate change and land degradation in Africa: a case study in the Mount Elgon region. Uganda Geo-Spatial Inf Sci 17:39–53

    Article  Google Scholar 

  • Jiu J, Wu H, Li S (2019) The implication of land-use/land-cover change for the declining soil erosion risk in the three Gorges reservoir region. China Int J Environ Res Public Health 16:1856

    Article  Google Scholar 

  • Jun C, Ban Y, Li S (2014) Open access to earth land-cover map. Nature 514:434–434. https://doi.org/10.1038/514434c

    Article  Google Scholar 

  • Kebede YS, Endalamaw NT, Sinshaw BG, Atinkut HB (2021) Modeling soil erosion using RUSLE and GIS at watershed level in the upper beles, Ethiopia. Environ Chall 2:100009

    Article  Google Scholar 

  • Khitrov NB, Ivanov AL, Zavalin AA (2007) Problems of degradation, protection and ways of recovery productivity of agricultural land. Vestn Orel GAU 6:29–32 (in Russian)

    Google Scholar 

  • Koirala P, Thakuri S, Joshi S, Chauhan R (2019) Estimation of soil erosion in Nepal using a RUSLE modeling and geospatial tool. Geosciences 9:147

    Article  Google Scholar 

  • Kulikov M (2018) Effects of land use and vegetation changes on soil erosion of alpine grazing lands-Fergana Range, Southern Kyrgyzstan

  • Kulikov M, Schickhoff U (2017) Vegetation and climate interaction patterns in Kyrgyzstan: spatial discretization based on time series analysis. Erdkunde 1:143–165

    Article  Google Scholar 

  • Kulikov M, Schickhoff U, Borchardt P (2016) Spatial and seasonal dynamics of soil loss ratio in mountain rangelands of south-western Kyrgyzstan. J Mt Sci 13:316–329. https://doi.org/10.1007/s11629-014-3393-6

    Article  Google Scholar 

  • Kulikov M, Schickhoff U, GrÖNgrÖFt A, Borchardt P (2020) Modelling soil erodibility in mountain rangelands of southern Kyrgyzstan. Pedosphere 30:443–456. https://doi.org/10.1016/S1002-0160(17)60402-8

    Article  Google Scholar 

  • Lee E, Ahn S, Im S (2017) Estimation of soil erosion rate in the Democratic People’s Republic of Korea using the RUSLE model. For Sci Technol 13:100–108

    Google Scholar 

  • Mamytov AM (1963) The soils of Central Thian Shan. Frunze

  • Mamytov AM (1987) Soils of the mountains of Central Asia and Southern Kazakhstan. Ilim, Frunze

  • Meliho M, Khattabi A, Mhammdi N (2020) Spatial assessment of soil erosion risk by integrating remote sensing and GIS techniques: a case of Tensift watershed in Morocco. Environ Earth Sci 79:1–19

    Article  Google Scholar 

  • Morgan R, Morgan D, Finney H (1984) A predictive model for the assessment of soil erosion risk. J Agric Eng Res 30:245–253

    Article  Google Scholar 

  • Mukanov Y et al (2019) Estimation of annual average soil loss using the Revised Universal Soil Loss Equation (RUSLE) integrated in a Geographical Information System (GIS) of the Esil River basin (ERB), Kazakhstan. Acta Geophys. https://doi.org/10.1007/s11600-019-00288-0

    Article  Google Scholar 

  • Nachtergaele F et al. (2009) Harmonized world soil database (version 1.1) FAO, Rome, Italy & IIASA, Laxenburg, Austria

  • Naipal V, Reick CH, Pongratz J, Van Oost K (2015) Improving the global applicability of the RUSLE model-adjustment of the topographical and rainfall erosivity factors. Geosci Model Dev 8:2893–2913

    Article  Google Scholar 

  • NatStatCom (2019a) Agriculture of the Kyrgyz Republic 2014–2018. National Statistical Committee of the Kyrgyz Republic, Bishkek

    Google Scholar 

  • NatStatCom (2019b) The environment in the Kyrgyz Republic 2014–2018. National Statistical Committee of the Kyrgyz Republic, Bishkek

    Google Scholar 

  • Nyesheja EM, Chen X, El-Tantawi AM, Karamage F, Mupenzi C, Nsengiyumva JB (2018) Soil erosion assessment using RUSLE model in the Congo Nile Ridge region of Rwanda. Phys Geogr 40:1–22

    Google Scholar 

  • Ostovari Y, Ghorbani-Dashtaki S, Bahrami H-A, Naderi M, Dematte JAM (2017) Soil loss prediction by an integrated system using RUSLE, GIS and remote sensing in semi-arid region. Geod Reg 11:28–36

