Ecological Engineering 23 (2004) 327–339
Modeling of riparian vegetated buffer strip width and placement
A case study in Shei Pa National Park, Taiwan
Young-Fa Lina,b , Chao-Yuan Linc , Wen-Chieh Choud,∗ ,
Wen-Tzu Line , Jing-Shyan Tsaif , Cho-Fu Wub
a Shei Pa National Park Headquarters, Miaoli County 364, Taiwan
Institute of Construction Management, Chung Hua University, 707, Sec.2, Wu-Fu Rd., Hsinchu City 300, Taiwan
c Department of Soil and Water Conservation, National Chung Hsing University, 250, Kuo-Kuang Road, Taichung City 402, Taiwan
d Department of Civil Engineering, Chung Hua University, 707, Sec.2, Wu-Fu Rd., Hsinchu City 300, Taiwan
Graduate Institute of Environmental Planning and Design, Ming Dao University, 369 Wen-Hua Rd., Peetow, Changhua County 523, Taiwan
f Department of Landscape Architecture, Chung Hua University, 707, Sec.2, Wu-Fu Rd., Hsinchu City 300, Taiwan
b
e
Received 19 February 2004; received in revised form 1 November 2004; accepted 9 November 2004
Abstract
This study addressed the suitable width for riparian vegetated buffer strips (RVBS) using topographic analyses, attenuation
curves, and an index model. The Chi Chia Wang Stream is susceptible to pollution because of highly saturated hydraulic
conductivity and excessive fertilizer use in the nearby cultivated lands. The buffer strip widths calculated from a potassium
attenuation curve in the vegetable plot were the widest due to easy potassium movement in the soil. A potassium safety soil depth
of 8.81 m was calculated or estimated for the vegetable area. The buffer width derived from this safety depth is recommended
for maximum agricultural nonpoint source pollution (ANSP) prevention.
© 2004 Elsevier B.V. All rights reserved.
Keywords: Agricultural nonpoint source pollution; Geographical information system; Attenuation curves; Index model
1. Introduction
Vegetated buffer strips can offer pollutant buffering
and riverbank stabilization. They can effectively reduce
the nonpoint source pollution from agricultural lands
by using appropriate streamside vegetation and area
development. Pollutant buffering can control nonpoint
∗
Corresponding author.
E-mail address: [email protected] (W.-C. Chou).
0925-8574/$ – see front matter © 2004 Elsevier B.V. All rights reserved.
doi:10.1016/j.ecoleng.2004.11.006
source pollution, improve soil and water conservation,
and enhance biodiversity. The regulations governing riparian vegetated buffer strips (RVBS) have not yet been
established in Taiwan. To reduce or prevent river water
pollution from agricultural nonpoint sources, it is better
to establish standards for RVBS through experimental
results and modeling.
This study focused on the Wu Ling Farm area,
neighboring the Chi Chia Wang Stream in Shei Pa National Park in Taiwan. Combining field investigation,
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topographic analyses, and chemical simulations, we
sought the appropriate RVBS width to provide to
policy-making authorities for watershed management
and reduction of the agricultural impact on the downstream river and reservoir water quality.
Since 1961, Wu Ling Farm development projects
have utilized lands near the Chi Chia Wang Stream. The
slope of these lands is steep, which speeds runoff. Agricultural development of these slopes for fruit trees and
vegetables deeply impaired the habitat of land-locked
salmon (Oncorhynchus masou formosanus). Because
the profit for cultivation of fruit trees in this watershed
has declined significantly, farmers have converted the
orchards into vegetable fields. Vegetables are shortterm crops, normally with two to three harvests per
year. Soil tillage, weed removal, and pesticide and fertilizer use on vegetables are more intensive than for
orchards. Additionally, both rainfall and drought season irrigation accelerate fertilizer transport through the
soil.
RVBS are gaining recognition and playing more important roles in land conservation polices. In cooperation between Taiwan’s Council of Agriculture and the
USDA, research on RVBS is one of the top priority
topics. RVBS are natural or planted vegetation areas
located between potential pollution sources and surface water bodies. Major purposes of this vegetation
are reductions in overland runoff, sediments, nutrients,
and pesticides.
Din and Chen (1979) suggested that 10-m buffer
strips would be enough for short-term effectiveness
on undissolved pesticides (chlordimeform) in Taiwan.
