Soil Erosion Modeling Using Ruscle and GIS at Cameron Highlands, Malaysia

3RD INTERNATIONAL CONFERENCE ON MANAGING RIVERS IN THE 21ST CENTURY:

6 - 9 DECEMBER 2011, PULAU PINANG, MALAYSIA

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SOIL EROSIO� MODELI�G USI�G RUSLE A�D GIS AT CAMERO�

HIGHLA�DS, MALAYSIA

Jansen Luis1, Soo Huey Teh

2, Lariyah Mohd Sidek

3,

Mohamed Nor Bin Mohamed Desa4, Pierre Y. Julien

5

Abstract: Upland erosion and reservoir sedimentation at Cameron Highlands are among the most important

sedimentation problems in Malaysia. Uncontrolled deforestation and indiscriminate land clearing for agricultural,

housing development and road construction resulted in widespread soil erosion over the land surface of Cameron

Highlands leading to sedimentation of the rivers and of the Ringlet Reservoir. The increasing rate of sedimentation

in the reservoir is adversely impacting the hydropower production scheme. The objective of this article is to present

the results of a GIS-based analysis of the mean annual soil loss rate using the RUSLE model for the Upper

Catchment of Cameron Highlands for the years 1997 and 2006. Data such as rainfall pattern, soil type, topography,

cover management and support practice were integrated for soil erosion modeling using RUSLE and ArcGIS. The

sub-catchments of Telom, Kial and Kodol, Upper Bertam, Middle Bertam, Lower Bertam, Habu, Ringlet and

Reservoir catchments were studied. Sediments were detached and transported from the upper catchment and were

eventually deposited in the Ringlet Reservoir. The soil loss of Cameron Highlands catchment was computed to be

282,465.5 m3/ year in 1997 and 334,853.5 m3/ year in 2006. The sediment yield for the Ringlet Reservoir was

therefore computed to be 1564 m3/km2/yr or 15.64 tons/km2/yr for 1997 and 1854 m3/km2/yr or 18.54 tons/km2/yr

in 2006 or an increase of 18.5% since 1997. Hence, the storage capacity of the reservoir is decreasing faster than

anticipated because of the increasing sediment yield with time. Consequently, the reservoir life expectancy has also

decreased considerable as compared to the design life expectancy.

Key words sedimentation, reservoir, catchment, source erosion

1. I�TRODUCTIO�

Cameron Highlands Hydroelectric Scheme was planned

and constructed from 1959 to 1964. The main feature of

the scheme was the Ringlet Falls/Sultan Abu Bakar Dam

which stands at 40m comprising of concrete buttress fitted

with four (4) gated spillways. The reservoir elevation at

full supply level is 1070.7m and has a surface area of 60

hectares. The reservoir receives waters from the rivers

namely Sg. Habu, Sg. Bertam, Sg. Ringlet and other minor

tributaries. Ringlet Reservoir was designed for a gross

storage of 6.3 million m3, of which 4.7 million m3 is the

active/live storage and 2.0 million m3 is the inactive/dead

storage. The dead storage was designed for a useful lifespan of

approximately 80 years which translates to a design sediment

inflow of 20,000m3/year.

From the bathymetric survey data the sediment rate of

40,000m3/year was recorded immediately after construction.

The data showed an increase of almost 100% from the

designed storage requirement, which means that the dead

storage would be filled up after 40 years of operation and not

as what was designed for. This increase is directly related to

the increase in the upstream activities such as deforestation,

un-controlled farming, residential and rapid developments

surrounding the catchments.

Main Author:

1Jansen, L., Engineering Services, Generation Asset Development, T�B

([email protected])

Corresponding Author: 2Soo Huey Teh, Renewable Energy System, University of Iceland.

