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

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 % of urbanized area.

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 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

SATEEC GIS System for Spatiotemporal Analysis of Soil Erosion and Sediment Yield 269

Fig. 12. Modeling process of integrated system using SATEEC, nLS, and USPED (Kang et al.,

USLE input data maps were used for SATEEC and USPED to estimate sheet/rill and gully erosion, the gully head map was developed by nLS model. The nLS map (Figure 13 (d)) was developed using slope map (Figure 13 (a)), overland flow map (Figure 13 (b)), and manning's n map (Figure 13 (c)), the values over 100 in the nLS map indicate gully head.

Fig. 11. Location of Haean-myeon watershed (Kang et al., 2010)

2010)

in BMP implementation is different based on each model, however, both models indicates that BMPs should be applied to reduce soil erosion for sub-watershed 2 and 1.

Fig. 10. Location of 54 sub-watersheds at Jawoon-ri Watershed (Seo et al.,2010)


Table 7. 5 Sub-watersheds Requiring BMPs and Soil Loss (ton/ha/year)

#### **3.3 SATEEC ver. 1.8 with USPED, nLS for gully erosion evaluation**

It is not possible to estimate gully erosion with USLE model because it estimates sheet and rill erosion. Kang et al. (2010) applied the SATEEC with nLS and USPED to estimate sheet/rill and gully erosion. These models were applied to the study watershed located at Haean-myeon Yanggu-gun in South-Korea (Figure11). Watershed area is 61.78 square kilometers, containing 58.8 % of forest, 37.2 % of agricultural area, 1.9 % of urbanized area, 1.3 % of water, 0.6 % of bare land, and 0.2 % of pasture.

Soil Loss considering sheet/rill erosion and gully erosion can be estimated by the process showed in Figure 12. The processes show how to develop input for nLS and USPED using USLE inputs, determine gully head determined with nLS, gully erosion by USPED, develop gully erosion map combining gully head map by nLS and gully erosion map by USPED, and to combine the map with sheet/rill erosion map by SATEEC.

in BMP implementation is different based on each model, however, both models indicates

that BMPs should be applied to reduce soil erosion for sub-watershed 2 and 1.

Fig. 10. Location of 54 sub-watersheds at Jawoon-ri Watershed (Seo et al.,2010)

Table 7. 5 Sub-watersheds Requiring BMPs and Soil Loss (ton/ha/year)

**3.3 SATEEC ver. 1.8 with USPED, nLS for gully erosion evaluation** 

1.3 % of water, 0.6 % of bare land, and 0.2 % of pasture.

to combine the map with sheet/rill erosion map by SATEEC.

watershed USPEDED

2 265.41 2 3.46 46 28.29 1 199.71 1 3.27 2 24.50 25 167.18 7 2.47 3 18.75 21 153.05 35 2.00 1 18.70 17 87.82 39 1.99 17 18.15

It is not possible to estimate gully erosion with USLE model because it estimates sheet and rill erosion. Kang et al. (2010) applied the SATEEC with nLS and USPED to estimate sheet/rill and gully erosion. These models were applied to the study watershed located at Haean-myeon Yanggu-gun in South-Korea (Figure11). Watershed area is 61.78 square kilometers, containing 58.8 % of forest, 37.2 % of agricultural area, 1.9 % of urbanized area,

Soil Loss considering sheet/rill erosion and gully erosion can be estimated by the process showed in Figure 12. The processes show how to develop input for nLS and USPED using USLE inputs, determine gully head determined with nLS, gully erosion by USPED, develop gully erosion map combining gully head map by nLS and gully erosion map by USPED, and

Sub-

watershed USPEDE

Sub-

watershed SATEEC Sub-

Fig. 11. Location of Haean-myeon watershed (Kang et al., 2010)

Fig. 12. Modeling process of integrated system using SATEEC, nLS, and USPED (Kang et al., 2010)

USLE input data maps were used for SATEEC and USPED to estimate sheet/rill and gully erosion, the gully head map was developed by nLS model. The nLS map (Figure 13 (d)) was developed using slope map (Figure 13 (a)), overland flow map (Figure 13 (b)), and manning's n map (Figure 13 (c)), the values over 100 in the nLS map indicate gully head.

SATEEC GIS System for Spatiotemporal Analysis of Soil Erosion and Sediment Yield 271

(a) Gully Head Map (b) Soil Erosion Map by USPED

(c) Gully Erosion Map (d) Sheet/Rill and Gully Erosion Map

Fig. 14. Soil Erosion Map (Kang et al., 2010)

Fig. 13. Maps to develop Gully Head Map (Kang et al., 2010)

Gully head map (Figure 14(a)) was derived from nLS map (Figure 13 (d)) of which cell values are greater than 100, which indicates potential gully head location. Using the Gully head map and soil erosion map by USPED (Figure 14 (b)), the map representing only gully erosion (Figure 14 (c)) was derived. And then the soil erosion map considering sheet/rill and gully erosion map was derived from gully erosion map and sheep/rill erosion map by SATEEC. The negative values in the maps indicate deposition, and positive values indicate erosion.

(a) Slope Map (b) Overland Flow Map

(c) Manning's n Map (d) nLS Map

Gully head map (Figure 14(a)) was derived from nLS map (Figure 13 (d)) of which cell values are greater than 100, which indicates potential gully head location. Using the Gully head map and soil erosion map by USPED (Figure 14 (b)), the map representing only gully erosion (Figure 14 (c)) was derived. And then the soil erosion map considering sheet/rill and gully erosion map was derived from gully erosion map and sheep/rill erosion map by SATEEC. The

negative values in the maps indicate deposition, and positive values indicate erosion.

