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© IWA Publishing 2015 Hydrology Research
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in press
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2015
A procedure for assessing the impacts of land-cover
change on soil erosion at basin scale
Chengguang Lai, Zhaoli Wang, Xiaohong Chen, Chong-Yu Xu, Bing Yang,
Qingqiang Meng and Bi Huang
ABSTRACT
Accelerated soil erosion is an undesirable process that adversely affects the conservation of water
and soil. This paper used a procedure linking the Revised Universal Soil Loss Equation (RUSLE) and
geographic information system (GIS) to map the soil erosion level from 1990 to 2010 caused by landcover change in the Dongjiang River basin, China. Results indicate that the significant land-cover
change greatly impacted soil erosion. The overall soil erosion level of the basin belonged to Level II
(mild erosion) but the erosion amount shown an uptrend. Erosion areas of Levels I and II occupied
more than 90% and other levels (Levels III–VI) occupied less than 10% of the total area. Approximately
90.85% of the area maintained the original levels, 5.84% converted from lower levels to higher levels,
and 3.32% converted from higher levels to lower levels. The erosion in the downstream regions was
more serious than that in the central and upstream regions. Although soil erosion was mild as a
whole in the study region, some local areas underwent intense erosion. The study demonstrated that
linking RUSLE with GIS tools is an efficient procedure for mapping soil erosion levels at basin scale.
The gradual deterioration condition caused by land-cover changes at present or in the future requires
further study.
Key words
| Dongjiang River basin, geographic information system, human activity, land-cover
change, Revised Universal Soil Loss Equation, soil erosion
Chengguang Lai
Xiaohong Chen (corresponding author)
Bing Yang
Center for Water Resource and Environment,
Sun Yat-Sen University, Guangzhou 510275,
China
and
Guangdong Engineering Technology Research
Center of Water Security Regulation and
Control for Southern China,
Guangzhou 510275,
China
E-mail: eescxh@mail.sysu.edu.cn
Zhaoli Wang
School of Civil and Transportation Engineering,
South China University of Technology,
Guangzhou 510641,
China
Chong-Yu Xu
State Key Laboratory of Water Resources and
Hydropower Engineering Science,
Wuhan University, Wuhan 430072,
China
and
Department of Geosciences,
University of Oslo, PO Box 1047,
Blindern N-0316 Oslo,
Norway
Qingqiang Meng
The Institute of Water Science Guangzhou,
Guangzhou 510220,
China
Bi Huang
School of Finance and Taxation and Public
Management,
Jiangxi University of Finance and Economics,
Nanchang 330013,
China
INTRODUCTION
Soil erosion is one of the most serious and global ecological
the ecological environment (Xin et al. ). Many methods
environmental crises in progress today (Renschler et al.
have been attempted to estimate soil erosion situations.
; Natalia et al. ). The problems that are caused by
Among these methods, soil erosion models, including
soil erosion include decreased soil fertility, increased land-
empirical models and physical models, are straightforward
contaminant
but effective tools. The first widely used empirical model,
diffusion, rocky desertification, and ecosystem disturbances,
Universal Soil Loss Equation (USLE), was developed in
all of which significantly impact human development
1965 based on numerous observational data and rainfall
(Syvitski et al. ; Jiang et al. ). The assessment of
simulation experiments (Wischmeier & Smith ). Lim-
soil erosion is critical, considering its significant impact on
ited by some deficiencies, USLE was continuously revised,
slide
activity,
doi: 10.2166/nh.2015.094
reservoir
sedimentation,
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leading to a new version named Revised Universal Soil Loss
Therefore, the main objectives of this study are: (1) to
Equation (RUSLE) in the 1990s (Renard & Ferreira ;
propose a modeling approach of soil erosion using
Renard et al. ). This new model can expediently evaluate
RUSLE and GIS tools and (2) to assess the soil erosion
the average annual soil erosion amount under different land-
situation in the Dongjiang River basin from 1990 to 2010.
cover conditions and predict the spatial heterogeneity of soil
The focal point of this study is to explore the spatial
erosion, providing a basis for soil conservation planning
dynamic changes of soil erosion caused by land-cover
(Tang et al. ). Although some physical models, such as
changes at basin scale. The proposed approach can expedi-
the Water Erosion Prediction Project (Foster & Lane
ently evaluate the spatial heterogeneity and dynamic
), the European Soil Erosion Model (Morgan et al.
changes of soil erosion. This study also provides methodo-
), the Limburg Soil Erosion Model (De Roo et al.
logical tools for soil conservation planning and soil erosion
), and the Soil Erosion Model for Mediterranean
prevention in the study area, which can be spread to simi-
regions (De Jong et al. ) have been proposed in recent
lar regions.
decades, their applications are presently limited due to
requirement of many parameters and complex calculation
process. Moreover, some data (e.g., temporally continuous
MATERIALS AND METHODS
rainfall data) are not available for many countries and
regions, making them difficult to promote. Benefitting
Study area and data
from the convenience in application and compatibility
with geographical information systems (GIS), the USLE
The Dongjiang River, a major tributary of the Pearl River,
and RUSLE models are still the most frequently used soil
China, is 562 km in length with a drainage area of approxi-
erosion models worldwide.
