沙漠研究 19-1, 287- 290 (2009 )Journal of Arid Land Studies“Desert Technology IX ”
Refereed Paper

Estimation of Soil Loss by Using Combination of Erosion Model and GIS-Case of Study Watersheds in TunisiaMohamed KEFI1, Kunihiko YOSHINO1, Khemaies ZAYANI2, Hiroko ISODA3
Abstract : Soil erosion due to water is a serious environmental problem. Its damage has
negative impacts not only on agriculture but also on economy. The purpose of this study is tocompare the estimation of soil loss due to soil erosion by water using GIS tools and UniversalSoil Loss Equation (USLE) as erosion model in three watersheds in Tunisia which havedifferent location, climate, land use and topography. USLE is a model to predict soil loss
from agricultural lands. It is based on rainfall pattern (R factor), soil type (K factor),
topography (LS factor), vegetation cover (C factor) and supporting practices (P factor). The
result of the research is that high potential soil loss area is an area with severe slope, poor
vegetation, sandy soil and no water and soil conservation practices. Therefore, thiscombination of USLE and GIS can be useful for decision makers to establish appropriate
strategies of soil and water conservation.
Keywords : GIS, Soil loss estimation, Tunisia, USLE

1. Introduction
Agriculture has a dominant role in the economy especially for developing countries. Because it has asubstantial economic impact, many countries have displayed important efforts to improve and to preserve
agriculture by protecting water and soil resources. But these resources are threatened by erosion phenomena.
This problem is defined as a process consisting of detachment and transport of soil particles by erosive agents
such as flowing water and wind. Due to its damage, soil erosion is a major environmental threat to thesustainability and productive capacity of agriculture and consequently to the economy of developing anddeveloped countries (Pimentel et al., 1995).
Because of its serious impact, many researchers have worked in this specific field using computer
technology and models to assess and predict the soil loss caused by water erosion. Thus, the emergence ofvarious models which differ by complexity such as Universal Soil Loss Equation (USLE) (Wischmeier andSmith, 1978) or Revised Universal Soil Loss Equation (RUSLE) (Renard et al., 1997). Despite theconsiderable number of erosion model, USLE is widely accepted and is considered as the most used to predict
soil loss.
In order to increase the accuracy of erosion assessment and to predict the spatial location and intensity ofdegradation, many researchers combined USLE model, Remote Sensing technique and Geographic
Information System (GIS) (Fistikoglu and Harmancioglu, 2002), (Mati et al., 2001). In recent studies, someresearchers have applied the remote sensing techniques to evaluate the soil loss by using USLE where the C
factor is estimated by Perpendicular Vegetation Index (Yoshino and Ishioka, 2005).
In addition to the researchers’ efforts and in order to protect their natural resources, many countries,
mainly those threatened by this environmental problem, have adopted different strategies such as Tunisia
where about 3 million ha are threatened by erosion with 50% seriously affected. For this reason, Tunisia has
adopted two strategies - the first during the period ranging from 1990 to 2001 and the second between 2002
and 2011- whose main objective is to protect and to preserve soil and reduce erosion effects (DG/ACTA,2002). Table 1 shows the main realizations of the first strategy and the prevision of the second.
Therefore, this research aims at comparing the estimation of soil loss due to soil erosion by water using
GIS tools and USLE as erosion model in three watersheds in Tunisia which differ by climate, land use andtopography. Then, we are going to predict the effects of soil and water conservation practices on thereduction of soil loss using a specific scenario.
1Graduate School of Systems and Information Engineering, Department of Social Systems and Management,
University of Tsukuba, Japan. E-mail : moh_kefi@yahoo.fr
2Borj Cedria Higher Institute of Environmental Sciences and Technologies, Tunisia
3Alliance for Research on North Africa (ARENA), Graduate School of Life and Environmental Sciences, Universityof Tsukuba, Japan

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Table 1. Realization and prevision of the Tunisian Strategies.