For soluble pesticides, the vegetated area should be
expanded to 30 m. Sometimes 60 m of vegetation is
needed for adequate results. Based on the Liu Kuei
experimental forest, Hsia et al. (1990) suggested that
for forest lands in Southern Taiwan, or similar areas,
the buffer width required for the sediment delivery
distance from road construction can be calculated as:
F = 10 + 0.03s2 , where F is the buffer strip width in
meters and s represents the slope in degrees.
Numerous studies have indicated that vegetated
buffer strips are one of the most effective management
strategies, especially for nonpoint source pollution control (Dillaha et al., 1989; Leeds-Harrison et al., 1999;
Dosskey, 2002; Qin, 2003). Several models have been
developed to simulate the effectiveness of vegetated
buffer strips. Williams and Nicks (1988) selected small-
scale plots around the United States and evaluated the
soil erosion, sediment, and nutrient transportation control effects from vegetated buffer strips using Chemicals, Runoff and Erosion from Agricultural Management Systems (CREAMS). Lee et al. (1989) developed a mathematical model called GRAss-Phosphorus
(GRAPH) to analyze runoff and phosphate transport
in grass buffer strips under a single storm. Hayes and
Dillaha (1992) proposed an effectiveness evaluation for
grass buffer strips in controlling runoff and sediment resistance using the WEPP model (Laflen et al., 1991) and
GRASSF model (Hayes and Hairston, 1983). Xiang
(1996) combined a geographical information system
(GIS) and pollutant detention equation to delineate vegetated buffers. To display the topographic attributes, the
mathematical model combining application GIS technology is best in evaluating the width and placement
of vegetated buffers.
The effectiveness of vegetated buffer strips is dependent on the vegetation species, buffer strips width,
placement, slope, and rainfall patterns. If the width of
the vegetated buffer strips is not sufficient, it will not attain the desired effectiveness. Conversely, if the width
is too great, it will cause agricultural land waste, preventing farmers’ interest in cooperating with environmental preservation efforts. For the above reasons, it is
important to set a reasonable width range when implementing slope conservation plans. In the U.S., Section
319 of the Clear Water Act of 1987 requires the States to
identify and submit best management practices (BMPs)
for USEPA approval to help control nonpoint pollution
sources. However, the improvement in water quality
from buffer strips as a BMP method cannot be predicted. Ironically, farmers complain that inappropriate
regulatory buffer strip widths decrease the amount of
productive land, while environmental scientists argue
that the width in the current regulations is not enough to
control undesirable drainage water quality in farming
watersheds (Puvis et al., 1989).
2. Methods
2.1. Study area
Wu Ling Farm, altitude 1740–2100 m, area 7000 ha,
annual mean temperature around 15 ◦ C, is located in
the Chi Chia Wang Stream riverine area in Shei Pa
Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
329
The nutrient concentration in the 60–70 cm soil
depth from nearby the forestland was used as
the environmental background value. On-site measured attenuation curves of nutrients in the soil
layer were used to predict safety depth by regression analyses and to provide the calculation of
width and placement of vegetated buffer strips.
(2) Prediction by index model
The calculation processes by index model are:
1. Convection
The convection of soil moisture is sometimes called
Darcian flow. The solute convection quantity Jc is
directly proportional to the solute concentration:
Fig. 1. Study watershed in northern Taiwan.
National Park, Taiwan (Fig. 1). This farm is surrounded
by giant woods, natural beautiful scenery, and one
of the most popular summer resorts in Taiwan. The
Chung Chin white peach, Fuji apple, summer vegetables, white crow, and land-locked salmon (O. masou
formosanus) are the most famous representatives in
this area. They are called the “Wu Ling Five Treasures”.
The Chi Chia Wang stream meanders through the farmlands. The view is gorgeous.
2.2. Analysis procedures
2.2.1. Soil physiochemical analyses
Soil samples were collected from different soil
layers in representative land-use areas. After being airdried, crushed, and sieved with a #10 sieve, according to soil analysis methods (Klute, 1986; Page, 1982),
the following analyzed properties were measured: pH,
texture, conductivity, saturated hydraulic conductivity,
available phosphorus, exchangeable cations (K, Na,
Ca, Mg), extractable trace elements (Fe, Mn, Zn, Cu),
and soluble anions (Cl− , NO2 − , NO3 − , SO4 2− ).
2.2.2. Methods for modeling vegetated buffer
strips
Pollutants’ attenuation curve measured on-site and
calculated from index model were employed to predict
the width of RVBS in this study.
