effectiveness assessment of soil erosion critical source areas for soil and water conservation

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BioOne sees sustainable scholarly publishing as an inherently collaborative enterprise connecting authors, nonprofit publishers, academic institutions, research libraries, and research funders in the common goal of maximizing access to critical research. Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation Author(s): Chen Lajiao , Zhu Axing , Qin Chengzhi and Liu Junzhi Source: Journal of Resources and Ecology, 3(2):138-143. 2012. Published By: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences DOI: http://dx.doi.org/10.5814/j.issn.1674-764x.2012.02.005 URL: http://www.bioone.org/doi/full/10.5814/j.issn.1674-764x.2012.02.005 BioOne (www.bioone.org ) is a nonprofit, online aggregation of core research in the biological, ecological, and environmental sciences. BioOne provides a sustainable online platform for over 170 journals and books published by nonprofit societies, associations, museums, institutions, and presses. Your use of this PDF, the BioOne Web site, and all posted and associated content indicates your acceptance of BioOne’s Terms of Use, available at www.bioone.org/page/terms_of_use . Usage of BioOne content is strictly limited to personal, educational, and non-commercial use. Commercial inquiries or rights and permissions requests should be directed to the individual publisher as copyright holder.

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Page 1: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation

BioOne sees sustainable scholarly publishing as an inherently collaborative enterprise connecting authors, nonprofit publishers, academic institutions,research libraries, and research funders in the common goal of maximizing access to critical research.

Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil andWater ConservationAuthor(s): Chen Lajiao , Zhu Axing , Qin Chengzhi and Liu JunzhiSource: Journal of Resources and Ecology, 3(2):138-143. 2012.Published By: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy ofSciencesDOI: http://dx.doi.org/10.5814/j.issn.1674-764x.2012.02.005URL: http://www.bioone.org/doi/full/10.5814/j.issn.1674-764x.2012.02.005

BioOne (www.bioone.org) is a nonprofit, online aggregation of core research in the biological, ecological,and environmental sciences. BioOne provides a sustainable online platform for over 170 journals and bookspublished by nonprofit societies, associations, museums, institutions, and presses.

Your use of this PDF, the BioOne Web site, and all posted and associated content indicates your acceptance ofBioOne’s Terms of Use, available at www.bioone.org/page/terms_of_use.

Usage of BioOne content is strictly limited to personal, educational, and non-commercial use. Commercialinquiries or rights and permissions requests should be directed to the individual publisher as copyright holder.

Page 2: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation

J. Resour. Ecol. 2012 3 (2) 138-143

DOI:10.5814/j.issn.1674-764x.2012.02.005

www.jorae.cn

June, 2012 Journal of Resources and Ecology Vol.3 No.2

Received: 2012-01-20 Accepted: 2012-02-20Foundation: the Knowledge Innovation Program, Chinese Academy of Sciences (KZCX2-YW-442), National Basic Research

Program of China (2007CB407207) and National Natural Science Foundation (40971236). * Corresponding author: ZHU Axing. Email: [email protected].

1 IntroductionSoil erosion shows high spatial variability with a few small areas contributing disproportionate high amount of

et al. 2003).

soil erosion, are referred as critical source areas (CSAs).

(White et al. 2009; Strauss et al. 2007; Gitau et al. 2004; Pionke et al. 2000; Sivertun et al. 1998). Conservation

practice targeting on CSAs can improve water quality most.

of conservation practices is a key issue in site-specific watershed management.

In recent years physically based distributed models such as ANSWERS (Bouraoui and Dillaha 2000; Bhuyan et al.2002), AGNPS (Hassen et al et al.1998), have been applied to evaluate the spatial distribution of sediment yield and to indentify CSAs. Among these

a robust interdisciplinary watershed modeling tool for

Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation

CHEN Lajiao1, 2, ZHU Axing1*, QIN Chengzhi1 and LIU Junzhi1,2

1 State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China2 Graduate University of Chinese Academy of Sciences, Beijing 100049, China

Abstract: Critical source areas (CSAs), characterized by severe soil erosion and high sediment yield, are

considered to have a high priority for conservation. How to identify CSAs and assess the effectiveness

of conservation practices is a key issue in site-specific watershed management. The Soil and Water

Assessment Tool (SWAT) model is a useful tool for site-specific conservation practices design and

several studies have attempted to identify CSAs based on watershed models. However, limited research

has reported about the effectiveness of conservation practices targeting CSAs. The aim of this study

was to assess the effectiveness of conservation pracrices targeted on CSAs using the SWAT model.

