Sains Malaysiana 47(10)(2018):
2241–2249
http://dx.doi.org/10.17576/jsm-2018-4710-01
Potensi Hakisan Tanih
di Lembangan Sungai Bilut,
Raub, Pahang menggunakan Integrasi RUSLE dan GIS
(Soil Erosion Potential at Sungai Bilut
Catchment, Raub, Pahang using Integration
of RUSLE and GIS)
TUKIMAT
LIHAN*,
NUR
FATIN
KHODRI,
MUZZNEENA
AHMAD
MUSTAPHA,
ZULFAHMI
ALI
RAHMAN
& WAN MOHD RAZI
IDRIS
Pusat Pengajian
Sains Sekitaran
dan Sumber Alam,
Fakulti Sains
dan Teknologi, Universiti Kebangsaan Malaysia,
46300 UKM Bangi, Selangor Darul
Ehsan, Malaysia
Received: 31 March 2018/Accepted:
8 June 2018
ABSTRAK
Aktiviti guna tanah di
kawasan lembangan
adalah salah satu
faktor yang mendorong
kepada kemerosotan kualiti air sungai akibat daripada hakisan tanih. Potensi hakisan
tanih di kawasan
lembangan Sungai Bilut, Raub, Pahang yang menjadi sumber bekalan air minuman utama di daerah Raub boleh
ditentukan dengan
menggunakan integrasi model Semakan Semula Persamaan Kehilangan Tanih Universal (RUSLE) dan
Sistem Maklumat
Geografi (GIS). Kajian
ini bertujuan
untuk menentukan potensi hakisan tanih dan faktor
utama yang mempengaruhi
kadar hakisan
tanih. Kajian ini melibatkan
penggunaan data sekunder
yang terdiri daripada
data hujan, data siri tanih dan topografi
bagi menghasilkan
faktor kehakisan hujan (R), kebolehhakisan tanih (K), serta panjang dan kecuraman
cerun (LS). Faktor litupan
tumbuhan (C) dan
amalan pemuliharaan (P) pula dijana daripada imej satelit Landsat 8 (2014).
Keputusan kajian
menunjukkan nilai faktor R di kawasan kajian ialah 8927.68-9775.18 MJ
mm ha-1 jam-1 tahun-1,
nilai K ialah
0.036-0.500 tan jam-1 MJ-1 mm-1,
nilai LS ialah
0-514, nilai C ialah
0.03-0.80 dan nilai
P ialah 0.1-0.7. Kawasan yang mempunyai potensi
hakisan sangat
rendah hingga rendah
meliputi 81%, manakala
potensi hakisan tanih sederhana hingga sangat tinggi
meliputi 19% daripada
keseluruhan kawasan kajian. Model yang dihasilkan mempunyai ketepatan sebanyak 81%. Faktor utama yang mempengaruhi berlakunya hakisan tanih di kawasan kajian adalah faktor
topografi, litupan
tumbuhan dan kebolehhakisan tanih.
Keputusan menunjukkan analisis
integrasi RUSLE dan
GIS
berpotensi dalam
penentuan potensi
hakisan tanih untuk
kawasan luas
yang mempunyai pelbagai jenis guna tanah,
topografi dan
jenis tanih.