(1) Prediction by nutrient attenuation curves
Jc = qC
(1)
where Jc is the solute convection rate (M/TL2 ; M:
mass, T: time, L: length), q the flux (L/T), and C the
solute concentration (M/L3 ).
v̄ =
q
θ
(2)
where v̄ is the mean flow velocity (L/T), q the flux
(L/T), and θ the volumetric wetness (Vwater /Vsoil ; V
is the volume, describes the volume of water per
unit volume of soil and is usually expressed as a
percentage by volume).
Combining (1) and (2), Eq. (3) can be obtained as
Jc = v̄θC
(3)
2. Diffusion
According to Fick’s law, the diffusion rate is related
to the concentration gradient:
Jd = −D0
dC
dx
(4)
where Jd is the diffusion rate (M/FL2 ), D0 the diffusion coefficient (L2 /T), and dC/dx the concentration
gradient (M/L4 ).
Because the aqueous phase only occupies part of
the soil volume and soil pores are tortuous in shape,
the effective diffusion coefficient will be less than
diffusion coefficient. The equation can be written as
Ds = D0 θξ
(5)
where Ds is the effective diffuse coefficient (L2 /T),
θ the volumetric wetness, and ξ the tortuosity.
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Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
Eq. (4) for an unsaturated soil aqueous phase can be
written as
dC
Jd = −Ds (θ)
(6)
dx
3. Dispersion
The hydrodynamic dispersion equation is similar to
the diffusion equation. Dispersion coefficient has a
linear relationship to the mean flow velocity:
Dh = αv̄
(7)
where Dk is the dispersion coefficient (L2 /T), α the
experimental parameter (L), v̄ the mean flow velocity (L/T).
dC
Jβ = −Dh (v̄)
(8)
dx
where Jβ is the dispersion rate (M/FL2 ).
4. Transportation
Transportation (J) of solute includes, convection
(Jc ), diffusion (Jd ), and dispersion (Jβ ), three phenomena. Combining Eqs. (3), (6) and (8), Eq. (9)
can be obtained as
∂C
∂C
J = v̄θC − Ds (θ)
+ Dh (v̄)
(9)
∂x
∂x
Actually the diffusion and dispersion cannot be separated; therefore equation above can be written as
∂C
J = v̄θC − Dsh (θ, v̄)
(10)
∂x
where Dsh is the diffusion–dispersion coefficient.
The flux and concentration will vary according to
temporal or spatial differences that can be written
as
∂(Cθ)
∂J
=−
∂t
∂x
(11)
Combining Eqs. (10) and (11), Eq. (12) can be derived as
∂(Cθ)
∂(v̄θC)
∂
∂C
=−
+
Dsh
(12)
∂t
∂x
∂x
∂x
Normally, θ, v̄, and Dsh can be considered as constants in a steady flow.
∂C Dsh ∂2 C
∂C
= −v̄
+
∂t
∂x
θ ∂x2
(13)
5. Adsorption
Eq. (13) indicates the movement of solute is related
to convection, diffusion, and dispersion processes;
the solute have no reaction with soil particles. If part
of solute can be adsorbed by soil, it can be expressed
as
Dsh ∂2 C
∂C ρ ∂S
∂C
=
− v̄
−
2
∂t
θ ∂x
∂x
θ ∂t
(14)
where S is the adsorbed solute (M/L3 ) and ρ the bulk
density (M/L3 ).
This process can be illustrated by the Freundlich
isotherm adsorption equation:
S = kCN
(15)
where k and N are Freundlich constants. A further
differential equation can be obtained as
∂C
∂S
= kNCN−1
∂t
∂t
(16)
Substituting (16) into (14), Eq. (17) can be derived
as
Dsh ∂2 C
ρkNCN−1 ∂C
∂C
=
1+
− v̄
(17)
θ
∂t
θ ∂x2
∂x
1+
ρkNCN−1
= Rf
θ
(18)
where Rf is the retardation factor for Freundlich adsorption.
Substituting Eq. (18) into (17), Eq. (19) can be given
as
∂C
Dsh ∂2 C
v̄ ∂C
=
−
∂t
θRf ∂x2
Rf ∂x
(19)
6. Index model establishment
The index method employs attenuation and retardation as two indicators to simulate chemical transportation in soil. The assumed conditions are (1) in
a soil column with uniform properties, (2) chemical concentration varied only by differences of
soil depth, and (3) constant soil moisture, so the
diffusion–dispersion function can be neglected. Eq.