mately 27,000 km2, accounting for approximately 5.96% of
In this study, an integrated approach linking the RUSLE
the Pearl River basin (Figure 1). The Dongjiang River
model with GIS tools was used to assess the soil erosion at
basin has a subtropical climate, with a mean annual temp-
basin scale where human activities have altered the physical
erature of approximately 21 C. Front and typhoon-type
characteristics of the region. The Dongjiang River basin, an
rainfalls are predominant in the basin, and the annual rain-
economically advanced and densely populated area in
fall ranges from 1,500 to 2,400 mm (Liu et al. ). Large
China, chiefly comprises six cities: Ganzhou, Heyuan, Huiz-
seasonal variations in rainfall and runoff exist within the
hou, Dongguan, Guangzhou, and Shenzhen. The river is the
basin, with 80% of the annual rainfall and runoff occurring
primary water source for these cities as well as Hong Kong.
in the rainy season (from April to September). Being a typi-
In fact, the proportion of Dongjiang water in Hong Kong’s
cal hilly area in south China, the main soil type of the basin
annual water supply has steadily increased, from only
is red soil. The basin is divided into three regions according
8.3% in 1960 to approximately 70% or even slightly greater
to the economic levels for the sake of convenient analysis
than 80% in recent years ( Jiang et al. ). It will have huge
(Figure 1).
W
implications for economic development or even social stab-
Digital elevation model (DEM), daily precipitation data,
ility if the water sources were to be affected by long-term
soil type data, and land-cover data were used in this study.
pollution events (e.g., pollution caused by water and soil ero-
DEM data (SRTM30) were available from the CGIAR-CSI
sion). Moreover, the downstream region of the basin is the
SRTM 30 m Database (http://srtm.csi.cgiar.org). Daily pre-
most developed area in Guangdong Province (even in
cipitation data of 34 rainfall observation stations (Figure 1)
China) after years of development. However, this region is
from 1960 to 2010 were accessed from the Hydrology
currently facing severe ecological and environmental
Bureau of Guangdong Province (http://www.gdsw.gov.cn/
issues including soil erosion caused by tremendous changes
wcm/gdsw/index.html) and the China meteorological data
in land cover (Liu et al. ; Wu & Chen ; Liu et al.
sharing service system (http://www.escience.gov.cn/met-
). A systematic study of soil erosion in the basin is
data/page/index.html). Soil type data were obtained from
urgently needed.
the Food and Agriculture Organization of the United
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Figure 1
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Land-cover change on soil erosion
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Map of the Dongjiang River basin.
Nations (http://www.fao.org/home/en/). Land-cover data
et al. ). The RUSLE model is expressed as:
of three years (1990, 2000, and 2010) used for analysis in
this study were provided by the Resources and Environment
A¼R×K×L×S×C×P
(1)
Science Data Center of Chinese Academy of Sciences
data-processing
where A (t/(ha·year)) is the average soil erosion, R (MJ·mm/
tools included ArcGIS 9.3 and MS Excel. The slope length
(ha·h·year)) is the rainfall erosivity factor, K (t·ha·h/
and steepness factor were estimated from SRTM DEM
(MJ·ha·mm)) is the soil erodibility factor, L is the slope length
(30 m). All the above-mentioned data were converted to
factor, S is the slope steepness factor, C is the land cover and
the spatial resolution of 100 × 100 m, which means that
management practice factor, and P is the conservation support
(http://www.resdc.cn/Default.aspx).
The
the Dongjiang River basin consists of approximately three
practice factor. The values of L, S, C, and P are dimensionless.
million grids.
GIS is used to realize the process of data pre-processing, factor
calculating, and result outputting. For the estimation of soil erosion, the main procedure includes: (1) pre-process the data and
RUSLE model
convert them to grid format; (2) estimate the amount of soil erosion by RUSLE using the ‘raster calculator’ tool of GIS; (3)
The RUSLE model was used to assess soil erosion. This
generate the spatial distribution of soil erosion.
model considers not only the influence of precipitation,
soil, topography, and land cover, but also the management
Rainfall erosivity factor (R)
of water and soil conservation (Renard et al. ). This
model has been extensively applied to estimate soil erosion
The rainfall erosivity factor R, combining the effects of the
amount and risk (Angima et al. ; Xu et al. ; Tang
duration, magnitude, and intensity of rainfall events, can
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be used to measure the potential ability of rain to cause ero-
is calculated using the daily precipitation from 1960 to
sion. Yu & Rosewell (a) proposed a simple statistical
2010 for each meteorological station. This paper used the
regression equation between R and precipitation variables.
average annual erosivity value as the rainfall erosivity
The equation is based on average daily precipitation and
factor and it can be computed by accumulating the monthly
has been extensively used in many regions including some
rainfall erosivity. The rainfall erosivity factor data were
basins in China (Yu & Rosewell a; Yu 1998; Xu et al.
placed into the attribute database for a specific meteorologi-
; Zhang et al. ; Ma et al. ). The equation used
cal station and then converted into grid format by the
in this paper is described as:
Kriging spatial interpolation method.
