1. Prediction of sedimentation using integration of RS, RUSLE model and GIS in Cameron
Highlands, Pahang, Malaysia
A. H. A. Ghani, T. Lihan, S. A. Rahim, M. A. Musthapha, W. M. R. Idris, and Z. A. Rahman
Citation: AIP Conference Proceedings 1571, 543 (2013); doi: 10.1063/1.4858711
View online: http://dx.doi.org/10.1063/1.4858711
View Table of Contents: http://scitation.aip.org/content/aip/proceeding/aipcp/1571?ver=pdfcov
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2. Prediction of Sedimentation Using Integration of RS,
RUSLE model and GIS in Cameron Highlands,
Pahang, Malaysia
A. H. A. Ghani, T. Lihan, S. A. Rahim, M. A. Musthapha,
W. M. R. Idris and Z. A. Rahman
School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti
Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
Abstract. Soil erosion and sediment yield are strongly affected by land use change. Spatially distributed erosion models
are of great interest to predict soil erosion loss and sediment yield. Hence, the objective of this study was to determine
sediment yield using Revised Universal Soil Loss Equation (RUSLE) model in Geographical Information System (GIS)
environment at Cameron Highlands, Pahang, Malaysia. Sediment yield at the study area was determined using RUSLE
model in GIS environment The RUSLE factors were computed by utilizing information on rainfall erosivity (R) using
interpolation of rainfall data, soil erodibility (K) using soil map and field measurement, vegetation cover (C) using
satellite images, length and steepness (LS) using contour map and conservation practices using satellite images based on
land use/land cover. Field observations were also done to verify the predicted sediment yield. The results indicated that
the rate of sediment yield in the study area ranged from very low to extremely high. The higher SY value can be found at
middle and lower catchments of Cameron Highland. Meanwhile, the lower SY value can be found at the north part of the
study area. Sediment yield value turned out to be higher close to the river due to the topographic characteristic, vegetation
type and density, climate and land use within the drainage basin.
Keywords: GIS, RUSLE, soil erosion, sediment yield, Cameron Highlands.
PACS: 92.40. GC, 07.07 DF
INTRODUCTION
Cameron Highlands is one of the wonder places in Malaysia. It is a highland region located in the state of
Pahang. With a total of approximately 71 218 hectares (175 978 acres), it occupies around two percent of the state
area and is bordered by Kelantan at the north, by Perak at the west and the Pahang’s district of Raub at the south and
the east [1]. The highest area in Cameron Highlands is 1500 m above sea level. It has a cool climate with
temperature less than 25 °C and rarely falls below 12 °C year round [2]. Cameron Highlands is drained by eight
rivers with Bertam, Telom and Lemoi being the major rivers and other 123 tributaries [3]. River system in Cameron
Highlands is an important source of water supply, hydroelectricity generation, tourism, recreation and irrigation for
highland farming [4].
For decades, Cameron Highlands has undergone rapid development as a popular tourist destination and area
exploited for human activities like agriculture, urbanization, infrastructure development, deforestation etc. These
activities have led to tremendous pressure to the existing river system and water courses [5]. Cameron Highlands is
known to have one of the worst sedimentation problems in Malaysia. Extensive deforestation and indiscriminate
earth bulldozing for agricultural and housing development as well as road construction have resulted in widespread
soil erosion over the land surface of Cameron Highlands leading to the sedimentation of the streams [6].
Different approaches can be used to study the sedimentation. Revised Universal Soil Loss Equation (RUSLE)
model was used to determine the soil erosion and its impact on the physical components of the environment and
changes in land use. RUSLE model not only provides an estimation of soil loss at the plot scale but also presents the
spatial distribution of soil erosion [7]. RUSLE model assumes that detachment and deposition are controlled by the
sediment content of the flow. Erosion is limited by carrying capacity of the flow but is not source limited.
Detachment will no longer take place when the sediment load has reached the carrying capacity of the flow [8]. The
model requiring less data is convenient to be used together with satellite images and Geographical Information
System (GIS). A RUSLE implement in GIS environment is the most frequently used empirical soil erosion model
The 2013 UKM FST Postgraduate Colloquium
AIP Conf. Proc. 1571, 543-548 (2014); doi: 10.1063/1.4858711
© 2014 AIP Publishing LLC 978-0-7354-1199-9/$30.00
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3. worldwide [9]. Integration of GIS and RUSLE is helpful in determining the potential for soil erosion and the
distribution of spatial data by reducing costs and more accuracy especially over a wide area [10]. The integration of
RUSLE and GIS also can be further applied as a core procedure for other geomorphologic and hydrologic
applications such as watershed condition analysis, water quality monitoring of environmental pollutants in soils,
sediment loading of streams and rivers and non-point source pollution [11].