(19) can be written as
λC = −
v̄ ∂C
Rf ∂x
(20)
Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
331
where λ is the coefficient for the first-order degradation kinetics (1/T):
∂C
λRf
C
=−
v̄
∂x
After integral of Eq. (21),
λRf
C
= exp −
H
C0
v̄
(21)
(22)
where C0 is the concentration in the surface soil,
C the concentration reached the soil depth H, H the
depth (L), λ the λ = ln 2/t1/2 , and t1/2 the half-time.
2.2.3. Geographical information manipulation
Using by resolution 40 m × 40 m digital elevation
model from the Center for Space and Remote Sensing Research, National Central University, aerial photos from the Agriculture and Forest Aviation Measurement Institution, terrain module in WinGrid system,
and ArcView GIS software, after the regional topographic data processes, digital figure files of elevation
(Fig. 2), slope (Fig. 3), aspect (Fig. 4) were created.
Soil nutrient concentrations from nearby forestland as
background values, nutrient attenuation curves, and index model were employed to estimate the required selfpurified depth, safety depth, in representative plots of
different land-use patterns. Combining stream system,
slope direction, and elevation data, using stream central
line as datum, stream bank and channel bed difference
derived from the developed program in this study, if the
difference value is less than flood elevation plus soil
safety depth, it will need placement of buffer strips and
prohibition of utilization. Fig. 5 shows the schematic
diagram of riparian vegetated buffer strips concepts.
Fig. 2. Elevation distribution in the Chi Chia Wang Stream watershed.
Fig. 4. Aspect distribution in the Chi Chia Wang Stream watershed.
Fig. 3. Slope distribution in the Chi Chia Wang Stream watershed.
2.3. System architecture
Successful watershed modeling for nonpoint source
pollution control depends upon how the large input data
volume is managed and manipulated. The function used
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Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
Fig. 5. Schematic diagram of the riparian vegetative buffer strip placement.
to summarize and display the model results in a variety
of forms and presentation styles that requires highly
flexible data management. We developed the WinGrid
(Lin and Lin, 2000) analysis software to generate and
organize the input parameters required by the riparian
buffer strip calculations. In the WinGrid system, the basic data storage unit can be represented as a single layer
in a map that contains information about the location
features. The spatial information consists of digital elevation data and derived safety depth. Elevation, slope,
and aspect distributions were obtained from digital elevation model in the Terrain Module. Safety depth for
specific nonpoint pollutant was derived from the attenuation curves and index model in the Riparian Buffer
Strip Module (Fig. 6).
3. Results
The saturated hydraulic conductivity of soil profile in Wu Ling Farm vegetable area shows a logarithmic decrease from soil surface to subsurface (Fig. 7).
The saturated hydraulic conductivity of surface soil
layer is extremely high (>4000 mm/h). The direction that the nutrients move is closely related to the
moisture transportation, especially for soluble nutri-
ent salts. The groundwater pollution control for the
Chi Chia Wang Stream from the Wu Ling Farm agricultural development emphasizes soluble nutrient salt
control.
Table 1 shows the high nutrient concentrations in
the surface soil from the large quantity of fertilizers
applied in the vegetable area. Except for magnesium,
the other nutrients in the orchard show lower values
because of the less frequent fertilizer application. The
estimated safety soil depths for the analyzed nutrients
are listed in Tables 2 and 3. Among the analyzed nutrients, potassium reached the highest safety soil depth
at 8.81 m in the vegetable area. Calcium contained
the highest safety soil depth at 6.26 m in the orchard
area.
Safety soil depth can be predicted by using the nutrient attenuation curves and calculated using the index
model. Each salt’s λRf in the soil profile and its mean
value (Table 4) can be estimated in the vegetation area
from Table 1. Using each salt’s λRf mean value, the nutrient concentration (C) in a 60–70 cm from forest soil
depth, nutrient concentration (C0 ) from the top soil, and
the average hydraulic conductivity of each soil layer,
the safety soil depth (Table 5) for each nutrient can
be obtained. Comparing the attenuation curves and index model results, a deeper safety depth was obtained
Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
333
Fig. 6. Illustration of the WinGrid (Lin and Lin, 2000) system for processing riparian buffer strip modeling.