^ j ¼ α[1 þ η cos (2πfj þ ω)]
E
N
X
Rβd when Rd > R0
(2)
Soil erodibility factor (K)
d¼1
The soil erodibility factor K is difficult to measure and is
^ j (MJ·mm/(hm2·h)) is the rainfall erosivity value for
where E
therefore generally calculated through analyzing soil tex-
the month j and it is a quantization value measuring the R
ture, organic matter, structure, and permeability (Maria
factor. Rd (mm) is the daily precipitation of the month j
et al. ). This paper used the modified equation that
with N days. R0 is the threshold precipitation amount,
was proposed by Williams in the Erosion-Productivity
which is fixed at 12.7 mm because storm events with less
Impact Calculator model (Williams et al. ) and it has
than 12.7 mm of rainfall amount are generally discarded in
been proved to be suitable for China (Hu et al. ). The
the R factor computations. The coefficient f is the frequency
equation can be expressed as:
of the cosine function and f ¼ 1/12 is recommended (Yu &
Rosewell a). The phase parameter ω is not particularly
sensitive and can be set to ω ¼ 5π=6. If the annual precipitation is more than 1,050 mm, the relationship between
parameters α and β can be written as in Equation (3); otherwise, the parameters α will be described as in Equation (4)
(Yu & Rosewell b). The relationship between parameter
η and the average annual precipitation can be written as in
Equation (5).
log α ¼ 2:11 1:57β
K ¼ {0:2 þ 0:3 exp [ 0:0256 San(1 Sil
Sil
)]} × (
)0:3
100
Cla þ Sil
× [1 0:25 Ca
]
Ca þ exp (3:72 2:95 Ca)
× [1 0:7 SN1
]
SN1 þ exp ( 5:51 þ 22:95 SN1 )
(6)
where San (%) is the sand content, Sil (%) is the silt content,
Cla (%) is the clay particle content, Ca (%) is the organic
when Ra > ¼ 1, 050 mm
n
o
α ¼ 0:395 1 þ 0:098[3:26(Sh =Ra )]
when Ra < 1, 050 mm
(3)
carbon content, and SN1 ¼ 1–San/100. Then the values of
the soil erodibility factor corresponding to soil type were calculated. As the unit of K factor calculated by Equation (6) is
(4)
a US unit (short ton·ac·h/(100ft·short ton·ac·in)), it needs to
be converted into an international unit (t·ha·h/(MJ·ha·mm))
by multiplying by 0.1317. Thereafter, soil erodibility factor
η ¼ 0:58 þ 0:25Ra =1000
data were placed into the attribute database of the soil
(5)
type map and then converted into grid format for further
analysis.
In Equation (3), the value range of β is 1.2 to 1.8 and β ¼
1.5 is used in this study according to previous researches in
similar regions of China (Yu & Rosewell a; Ma et al.
Slope length and steepness factor (L and S)
). In Equations (4) and (5), Sh (mm) is the precipitation
The slope length factor L and slope steepness factor S,
amount of the next half year, and Ra (mm) is the average
respectively, represent the effect of slope length and slope
annual precipitation. The rainfall erosivity of each mouth
gradient on erosion, and both reflect the effect of
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topography on erosion (Lu et al. ). Increases in slope
errors when using this equation (McCool et al. ). In
length and slope steepness can produce higher overland
response to this issue, the Chinese researchers Liu et al.
flow velocities and correspondingly higher erosion (Haan
(, ) proposed an equation for use in south China.
et al. 1994). Slope length has been broadly defined as the dis-
The equation is expressed as:
tance from the point of origin of overland flow to the point
where either the flow is concentrated in a defined channel
or the slope gradient decreases enough where deposition
begins. An empirical equation that was proposed by Wischmeier & Smith () is used to calculate the slope length
factor L in this paper and the equation is expressed as:
L ¼ (λ=22:1)m
S¼
8
<
10:8 sin θ þ 0:03 θ < 5
16:8 sin θ 0:5 5 θ < 10
:
21:9 sin θ 0:96 θ 10
W
W
W
(10)
W
where S is the slope steepness factor and θ (degree) is the
slope.
(7)
where 22.1(m) is the slope length of a standard plot, and λ
Both the factors of L and S were calculated using the
raster calculator tool of Arc.GIS 9.3 according to Equations
(7)–(10) and were merged as a LS factor.
(m) is the slope length of a horizontal projection. In fact,
the Chinese researchers Pan et al. () calculated the aver-
Land cover and management practice factor (C)
age λ value of the Dongjiang River basin (Table 1) which is
used in this paper. In Equation (7), m is the slope length
The land cover and management practice factor C is used to
index which depends on the ratio γ between rill erosion
reflect the effect of cropping and management practices on
and inter-rill erosion. Here m is computed by Equation (8)
soil erosion rates in agricultural lands, and the effects of veg-
(McCool et al. ).
etation canopy and ground covers on reducing the soil
erosion in forested regions (Renard et al. ). This factor
m ¼ γ=(1 þ γ)
(8)
considers the variability of the vegetation cover and
methods of land management, reflecting their protective
The ratio γ can be computed by Equation (9) based on
function to the topsoil (Xiao et al. ). The C factor is gen-
the slope θ (degree) if the soil sensibility between rill erosion
erally determined by the Normalized Difference Vegetation
and inter-rill erosion is the same (Foster et al. ).