([email protected] )

Main Supervisor: 3Assoc. Prof. Dr. Ir. Lariyah Mohd Sidek, Department of Civil Engineering,

U�ITE� ([email protected])

Co – Supervisor [1]: 4Prof. Dr. Ir. Hj Mohamed �or bin Mohamed Desa, Department of Civil

Engineering, U�ITE� (Mohamed�[email protected])

Co – Supervisor [2]: 5Prof Pierre Y. Julien, Department of Civil Engineering, Colorado State

University, Fort Collins ([email protected])



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2. CATCHME�T CHARACTERISTICS

Cameron Highland catchment area is mountainous terrain

having various mountain peaks ranging from 1524m to

2032m. The highest peak within the catchment is Gunung

Brinchang standing at 2032m (6666 ft). Under the

Cameron Highlands Hydroelectric Scheme- Stage I

Construction, the scheme was designed as a high head

scheme which involves the combined flow from two major

Figure 1. Cameron Highlands sub-catchment

rivers, Sungei Telom and Sungei Bertam being conveyed

by pressure tunnel to an underground power station. The

gross head estimated between S. Bertam and S. Batang

Padang was 568m.The total catchment area of Cameron

Highlands Scheme is 183 square km comprising of 111

square km of Telom Catchment and 72 square km of

Bertam Catchment. The respective areas of the individual

catchments area are shown in Table 1.0.

3. FACTORS AFFECTI�G RESERVOIR

SEDIME�TATIO�

Eroded sediments from the catchment is most likely

contributes to the increase in sedimentation rate in

reservoir. The major factor that relates to the increase in

sediment inflow is the climatic characteristic such as the

rainfall intensity. However other factors such as the

catchment characteristic which includes soil, geology of

the area, vegetation cover, land use pattern and slopes also

plays an important part in the estimation of the soil erosion

rates. Such estimates on the source erosion are well

estimated using the Universal Soil Loss Equation (USLE)

combined with the more recent revision model named

Revised Universal Soil Loss Equation (RUSLE).

4. SOURCE EROSIO�

The well-known and widely used model used to calculate

the soil erosion losses from the catchment is the

USLE Equation was developed at National Runoff and Soil

Loss Data Center, USA. The USLE equation combines

various parameters as described in Equation 1:

A = R x K x L x S x C x P ------------- (1)

Where:

A – Soil Loss in kg/m2

R – The rainfall erosivity factor

K – The soil erodibility factor

L – Slope length factor

S – Slope gradient factor

C – Cover factor

P – Erosion control factor

5. SOIL ASSESSME�T USI�G GIS

The Geographic Information System (GIS) integrates

hardware, software, and data for capturing, managing,

analyzing, and displaying all forms of geographically

referenced information. GIS allows us to view, understand,

question, interpret, and visualize data in many ways that

reveal relationships, patterns, and trends in the form of maps,

globes, reports, and charts. For this study, ArcGIS version 9.3

was utilized. Figure 2 below shows the procedures of RUSLE

model integrated with ArcGIS.

Figure 2. Flow chart for mathematical computation and GIS

sediment yield assessment

5.1 Rainfall Factor (R)

The rainfall erosivity factor (R) describes that the rainstorm

energy of the rainfall, which varies with climate and location

within a certain region. From the DID Design Guides Report,

(Oct 2010) the computed annual EI30 and averaged R factor

for Pahang State for Station 4513033, Gunong Brinchang was

9,068.



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Table 1. Main features of Cameron Highlands hydroelectric scheme

Upper Catchment, Pahang

• Sg Telom (76.7km2) receiving water from Sg Plau’ur

(9.7km 2) in Kelantan via a 480m long diversion

tunnel.

• Sg Kodol (1.3km2) diverting water into Sg. Telom at

Telom Tunnel entrance.

• Sg. Kial (22.7km2) diverting water into Sg. Telom via

a 423m long tunnel.

• Kampung Raja (0.8MW)

• Kuala Terla (0.5MW)

Lower Catchment, Pahang

• Sg. Bertam (72.6km2) receiving water from upper

catchment via a 10.25km Telom Tunnel.