CSA was firstly identified based on the 4-year average yearly erosion of each HRU. Appropriate soil

conservation practices were then designed for the CSAs. A scenario with conservation practices for

the whole watershed was also established as the contrasting counter parts scheme and then compared

to the outcome of CSA-targeted conservation pracrices. The result shows that SWAT can accurately

simulate sediment yield in the study area. CSAs were mainly located in slope farmland areas and steep

gullies, coinciding with the distribution of land use and slope. The identified CSA covered 20% of the

HRUs and contributed on average 44% of sediment yield. Conservation practices targeting CSAs had

higher sediment reduction effectiveness (24 115 t km-2 y-1) than conservation practice covering the

whole watershed (20 290 t km-2 y-1). Thus conservation practices targeting CSAs are more effective than

broad conservation practices. We conclude that soil conservation practices focusing on CSAs do increase

sediment reduction effectiveness. Targeting the placement of soil conservation practices based on the

CSAs concept will assist water quality control in watersheds.

Key words: effectiveness assessment; critical source areas; SWAT; HRUs; soil conservation practice

Page 3: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation

CHEN Lajiao, et al.: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation 139

watershed management plan development (Gassman et al.

yield and is widely used to assess the effect of conservation practices on water resources. Furthermore, the model offers the greatest number of management alternatives for agricultural watersheds (Arabi et al. 2008). Many soil conservation projects such as CEAP (Conservation Effects Assessment Project) funded by the USDA and the WEBs project (Watershed Evaluation of Beneficial Management

watershed soil conservation practices and water quality research (Srinivasan et al. 2005; Gassman et al. 2007).

(Busteed et al. 2009; Ouyang et al. 2008; White et al. 2009; et al. 2003). However, few studies have reported

the effectiveness of conservation practices directed towards CSAs.

model. CSA was firstly identified based on the 4-year average yearly erosion of each HRU. Appropriate soil conservation practices were then designed for the CSAs. A scenario with conservation practices for the whole watershed was also established as the contrasting counter parts scheme and then compared to the outcome of CSA-targeted conservation pracrices.

2 Study area and model description2.1 Study area and data

whole area is 0.2 km2 and the annual temperature is 9 .Annual precipitation is 505.7 mm. Precipitation occurs mainly in summer, from May to September which accounts for 80.6% of annual precipitation. Soils in this area are mainly Loess soil with Red clay soil in the valley.

watershed of the Loess Plateau for severe soil erosion. With no soil conservation practices the area remains in a nature

physical state. Characterized by high mountains and steep slopes, the watershed is crisscrossed by gullies and ravines with an average slope of 31° (Fig.2a). Approximately 58% of the watershed is under intensive cultivation, and the rest of the watershed is steep ravines not suitable for agriculture or remaining barren land (Fig. 2b). Agricultural activities have led to serious soil erosion.

digital elevation model (DEM), soil type map and land use maps of 1968 were provided by the Environmental and Ecological Science Data Center for West China. Soil properties were obtained from the Chinese Soil Database of the Institute of Soil Science, and land use properties were

Climate data included precipitation, daily data of maximum and minimum temperature, humidity and wind speed. Precipitation data was from measured data in the Yangdaogou watershed, and Lishi weather station near Yangdaogou watershed collected by the China Meteorological Administration.

the basin outlet were used for calibration and validation and obtained from experimental data of stream flow and sediment from the Institute of Shanxi Soil, and conservation research conducted in Shanxi province.

2.2 Description of SWAT model

scale model that predicts the long-term impact of land management practices on water, sediment and agricultural yield (Arnold et al. 1998; Gassman et al. 2007). It is

erosion, crop growth, weather, agricultural management

the watershed into sub-basins based on the number of tributaries. Each sub-basin is then further disaggregated

Fig. 1 Location of the study area. Fig. 2 Slope (a) and land use (b) of the study area.

