Sains Malaysiana 48(11)(2019): 2565–2574

http://dx.doi.org/10.17576/jsm-2019-4811-26

Prediction of Soil Erosion in Pansoon Sub-basin, Malaysia using RUSLE integrated in Geographical Information System

(Ramalan Hakisan Tanah di Sub-lembangan Pansoon menggunakan Integrasi RUSLE dan Sistem Maklumat Geografi)

NOOR FADZILAH YUSOF, TUKIMAT LIHAN*, WAN MOHD RAZI IDRIS, ZULFAHMI ALI RAHMAN, MUZZNEENA AHMAD MUSTAPHA & MOHD. ABDUL WAHAB YUSOF

Center for Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan, Malaysia

Received: 10 April 2019/Accepted: 15 August 2019

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.

Keywords: GIS; Langat; Pansoon; RUSLE; soil erosion

ABSTRAK

Masalah hakisan yang disebabkan oleh air merupakan salah satu masalah alam sekitar yang dihadapi di seluruh dunia terutamanya di negara membangun. Objektif kajian ini adalah untuk menganggarkan kadar hakisan di sub-lembangan Pansoon menggunakan gabungan pendekatan konvensional dan teknologi penderiaan jauh. Sub-lembangan Pansoon adalah kawasan hulu lembangan Langat, Malaysia yang terletak di kawasan pergunungan yang dikelilingi oleh cerun curam dan beberapa jenis tanih yang merupakan faktor penting yang menyumbang kepada hakisan tanah. Semakan Semula Persamaan Kehilangan Tanih Universal (RUSLE) yang diintegrasikan dalam Sistem Maklumat Geografi digunakan untuk meramal kadar hakisan tanah dan peta ruangan dengan menggunakan data hujan, siri tanih dan topografi bagi menghasilkan faktor erosiviti hujan, faktor kebolehhakisan tanah dan faktor topografi. Peta guna tanah digunakan bagi menghasilkan faktor liputan dan amalan pengurusan. Hasil kajian mendapati 66% (7433 ha) daripada sub-lembangan Pansoon dikelaskan sebagai berisiko sangat rendah, 22% daripadanya adalah berisiko rendah (2433 ha), 5% daripadanya adalah sederhana (582 ha), 2% (251 ha) dan 5% daripadanya adalah hakisan yang sangat tinggi (549 ha). Sub-lembangan Pansoon terdedah kepada masalah hakisan tanah di wilayah barat daya mungkin disebabkan oleh faktor kebolehhakisan tanah, panjang cerun dan kecerunan. Kajian ketepatan diperoleh antara model ramalan dan data kerja lapangan (p=0.97) yang bermaksud pendekatan integrasi RUSLE dan GIS sesuai digunakan untuk meramal dan mentaksir kadar hakisan tanah. Kesimpulannya, ramalan hakisan tanah menggunakan RUSLE dalam GIS dapat dinilai secara tepat dengan gabungan data pemerhatian lapangan.

Kata kunci: GIS; hakisan tanih; Langat; Pansoon; RUSLE

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*Corresponding author; email: matt@ukm.edu.my