    Google Scholar 

  • Panagos P et al (2015) The new assessment of soil loss by water erosion in Europe. Environ Sci Policy 54:438–447

    Article  Google Scholar 

  • Panagos P, Ballabio C, Poesen J, Lugato E, Scarpa S, Montanarella L, Borrelli P (2020) A soil erosion indicator for supporting agricultural, environmental and climate policies in the European Union. Remote Sens 12:1365

    Article  Google Scholar 

  • Pimentel D (2006) Soil erosion: a food and environmental threat. Environ Dev Sustain 8:119–137

    Article  Google Scholar 

  • Prasannakumar V, Vijith H, Abinod S, Geetha N (2012) Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India, using Revised Universal Soil Loss Equation (RUSLE) and geo-information technology. Geosci Front 3:209–215

    Article  Google Scholar 

  • Renard KG, Freimund JR (1994) Using monthly precipitation data to estimate the R-factor in the revised USLE. J Hydrol 157:287–306

    Article  Google Scholar 

  • Renard KG, Foster GR, Weesies G, McCool D, Yoder D (1997) Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE), vol 703. United States Department of Agriculture, Washington

    Google Scholar 

  • Ryskal MO (2020) Estimation of the amount of precipitation in the territory of Kyrgyzstan based on satellite observations. Kyrgyz-Russian Slavic University, Kyrgyzstan

    Google Scholar 

  • Sharma A (2010) Integrating terrain and vegetation indices for identifying potential soil erosion risk area. Geo-Spatial Inf Sci 13:201–209

    Article  Google Scholar 

  • Sujatha ER, Sridhar V (2018) Spatial prediction of erosion risk of a small mountainous watershed using RUSLE: a case-study of the Palar Sub-Watershed in Kodaikanal. South India Water 10:1608

    Google Scholar 

  • Teng H, Rossel RAV, Shi Z, Behrens T, Chappell A, Bui E (2016) Assimilating satellite imagery and visible–near infrared spectroscopy to model and map soil loss by water erosion in Australia. Environ Model Softw 77:156–167

    Article  Google Scholar 

  • Teng H et al (2018) Current and future assessments of soil erosion by water on the Tibetan Plateau based on RUSLE and CMIP5 climate models. Sci Total Environ 635:673–686

    Article  Google Scholar 

  • Teng H-F, Hu J, Zhou Y, Zhou L-Q, Shi Z (2019) Modelling and mapping soil erosion potential in China. J Integr Agric 18:251–264. https://doi.org/10.1016/S2095-3119(18)62045-3

    Article  Google Scholar 

  • Tucker CJ (1978) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8(2):127–150

    Article  Google Scholar 

  • Uddin K, Murthy M, Wahid SM, Matin MA (2016) Estimation of soil erosion dynamics in the Koshi basin using GIS and remote sensing to assess priority areas for conservation. PLoS ONE 11:e0150494

    Article  Google Scholar 

  • Uddin K, Abdul Matin M, Maharjan S (2018) Assessment of land cover change and its impact on changes in soil erosion risk in Nepal. Sustainability 10:4715

    Article  Google Scholar 

  • Van der Knijff J, Jones R, Montanarella L (2000) Soil erosion risk assessment in Europe. European Soil Bureau. European Commission Belgium, Belgium

    Google Scholar 

  • Wang L, Zhang F, Fu S, Shi X, Chen Y, Jagirani MD, Zeng C (2020) Assessment of soil erosion risk and its response to climate change in the mid-Yarlung Tsangpo River region. Environ Sci Pollut Res 27:607–621

    Article  Google Scholar 

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses-a guide to conservation planning Predicting rainfall erosion losses-a guide to conservation planning

  • Wuepper D, Borrelli P, Finger R (2020) Countries and the Global rate of soil erosion nature. Sustainability 3:51–55

    Google Scholar 

  • Yang D, Kanae S, Oki T, Koike T, Musiake K (2003) Global potential soil erosion with reference to land use and climate changes. Hydrol Process 17:2913–2928

    Article  Google Scholar 

  • Zhumabekov EZ (2017) Problems of mountain soil in the works of the academician Mamytov. Bull Kyrg Natl Agrar Univ 2:15–21

    Google Scholar 

Download references

Acknowledgements

The Research Centre of Ecology and Environment of Central Asia (Bishkek) and postdoctoral fellowship provided by Al-Farabi Kazakh National University supported this work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Quoc Bao Pham.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Duulatov, E., Pham, Q.B., Alamanov, S. et al. Assessing the potential of soil erosion in Kyrgyzstan based on RUSLE, integrated with remote sensing. Environ Earth Sci 80, 658 (2021). https://doi.org/10.1007/s12665-021-09943-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-021-09943-6

Keywords

Navigation