• Ringlet Reservoir impounded by Sultan Abu Bakar Dam.

• Robinson Falls (0.9MW)

• Habu (5.5MW)

• Sultan Yussof or JOR (100MW)

This value seems to be very high. The value could have

been originated from technical error during data collection.

Furthermore there are only 31 automatic rainfall gauge

stations installed in the State of Pahang and only one

automatic rainfall gauge station in Cameron Highlands

situated on Mount Brinchang (Ministry of Natural

Resources and Environment Malaysia, 2010) which

provides continuous 10-minute interval rainfall records to

calculate the maximum 30 minute rainfall intensity (EI30).

Therefore, data from one automatic rainfall gauge station

does not provide enough spatial coverage of pluviographic

data to obtain an accurate R factor.

Therefore further research in the R factor revealed similar

and simplified equations used for other catchments

throughout the Asia region.

Bols, (1978) equation for calculation of the R value based

on empirical study in Indonesia is as below:

-------------------(2)

Another study was by Hartcher (2005) which

investigates the hill slope erosion at Mae Chaem, Thailand

was also researched. The rainfall erosivity factor was

determined using the following equation:

R = 38.5 + 0.35P

-------------------(3)

Therefore for Cameron Highland’s catchment the annual

average value was based on the existing monthly rainfall

grids. Several equations were compared and the following is

the results are shown in Table 2. Both Harper (2005) and Bols

(1978) provided an average R factor of 972.597 which was

used in the RUSLE mathematical and GIS model

computation.

5.2Annual Precipitation

As comparison the mean annual rainfall during the design

stages (1956) was observed at approximately 2620mm and is

distributed fairly and evenly over the year with somewhat

heavier periods in April and November. This estimate is

slightly lower in recent years where the mean annual rainfall

in Cameron Highlands catchment is 2550mm. However the

heavier rainfall periods during the months of April and

November are still consistent as compared to recent times. It is

observed high precipitation occurs twice in a year especially

during the months between April to May and October to

November. Maximum recorded monthly rainfall occurred in

November at 315mm. Lowest recorded rainfall is 117mm

which occurred in the month of Feb.

Figure 3. Mean annual rainfall computed for Cameron

Highland catchment



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Table 2. Computed Rainfall Erosivity Factor, R

5.2.1 Results

Using the methods outlined above the rainfall erosivity or

isohyets map for the R factor was developed. The R factor

produced using equation from (Bols, 1978) is as shown in

Figure 4.

Figure 4. Rainfall Erosivity Map, R ranging from 700 –

950 using Bols, (1978)

5.3Soil Erodibility Factor (K)

The soil erodibility factor, K in the equation is a

quantitative value which is normally determine by

extensive experiments. It relates to the soil texture and

composition. The K factor is defined as a unit of mass per

area per erositivity unit and it indicates the ability of the

soil to erode which are found either in soil map or soil

analysis. Findings from the 2005 study by Ministry of

Natural Resources and Environment, Department of

Environment Malaysia, for Cameron Highlands reveals

that the soil erodibility factors in the study area ranges

from the order of 0.103 to 0.2.

Fortuin, (2006) elaborates that the surface soils in Cameron

Highlands are highly weathered; they are approximately 50%

sand and 30% silt or clay. From laboratory sampling

conducted in 2010, the particles size distribution for sediments

at Cameron catchment consists of 13% sand, 60% silt, 25%

clay and 2% organic matter.

The K factor values can be estimated using the soil erodibility

monograph method which depends on soil properties such as

the percentage of silt, clay and fine sand, percentage of

organic matter, soil structure code and permeability class.