N

Wangjiagou

DEM (m)

0

8848

N N

0500 1000 2000km

0 0.5 1 2km

Yangdaogou

DEM (m)

0

3450 50 100 200

m

DEM (m)

55

218

River

0 50 100 150m

0

60.9

25

N

0 50 100 150m25

Farmland

N

Barren landSlope Farmland

(a) (b)

Page 4: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation

Journal of Resources and Ecology Vol.3 No.2, 2012140

into Hydrological Response Units (HRUs), considered homogeneous in terms of land use and soil, as the basic modeling unit. Surface runoff and sediment is calculated for each HRU, and then added to channels and routed to the outlet.

Surface runoff is estimated for each HRU by the Soil Conservation Service Curve Number (SCS-CN) method as follows:

2day a

surfday a

R IQ

R I S(1)

where Qsurf is the accumulated runoff or rainfall excess (mm H2O); Rday is the rainfall depth for the day (mm H2O);Ia is the initial abstractions and includes surface storage,

2O); S is the retention parameter (mm H2O), which varies spatially due to changes in soils, land use, management practices and slope and temporally due to changes in soil water content.

100025.4( 10)S

CN(2)

where CN is the curve number for a day, which depends on the hydrologic soil group of HRU.

Erosion and sediment yield are calculated for each HRU

equation eliminates the need for delivery ratios and allows

MUSLE equation improves sediment yield prediction as it takes into consideration actual runoff generation and soil erosion processes to some degree which makes it suitable

0.56

11.8 ( )sed surf peak hru USLE

USLE USLE USLE

Y Q q area K

C P LS CFRG(3)

where Ysed is the sediment yield on a given day (metric tons); Qsurf is the surface runoff volume (mm H2O ha-1); qpeak is the peak runoff rate (m3 s-1); areahru is the area of HRU (ha); KUSLE is the USLE soil erodibility factor (0.013 t m2 h m-3 t-1 cm-1); CUSLE is USLE cover and management factor; PUSLE is the USLE support practice factor; LSUSLE is the USLE topographic factor; CFRG is the coarse fragment factor.

3 Methodology

and calibrate the model using the observed daily stream flow and sediment data. Once the model is calibrated and verified, it is applied to identify of CSAs based on the spatial sediment yield. Soil conservation scenarios are then designed targeting CSAs and the effectiveness of the practices are evaluated.

3.1 Simulation of sediment yield based on SWAT

Value was set to 0.35 ha for digital stream extraction and the watershed was then disaggregated into 28 sub-

for HRUs definition below which to be underestimated of land use, soil and slope were all set to 0% so that each different combination of soil and land use type was

HRUs. Parameters for each HRU such as soil evaporation compensation factor (ESCO), plant uptake compensation factor (EPCO), curve number (CN2) and available water capacity (AWC) were set according to land use and soil data.

Model validation was conducted by evaluating the

method (N-S coefficient) (Nash and Sutcliffe 1970) was

2

1

2

1

1

N

i i

i

N

i i

i

observed predicted

Ens

observed observed

(4)

where observedi and predictedi are the daily observed values and simulated values; observed is the average observed value; N is the number of days in the simulation time series.

CSAs could be captured, we adopted HRU-level sediment yield to identify CSAs.

load, above which a HRU was categorized as a CSA. Such threshold highly depends on the characteristics of a given watershed. White et al. (2009) suggested that an appropriate threshold should be defined by ranking each discrete unit within a watershed based on the predicted sediment yield and regarding the highest ranking fraction as the value of the threshold. In this study, CSAs were defined by firstly ranking HRUs in terms of average annual sediment yield.

Table 1 Input data for SWAT model.