Index (NDVI) (Maria et al. ; Chen et al. ) or land-
cover type (Xu et al. ; Pan & Wen ). NDVI tends
sin θ
=[3:0 × ( sin θ)0:8 þ 0:56]
0:0896
γ¼
(9)
to focus on the vegetation situation, but the land-cover
type considers more comprehensive terrestrial situations,
such as cultivated land, forest land, grassland, mudflat,
As the general equation for the slope steepness factor in
the RUSLE model was based on the US terrain, it may cause
urban land, construction land, bare land, and water body.
Therefore, this paper used the land-cover type to estimate
the C factor (Table 2) by referring to relevant studies in
Table 1
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Average slope length of different slope ranges in the Dongjiang River basin
south China. This paper mainly referred to the studies of
Chen et al. () and Lu et al. () as their study regions
Slope range (degree)
Average slope length of horizontal projection (m)
<10
155
10 ∼ 20
133
20 ∼ 30
97
30 ∼ 40
67
40 ∼ 50
33
50 ∼ 60
30
>60
10
were close to the Dongjiang River basin and had similar
natural conditions.
Support practice factor (P)
The support practice factor P (ranging from 0 to 1) is the
soil-loss ratio with a specific support practice to the corresponding soil erosion with upslope and downslope tillage
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Table 2
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for this paper. Then, the P factor values were assigned to
Land-cover type and C factor values of the Dongjiang River basin
Land-cover type
C factor
value
Paddy field
0.06
Low coverage
grassland
0.1
Nonirrigated
farmland
0.1
Mudflat
0.8
Closed forest land
0.003
Urban land
0.15
Shrubbery
0.005
Rural residential
area
0.2
Open forest land
0.01
Construction land
0.3
Garden plot
0.03
Bare land
1
High coverage
grassland
0.05
Water body
0
Moderate coverage
grassland
0.08
Land-cover type
|
C factor
value
the raster for further analysis.
RESULTS AND DISCUSSION
Land-cover change
The land-cover in the Dongjiang River basin was grouped to 15
types in this paper. Figure 2 and Table 4 show that the overall
land-cover composition has significantly changed from 1990
to 2010. Evidently, more dramatic changes occurred in the
downstream region than in the up- and midstream regions.
The paddy field, non-irrigated farmland, closed forest land,
shrubbery, open forest land, high coverage grassland, moderate coverage grassland, and rural residential areas have in
total decreased by 1,175.79 km2 in the past two decades.
(Renard et al. ). The P factor is set to 1 in the regions
Approximately 58.06% and 20.29% of these areas were,
without any soil and water conservation measures in general
respectively, converted into urban and construction lands.
and to 0 in the regions where water and soil erosion will not
The urban land rapidly increased from 191.22 km2 in 1990
occur. A lower P factor value indicates effective conserva-
to 873.92 km2 in 2010. Moreover, the construction land
tion practice at reducing soil erosion. In fact, an
increased from 64.07 to 302.62 km2, and the area of garden
authoritative and universal method to determine the P
plots increased from 1,134.17 to 1,353.53 km2 in the same
factor has not been found so far, making this factor an
time period. However, water body, low coverage grassland,
uncertain factor in the RUSLE model. This paper referred
mudflat, and bare land showed little change.
to the experimental method of Lu et al. () that considers
The land-cover variation related greatly to the increasing
both the land-cover type and the slope (Table 3). The study
regional economy. A large area of paddy field, forest land,
region of Lu et al. () was close to the Dongjiang River
and grassland was invaded by urban land, construction
basin and their results were based on the investigation of
land, and garden plots, especially in the downstream
soil and water conservation, providing a reliable reference
region. A typical example is that Shenzhen City used to be
a small fishing village in south Guangdong Province three
decades ago but now has become an overwhelming mega-
Table 3
|
Support practices factor values of the Dongjiang River basin
city, tremendously changing the original land cover. The
P factor
expansion of urban land displays rapid urbanization and
Land-cover type
Slope/%
value
intensive human activities, meaning that humans have also
Water body
/
0
changed the original ecosystem causing huge pressure on
Paddy field; Nonirrigated farmland;
Garden plot
0∼5
5 ∼ 10
10 ∼ 20
20 ∼ 30
30 ∼ 50
>50
0.11
0.12
0.14
0.19
0.25
0.33
water and soil conservation.
Closed forest land; Shrubbery; Open
forest land
0 ∼ 200
0.8
(2)–(5) based on daily precipitation data from the 34 rainfall
The rest
0 ∼ 200
1
Factor characteristics
The rainfall erosivity factor R was calculated by Equations
observation stations. The Kriging interpolation was used to
produce the spatial distribution map based on the annual
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Figure 2
Table 4
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Land-cover maps of the Dongjiang River basin in 1990, 2000, and 2010.