The aim of this research is to estimate the sediment yield in Cameron Highlands, Pahang Malaysia using Revised
Universal Soil Loss Equation (RUSLE) model in conjunction with remote sensing and GIS framework.
MATERIALS AND METHODS
This study was conducted at Telom and Bertam catchment area in the Cameron Highlands district of Pahang
Malaysia (FIGURE 1). It is located at latitude 04° 24’N-04° 29’N and longitude 101° 21’E-101° 23’E. In this study,
RUSLE model was integrated with satellite images and GIS to predict the sediment yield in Cameron Highlands.
Two methods have been used to calculate sediment yield in the study area which is by using GIS environment and
field observation.
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4. FIGURE 1. Study area at Cameron Highlands showing sampling points for field observation.
Sediment Yield in GIS Environment
Sediments can be defined as the material deposited at the bottom of the rivers [12]. In this study, sediment yield
(SY) was calculated using the sediment Delivery Ratio (SDR). The formula used for the study area was adopted
from the USDA SCS as shown below:
SDR = 0.51A-0.11
(1)
Where A is the area in km2
.
By using the SDR value from Eq. (1), SY values were calculated using the formula below [14]:
SY = SDR × SE (2)
Where SY = sediment yield (ton ha-1
yr-1
), SDR = sediment delivery ratio and SE = annual potential soil loss (A)
(ton ha-1
yr-1
).
The annual potential soil loss was calculated using RUSLE model in GIS framework. The RUSLE represents
how climate, soil, topography and land use effect rill and interrill soil erosion caused by raindrop impact and surface
runoff [7]. The factors used in RUSLE were produced from the meteorological station, soils map, contour map and
satellite images. Each RUSLE factor was calculated in GIS environment and all factors were analyzed together in
the model to predict the potential soil loss at the study area. The RUSLE equation is:
A = R×K×LS×C×P (3)
Where A is the average annual soil loss in tons per hectares per year (ton ha-1
yr-1
), R is the rainfall erosivity, K is
the soil erodibity, LS is the slope length and steepness, C is the cover management and P is the support practice.
In order to estimate the R factor, the daily and monthly rainfall data was obtained from the records of 10 gauging
stations for 21 years (1990-2011) through the Malaysian Meteorological Department. Spatial annual rainfall data
was derived from each station using kriging estimator technique with Spherical Semivariogram Model. The spatial
rainfall data results were compared and validated with the precipitation map from the Department of Irrigation and
Drainage Malaysia (JPS). The erosivity factor was calculated by using the equation from Morgan [15] and Roose
[16]. While, distribution of soil series within the study area was extracted from soil map of Cameron Highlands
produced by Department of Agriculture Malaysia (DOA). The effect of topography on soil erosion was accounted
by LS factor in RUSLE, which combines the effects of a slope length factor, (L), and a slope steepness factor, (S). In
this study, contour map from JUPEM was used to calculate LS factor in spatial distribution. LS factor was
calculated by using the equation from Wischmeier [17].
In this study, the NDVI of SPOT 5 image acquired on 2010 was used to determine the C factor. After a reversal
linear transformation derived from training samples, the relationship between C and NDVI can be establish [18].
Meanwhile, the values of P was estimated and assigned to the corresponding land cover using Spot image 2010 of
Cameron Highlands.
Field Observation
Fourteen sampling stations (FIGURE 1) were selected in this study. Water samples were taken from each station
for analysis of the total suspended sediments (TSS) in Bertam and Telom Rivers, Cameron Highlands. Three sample
replicates were collected at each station. The cross section length, depth and flow velocity were also measured at
each station using several types of apparatus such as range finder, depth finder and flow meter. These parameters
were measured to determine specific discharge values. While, the measurement of TSS was carried out using
gravimetric methods. Gravimetric methods were calculated using the following formula:
waterfilteredofVolume
filtermembraneofWeightresiduedryfiltermembraneofweight
TSS
1000])[(
(4)
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5. Discharge value (Q) is the product of average velocity (v) and cross section area (A) or Q = vA. Cross section
area is derived from the product of depth (d) and width (w). The calculation of suspended sediment yield (SY) is
based on the discharge value, TSS value and area of sampling basin. Sediment yield was calculated using the
equation below:
SY = (Q x TSS)/ (area of sampling basin) (5)
RESULTS AND DISCUSSION
Study area at Cameron Highlands is divided into three sub catchments (FIGURE 1) which is upper catchment,
middle catchment and lower catchment. Upper catchment of Cameron Highlands consists of Telom River, while
middle catchment consists of Bertam River and lower catchment consists of Lemoi River. The total sediment yield
of Cameron Highlands was calculated by summing the sediment yield of all three sub-catchment areas.