Kata kunci: GIS; hakisan
tanih; RUSLE
ABSTRACT
Land use activities
within catchment area are one of the factors contributing to deterioration
of river water quality due to soil erosion. Potential soil erosion
at the Sungai Bilut catchment, which is the main source of water supply
in Raub district, can be determined
using Revised Universal Soil Loss Equation (RUSLE) and Geographical Information
System (GIS). The aims of this research were
to determine the potential soil loss and also to determine the
main factors that influence the rate of soil erosion. This study
involved analysis of secondary data of rainfall, soil series and
topography data to generate factors of rainfall erosivity
(R), soil erodibility (K) and length and steepness of slope (LS). Vegetation coverage and conservation
practices factors were generated from satellite image of Landsat
8 (2014). The results showed that the R factor value in the study
area is 8927.68-9775.18 MJ mm ha-1 h-1 yr-1,
K value is 0.0036-0.500 tones h-1 MJ-1 mm-1,
LS
value is 0-514, C value is 0.03-0.80 and P value
is 0.1-0.7. The area that has very low to low erosion potential
is 81%, while medium to very high erosion potential is 19% of
total study area. The model has an accuracy of 81%. The main factors
that contribute to the potential of soil erosion in the study
area are topography, vegetation cover, and soil erodibility. The
results indicated the potential of integration of RUSLE and
GIS
analysis in determination of potential soil erosion
in wide area consisting of various land use, topography and soil
type.
Keywords: GIS; RUSLE;
soil erosion
REFERENCES
Abdulla,
H.H. 1966. A study of development of Podzol
profiles in Dovey Forest. Ph.D.
Thesis, University of Wales, Aberystwyth
(tidak diterbitkan).
Avery,
B.W. & Bascomb, C.L. 1982. Soil Survey Laboratory Methods. Harpenden: Soil survey Technical Monograph No. 6.
Baharuddin, K.
1988. Effect of logging on sediments yield in
a hill dipterocarp forest in Peninsular Malaysia. The
Journal of Tropical Forest Science 1(1): 56-66.
Beskow,
S., Mello, C.R., Norton, L.D., Curi,
N., Viola, M.R. & Avanzi, J.C. 2009. Soil
erosion prediction in the Grande River Basin, Brazil using distributed
modelling. Catena 79: 49-59.
Brandy,
N.C. & Weil, R.R. 2000. Elements of
the Nature and Properties of Soils. 2nd ed.
New Jersey: Prentice Hall.
Drzewiecki,
W., Wężyk, P., Pierzchalski,
M. & Szafrańska, B. 2013. Quantitative
and qualitative assessment of soil erosion risk in Małopolska (Poland), supported by an object-based analysis
of high-resolution satellite images. Pure and Applied Geophysics
171(6): 867-895.
Ibrahim,
A.L., Lateh, H., Ismail, W.R., Weng,
C.N., Hsiang-te, K. & Pin-Shuo,
L. 2002. Effects of hill land development and soil erosion
on sedimentation and water resources in Malaysia. In River
99: Towards Sustainable Development, Penang. Universiti Sains Malaysia. hlm. 314-319.
Jaafar,
M., Yusof, A.H. & Yahaya,
A. 2011. Analisis tahap kebolehruntuhan tanah dengan menggunakan
skala ROM: Kajian
di kampus Universiti Kebangsaan Malaysia, Bangi. Geografia Malaysian Journal of Society and Space
7(3): 45-55.
Jabatan
Pengairan dan
Saliran Malaysia. 2010. Potensi Hakisan Tanih Semenanjung
Malaysia. Kuala Lumpur: Kementerian
Sumber Asli dan
Alam Sekitar.
Kamaludin,
H., Lihan, T., Ali Rahman, Z., Mustapha,
M.A., Idris, W.M.R. & Rahim., S.A. 2013. Integration of
remote sensing, RUSLE and GIS to model potential soil loss and
sediment yield (SY). Hydrology and Earth System Sciences
Discussion 10: 4567-4596.
Kementerian
Sumber Asli
dan Alam Sekitar. 2010.
Preparation of Design Guides for Erosion and Sediment Control
in Malaysia. Kuala Lumpur: Jabatan
Pengairan dan Saliran.
Kirkby, M.J.
1980. Soil Erosion: Soil Loss Estimation. New York: John
Wiley & Sons.
Kwi,
S.N., Haridas, G., Seng, Y.C. &
Hua, T.P. 1980. Soil Erosion and Conservation in Peninsular Malaysia.