Structure and variation trend of land-cover in the Dongjiang River basin in 1990, 2000, and 2010
1990
Land-cover type
2000
Area (km2)
Ratio (%)
2010
Area (km2)
Ratio (%)
1990–2010
Area (km2)
Ratio (%)
Area (km2)
Ratio (%)
Water body
799.04
2.64
809.87
2.67
820.01
2.71
20.97
0.07
Paddy field
2,549.91
11.72
2,515.09
11.60
2,245.45
11.04
204.45
0.67
Nonirrigated farmland
Closed forest land
1,922.15
6.25
1,825.00
6.02
1,655.82
5.47
267.22
0.88
18,159.12
59.92
18,097.50
59.72
18,065.79
59.62
92.22
0.21
298.00
1.21
212.45
1.02
202.05
1.00
94.95
0.21
Open forest land
2,566.20
8.47
2,495.84
8.24
2,255.47
7.44
210.72
1.02
Garden plot
Shrubbery
1,124.17
2.74
1,217.76
4.02
1,252.52
4.47
219.26
0.72
High coverage grasslands
965.98
2.19
928.09
2.06
824.12
2.75
121.85
0.44
Moderate coverage grasslands
198.76
0.66
199.96
0.66
178.85
0.59
19.91
0.07
1.42
0.00
2.21
0.01
2.54
0.01
1.11
0.00
Low coverage grasslands
Mudflat
16.22
0.05
16.79
0.06
28.72
0.09
12.49
0.04
Urban land
191.21
0.62
280.99
1.26
872.92
2.88
682.70
2.25
Rural residential area
221.26
1.09
421.86
1.42
278.02
0.92
52.24
0.18
64.07
0.21
64.08
0.21
202.62
1.00
228.55
0.79
0.56
0.00
0.58
0.00
0.57
0.00
0.01
0.00
Construction land
Bare land
average rainfall erosivity values in each station. Figure 3(a)
average value of 6,822.78 MJ mm/(ha·h·year) and a Cv
indicates that the basin’s annual rainfall erosivity ranges
value of 0.1496. The abundant precipitation in the basin
from 5,225.89 to 10,844.2 MJ mm/(ha·h·year) with an
causes large rainfall erosivity values in general, indicating
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Figure 3
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Spatial distribution maps of rainfall erosivity, soil erodibility, and topography factor.
a high potential collapsing force to topsoil. The large value
There are 22 soil types in the Dongjiang River basin and
of Cv reveals the uneven spatial-temporal distribution. Rela-
the soil erodibility factor was calculated by Equation (6)
tively larger values of Cv are mainly distributed in the
based on the soil type data. The spatial distribution map of
southeast and the central west of the basin. Rainfall erosivity
soil erodibility (Figure 3(b)) and soil types in Table 5 show
in the downstream region is at the middle level and in the
that the main soil types include hydromorphic paddy soil,
upstream region at the lower level. From south to north,
pitted lateritic red soil, page latosolic red soil, pitted
the rainfall erosivity decreases overall. Both the values of
yellow soil, pitted red soil, pitted yellow-red soil, yellow-
the rainfall erosivity and their spatial distribution are con-
page soil, and red-page soil, which in total account for
sistent with that of Luo et al. ().
approximately 94.10% of all the soil types. The K factor
Table 5
|
Soil type and soil erodibility factor in the Dongjiang River basin
Serial
Area ratio
K factor
Serial
(%)
value
number
Soil type
Area ratio
K factor
(%)
value
number
Soil type
1
Alkaline purplish soils
0.19
0.416
12
Pitted yellow soil
2
Mountain shrubby meadow
soil
0.10
0.2221
12
Pitted red soil
2
Fluvo-aquic soil
0.47
0.2228
14
Acid skeletol soil
0.09
0.2568
4
Acid lithosol
0.10
0.2162
15
Yellow-page latosolic red
soil
0.24
0.2555
5
Acid purplish soils
0.79
0.2040
16
Pitted yellow-red soil
2.25
0.2491
6
Hydromorphic paddy soil
17.26
0.2016
17
Bleached paddy soil
0.25
0.2485
7
Pitted lateritic red soil
16.21
0.2988
18
Eroded latosolic red soil
0.28
0.2458
8
Volcanic soils
0.07
0.2958
19
Yellow-page soil
9
Ergogenic paddy soil
0.68
0.2812
20
Red-page soil
10
Lateritic red soil
0.69
0.2704
21
11
Page latosolic red soil
20.44
0.2664
22
2.77
0.2657
17.25
0.2590
4.20
0.2255
12.42
0.2195
Eroded red soil
0.01
0.2116
Reservoir
1.74
0
Note: The soil type under the reservoir was undetected and the K factor value was set to 0; the unit of K factor is (short ton·ac·h/(100 ft·short ton·ac·in)), which is a US unit.
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value ranges from 0.2216 to 0.416 and the average value is
soil erosion can be regarded as the result of the three natural
0.2652 with a Cv of 0.1696. The soil erodibility factor
factors. Assuming no cover and management practices or
values in the basin are overall relatively small, indicating
support practices, the C and P factors were set to 1 and
that the topsoil in the Dongjiang River basin has some
potential annual soil erosion could be computed using the
anti-erosion ability. An overall lower K factor was found in
following simplified equation (Tang et al. ):
the north as compared to that in the southern region of
the basin.