Using this formula, the current K value was estimated for the

Cameron Highlands Catchment. The Wischmeier, (1971)

equation is as follows:

----- (4)

Where:

Percentage silt (MS: 0.002 – 0.05mm)

Percentage very fine sand (VPS; 0.05 – 0.1mm)

Percentage sand (SA: 01 – 2mm)

Percentage organic matter (OM)

Structure (S1)

Permeability (P1)

While the (Tew, 1999) for Malaysia condition proposed the

following method:

----- (5)

Where:

K– Soil Erodibility Factor (ton/ha)(ha.hr/MJ.mm)

M– (% silt +% very fine sand) x (100 – % clay)

OM– % of organic matter

S– Soil structure code

P– Permeability code



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5.3.1 Results

Using the (Wischmeier, 1971) formula, the K value for

Cameron Highlands was determined to be 0.052 while

(Tew, 1999) provided 0.033. Meanwhile, the soil

erodibility map for K factor developed using the GIS

method obtained a higher value of 0.0659. However all K

Factor for Peninsular Malaysia (DOA, 2008) shown in the

soil erodibility map shows a very low maximum value of

0.006. The DID Design Guide cites that the K values that

were used under a study in China was generally lower

compared to those in the USLE database for the

conterminous United States and that the K value

estimation method developed using the datasets from the

United States cannot be directly applied to soils in China.

Similarly in Malaysia, the Weishmeier method has also

been found to be significantly over estimated. However the

nomograph and equation developed by Tew (1999) are

based on limited data restricted to highland areas in

Malaysia. Therefore no exact value could be derived and

further study is therefore required on this field.

However for the study a higher value indicated by the

GIS method will be used to generate the model results. The

values of K are assumed to be uniform for this study and

are adopted from the Department of Agriculture. Therefore

the K factor used for steepland, urbanland and minedland

was 0.066. The theme was in vector form and was

converted to grid form with cell size of 20m.

Figure 5. Soil erodibility K factor in imperial units (DOA,

2006)

5.4 Topographic Factor (LS)

The two factors L and S are usually researched and

determined as separate values. However with the recent

development in the computer models and for practical

application purposes both the factors are combined into a

single factor LS. For Cameron Highlands catchment the

topographic factors, L and S is obtained from the topographic

information provided by the Digital Elevation Model (DEM)

derived from the NASA Shuttle Radar Topographic Mission

(thereafter SRTM) dataset. The DEM used will have a

horizontal resolution of 100m. A DEM of scale 1:50000 were

obtained for this study whereby the slope length and slope

steepness can be used in a single index, which expresses the

ratio of soil loss as defined mathematically by (Wischmeier

and Smith 1978);

The boundary and contour themes were used to generate

triangulated irregular network (TIN) and digital elevation

model (DEM). The boundary and contour shape files of

Cameron Highlands were obtained from the Department of

Agriculture, Malaysia shown in Figure 6. These shape files

were added as data into ArcGIS.

Figure 6. Boundary and contour map, Department of

Agriculture, Malaysia

Figure 7. Slope map derived from DEM



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5.4.1 Results

Using the Raster calculator function under Spatial

Analyst the modified equation to compute LS factor were

obtained. Themes of slope of DEM in percentage and flow

accumulation were activated to run the process. Cell value

of 20m was utilized in equation where the m value of 0.6

selected because the average slope is 12%. Table 3 shows

the calculated LS factor using the mathematical model for

the sub-catchments along with the average slope

percentage.

Table 3. LS value for the sub catchment area in Cameron

Highlands

Using the available data from ArchGIS, the slope length

and steepness for LS factor was developed using the

method described above. The LS factor for each sub –

catchment is regenerated as shown in Figure 8 below.

Figure 8. LS Factor for Cameron Highlands sub-

catchment generated from GIS model

5.5 Cover Factor (C) and Erosion Control Factor (P)

The crop management factor represents the ratio of soil loss

under a given crop to that of the base soil (Morgan, 1994).

The cover factor, C is related to land use characteristics.

Based on the previous studies on land use and available land

use maps, the values on Table 4 from Ministry of Natural

Resources and Environment, Department of Environment for

the C factor was used for this study.