Fig. 7. Saturated hydraulic conductivity of soils sampled from the
vegetable plot.
from the attenuation curve calculations. To ensure the
pollution control effects, the suggested safety depth
would be obtained from the attenuation curve simulations. Another study focused on 46 kinds of selected
pesticides in the same area (Lin et al., 2002). The safety
depth obtained from the index model was established
successfully.
Fig. 8 shows the Chi Chia Wang Stream riparian
vegetated buffer strips placement in the vegetable area
estimated by using the safety depth from the potassium
attenuation curve in vegetable area with topographic
analysis. When overlapping the vegetated buffer strip
placement and aerial photos (Fig. 9), the darker area
in the aerial photo is forestland. Fig. 9 shows that the
width of vegetated buffer strip is not wide enough due to
agricultural activity (lighter area) along the streamside.
In areas with inadequate vegetated buffer strips, on-site
334
Table 1
Nutrient distribution in the soil profile at the sampling-sties
Sampling
depth (cm)
pH
Vegetable
0–5
5–10
10–15
15–30
30–45
45–60
60–75
75–100
Orchard
Forestry
EC
(mmho/cm)
Available P
(ppm)
Exchangeable
K
(ppm)
Na
(ppm)
Ca
(ppm)
Mg
(ppm)
Fe
(ppm)
Mn
(ppm)
Zn
(ppm)
Cu
(ppm)
Cl−
(ppm)
NO2 −
(ppm)
NO3 −
(ppm)
SO4 2−
(ppm)
7.20
7.39
7.43
7.57
6.67
6.78
6.41
5.99
22.38
13.86
10.97
4.92
2.47
0.99
1.43
0.85
991
510
420
411
435
169
44
33
5743
1048
949
739
872
783
717
552
14969
5705
4963
7928
2016
2115
1793
1670
8414
8414
8414
8414
2982
2194
1555
954
254
257
250
266
103
56
32
26
41
21
19
23
83
73
35
39
118
110
92
67
45
37
28
23
46
41
38
41
28
13
4
7
2.5
2.5
2.2
3.0
4.0
4.0
3.3
2.7
1179
1086
612
183
95
62
82
17
708
621
286
T
T
T
T
T
301
1374
2248
1550
584
275
373
130
4480
529
504
174
105
39
95
74
0–5
5–15
15–30
30–60
60–70
6.48
6.61
6.49
6.56
6.56
0.37
0.15
0.13
0.11
0.10
54
80
55
47
25
228
102
141
75
60
505
613
592
505
122
3145
1057
982
808
584
641
260
227
160
171
14
22
17
17
12
71
31
24
28
12
13
6
3
5
2
2.1
1.1
0.9
1.5
0.7
27
25
25
22
18
T
T
T
T
T
59
16
14
T
T
23
23
13
18
12
0–5
5–15
15–30
30–60
60–70
6.10
5.51
5.07
4.96
4.79
0.17
0.15
0.11
0.17
0.21
8
6
9
10
7
186
149
141
142
156
733
483
429
603
537
158
163
170
165
198
243
224
243
252
281
15
13
15
15
16
17
13
17
14
19
3
3
2
2
3
1.1
1.1
1.5
1.1
1.3
32
24
46
41
34
T
T
T
T
T
T
T
T
T
T
T: trace amount < 0.01 ppm.
Extractable
Soluble
23
T
15
11
11
Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
Site
Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
335
Table 2
Safety depth for each nutrient in the vegetation area
Item
Nutrient attenuation equations in
soil layers of vegetable area
r
Concentration (ppm) of
soil depth 60–70 cm from
forest land
Safety depth (m) in
vegetable area
EC
[EC] = 26.778 − 6.294 ln D
−0.981**
0.21 (mmho/cm)
0.68
Available
P
ln[P] = 6.835 − 0.038D
−0.951***
7.00
1.29
Exchangeable
K
Na
Ca
Mg
ln[K] = 8.508 − 0.510 ln D
ln[Na] = 10.143 − 0.613 ln D
ln[Ca] = 9.288 − 0.028D
ln[Mg] = 5.841 − 0.032D
−0.857**
−0.918**
−0.977***
−0.972***
156.00
537.00
198.00
281.00
8.81
5.40
6.26
1.43
Extractable
Fe
Mn
Zn
Cu
ln[Fe] = 3.331 + 0.007D
ln[Mn] = 4.743 − 0.020D
[Zn] = 46.331 − 0.526D
ln[Cu] = 0.747 + 0.1091 ln D
0.407
−0.983***
−0.956***
0.597
15.80
18.80
2.80
1.33
–a
0.90
0.83
–a
Soluble
Cl
NO2
NO3
SO4
ln[Cl] = 6.896 − 0.047D
[NO2 ] = 914.828 − 299.419 ln D
ln[NO3 ] = 7.177 − 0.023D
ln[SO4 ] = 9.079 − 1.183 ln D
−0.949***
−0.925**
−0.705**
−0.954***
33.70
0.01
0.01
11.00
0.72
0.21
6.12
2.84
a
∗∗
∗∗∗
Related coefficients too low to estimate.
