Spatial prediction of soil erosion risk by remote sensing, GIS and RUSLE approach: a case study of Siruvani river watershed in Attapady valley, Kerala, India

• Published in: Environmental earth sciences Vol. 64; no. 4; pp. 965 - 972
• Main Authors: Prasannakumar, V., Shiny, R., Geetha, N., Vijith, H.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01-10-2011; Springer; Springer Nature B.V
• Subjects: Applied geophysics; Areal geology; Areal geology. Maps; Biogeosciences; Earth and Environmental Science; Earth Sciences; Earth, ocean, space; Environmental Science and Engineering; Erosion rates; Exact sciences and technology; Forest degradation; Geochemistry; Geologic maps, cartography; Geology; Hydrology/Water Resources; Internal geophysics; Original Article; Remote sensing; Shifting cultivation; Soil classification; Soil conservation; Soil erosion; Soils; Surficial geology; Terrestrial Pollution; Valleys; Watersheds; Western Ghats; Kerala India; Asia; Ghats; India; India, Kerala; RUSLE; Attapady; Erodability; Slope length; Erosivity; Siruvani; geographic information systems; degradation; rain water; case studies; slopes; spatial distribution; drainage basins; soils; RUSTLE; rivers; models; rainfall; maps; remote sensing; classification; forests; erosion rates; prediction; soil erosion; valleys; landform evolution; Pixel
• ISSN: 1866-6280; 1866-6299
• DOI: 10.1007/s12665-011-0913-3

Siruvani watershed with a surface area of 205.54 km
2
(20,554 hectare), forming a part of the Western Ghats in Attapady valley, Kerala, was chosen for testing RUSLE methodology in conjunction with remote sensing and GIS for soil loss prediction and identifying areas with high erosion potential. The RUSLE factors (
R
,
K
, LS,
C
and
P
) were computed from local rainfall, topographic, soil classification and remote sensing data. This study proved that the integration of soil erosion models with GIS and remote sensing is a simple and effective tool for mapping and quantifying areas and rates of soil erosion for the development of better soil conservation plans. The resultant map of annual soil erosion shows a maximum soil loss of 14.917 t h
−1 
year
−1
and the computations suggest that about only 5.76% (1,184 hectares) of the area comes under the severe soil erosion zone followed by the high-erosion zone (11.50% of the total area). The dominant high soil erosion areas are located in the central and southern portion of the watershed and it is attributed to the shifting cultivation, and forest degradation along with the combined effect of
K
, LS and
C
factor. The RUSLE model in combination with GIS and remote sensing techniques also enables the assessment of pixel based soil erosion rate.