Soil erosion analysis by RUSLE and sediment yield models using remote sensing and GIS in Kelantan state, Peninsular Malaysia
M. T. Anees A D , K. Abdullah A , M. N. M. Nawawi A , N. A. N. Norulaini B , M. I. Syakir C and A. K. M. Omar C
+ Author Affiliations
- Author Affiliations
A School of Physics, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia.
B School of Distance Education, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia.
C School of Industrial Technology, Universiti Sains Malaysia, 11800, Minden, Penang, Malaysia.
D Corresponding author. Email: talhaanees_alg@yahoo.in
Soil Research 56(4) 356-372 https://doi.org/10.1071/SR17193
Submitted: 24 July 2017 Accepted: 19 December 2017 Published: 1 March 2018
Abstract
The present study used pixel-based soil erosion analysis through Revised Universal Soil Loss Equation (RUSLE) and a sediment yield model. The main motive of this study is to find soil erosion probability zones and accordingly prioritise watersheds using remote sensing and Geographic Information System (GIS) techniques in Kelantan state, Peninsular Malaysia. The catchment was divided into 82 watersheds and soil loss of the catchment was calculated. Soil loss and sediment yield were divided into five categories ranging from very low to very high. Maximum area of the very high soil-loss category was observed in uncultivated land and the maximum area of very low soil-loss category was in forest. Soil erosion probability zones were also divided into five categories in which 36.1% of the area experienced zero soil erosion and 20.1% and 17.8% represented very high and high probability zones respectively. The maximum very high and high probability zones were 61.6% and 28.5% of the watershed area respectively. Prioritisation was according to the area covered by very high and high soil erosion probability zones, which showed that out of 82 watersheds, two had the very high and high priority categories respectively. The overall results indicate that high rainfall and agricultural activities enhanced the soil erosion rate on steep slopes in the catchment. Pixel-based soil erosion analysis through remote sensing and GIS was a very effective tool in finding accurate causes of soil erosion. Furthermore, it was suggested that agricultural activities and deforestation should be stopped on steep slopes because of their contribution in increasing soil erosion.
Additional keywords: geographic information system, prioritisation, remote sensing, RUSLE, sediment yield, soil loss watersheds.
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