Potensi Hakisan Tanih di Lembangan Sungai Bilut, Raub, Pahang menggunakan Integrasi Rusle dan GIS

Lihan, Tukimat; Khodri, Nur Fatin; Mustapha, Muzzneena Ahmad; Rahman, Zulfahmi Ali; Idris, Wan Mohd Razi

doi:10.17576/jsm-2018-4710-01

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…ha -1 yr -1 . This result is consistent with the study by Kamaludin et al (2013) and Lihan et al (2018). Similar study by Asmamaw and Mohammed (2019) has stated that at the steeper slope, the velocity and volume of the surface runoff will be accelerated which lead to much higher potential of soil loss.…”

Section: Discussionsupporting

confidence: 92%

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

Yusof¹,

Lihan²,

Idris³

et al. 2019

JSM

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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. ABSTRAKMasalah 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...

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Section: Discussionsupporting

confidence: 92%

“…The LS factor estimated in GIS environment is in the range of 0 to 332 with the average of 7.8. The LS factor were categorized following the study by Kamaludin et al (2013) and Lihan et al (2018). The LS factor for less than 5 is approximately 74% (9494 ha) whereas LS factor more than 5 is 26% (3379 ha).…”

Section: Resultsmentioning

confidence: 99%

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

Yusof¹,

Lihan²,

Idris³

et al. 2019

JSM

Self Cite

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Spatially distributed soil losses and sediment yield: A case study of Langat watershed, Selangor, Malaysia

Yusof

Lihan

Idris

et al. 2021

Journal of Asian Earth Sciences

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Identification of critical erosion prone areas in Temengor Reservoir Basin using Universal Soil Loss Equation (USLE) and Geographic Information System (GIS)

Basri

Adam

Teh

et al. 2019

IOP Conf. Ser.: Earth Environ. Sci.

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In this study, the Geographic Information System (GIS) was integrated with the Universal Soil Loss Equation (USLE) model to identify the risk of erosion at 360,000 ha in the Temengor Reservoir Basin. GIS was utilized as a tool for generating, manipulating and spatializing data from government agencies for sediment yield modelling and offering spatial input data to the erosion model. Meanwhile, USLE was used to predict the spatial distribution of the sediment yield on the grid basis. The five main parameters used in this study were the rainfall erosivity factor (R), topographic factor (LS), soil erodibility factor (K), crop management factor (C) and practice support factor (P). The R factor was calculated based on the annual rainfall data of the study area. The soil survey data was used to generate the K value and Digital Improvement Model (DEM) of the study area was used to generate LS factor. The values of C and P factors were derived from the land use map. After generating all parameters, analysis was performed to estimate the soil erosion using USLE model with spatial information analysis approach. It was discovered that the average annual soil loss in the study area was 8 t ha-1 year-1 and only 4% of the total area was under extreme erosion risk.

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Potensi Hakisan Tanih di Lembangan Sungai Bilut, Raub, Pahang menggunakan Integrasi Rusle dan GIS

Cited by 3 publications

References 7 publications

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

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

Spatially distributed soil losses and sediment yield: A case study of Langat watershed, Selangor, Malaysia

Identification of critical erosion prone areas in Temengor Reservoir Basin using Universal Soil Loss Equation (USLE) and Geographic Information System (GIS)

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