Prediction of soil erosion in pansoon sub-basin, Malaysia using rusle integrated in geographical information system

Noor Fadzilah Yusof, Tukimat Lihan, Wan Mohd Razi Idris, Zulfahmi Ali Rahman, Muzzneena Ahmad Mustapha, Mohd Abdul Wahab Yusof

Research output: Contribution to journalArticle

Abstract

Water-borne erosion problem is one of the environmental problems faced globally particularly in developing countries. The objective of this study was to estimate the erosion rate at the Pansoon sub-basin using combination of conventional approach and remote sensing technology. Pansoon sub-basin is the upper stream of Langat watershed, Malaysia located in the mountainous area dominated by steep slopes and various type of soils which are the important factors contributed to soil erosion. The Revised Universal Soil Loss Equation (RUSLE) integrated in a Geographical Information System used to predict the soil erosion rate and spatially maps its distribution using rainfall, soil series and topography data to generate rainfall erosivity factor, soil erodibility factor and topography factor. Land use map was used to produce coverage and management practice factor. The result shows that 66% (7433 ha) of the Pansoon sub-basin is classified at very low risk, 22% of low risk (2433 ha), 5% of moderate (582 ha), 2% of the area with high risk (251 ha) and 5% of very high risk of erosion (549 ha). Pansoon sub-basin is prone to soil erosion problem on the southwest region may due to soil erodibility factor, slope length and slope steepness. Accuracy assessment was obtained between prediction model and field observation data (p=0.97) which means the RUSLE approach integrated in GIS is suitable to be used to predict and assessing the soil erosion rate. In conclusion, the prediction of soil erosion using RUSLE in GIS can be accurately assessed with the combination of field observation data.

Original languageEnglish
Pages (from-to)2565-2574
Number of pages10
JournalSains Malaysiana
Volume48
Issue number11
DOIs
Publication statusPublished - 1 Jan 2019

Fingerprint

soil erosion
Revised Universal Soil Loss Equation
GIS
erosion rate
prediction
basin
erodibility
soil
topography
erosion
erosivity
rainfall
accuracy assessment
integrated approach
management practice
developing world
watershed
remote sensing
land use
water

Keywords

  • GIS
  • Langat
  • Pansoon
  • RUSLE
  • Soil erosion

ASJC Scopus subject areas

  • General

Cite this

Prediction of soil erosion in pansoon sub-basin, Malaysia using rusle integrated in geographical information system. / Yusof, Noor Fadzilah; Lihan, Tukimat; Idris, Wan Mohd Razi; Rahman, Zulfahmi Ali; Mustapha, Muzzneena Ahmad; Yusof, Mohd Abdul Wahab.

In: Sains Malaysiana, Vol. 48, No. 11, 01.01.2019, p. 2565-2574.

Research output: Contribution to journalArticle

Yusof, Noor Fadzilah ; Lihan, Tukimat ; Idris, Wan Mohd Razi ; Rahman, Zulfahmi Ali ; Mustapha, Muzzneena Ahmad ; Yusof, Mohd Abdul Wahab. / Prediction of soil erosion in pansoon sub-basin, Malaysia using rusle integrated in geographical information system. In: Sains Malaysiana. 2019 ; Vol. 48, No. 11. pp. 2565-2574.
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AB - Water-borne erosion problem is one of the environmental problems faced globally particularly in developing countries. The objective of this study was to estimate the erosion rate at the Pansoon sub-basin using combination of conventional approach and remote sensing technology. Pansoon sub-basin is the upper stream of Langat watershed, Malaysia located in the mountainous area dominated by steep slopes and various type of soils which are the important factors contributed to soil erosion. The Revised Universal Soil Loss Equation (RUSLE) integrated in a Geographical Information System used to predict the soil erosion rate and spatially maps its distribution using rainfall, soil series and topography data to generate rainfall erosivity factor, soil erodibility factor and topography factor. Land use map was used to produce coverage and management practice factor. The result shows that 66% (7433 ha) of the Pansoon sub-basin is classified at very low risk, 22% of low risk (2433 ha), 5% of moderate (582 ha), 2% of the area with high risk (251 ha) and 5% of very high risk of erosion (549 ha). Pansoon sub-basin is prone to soil erosion problem on the southwest region may due to soil erodibility factor, slope length and slope steepness. Accuracy assessment was obtained between prediction model and field observation data (p=0.97) which means the RUSLE approach integrated in GIS is suitable to be used to predict and assessing the soil erosion rate. In conclusion, the prediction of soil erosion using RUSLE in GIS can be accurately assessed with the combination of field observation data.

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