**3. Application of SATEEC GIS system**

The SATEEC system has been applied for various soil erosion studies because it is available in GIS interface and is freely downloadable from the SATEEC website (http://www.EnvSys.co.kr/~sateec). In this chapter, several SATEEC applications will be introduced to give various insights of using SATEEC system to the readers.

SATEEC GIS System for Spatiotemporal Analysis of Soil Erosion and Sediment Yield 263

Then the USLE C factor reflects the effects on soil erosion of surface condition of watershed, rainfall drop impact and flow velocity are affected by the surface condition of watershed in real field. Jung et al. (1984) suggested the values of the factor to apply noncrop area such as urbanized area (Table 3). It has the range 0 to 1 as a fraction; lower value indicates that the surface is covered well so that less soil erosion occurs, while higher value indicates that the surface is covered roughly which has higher possibility of much

> Land use USLE C factor Water 0.000 Forest 0.001 Pasture 0.010 Agriculture 0.260 Urbanization 0.010 Bare Ground 1.000

USLE P factor represents a conservation or support practice such as contouring, strip

SATEEC computed the LS factor map based on DEM and the method suggested by Moore and Burch (1986, equation (13). The length of hill slope in the USLE experimental plots ranged from 10.7 m (35ft) to 91.4 m (300 ft), thus, it was recommended to use of slope lengths less than 122 m (400 ft) because overland flow becomes concentrated into the rills in

To compare sediment yield by both area-based and slope-based SDRs, which was main purpose of the study, 19 small sub-watershed having 0.0219 square kilometers were selected (Figure 8), they had different watershed characteristics (Table 5). As shown in Table 5, areas of 19 sub-watersheds were identical to investigate effect of different SDR methods. However the slopes for these watersheds ranged from 0.73 % to 3.17 %. The 'Distance (km)' in the table indicates length of the sub-watershed which is from the outlet to the farthest point, and

ൈ ቀ ୱ୧୬ Ǥ଼ଽቁ

ଵǤଷ

(13)

Slope P factor 0 % – 2 % 0.60 2 % – 7 % 0.50 7 % – 12 % 0.60 12 % – 18 % 0.80 18 % – 24 % 0.90 24 % – 30 % 0.95 > 30 % 1.00

Table 3. C Factor for Various Land uses (Jung et al., 1984)

Table 4. USLE P Factors for Various Land uses and Slopes

less than 122 m (400 ft) under natural condition (Foster et al., 1996).

 ൌ ቀ ଶଶǤଵଷቁ Ǥ

Land use P Factor Paddy land 0.20

cropping, terracing, and etc (Table 4).

Upland

soil erosion.

#### **3.1 SATEEC ver. 1.5 evaluation using area-based and channel slope-based SDR modules**

The comparison of area-based and slope-based SDR modules was performed by Park et al. (2007). The SATEEC provides two SDR modules to estimate sediment yield using soil loss estimated with USLE. The SATEEC was applied to 19 sub-watersheds in South-Korea (Figure 6) which have identical area with various slopes. The study area is located at Chuncheon-si in South-Korea, total area of the watershed is 11.17 square kilometers.

Fig. 6. Location and figure of Sudong watershed (Park et al., 2007)

The USLE R factor suggested by Jung et al. (1999) was used for this study. Table 2 shows USLE R factors of Gangwon province in which Chuncheon-si is located.


Table 2. USLE R factors for administrative districts in Gangwon province (Jung et al., 1999)

USLE K factor indicating soil erodibility was calculated with equation suggested by Williams (1975), which requires the percentage of sand, silt, and clay (equation (12)).

USLE K = ���� � ��� � ��� �������� � S�� � �� � ���� ������� � ����� � � �������� ������� ���������������� � ���� � ���� � ��� ������� ������������������ (12)

Where, SAN is the percentage of sand (%), SIL is the percentage of silt (%), CLA is the percentage of clay (%), and SN1 is (1-SAN/100).

The comparison of area-based and slope-based SDR modules was performed by Park et al. (2007). The SATEEC provides two SDR modules to estimate sediment yield using soil loss estimated with USLE. The SATEEC was applied to 19 sub-watersheds in South-Korea (Figure 6) which have identical area with various slopes. The study area is located at

The USLE R factor suggested by Jung et al. (1999) was used for this study. Table 2 shows

Administrative district R factor Administrative district R factor Kangnung 297 Kosung 250 Samchok 215 Sokcho 255 Yangyang 255 Yongwol 350 Wonju 578 Inje 294 Cheolwon 400 Chuncheon 464 Hwacheon 450 Hongcheon 417 Yanggu 350 Pyongchang 269 Chongson 250 Hoengsung 400 Table 2. USLE R factors for administrative districts in Gangwon province (Jung et al., 1999) USLE K factor indicating soil erodibility was calculated with equation suggested by

Williams (1975), which requires the percentage of sand, silt, and clay (equation (12)).

���� � ��� � ��� �������� � S�� � �� � ����

percentage of clay (%), and SN1 is (1-SAN/100).