Data type Data description/propertiesDigital elevation model with a grid size of 5m×5m

Soil Soil type and soil physical properties including texture, saturated conductivity, etc. with a grid size of 5m×5m

Land useClimate data

Page 5: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation

CHEN Lajiao, et al.: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation 141

Second, a cumulative sediment yield curve of the watershed was generated which illustrated the relationship of the

highest ranking fraction of HRUs was defined as CSAs. Multiple threshold values (i.e., 10% or 20%) could be used

3.3 Assessment of the effectiveness of conservation practices targeting CSAs

conservation practices were established according to slope position and slope degree at certain sites based on early

according to slope position and slope degree characteristics. In order to evaluate the effectiveness of the conservation practices targeting CSAs, a scenario with conservation practices applied to the whole watershed was established

modeling.

4 Results and discussion

and 0.89 for sediment yield. Simulated daily stream flow and sediment were plotted against observed values (Figs. 3 and 4). Most of the points were distributed along the 1:1 line. Such results indicated good agreement between the observed values and simulated results. One point that

heavily deviated from the 1:1 line is due to an extremely heavy storm in 1969 which the model failed to simulate well.

Spatial simulation results of average 4-year sediment yields at the HRU scale are shown in Fig. 5. By comparing to land use (Fig. 2a) and slope (Fig. 2b), we found that the spatial distribution of simulation results coincides with the distribution of land use and slope. Sediment yield was

comes from slope farm land and barren land mainly located in the gully. As slope farmland and gully barren land are the main source of soil erosion in the Loess Plateau, the spatial distribution of the simulation result captures the spatial variation in sediment yield and therefore are applicable to

HRUs were ranked in terms of 4-year average annual

corresponding accumulative sediment yield were calculated

HRUs covered 10% of the watershed area and contributed on average 30% of sediment yield with a slope of 3.0, and the top 30% HRUs contributed on average 58% of

increasing contributing area, the cumulative sediment yield increased slowly, with a decreasing slope of the curve.

about 78% of sediment yield with a slope of 1.56, and the accumulative contributing area of 70% contributed 90% of

Table 2 Conservation practices design according to slope and landform position.

Original land cover Designed conversation practicesUp-slope of Loess hills (slope <15°) Farm landDown-slope of Loess hills (15°<slope<25°) Slope Farmland Contour hedgerowDown-slope of Loess hills (slope>25°) Slope Farmland GrassGully slope Barren land ShrubGully bottom Farmland Arbor forest

Fig. 4 Simulated sediment yield vs observed sediment yield.

3 s-1)

3 s-1)

0 0.1 0.15 0.20.050

0.1

0.15

0.2

0.05

1:1 line

Sim

ulate

d se

dim

ent y

ield

(t)

Observed sediment yield (t)

0 4000 6000 800020000

4000

6000

8000

2000

1:1 line

10000 12000

10000

12000

Page 6: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation

Journal of Resources and Ecology Vol.3 No.2, 2012142

indicates that targeting top ranking HRUs has the potential to be more effective because they generate a greater sediment yield for treatment and control.

6. Compared with land use (Fig. 2a) and the slope map (Fig. 2b), we found that steep gullies and cultivated areas with high slopes were primarily targeted as CSAs. HRUs in the valley plain with flat terrain were not identified as

is reasonable in this study area because slop farmland with intensive agricultural activity and the gully area of little vegetation cover are prone to soil erosion and are the main sources of sediment.

4.3 Effectiveness of conservation practices targeting CSAs

Conservation practices scenarios applied to CSAs and the whole watershed were established according to section

reduction effectiveness of the two scenarios was examined

CSAs which only cover 20% of the watershed area had higher sediment reduction effectiveness which reduced 24 025 t km-2 y-1 sediment. Conservation practices covering the whole watershed had lower sediment reduction

effectiveness which reduced 202 90 t km-2 y-1 sediment. Conservation practices targeting CSAs are more effective than broad conservation practices. We conclude that soil conservation practices focusing on CSAs can increase the effectiveness of sediment reduction strategies and the placement of soil conservation practices based on the CSAs concept will assisting water quality control in watersheds.

5 Conclusions

of sediment reduction of targeting CSAs. CSAs were defined with a contribution area threshold of top 20%. Appropriate conservation practices targeting CSAs and the whole watershed were established and their sediment

cumulative sediment yield curve illustrates a steep slope by small portion of contributing watershed area, and a decreasing slope with increasing watershed contribution

Contributing watershed area (%) Contributed sediment yield (%)10 3020 4430 5840 7050 7860 8470 90

Conservation practices Sediment reduction effectiveness(t km-2 y-1)

Covering whole watershed 20 29024 025

Fig. 7 Designed conservation practices.

