GIS AND REMOTE SENSING-BASED USLE MODEL FOR THE PREDICTION AND QUANTITATIVE ASSESSMENT OF EROSION RISKS IN AZERBAIJAN
Paper ID : 1018-SMPR
Authors:
Emil Bayramov *1, Rafael Bayramov2
1Geography Institute of Azerbaijan National Academy of Sciences
2Baku State University, Geography Faculty
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 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; oil and gas; oil pollution
Status : Paper Accepted (Oral Presentation)