 ���� � ���� � ���

USLE K =

Where, SAN is the percentage of sand (%), SIL is the percentage of silt (%), CLA is the

������� ������������������ (12)

������� � ����� � � ��������

������� ���������������� �

**3.1 SATEEC ver. 1.5 evaluation using area-based and channel slope-based SDR** 

Chuncheon-si in South-Korea, total area of the watershed is 11.17 square kilometers.

Fig. 6. Location and figure of Sudong watershed (Park et al., 2007)

USLE R factors of Gangwon province in which Chuncheon-si is located.

**modules** 

Then the USLE C factor reflects the effects on soil erosion of surface condition of watershed, rainfall drop impact and flow velocity are affected by the surface condition of watershed in real field. Jung et al. (1984) suggested the values of the factor to apply noncrop area such as urbanized area (Table 3). It has the range 0 to 1 as a fraction; lower value indicates that the surface is covered well so that less soil erosion occurs, while higher value indicates that the surface is covered roughly which has higher possibility of much soil erosion.


Table 3. C Factor for Various Land uses (Jung et al., 1984)

USLE P factor represents a conservation or support practice such as contouring, strip cropping, terracing, and etc (Table 4).


Table 4. USLE P Factors for Various Land uses and Slopes

SATEEC computed the LS factor map based on DEM and the method suggested by Moore and Burch (1986, equation (13). The length of hill slope in the USLE experimental plots ranged from 10.7 m (35ft) to 91.4 m (300 ft), thus, it was recommended to use of slope lengths less than 122 m (400 ft) because overland flow becomes concentrated into the rills in less than 122 m (400 ft) under natural condition (Foster et al., 1996).

$$\text{LS} = \left(\frac{A}{22.13}\right)^{0.6} \times \left(\frac{\sin \theta}{0.0896}\right)^{1.3} \tag{13}$$

To compare sediment yield by both area-based and slope-based SDRs, which was main purpose of the study, 19 small sub-watershed having 0.0219 square kilometers were selected (Figure 8), they had different watershed characteristics (Table 5). As shown in Table 5, areas of 19 sub-watersheds were identical to investigate effect of different SDR methods. However the slopes for these watersheds ranged from 0.73 % to 3.17 %. The 'Distance (km)' in the table indicates length of the sub-watershed which is from the outlet to the farthest point, and

SATEEC GIS System for Spatiotemporal Analysis of Soil Erosion and Sediment Yield 265

(e) DEM (f) USLE LS Factor Map derived using DEM

Fig. 7. Input data for Soil loss in SATEEC (Park et al., 2007)

Fig. 8. Location of 19 watersheds in study area (Park et al., 2007)

(sub-watershed 1).

As shown in Table 6, soil loss for each sub-watershed was different due to different subwatershed characteristics. However sediment yield estimation was also affected by the SDR methods utilized. Area-based SDRs showed the same results due to identical watershed area, while slope-based SDRs for study watershed ranged from 0.553 to 0.999. The subwatershed 9 and 11, which are pasture-dominant sub-watershed, showed relatively less soil loss, though, the difference of sediment yield by SDR module was -79.74 %. The difference in percentage ranged from -79.74 % (sub-watershed 11) to 27.45 % (sub-watershed 1), and the difference in 'ton/ha' showed from -89.61 ton/ha (sub-watershed 16) to 73.84 ton/ha

the 'Unity shape factor' indicates a water shape factor which is ratio of the longest distance to the shortest distance in the sub-watershed.

(c) USLE C Factor Map (d) USLE P Factor Map

the 'Unity shape factor' indicates a water shape factor which is ratio of the longest distance

(a) USLE R Factor Map (b) USLE K Factor Map

(c) USLE C Factor Map (d) USLE P Factor Map

to the shortest distance in the sub-watershed.

Fig. 7. Input data for Soil loss in SATEEC (Park et al., 2007)

Fig. 8. Location of 19 watersheds in study area (Park et al., 2007)

As shown in Table 6, soil loss for each sub-watershed was different due to different subwatershed characteristics. However sediment yield estimation was also affected by the SDR methods utilized. Area-based SDRs showed the same results due to identical watershed area, while slope-based SDRs for study watershed ranged from 0.553 to 0.999. The subwatershed 9 and 11, which are pasture-dominant sub-watershed, showed relatively less soil loss, though, the difference of sediment yield by SDR module was -79.74 %. The difference in percentage ranged from -79.74 % (sub-watershed 11) to 27.45 % (sub-watershed 1), and the difference in 'ton/ha' showed from -89.61 ton/ha (sub-watershed 16) to 73.84 ton/ha (sub-watershed 1).

