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Quantitative assessment of climate change impacts onto predicted erosion risks and their spatial distribution within the landcover classes of the Southern Caucasus using GIS and remote sensing

  • Emil Bayramov
  • Patric Schlager
  • Martin Kada
  • Manfred Buchroithner
  • Rafael Bayramov
Original Article
  • 26 Downloads

Abstract

The objectives of this research are the following: quantitative assessment of erosion-prone areas, assessment of the impacts of climate change on future erosion risks and quantification of erosion risks in relation to landcover classes. The practical value of this study is that it promotes a collaborative planning and decision-making tool for the mitigation of erosion risks and consequences which are inevitable for the Southern Caucasus. The selected study area in the Southern Caucasus is the Ismayilly District. The scientific novelty lies in the fact that it considers the aspects of climate change in the prediction of erosion risks. The Universal Soil Loss Equation was used for the prediction of soil loss rates. Out of 2559 km2, 292 km2 were predicted as critical erosion classes with soil loss rates of more than 10 tons/ha/year. Precipitation impacts calculated by means of theHadGEM2-AOclimate change model to erosion processes also showed an increase in soil loss rates. The quantification of predicted erosion related to landcover revealed a significant variation of critical erosion classes within bare lands (5–10 ton/ha/year to 6.21 km2, 10–20 ton/ha/year to 11.90 km2, 20–50 ton/ha/year to 28.24 km2, 50–100 ton/ha/year to 15.44 km2, 100–200 ton/ha/year to 0.75 km2). The quantification of erosion rates related to landcover classes showed their highest spatial distribution variability within barelands (62.55 km2 out of total 71 km2) and grasslands (339.44 km2 out of total 895 km2). Significant areas of stressed vegetation with low NDVI values (0.1–0.2) were observed to be 259.51 km2 within croplands affected by intensive agricultural activities which reduced soil productivity over years.

Keywords

GIS Remote sensing Erosion USLE NDVI Landcover 

Notes

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Emil Bayramov
    • 1
  • Patric Schlager
    • 2
  • Martin Kada
    • 1
  • Manfred Buchroithner
    • 3
  • Rafael Bayramov
    • 4
  1. 1.Institut für Geodäsie und GeoinformationstechnikTechnische Universität BerlinBerlinGermany
  2. 2.GIZ Office AzerbaijanBakuAzerbaijan
  3. 3.Institute for CartographyDresden University of TechnologyDresdenGermany
  4. 4.Faculty of GeographyBaku State UniversityBakuAzerbaijan

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