The terrain within the study area can be classified according to

the slope category as define by the Department of Agriculture,

Malaysia. The terrain / topography classification is then used

in the erosion practice factor, P as in Table 5, where it

considers the best practices to reduce source erosion such as

contouring and terracing. The values proposed which is

dependent on the terrain slope.

Table 4. Land use Cover Factor, C (DOA)

Landuse Type C Factor

Agriculture Experimental Stn. 0.600

Associated Areas 0.350

Bare Land 1.000

Forest 0.010

Grassland 0.015

Market Gardening 0.350

Mine 1.000

Mixed Agriculture 0.350

Orchard 0.250

Residential Area 0.003

Scrub forest 0.010

Shifting Cultivation 0.250

Sundry Non-Tree Cultivation 0.250

Tea 0.350

Urban 0.500

Water body 0

Table 5. Erosion Control Factor, P (DOA)



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5.6 RUSLE Model using GIS Method

The Malaysian land use map for year 1997 and 2006 from

Department of Agriculture (DOA) was used as a

comparison of the results on soil loss. The Cameron

Highlands land use shape file for ArcGIS input was

requested and obtained from the Department of

Agriculture for 1997 and 2006 as shown in Figure 9 and

10.

Figure 9. Landuse map for year 1997 (DOA)

Figure 10. Landuse map for year 2006 (DOA)

C and P factors were generated the same way as K

factor by cross referencing the attribute table to ArchGIS.

The values of C were adopted from the Department of

Agriculture. For this study, P values were chosen based on

the land use instead of soil management. The theme was

converted from vector form to grid form with the cell size

of 20m.

5.6.1 Results

The land cover and management factor expressed the ratio

of soil loss under specified field conditions to the

corresponding loss from the standard soil plot. Relevant

landuse maps obtained from DOA for various years, i.e.

1997 and 2006 were used as comparison for the analysis.

Using the ArchGIS, the Cover Management factor (C) and

Erosion Control Factor (P) were developed using the method

described above for 1997 and 2006. The theme produced for

1997 is shown in Figure 11 and Figure 12 respectively. The

theme produced for 2006 is shown in Figure 13 and Figure 14

respectively. The maps produced for 2006 excludes the area of

Plau’ur sub-catchment due to unavailability of data.

Figure 11. Computed 1997 C factor

using ArchGIS

Figure 12. Computed P factor 1997

using ArchGIS



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Figure 13. Computed 2006 C factor

using ArchGIS

Figure 14. Computed P factor 2006

using ArchGIS

As computed the land changes have been quite drastic

since the year 1946. Figure 15 shows the forested area

reduction is almost all sub-catchment. The average

percentage of reduction in forested area is 35% compared

between years 1946 against 1997. Lower Bertam sub-

catchment recorded the lowest percentage in 1997 at 30%

for the forested area.

Land Use (Forest Area)

0

20

40

60

80

100

120

1946 1997

Year

Percentage (%)

UB

MB

LB

H

RL

R

P

KK

T

Avg

Figure 15. Comparison of largest land use area of forested

area by sub-catchment by percentage of loss for year 1946 and

1997

5.7 Results of soil erosion assessment

The mathematical computation was compared against the

RUSLE model generated from ArchGIS. The mathematical

model results and distribution of sediment yield by sub –

catchment is shown in Table 6.

Table 6. Mathematical model results on sediment soil loss and

sediment yield for Cameron Highlands catchment using 1997

landuse map

The result indicates that Telom and Bertam contribute almost

equally to the total soil loss of 278,282 m3/yr from the

catchment. However the Lower Bertam contributes the highest

sediment yield at 6,136 m3/km

2/yr due to the fact that the sub

catchment is more urbanized location and increasing numbers

land use activities and developments.

In order to compare the annual average soil loss rate (A) in

ton/ha/year and to study the present time trend of soil loss two

separate years of 1997 and 2006 where computed using

RUSLE model.