SATEEC GIS System for Spatiotemporal Analysis of Soil Erosion and Sediment Yield 267

This application study indicated that the SDR method could affect sediment yield estimation significantly than the USLE factors do. Thus, soil erosion assessment needs to be performed with not only meticulous collection of USLE input data but also appropriate SDR estimation

To determine of soil erosion hot spot watershed, the SATEEC with USPED was applied to a watershed that was referred as requiring BMPs by the Korean government to reduce soil erosion due to severe sediment-laden water problem in the stream. The study watershed is located at Jawoon-ri, Hongcheon-gun in South-Korea, watershed area is 6,906 ha, containing 82.93 % of forest, 12.32 % of agricultural area, 2.02 % of water, 1.62 % of pasture, and 1.09 %

Table 2 shows USLE R factors of Gangwon province in which Hongcheon-gun is located. USLE K factor indicates soil erodibility, was calculated by the equation suggested by Williams (1975). The USLE K map was developed with the soil map for the study. USLE C factor map was developed using the values suggested by Jung et al. (1984) (Table 3), and USLE P factor map was developed based on slope (Table 4). USLE LS factor map was developed with the module in SATEEC using DEM. To determine hot spot area in the watershed and decide the order of priority in BMP implementation, the given watershed was divided into 54 sub-watersheds (Figure 10, Table 7), soil loss for each sub-watershed

**3.2 SATEEC ver. 1.5 and USPED applications for soil erosion hot spot areas** 

method.

of urbanized area.

was estimated with SATEEC and USPED.

Fig. 9. Location of watershed in Hongcheon-gun (Seo et al.,2010)

The estimated soil erosion values for each sub-watershed are different although these SATEEC and USPED estimate soil erosion with the USLE input data set. However, they showed similar trends for the order of priority in BMP implementation. The soil loss (ton/ha/year) estimated with SATEEC showed higher values in the sub-watershed 2, 1, 25, 21, and 17, the soil loss with USPED considering both erosion and deposition showed higher values in the sub-watershed 2, 1, 7, 35, and 39, and the soil loss by USPED considering only erosion showed higher values in the sub-watershed 46, 2, 3, 1, and 17. The order of priority




Table 6. Soil loss, sediment yield using SDRA and SDRS for 19 Sub-watersheds (Park et al., 2007)

Sub-watershed Slope (%) Area (sq. km) Distance (km) Unity shape factor 1 0.73 0.0219 0.207 1.399 2 0.76 0.0219 0.181 1.223 3 0.85 0.0219 0.252 1.703 4 0.86 0.0219 0.216 1.46 5 1.01 0.0219 0.203 1.372 6 1.12 0.0219 0.235 1.588 7 1.21 0.0219 0.252 1.703 8 1.46 0.0219 0.195 1.318 9 1.52 0.0219 0.185 1.25 10 1.58 0.0219 0.309 2.088 11 1.75 0.0219 0.277 1.872 12 2.12 0.0219 0.356 2.406 13 2.49 0.0219 0.302 2.041 14 2.55 0.0219 0.349 2.358 15 2.66 0.0219 0.282 1.906 16 2.67 0.0219 0.285 1.926 17 2.87 0.0219 0.304 2.054 18 3.07 0.0219 0.307 2.075 19 3.17 0.0219 0.251 1.696 Table 5. Subwatershed, slope, area, distance and unity shape factor characteristics (Park et

al., 2007) Subwatershed

Area (sq. kilometer)

Slope (%) Soil loss

(ton/yr)

Area-Based Slope-Based

Yield (ton/yr) SDR Sediment

Yield (ton/yr)

SDR Sediment

1 0.0219 0.73 353.125 0.762 268.995 0.553 195.160 2 0.0219 0.76 196.000 0.762 149.304 0.56 109.790 3 0.0219 0.85 311.250 0.762 237.097 0.587 182.551 4 0.0219 0.86 169.688 0.762 129.261 0.59 100.069 5 0.0219 1.01 180.125 0.762 137.211 0.629 113.278 6 0.0219 1.12 100.813 0.762 76.795 0.657 66.227 7 0.0219 1.21 37.375 0.762 28.471 0.678 25.339 8 0.0219 1.46 99.188 0.762 75.557 0.731 72.457 9 0.0219 1.52 1.938 0.762 1.476 0.742 1.438 10 0.0219 1.58 161.938 0.762 123.357 0.754 122.031 11 0.0219 1.75 27.750 0.762 12.139 0.786 21.818 12 0.0219 2.12 354.125 0.762 269.757 0.849 300.581 13 0.0219 2.49 153.438 0.762 116.882 0.905 138.910 14 0.0219 2.55 214.688 0.762 163.540 0.914 196.194 15 0.0219 2.66 134.500 0.762 102.456 0.93 125.121 16 0.0219 2.67 527.250 0.762 401.636 0.932 491.243 17 0.0219 2.87 62.438 0.762 47.562 0.959 59.883 18 0.0219 3.07 141.813 0.762 108.027 0.985 139.652 19 0.0219 3.17 167.938 0.762 127.928 0.999 167.711 Table 6. Soil loss, sediment yield using SDRA and SDRS for 19 Sub-watersheds (Park et al., 2007) This application study indicated that the SDR method could affect sediment yield estimation significantly than the USLE factors do. Thus, soil erosion assessment needs to be performed with not only meticulous collection of USLE input data but also appropriate SDR estimation method.
