Assessment of Soil Erosion Using Large-scale Soil Information and GIS in Utkal Coastal Plain, Odisha
Keywords:
Large scale, remote sensing, soil erosion, utkal coastal plainAbstract
The present study was conducted during 2017–2018 to estimate soil loss in the Utkal coastal plain, Odisha, India using the soil loss model, Universal Soil Loss Equation (USLE) integrated with GIS. A 16-soil series (management units) was established with 30 mapping units. Each mapping unit having different characteristics which are integrated and developed soils erosion maps of the area. The five major input parameters used in the study are rainfall erosivity factor (R), soil erodability factor (K), Length slope factor (LS), vegetation cover factor (C) and erosion control factor (P) were collected during field work and analyzed for estimation. The quantitative soil loss (t ha-1 year-1) ranges were estimated and classified the coastal plain into different levels of soil erosion severity map was developed. The annual average R factor ranged from 697.48 to 710.16 mt ha-1cm−1. The K factor was low in loamy sand and sandy loam texture and poor organic matter soils. Topographic factor increases in a range of 0.1 to 5.0 and flow accumulation also increased. P factor is <0.25 in uplands soils and 0.25−0.5 in low land soils. The study area is classified according to Indian condition into different erosion classes such as (>5 t ha-1 year-1) slight, (5-10 t ha-1 year-1) moderate, (10−15 t ha-1 year-1) strong, (15−20 t ha-1 year-1) severe, (20−40 t ha-1 year-1) very severe, and (>40 t ha-1 year-1) extremely severe. The study area 42.68% has moderate erosion risk and 21.96% slight erosion risk of the total area. The results can certainly aid in the implementation of soil management and conservation practices to reduce soil erosion in coastal systems.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Authors retain copyright. Articles published are made available as open access articles, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.
This journal permits and encourages authors to share their submitted versions (preprints), accepted versions (postprints) and/or published versions (publisher versions) freely under the CC BY-NC-SA 4.0 license while providing bibliographic details that credit, if applicable.