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To predict the annual average soil loss rate in the upper

catchment of Cameron Highlands, the R, K, LS, C and P

factors were multiplied using the raster calculator function

tool of ArcGIS and the respective annual soil loss maps for

the catchment of Cameron Highlands were produced for

the year 1997 and 2006. However the Plau’ur sub-

catchment was excluded from the computation because of

insufficient land use data and the area is still relatively

undeveloped.

Table 7. RUSLE model results on sediment soil loss and

sediment yield for Cameron Highlands catchment using

1997 and 2006 landuse map

The mathematical model for sediment yield for land use

1997 was compared against the 1997 RUSLE model

results. Both values were observed to have good linear

agreement with R2=0.79 as shown in Figure 16 below.

Figure 16. Relationship between RUSLE and

Mathematical Model of sediment load (m3/yr) for year

1997

However, the sediment yield value in RUSLE model is

slightly lower than the mathematical model at

13,618.35m3/km

2/yr as compared to 19,180m

3/km

2/yr.

This is might have been caused by the omission of Plau’ur

sub catchment from the computation in the RUSLE model.

The highest sediment yield by sub – catchment area was

observed at Ringlet at 2,633.02m3/km

2/yr. This contradicts

with the mathematical model result that which shows Lower

Bertam having the highest sediment yield at 6,136m3/km

2/yr.

The possible explanation for this is the boundary limits and

parameter inputs in RUSLE are different in both the models

calculations.

As for the sediment yield observed using the RUSLE model

for year 2006, the trend were notice to increase to 16,947

m3/km

2/yr or increased by 24.4% within a period of 9 years.

The soil loss calculated from the ArchGIS RUSLE model

increased from 282,465m3/yr in 1997 to 334,853m

3/yr in year

2006. This computes to an increase in soil loss of 52388m3/yr.

The annual soil loss thickness increased from 1.57mm/yr in

year 1997 to 1.85mm/yr in 2006. The average increase in soil

loss thickness since 1997 is calculated at 0.29 mm/yr.

Figure 17: The respective soil loss throughout Cameron

Highlands catchment using RUSLE model for 1997 soil map.

Two separate sub-catchment Habu and Ringlet were

investigated further in detail for the soil loss. Using the higher

soil loss values obtained in the RUSLE model the increase in

soil loss at Habu sub – catchment was noticed to be from

32,019.50m3/yr in 1997 to 50,626.70m

3/yr in year 2006 or

58.1% increase. Meanwhile at Ringlet sub- catchment the

increase is more extreme where the soil loss computed was

from 25,592.95m3/yr in 1997 to 50,909.81m

3/yr in year 2006

or a 100% increase.



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Figure 18. Soil erosion map showing the increase in soil

loss in Habu sub - catchment in year 2006 (B) and

compared to soil loss in year 1997 (A)

Figure 19. Soil erosion map showing the increase in soil

loss in Ringlet sub - catchment in year 2006 (D) as

compared to soil loss in year 1997 (C)

5.8 Conclusion

As a conclusion the increase in soil loss since 1997 is

observed at 18.5% over a period of 9 years. As more and

more area is developed it is clear that the landuse of both

Habu and Ringlet sub-catchment will change substantially

over the time frame leading to major soil erosion

problems. This substantial increase in erosion risk is in

agreement to the study by TNB Research study in 2004.

From this study using the RUSLE model, the annual

average annual soil loss rate of the Cameron Highlands

catchment was estimated at 282,465 m3/year for 1997 and

334,854 m3/year for 2006 The sediment yield for the

catchment was therefore computed to be 1564 m3/km

2/yr

or 15.64 tons/km2/yr for 1997 and increased 18.5 % to

1854 m3/km

2/yr or 18.54 tons/km

2/yr in 2006.

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Documents

Soil Erosion Modeling Using Ruscle and GIS at Cameron Highlands, Malaysia