Fig. 5 Predicted sediment yield distribution of the study area.

source areas of the study area.

FarmlandBarren landSlopfarmland

Arbor forestShrub

N

Conservation practices

(a) Conservation practice targeting CSAs

N

Arbor foreatShrub

Contour hedgerowGrass

Conservation practices

(b) Conservation practice covering whole watershed

CSAs

0 50 100 150m25

N

0-10 00010 000-20 00020 000-30 00030 000-40 00040 000-54 188

N

0 50 100 150m25

Sedimentyield

Contour hedgerowGrass

Page 7: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation

CHEN Lajiao, et al.: Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation 143

area. Such a trend indicates that targeting top ranking contribution areas has the potential to be more effective because these areas generate a greater sediment yield to

contributed on average 44% of sediment yield. Conservation practices targeting CSAs are more effective than undirected conservation practice. We conclude that soil conservation practices focusing on CSAs can increase sediment reduction

practices based on the CSA concept will assist water quality control in watersheds.

ReferencesArnold J G, R Srinivasan, R S Muttiah. 1998. Large area hydrologic

modeling and assessment. Part I: Model development. Journal of the American Water Resources Association, 34: 73-89.

Arabi M, Frankenberger J R, Engel B A, et al. 2008. Representation of Hydrological Processes,

22(16): 3042-3055.Bhuyan S, P K Kalita, K A Janssen. 2002. Soil loss predictions with three

erosion simulation models. Environmental Modelling & Software, 17: 135-144.

planning model. Journal of Environment Engineering, 126(11): 1045-1055.

Busteed P R, D E Storm, M J White, et alCritical Source Sediment and Phosphorus Areas in the Wister Lake Basin, USA. American Journal of Environmental Sciences, 5 (2): 156-163.

Drungil C C, M S Srinivasan, et al. 2002. Variable-Source-Area Controls on

Journal of Soil and Water Conservation, 57(6): 534-543.Gassman P W, M R Reyes, C H Green, et al

research directions. Transaction of ASABE, 50: 1211-1250.

placement for cost-effective pollution reduction. Transaction of ASABE,47: 1923-1931.

Hassen M, Y Fekadu, Z Gete. 2004. Validation of agricultural non-point source (AGNPS) pollution model in Kori watershed, South Wollo, Ethiopia. International Journal of Applied Earth Observation and Geoinformation, 6: 97-109.

Nash J E, J V Sutcliffe. 1970. Riverflow forecasting through conceptual models. Journal of Hydrology, 10(3): 282-290.

Ouyang W, H F Hao, X L Wang. 2008. Regional Nonpoint Source Organic

Environmental Management. Water Air Soil Pollution, 187: 251-261.Pionke H B, W J Gburek, A N Sharpley. 2000. Critical source area controls

on water quality in an agricultural watershed located in the Chesapeake basin. Ecological Engineering, 14: 325-335.

Sivertun A, L E Reinelt, R Castensson. 1998. A GIS method to aid in non-point source critical area analysis. International Journal of Geographical Information Science. 2: 365-378.

et al. 2005. Watershed scale modeling of critical source areas of runoff generation and phosphorus transport. Journal of American Water Resources Association, 41: 361-377.

Strauss P, A Leone, M N Ripa, et al. 2007. Using critical source areas for targeting cost-effective best management practices to mitigate phosphorus and sediment transfer at the watershed scale. Soil Use and Management,23 (Suppl. 1): 144-153.

prioritization of critical sub-watersheds for soil conservation management Biosystems Engineering, 85: 365-379.

White M J, D E Storm, P R Busteed, et al. 2009. Evaluating Nonpoint Source Critical Source Area Contributions at the Watershed Scale. Journal of Environment Quality, 38(4): 1654-1663.

Williams J R. 1975. Sediment routing for agricultural watersheds. Water Resources Bulletin, 11(5): 965-974.