1% significance level.
0.1% significance level.
0k + 300, 0k + 400, and 0k + 450 in this 600 m creek
segment (Fig. 10). Vegetated buffer strips need to be
placed between the A and B sections of the Chi Chia
Wang Stream as illustrated in Fig. 11.
samples were collected and analyzed for every 50 m
along river course from the forestland (S) to the front
of the buffer strips (E). The obtained results are listed
in Table 6. Pollution sites can be observed at 0k + 200,
Table 3
Safety depth for each nutrient in the orchard
Item
Nutrient attenuation equations in
soil layers of vegetable area
r
Concentration (ppm) of
soil depth 60–70 cm from
forest land
Safety depth (m) in
vegetable area
EC
ln[EC] = −0.769 − 0.393 ln D
−0.963**
0.21 (mmho/cm)
0.07
Available
P
ln[P] = 4.602 − 0.015D
−0.838
7.00
1.77
Exchangeable
K
Na
Ca
Mg
[K] = 255.975 − 47.345 ln D
[Na] = 644.745 − 6.334 ln D
ln[Ca] = 8.347 − 0.475 ln D
ln[Mg] = 6.732 − 0.421 ln D
−0.903*
−0.765
−0.959**
−0.969**
156.00
537.00
198.00
281.00
0.02
0.17
6.26
0.13
Extractable
Fe
Mn
Zn
Cu
ln[Fe] = 2.910 − 0.005D
[Mn] = 78.850 − 16.043 ln D
[Zn] = 14.177 − 2.943 ln D
[Cu] = 2.199 − 0.319 ln D
−0.501
−0.922*
−0.922*
−0.738
15.80
18.80
2.80
1.33
0.30
0.42
0.48
0.15
Soluble
Cl
NO3
SO4
[Cl] = 27.296 − 0.142D
ln[NO3 ] = 3.918 − 00072D
[SO4 ] = 26.594 − 3.096 ln D
−0.964**
−0.960**
−0.773
33.70
0.01
11.00
0.00
0.54
1.54
∗
∗∗
5% significance level.
1% significance level.
336
Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
Fig. 8. Riparian vegetated buffer strip (RVBS) layout along the Chi Chia Wang Stream.
Fig. 9. RVBS overlap placement with aerial photo (pixel size: 40 m × 40 m).
Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
337
Table 4
Variation of λRf for each nutrient in soil depth
Soil depth (cm)
P
K
Na
Ca
Mg
Fe
Mn
Zn
Cu
Cl
NO2
NO3
SO4
2.5–7.5
7.5–12.5
12.5–22.5
22.5–37.5
37.5–52.5
52.5–67.5
67.5–87.5
49.99
12.57
0.523
−0.69
7.3
6.629
0.594
128.9
6.44
6.04
−2
0.83
0.434
0.54
73.07
9.05
−11.3
16.59
−0.37
0.814
0.147
0
0
0
12.57
2.37
1.696
1
−0.89
1.79
−1.49
11.5
4.71
2.76
0.429
50.68
6.49
−4.61
−15.5
0.992
3.62
−0.22
5.318
11.60
7.65
4.824
1.512
1.37
0.406
8.717
4.934
−7.49
−3.48
0
0.948
0.415
0
8.3
−7.49
−3.48
0
0.948
0.415
6.224
37.24
29.16
7.94
3.29
−1.37
3.25
9.87
50.22
247.7
0
0
0
0
−115
−32
8.98
11.83
5.82
−1.5
2.17
162
3.14
25.68
6.12
7.65
−4.38
0.516
Mean value
6.24
8.67
3.17
3.32
3.35
−0.74
−0.74
8.49
32.67
−4.23
6.54
0.84
14.51
Fig. 10. Area marked by the circle shows insufficient RVBS placement width (pixel size: 40 m × 40 m).