Erosion Control measures
Watershed management (ha)(contour ridges, Bench terracing,…)
Cereal areas protection (ha)Maintenance (ha)Spreading and Refill works ( unit)
Hills dams (unit)

First Strategy Realizations
892 573
70 494338 496
3 556
580

Second Strategy Prevision
700 000
100 000
700 000
4 500
500(DG/ACTA, 2002)

2. Materials and Methods
2.1. Study area
The survey was conducted in three different watersheds which are located in different prefectures inTunisia. Batta watershed is situated in Siliana between 36˚2.648' to 36˚5.048' N latitude and 9˚33.519' to9˚35.007' E longitude. The area of this watershed is about 961 ha which is mainly covered by rangeland
and agriculture land suitable for cereal. The annual average rainfall is around 495 mm. The watershed iscomposed of different soil types as vertisol and rendzina. Boulabouz watershed is located in Zaghouan
between 36˚14.404' to 36˚16.9' N latitude and 10˚10.833' to 10˚10.868' E longitude. Its area is about 1435
ha. Around 80% of the basin is covered by rangeland. The annual average rainfall is about 365 mm. The
soil is rich of lithosols and regosols. For Koukat watershed, it is situated in Kairouan between 35˚49.218'
to 35˚52.676' N latitude and 9˚43.916' to 9˚45.908' E longitude. The total area is about 3210 ha which is
totally covered by forest and rangeland. The annual average rainfall is about 348 mm. The soil type isdominated by lithosols, regosols and rendzina.
2.2. Methodology
USLE model is to predict soil loss from agricultural lands due to rill and sheet erosion and it is basedon rainfall pattern, soil type, topography, land use and land management practices (Wischmeier and Smith,1978). It is composed of 5 factors and can be written as
A = R x K x C x LS x P(1)
A is the annual loss (Ton/ha/year). R represents the rainfall erosivity factor (MJ.mm/ ha.Hr.year). K
is the erodibility factor (Ton.ha.hr/ha.MJ.mm). C is the crop management factor. P is the supporting
practice factor and LS is the slope length and Slope inclination factor. C,P and LS are dimensionless.
Different data is used to obtain these factors. R factor was derived from rainfall data of General
Directorate of Water Resource in Tunisia. Taking account of FAO soil classification and by using soil mapof Tunisia and some informations of the study areas, we analyzed the K factor. C factor and P factor areobtained by using Landsat 7 ETM+ data and aerial photos of the study area and supplemented by someobservations in the field. Finally, LS factor is analyzed by using a Digital Elevation Model "DEM" with90 meter resolution developed by NASA. By using all required data and Arcview 3.2, we will be able toobtain all factors’ layer at first and then, the amount of soil loss in the three watersheds.
2.2.1. Rainfall Erosivity factor (R factor)
This factor represents the erosive potential of rainfall. To obtain this factor, the following relationship(Arnoldus, 1980), which is based on monthly and the annual rainfall data, is used.
12R=Pi 2Pi =1∑(2)

Where Pi is the monthly rainfall (mm) and P is the annual rainfall (mm).
2.2.2. Soil Erodibility factor (K factor)
K factor represents the susceptibility of soil to erosion. It is calculated using the following
relationship (Wischmeier and Smith, 1978), which is a combination of soil’s texture, organic matter,structure and permeability.
(3)
K = 2.8 x 10-7 x (12 - OM) x M1.14 + 4.3 x 10-3 x (s - 2) + 3.3 x 10-3 x (p - 3)
Where K is the soil erodibility factor. OM is the percent of organic matter content. p is the soilpermeability code. s is the soil structure code. M is the particle size parameter and can be written such as289

M = (% silt + % very fine sand) x (100 - % clay)(4)
2.2.3. Crop Management factor (C factor)
C factor is used to reflect the effect of cropping on erosion rate. According to Cormary and Masson(1964), C value is attributed to each land use. Bare soil is 1, olive tree is 0.6, cereal is 0.4, rangeland is
0.15 and forest is 0.01.
2.2.4. Topographic factor (LS factor)
Topographic factor is a combination of two factors L and S where L is the slope length factor,
representing the effect of slope length on erosion and S is the slope steepness, representing the effect ofslope steepness on erosion.
LS factor can be estimated from the DEM and we have used a technique proposed by (Moore andBurch, 1986) which is based on flow accumulation and slope steepness. The equation is:

LS = (Flow Accumulation x cell size 22.13) 0.4 x (sin slop 0.0896)1.3(5)
2.2.5. Supporting Practice factor (P factor )According to Wischmeier and Smith (1978), the supporting practice factor P represents the water andsoil conservations practices or measures that control the erosion such as contour ridge and terrace. The
value of P factor depends on the soil management measures which are related to the slope of area. In
addition P value is attributed as 1 in area without erosion control practice, 0.11 in area with slope (0-5%),
0.12 with a slope (5-10%), 0.14 with a slope (10-20%) and 0.19 with a slope (20-30%).
3. Results and Discussions
The results obtained using USLE model are presented in Table 2 which shows the mean of soil loss
and all factors by watershed. The comparison between the three watersheds shows that Batta watershed
has the highest average of soil loss which is due essentially to a higher value of LS factor and R factor.
Besides, in this watershed, vegetation cover is scarce which is proved by the high value of C factor. Inaddition conservation practices are low for this reason P value is almost 1 which indicates no erosion
control practice founded. Even for Boulabouz watershed, it has also an average of a quite important soil
loss which is caused especially by these factors LS, C and P. However, Koukat watershed has the lowest
mean of soil loss because LS factor is low and a large part of the watershed is covered by forest which is a
substantive factor in intercepting rainfall hence declining the effect of erosion. Furthermore, P factor value
is lower than the other watersheds. It means that soil and water conservation practices are more
accomplished there. For K factor, it is almost the same for the three watersheds with a value ranging from0.06 to 0.08 ton.ha.hr/ha.MJ.mm which is recognized as a high soil erodibility (Foster et al., 1981).
According to the result mentioned in Table 2, the highest soil loss amount occurs where the slope andthe rainfall are important. That’s why, soil loss variation is mainly due to a high value of two factors, Rand LS. The higher they are, the more soil loss is detected. But, C and P factors have a positive impact on
the preservation of soil as they reduce the effects of soil erosion by water. Therefore, high potential soil
loss can occur particularly in areas with steep slope, poor vegetation, sandy soil, which is easy to be
detached, and no water and soil conservation practices.
In order to examine the impact of soil and water conservation practices, a specific scenario isproposed to assume the realization of about 5% of the watersheds by some conservation measures such as
contour ridges especially in steep areas. Therefore, only P factor will be altered.
Figure 1 shows the result of the assumed scenario. We can notice the decrease of soil loss in the three
Table 2. Estimation of soil loss and factors by watersheds.
Batta watershed
Boulabouz watershed
Soil Loss predicted(T/ha.year)
R factor
LS factor
C factor
K factor
P factor

Koukat watershed

16.75

5.18

0.39

90.40
10.95
0.30
0.06
0.94

64.00
7.25
0.20
0.06
0.93

65.40
2.31
0.04
0.08
0.81

29018
16

Soil loss (T/ha.year)

watersheds. It is quite clear that soil and water
conservation practices have a positive impact on
reducing erosion effects, the fact that has urged
Tunisia to follow this strategy which will be
more successful by combining erosion modeland GIS to determine the spatial location of highpotential soil loss. In addition, erosion effects
can be also reduced by increasing and preserving
the vegetation coverage specially forest.

14121086
4
20
Batta

Boulabouz

KoukatWatersheds

4. Conclusion
Current condition
ScenarioIn this study, we have used a simple
methodology to show that in a GIS environment
Fig. 1. Effect of conservation measures.
the USLE can be applied to determine soil loss
on a local scale. Moreover, soil loss can increase under the effect of LS and R factors but it can decrease
with the effect of C and P factors.
In addition and in order to prevent and to preserve soil and water resource against water erosion, it isrequired to follow these recommendations:- Vegetation coverage such as forest and rangeland should be preserved and increased- Conservation measures should be established especially in the steep slope lands- Farmers should be encouraged to adopt the techniques of Agriculture of conservation such as croprotation, fertilization and no-till farming.
- Planning appropriate measures by the integration of GIS and erosion model
Acknowledgement
The authors gratefully acknowledge the Grant-in-Aid for Scientific Research (A) No. 17255011 withtitle Investigation research on bio-resources in semi arid and arid area in North Africa for its support. We
also thank the CRDA (Regional Office of the Ministry of Agriculture) of Kairouan, Siliana and Zaghouan
and the General Directorate of Water Resources in Tunisia for their help and data providing. The authors
would also like to thank the two anonymous reviewers for their useful comments and suggestions.
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