A¼R×K×L×S
(11)
The slope length factor (L) and the steepness factor (S)
were merged as a topography factor (LS) in this paper.
The spatial distribution map of potential soil erosion
The LS factor value ranges from 0 to 29.4, with an average
was then produced using the GIS technique. Figure 5
value of 8.86. However, the Cv reached 0.8691, suggesting
shows that the potential annual soil erosion ranges from 0
that spatial topography variation is considerable in this
to
hilly basin. Figure 3(c) shows that the lower values are
2,070.25 t/(ha·year), suggesting that rain-wash without
mainly distributed in the downstream regions and the
restraint will cause a large amount of soil erosion. Relatively
higher values are mainly in the western part of the basin.
larger values are mainly distributed in the southeast and the
An overall higher LS factor was found in the north than in
central west due to large rainfall erosivity and relatively
the southern region.
large values of LS factor. However, the upstream and the
12,227.2 t/(ha·year),
with
an
average
value
of
The land cover and management practice factor (C) and
downstream regions are at lower levels. Although the
support practice factor (P) were determined based on the
values of the LS factor are large in the upstream, the rainfall
land covers. The distribution of these factors is closely
erosivity values in the upstream regions are obviously smal-
related to the distribution characteristics of land cover in
ler than in other regions, causing the R factor to play a
the basin. For the C factor, the average values, reflecting
dominant role in weakening the potential annual soil ero-
the level of land cover and management practice of the
sion. However, the values of the LS factor are relatively
basin, were respectively 0.0235, 0.0247, and 0.0278 in
small in the downstream regions, causing the LS factor to
1990, 2000, and 2010, which show an increasing trend.
dominate the potential annual soil erosion with lower
The quite low values indicate that many management prac-
levels. The potential annual soil erosion is unevenly distrib-
tices have been taken to guard against soil erosion but the
uted in space in general, which can be reflected by a high Cv
uptrend indicates that these practices remain to be gradually
value of 0.9158. The spatial distribution map can identify the
increased and strengthened. For the P factor, the average
potentially high-risk erosion areas, which can provide a
values that reflect the level of support practice of the basin
reference for the human actions in the basin. For example,
are 0.6440, 0.6467, and 0.6551 in 1990, 2000, and 2010,
agricultural activities, deforestation, and mining explora-
respectively, which also shows an increasing trend.
tions should take various measures to prevent water and
Although many support practices have been taken to pre-
soil erosion in the potential high-risk erosion areas.
vent the erosion, the quite large values indicate that these
practices need to be improved. Figure 4 shows the spatial
distribution maps of both the C factor and P factor.
Soil erosion assessment
Potential annual soil erosion
As the potential annual soil erosion does not consider social
Rainfall erosivity, soil erodibility, and topographic factor are
based on geographical and geological environment con-
three natural factors determining the erosion process in the
ditions but cannot reflect the actual situation of erosion in
RUSLE model. The land cover and management practice
the Dongjiang River basin. A large value of potential soil
and support practice factors are the social factors that are
erosion does not mean severe erosion will actually occur.
greatly impacted by human actions. The potential annual
For example, an appropriate irrigation system and soil
factors, it only reflects the rainfall erosion vulnerability
Uncorrected Proof
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Figure 4
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Spatial distributions of land cover and management practice factor (C) and support practice factor (P) in 1990, 2000, and 2010.
management practices can greatly reduce soil erosion,
R, soil erodibility factor K, slope length factor L, steepness
demonstrating that these human actions are capable of redu-
factor S, cover and management practice factor C, and sup-
cing the potential effect to a certain extent. Human activities
port practice factor K, have all been calculated, the soil
can be reflected by the land cover as displayed by the C and
erosion amount was calculated by Equation (1). The calcu-
K factor in the RUSLE model. The land-cover types of 1990,
lation results show that the soil erosion amounts ranges
2000, and 2010 were selected and the influence of human
are 0 to 4,265.72, 0 to 4,265.72, and 0 to 4,999.69 t/(ha·year)
activity was mainly focused on the dynamic changes of the
in 1990, 2000, and 2010, respectively. The results were then
land-cover type. As the six factors – rainfall erosivity factor
classified into six levels according to the Standards for
Uncorrected Proof
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most of the areas belong to Level I and Level II. Areas of
Levels III–VI are sparse and scattered across the basin.
Table 6 shows that the areas of Levels I and II occupy,
respectively, 92.9%, 92.4% and 91.15%, while the other
levels only occupy 7.10%, 7.60%, and 8.85% in total in
1990, 2000, and 2010, respectively. The areas of Level I
decrease but Levels II–VI increase slightly in general. The
overall soil erosion situation in the Dongjiang River basin
is considered to be not severe since 1990. However, some
local areas, such as the western Huiyang, face a critical situation of soil erosion. The study of Pan et al. () indicated
that the annual average soil erosion is 18.73 t/(ha·year) in
2009 while our study is 15.31 t/(ha·year) in 2010. This difference is partly because their study region included the
Zengcheng River basin which occupies 3,160 km2 and the
average level of soil erosion in the Zengcheng River basin
is higher than that of our study areas. Therefore, the soil erosion situation between the two studies would be basically
the same excluding this small basin.