Table 5
Safety depth derived from the attenuation curves and index model
Item
Safety depth (m)
Attenuation curve
Index model
Available
P
1.29
1.15
Exchangeable
K
Na
Ca
Mg
8.81
5.40
6.26
1.43
0.60
0.74
1.71
0.00
Extractable
Fe
Mn
Zn
Cu
–
0.90
0.83
–
1.62
0.79
1.24
0.00
Soluble
Cl
NO2
NO3
SO4
0.72
0.21
6.12
2.84
0.61
0.54
0.00
0.60
Fig. 11. Required RVBS width placement between the A and B sections of the Chi Chia Wang Stream.
338
Y.-F. Lin et al. / Ecological Engineering 23 (2004) 327–339
Table 6
Chemical properties of the soil sampled from a gully with an insufficient RVBS placement width
Sample
S(0k + 000)
0k + 050
0k + 100
0k + 150
0k + 200
0k + 250
0k + 300
0k + 350
0k + 400
0k + 450
0k + 500
0k + 550
E(0k + 600)
EC (s/cm)
100
100
86
105
373
155
385
189
290
317
183
99
118
pH
7.97
8.02
8.22
7.83
8.03
7.54
7.84
7.88
7.86
7.97
7.90
8.05
7.62
Available P (ppm)
11.63
9.29
15.25
11.30
171.30
10.43
29.34
14.30
232.70
225.40
13.89
10.68
7.25
Exchangeable
Extractable
K
(ppm)
Na
(ppm)
Ca
(ppm)
Mg
(ppm)
Fe
(ppm)
Mn
(ppm)
Zn
(ppm)
Cu
(ppm)
115
68
34
78
269
87
420
88
238
292
107
46
73
191
102
57
126
420
130
540
133
420
460
167
74
106
327
357
615
503
1205
352
923
744
1128
2100
641
452
515
83
83
108
97
115
71
226
138
163
132
90
83
84
113
93
75
82
109
88
98
105
157
61
216
98
111
34
37
44
42
76
29
81
58
118
149
57
36
48
3.54
3.46
3.64
4.85
13.71
4.14
9.43
5.71
13.71
34.29
4.66
4.44
4.93
1.54
1.32
1.54
1.43
3.08
1.21
2.31
1.65
5.60
3.08
2.53
1.43
1.65
4. Discussion and conclusions
Sediment, nutrients, pesticides, and other nonpoint
source pollutants from slope land agricultural activities
are the major reasons for the worsening water quality.
Vegetated buffer strips provide several functions such
as pollutant buffering, stream bank stabilization, and
conservation. Buffer strips can effectively prevent nonpoint pollution from slope land agriculture. The major
soil pattern in Taiwan mountain areas is sandy or rocky
soil mixed with shale or gravels exhibiting a high percentage of coarse pores. Agricultural nonpoint source
pollution control and pollutant removal from infiltrated
water from areas with high infiltration capacity occurs
primarily through self-purification, i.e. soil adsorption,
biological fixation, biodegradation, and chemical reactions. Maintaining proper soil depth in high infiltration
areas is important to ensure soil self-purification and
avoid groundwater pollution.
Comparing the attenuation curves and index model
analyses, a deeper safety depth was obtained from the
attenuation curve calculations. To ensure the pollution
control effects, the suggested safety depth is better obtained from the attenuation curve simulations. Among
the analyzed nutrients, potassium exhibited the highest safety soil depth value of 8.81 m in the vegetable
area from nutrient attenuation curve analyses. Because
potassium exhibits the fastest mobility among the analyzed nutrients, calculating the Chi Chia Wang Stream
riparian vegetated strip width using safety depth ob-
tained from the potassium attenuation rate is the best
approach. The placement and width of riparian buffer
strips designed for the potassium safety depth can effectively prevent other nutrient pollution. The obtained riparian vegetated buffer strip widths and placement can
be provided to the Shei Pa National Park Headquarters
as projects for best management practices.
In addition to vegetated buffer strip placement, we
should also provide grass ditches and agricultural detention tanks in the potential polluted agriculture areas in the watershed. Retaining sediment, nutrients,
and other nonpoint pollutants in agricultural lands is in
the spirit of sustainable agriculture. Prevention at the
source is more important than protection downstream.
This design concept should be utilized in planning vegetated buffer strip placement.
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