The annual sediment yield values were divided into seven classes. Derivation of the ordinal categories of
sediment yield value showed that about 28% of the study area was classified having very low sediment yield, 32% is
low, 36 % is moderate and the rest is (6%), high 3%, very high 2%, severe 0.7% and extreme 0.3%. The result
shows that the catchment of study area is quite prone to soil loss especially in the high land area (FIGURE 2). The
higher SY value can be found at middle and lower catchments of Cameron Highland. Meanwhile, the lower SY
value was observed in the northern part of the study area (FIGURE 2). High correlation (r = 0.99) occurred between
soil loss potential and sediment delivery (SY) in the catchment of the study area. Undeniably, land reclamation will
result in sedimentation and soil loss that occurs along the river.
Sediment yield analysis using field data shows that the value of SY ranged from 80.04 to 4372.541 ton/ha/year
with the mean 1242.22 ton/ha/year (TABLE (1)). The higher discharge value was observed at station 3 (237.7
m3
/sec) and the lowest discharge value is at station 9 (5.8 m3
/sec). The highest daily sediment load was observed due
to highest discharge value and total suspended sediment (TSS). The highest TSS value (5.2 mg/L) occurred at
station 12 and the lowest value (96 mg/L) at station 8. Meanwhile, the highest and lowest sediment yields at the
study area were observed at station 8 (80.04 ton/ha/year) and station 12 (4372.54 ton/ha/year). This study showed
high correlation (r = 0.99) between discharge values (Q) and total suspended sediment values in Bertam and Telom
Rivers. It indicates that an increase in discharge value (Q) would cause an increase in TSS value, thus causing an
increase in water turbidity. Therefore, discharge value (Q) is a factor that could influence the mobility or TSS
values. The higher velocity of water and higher rate of erosion produces higher suspended sediment. Sediment
yields were closely related to incidence of rainfall that affected the increasing values of river discharge. Activities
within the vicinity of the basin such as agriculture also contributed to the increasing levels of sediment yield.
There is high correlation (r = 0.80) between predicted SY and the measured data. It is the evident that with the
lack of canopy cover, the impact of rainfall on the soil surface increase, thus weakening the natural structure of the
soil layers and promoting higher erosion. Soil erosion is a major contributor of suspended sediments and siltation in
Cameron Highlands. Sediment yield is a complex problem in tropical area as soil erosion due to very high rainfall
contributes to it [19]. Besides, the severe pollution with organic compounds, siltation which is increase the turbidity
of the water is the most significant factor causing water quality deterioration. Most important source of silt into the
river course is agriculture, mostly on extremely steep slopes of Cameron Highlands [5]. The density of forest canopy
plays an important role towards reducing surface erosion which contributes to sediment load in rivers. The multi
tiered canopy layers function as filter in the process of interception [20] and reduce the effect of rain splash erosion
[19].
CONCLUSION
This study shows sediment yield was determined using RUSLE model in GIS environment. The predicted
sediment yield shows that its distribution at Cameron Highlands is highly variable in its value which ranged from
very low to extreme class. The higher sediment yield value was observed at middle and lower catchments of
Cameron Highlands. Meanwhile, the lower sediment yield was observed in the northern part of the study area.
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6. Sediment yield analysis using field data shows that the value of SY ranged from 80.04 to 4372.541 ton/ha/year with
the mean 1242.22 ton/ha/year. There is high correlation (r = 0.80) between predicted SY and the measured data. A
comprehensive approach of planning and management program is needed for the development of Cameron
Highlands in order to reduce the occurrence of potential disaster such as soil erosion, sedimentation and flash
food.
FIGURE 2. Study area with Sampling point location.
Sampling station Q (m3
/sec) TSS (mg/l) SY (ton/ha/yr)
1 118.02 7.83 309.39
2 7.70 7.70 415.18
3 237.68 8.67 581.17
4 100.98 76.67 3112.61
5 39.20 39.20 1502.58
6 37.80 37.80 1784.42
7 27.50 27.50 2793.14
8 46.74 5.17 80.04
9 5.80 5.80 93.83
10 137.83 14.17 598.28
11 13.50 13.50 614.89
12 96.00 96.00 4372.54
TABLE (1). Sediment yield in Cameron Highlands.
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7. 13 46.80 46.80 830.78
14 22.00 22.00 302.17
ACKNOWLEDGMENTS
The authors would like to thank the Metrology Department for providing rainfall data and soil map (from
Department of Agriculture Malaysia), contour map (from Survey and Mapping Department Malaysia; JUPEM), and
SPOT 2010 image (from Remote Sensing Agency of Malaysia). This research was supported by UKM-GUP-2011-
185 grant and Zamalah UKM.
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