For different regions, the characteristic values of soil
erosion are shown in Table 7. Evidently, the annual average
value increases from upstream to downstream, suggesting
that the soil erosion in the downstream region is more
severe than that in the upstream region. In addition, the
mean values increased from 1990 to 2010 among the
three regions, including the whole basin. From upstream
Figure 5
|
Spatial distribution of potential soil erosion in the Dongjiang River basin.
to downstream, the soil erosion situation becomes more
serious from a space perspective. Meanwhile, erosion has
Classification and Gradation of Soil Erosion (SL 190–2007)
slightly increased in the past two decades from a time
published by the Ministry of Water Resources of the
perspective.
People’s Republic of China in (). The classification stan-
To analyze the change in the soil erosion levels, a con-
dards, with a unit of t/(ha·year), were set as follows: Level I
version map was produced and is shown in Figure 7.
(tiny erosion), A < 5; Level II (mild erosion), 5≦A < 25;
According to the statistics in Table 8, approximately
Level III (moderate erosion), 25≦A < 50; Level IV (intense
27,516 km2 (90.85%) maintained the original levels but
erosion), 50≦A < 80; Level V (more intense), 80≦A < 150;
approximately 2,771 km2 (9.15%) changed, of which
and Level VI (extreme intense), A ≧ 150. The higher the
approximately 1,767 km2 (5.84%) was converted from
level is, the greater soil erosion will be.
lower levels to higher levels, but approximately 1,004 km2
For the entire basin, the annual average soil erosion in
(3.32%) was converted from higher levels to lower levels.
1990, 2000, and 2010 is, respectively, 12.63, 13.08, and
The above assessment and analysis indicate that the
15.31 t/(ha·year), all belonging to Level II, suggesting that
overall soil erosion situation in the Dongjiang River basin
the soil erosion situation was mild on the whole in the
was not severe since 1990 as most of the areas belong to
past two decades. However, the Cv values respectively
Level I and Level II. This is because, first, the Dongjiang
reached 3.13, 3.10, and 3.75, suggesting that quite notable
River basin is located in the subtropical zones of south
spatial variation exists in the basin. Figure 6 shows that
China. Abundant rain, warm temperature, and fertile land
Uncorrected Proof
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C. Lai et al.
Figure 6
Table 6
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Land-cover change on soil erosion
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Spatial distribution of soil erosion in 1990, 2000, and 2010 in the Dongjiang River basin.
Areas and ratios of different levels of soil erosion
Level I
Level II
Level III
Level IV
Level V
Level VI
Year
Area (km2)
Ratio (%)
Area (km2)
Ratio (%)
Area (km2)
Ratio (%)
Area (km2)
Ratio (%)
Area (km2)
Ratio (%)
Area (km2)
Ratio (%)
1990
14,289.30
47.18
13,849.30
45.72
1,061.88
3.51
337.73
1.12
319.47
1.05
430.75
1.42
2000
14,053.78
46.40
13,934.13
46.00
1,142.16
3.77
370.30
1.22
339.60
1.12
448.46
1.48
2010
13,701.14
45.24
13,905.98
45.91
1,322.78
4.37
438.38
1.45
392.89
1.30
526.61
1.74
Table 7
|
Characteristic values of soil erosion in different regions and years
Upstream
Midstream
Downstream
The entire basin
Year
Mean
Cv
Mean
Cv
Mean
Cv
Mean
Cv
1990
11.26
2.68
12.70
3.29
17.92
3.18
12.63
3.13
2000
11.27
2.70
12.64
3.28
23.48
2.76
13.08
3.10
2010
11.82
3.07
14.43
4.10
35.66
2.85
15.31
3.75
result in lush vegetation throughout the basin (Liu et al.
second-class protection zones were set up to protect the
). Even if destroyed, the vegetation will quickly repair
water sources (DRBA ). Unreasonable human activities
itself under the favorable environment. The self-healing fea-
in these zones, such as draining sewage, building factories,
ture of the vegetation is a necessity for conserving soil and
farming and grazing, have been under great restrictions, tre-
water in the destructive and vulnerable areas. Second,
mendously improving the resistance to water and soil
numerous protection measures have been taken in the
erosion. In view of the serious soil erosion problems in
last two decades. For example, 45 first-class and 41
some local areas, a large number of measures have been
Uncorrected Proof
13
C. Lai et al.
Figure 7
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Land-cover change on soil erosion
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2015
Conversion map of soil erosion in the Dongjiang River basin. (The Roman numeral on the left of ‘ → ’ represents the previous soil erosion level, while that on the right represents
the later soil erosion level.