Soil Erosion and Conservation in Peninsular
Malaysia. Kuala Lumpur: Rubber Research Institute of
Malaysia.
Mahmud,
A.R., Sakawi, Z. & Abdul Maulud,
K.A. 2015. Pakej penambahbaikan
EIA di Malaysia: Suatu ulasan
kritis dalam
aspek kawalan hakisan
tanah dan
sedimentasi. Journal of Society and Space 6: 23-35.
Markose,
V.J. & Jayappa, K.S. 2016. Soil loss estimation and prioritization of sub-watersheds of Kali
River basin, Karnataka, India, using RUSLE and GIS. Environmental
Monitoring and Assessment 188(4): 1-16.
Millward,
A.A. & Mersey, J.E. 1999. Adapting the
RUSLE to model soil erosion potential in a mountainous tropical
watershed. Catena 38(2): 109-129.
Mitasova,
H., Hofierka, J., Zlocha,
M. & Iverson, L.R. 1996. Modelling topographic
potential for erosion and deposition using GIS. International
Journal of Geographical Information Systems 10(5): 629-641.
Mohamad
Abd Manap,
Mohammad Firuz Ramli, Wan Nor Azmin Sulaiman
& Noraini Surip.
2010. Application of remote sensing in the identification of the
geological terrain features in Cameron Highlands, Malaysia. Sains
Malaysiana 39(1): 1-11.
Morgan,
R.P.C. 2005. Soil Erosion and Conservation.
Edisi
ke-3. UK: Blackwell.
Muhammad
Rendana, Sahibin
Abdul Rahim, Wan Mohd Razi
Idris, Tukimat Lihan
& Zulfahmi Ali Rahman. 2017. Soil erosion
assessment in Tasik Chini
catchment using remote sensing and GIS techniques. Sains
Malaysiana 46(4): 529- 535.
M. Hamid,
C.H., M., Ashraf, Qudsia Hamid, Syed
Mansoor Sarwar & Zulfiqar Ahmad
Saqib. 2017. Geospatial techniques for
assessment of bank erosion and accretion in the Marala
Alexandria Reach of the River Chenab, Pakistan. Sains
Malaysiana 46(3): 413-420.
NRCS
- USDA State Office of Michigan. 2002. Technical Guide to RUSLE
use in Michigan.
Panagos, P.,
Meusburger, K., Ballabio,
C., Borrelli, P. & Alewell,
C. 2014.
Soil erodibility in Europe: A high-resolution dataset based on
LUCAS. Science of the Total Environment 479-480: 189-200.
Qing,
X.Y., Mei, S.X., Bin, K.X., Jian, P. & Long, C.Y. 2007. Adapting
the RUSLE and GIS to model soil erosion risk in a mountains karst
watershed, Guizhou Province, China. Journal of Environmental
Monitoring and Assessment 141(1): 275-286.
Renard, K.G.,
Foster, G.R., Weesies, G.A., McCool,
D.K. & Yooder, D.C. 1997. Predicting
Soil Erosion by Water: A Guide to Conservation Planning with the
Revised Soil Loss Equation (RUSLE). Washington:
US Department of Agriculture.
Terrence,
J.T., George, R.F. & Kenneth, G.R. 2002. Soil Erosion: Processes, Prediction,
Measurement and Control. United States: John Wiley & Sons.
Troeh, F.R.,
Hobbs, A.J. & Donahue, R.L. 1991. Soil and Water
Conservation. 2nd ed. Englewood Cliffs, N.J.: Prentice-Hall
Incorporation.
Troeh, F.R.,
Hobbs, A.J. & Donahue, R.L. 1999. Soil and Water Conservation:
Productivity and Environment Protection. New Jersey: Prentice
- Hall.
Wischmeier, W.H.
& Smith, D.D. 1978. Predicting Rainfall Erosion Losses:
A Guide to Conservation Planning. Washington: US Department
of Agriculture.
*Corresponding
author; email: matt@ukm.my