adopted by the Guangdong government, such as engineer-
process that adversely affects the conservation of water
ing measures, biological measures, and agrotechnical
and soil. Second, the different intensity of human activities
measures. The engineering measures mainly included build-
resulted in a great regional difference in the erosion degree
ing small reservoirs, planting shelter forests, and building
across the basin. For example, the annual average value of
terraced fields in the potential erosion areas. The biological
the downstream regions reached 35.66 t/(ha·year) (Level
measures, such as afforestation and conversion of farmland
III, moderate erosion) in 2010, but only 11.82 and
to forest or grass, were included in the ecologically vulner-
14.43 t/(ha·year) (Level II, mild erosion) in the up- and mid-
able areas. Agrotechnical measures, such as sprinkler
stream regions. Some downstream areas, such as the
irrigation, plastic film mulching, rotation tillage, and inter-
western Huiyang, face a particularly serious erosion pro-
planting, were taken in the cultivation areas. These
blem and some erosion sites even reached 4,999.69 t/
measures can effectively reduce water and soil loss. There-
(ha·year)(Level VI, extreme intense erosion). Finally, the
fore, both natural and human factors are applied to the
pressure for water and soil conservation will be greater in
mild erosion in the Dongjiang River basin on the whole.
the future due to the continuous and strengthening human
Even so, the soil erosion situation requires more atten-
activities. The cities in the mid- and downstream regions
tion. First, the increased annual average values, areas of
are presently eager to develop the economy, which may
higher levels (Levels IV–VI), and areas that were converted
lead to more intensive land-cover changes. Similarly, the
from lower levels to higher levels indicate accelerated soil
upstream regions will also face much more pressure by a
erosion from 1990 to 2010. Despite taking many measures,
developing economy in the future, posing great challenges
the rapid expansion of urban areas occupying a large
to the basin’s soil and water conservation. Therefore, the
amount of paddy fields, grasslands, and forestlands has
soil erosion situation requires attention at present and in
greatly changed the characteristics of the original soil eco-
the future. Given the important economic and political
system conditions, causing an accelerated soil erosion
status in Guangdong Province, successful and efficient
Uncorrected Proof
14
Table 8
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CONCLUSION
Statistics of soil erosion change from 1990 to 2010
Conversion
Area (km2)
Ratio (%)
No change
13,079.79
43.19
I → II
760.52
2.51
I → III
210.84
0.70
I → IV
103.73
0.34
I→V
79.27
0.26
I → VI
54.29
0.18
II → I
526.68
1.74
12,805.00
42.28
II → III
290.04
0.96
II → IV
66.38
0.22
II → V
50.99
0.17
impacted soil erosion and the erosion amount increased
II → VI
109.66
0.36
on the whole from 1990 to 2010 and the erosion in the
III → I
46.84
0.15
downstream region is more serious than that in the
III → II
196.16
0.65
mid- and upstream region.
No change
790.04
2.61
III → IV
7.97
0.03
approximately 92.9%, 92.4%, and 91.15% in 1990, 2000,
III → V
7.75
0.03
and 2010, respectively, while the other high levels of ero-
III → VI
13.13
0.04
sion occupied less than 10% in the study region. The
IV → I
24.44
0.08
overall soil erosion situation in the Dongjiang River
IV → II
42.24
0.14
basin is mild but extreme intense erosion occurs in
IV → III
11.01
0.04
some local areas.
252.13
0.83
IV → V
1.87
0.01
inal levels of erosion, but 9.15% changed. Among the
IV → VI
6.03
0.02
changed areas, 5.84% converted from lower levels to
V→I
16.68
0.06
higher levels and 3.32% converted from higher levels to
V → II
38.30
0.13
lower levels.
V → III
5.27
0.02
The gradual deterioration condition caused by land-
V → IV
4.73
0.02
cover changes at present or in the future requires more
249.81
0.82
attention. These results are important in terms of soil conser-
V → VI
4.68
0.02
vation planning and prevention, the reduction of water and
VI → I
6.26
0.02
soil erosion, and other applications in the region, while the
VI → II
63.47
0.21
procedure is worth applying in other regions.
VI → III
15.58
0.05
VI → IV
3.43
0.01
VI → V
3.19
0.01
338.81
1.12
The study proposed an approach that links RUSLE and GIS
No change
No change
No change
No change
Note: The Roman numeral on the left of ‘ → ’ represents the soil erosion level in 1990,
while that on the right represents the level in 2010.
tools to assess and map soil erosion at basin scale. The procedure was applied on the Dongjiang River basin (south
China) where human activities have altered physical characteristics of the basin. The following conclusions are drawn
from the study:
•
•
•
•
The procedure linking RUSLE and GIS tools was found
to be an efficient approach to assessing and mapping
soil erosion on basin scale.
Land-cover change in the Dongjiang River basin greatly
The total areas of Levels I and II (mild erosion) occupied
Approximately 90.85% of the areas maintained the orig-
ACKNOWLEDGEMENT
The research is financially supported by the National Natural
Science Foundation of China (Grant No.51210013, 51479216,
conservation measures are thus still highly imperative to
51579105), the water science and technology program of
safeguard water and soil resources in the Dongjiang River
Guangzhou (Grant No. GZSWKJXM2012-02), the Public
basin.
Welfare Project of Ministry of Water Resources (Grant
Uncorrected Proof
15
C. Lai et al.
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Land-cover change on soil erosion
No.201201094, 201301002-02, 201301071), the project for
Creative Research from Guangdong Water Resources
Department (Grant No. 2011-11). The authors greatly
appreciate the reviewers and the editors for their critical
comments that greatly helped in improving the quality of this
paper.
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