Fig. 13. Maps to develop Gully Head Map (Kang et al., 2010)

Fig. 14. Soil Erosion Map (Kang et al., 2010)

SATEEC GIS System for Spatiotemporal Analysis of Soil Erosion and Sediment Yield 273

(b) Daily USLE C factor DB (c) Land use Map

(a) Calibration (1999–2004) (b) Validation (2005-2008)

SDR = (6 × 10��) × AREA����� × SLOPE������ × CN������ (14)

Fig. 16. Data for Time-Variant modules (Park et al., 2010)

Fig. 17. Calibration and Validation of SATEEC

(a) Daily Precipitation Data

#### **3.4 SATEEC ver. 2.0 for sediment evaluation using time-variant R and C modules**

One of significant modification in SATEEC was development and integration of Time-Variant Modules and GA-SDR modules that are to estimate monthly/yearly sediment yield at the watershed outlet using USLE model which is field-scale. Park et al. (2010) applied the modules to Imha watershed located in South-Korea (Figure 15), the area of the watershed is 1,361 square kilometers containing 79.8 % of forest, 16.0 % of agricultural areas, 1.4 % of residential areas, 2.4 % of water, and 0.4 % of pasture. The watershed is forest-dominant, but much of agricultural areas are located nearby stream, increasing chance of being transported into the stream after soil eroded from the agricultural areas.

Park et al. (2010) set USLE K, P, and LS factor map with similar method and process to previous one in SATEEC, but USLE R factor was estimated using Time-Variant R module with daily precipitation data from Jan/1/1999 to Oct/31/2004 (Figure 16(a)), and USLE C factor was estimated using Time-Variant C module with SATEEC DB (Figure 16(b)) and land use map (Figure 16(c)). To estimate sediment yield at the watershed outlet, GA-SDR module was applied.

Fig. 15. Location and land-use at Imha Watershed, Gyeongsangbuk-do, South-Korea (Park et al., 2010)

GA-SDR module estimated the coefficient and exponents for the formula to calculate SDR of the watershed (equation (14)), comparing to measured data. SATEEC was calibrated with measured data from 1999 to 2004, was validated with measured data from 2005-2008, it showed 0.721 and 0.720 of R2 and NSE in calibration, 0.906 and 0.881 for R2 and NSE in validation (Figure 17).

Park et al. (2010) set USLE K, P, and LS factor map with similar method and process to previous one in SATEEC, but USLE R factor was estimated using Time-Variant R module with daily precipitation data from Jan/1/1999 to Oct/31/2004 (Figure 16(a)), and USLE C factor was estimated using Time-Variant C module with SATEEC DB (Figure 16(b)) and land use map (Figure 16(c)). To estimate sediment yield at the watershed outlet, GA-SDR

Fig. 15. Location and land-use at Imha Watershed, Gyeongsangbuk-do, South-Korea

GA-SDR module estimated the coefficient and exponents for the formula to calculate SDR of the watershed (equation (14)), comparing to measured data. SATEEC was calibrated with measured data from 1999 to 2004, was validated with measured data from 2005-2008, it showed 0.721 and 0.720 of R2 and NSE in calibration, 0.906 and 0.881 for R2 and NSE in

**3.4 SATEEC ver. 2.0 for sediment evaluation using time-variant R and C modules**  One of significant modification in SATEEC was development and integration of Time-Variant Modules and GA-SDR modules that are to estimate monthly/yearly sediment yield at the watershed outlet using USLE model which is field-scale. Park et al. (2010) applied the modules to Imha watershed located in South-Korea (Figure 15), the area of the watershed is 1,361 square kilometers containing 79.8 % of forest, 16.0 % of agricultural areas, 1.4 % of residential areas, 2.4 % of water, and 0.4 % of pasture. The watershed is forest-dominant, but much of agricultural areas are located nearby stream, increasing chance of being transported

into the stream after soil eroded from the agricultural areas.

module was applied.

(Park et al., 2010)

validation (Figure 17).

Fig. 17. Calibration and Validation of SATEEC

SATEEC GIS System for Spatiotemporal Analysis of Soil Erosion and Sediment Yield 275

(a) Daily Precipitation Data

estimation.

SATEEC L module.

Fig. 19. Data for Time-Variant modules (Kang et al., 2009)

(b) Daily USLE C factor DB (c) Land use Map

Kang et al. (2009) compared USLE L factor maps without and with SATEEC L module as shown in Figure 20(a) and 20(b). With agricultural field boundaries and roads considered in L factor estimation, flow length segmentation could be considered in soil erosion

Annual soil erosion with and without SATEEC L module were shown in (Figure 21). The average annual soil loss estimated without L module was 91,714.71 ton, while the average annual soil loss estimated with L module was 68,469.49 ton. The application indicates that soil erosion could be overestimated if the flow segmentation was not considered with the

In addition, the estimated sediment yields with SATEEC were compared with SWAT monthly simulation since no measured sediment values available. The R2 and NSE were 0.729 and 0.719 for calibration period, 0.818 and 0.800 of R2 and NSE for validation period, when the module was not applied. Sediment yield estimated with the L module showed 0.730 and 0.720 of R2 and NSE in calibration, 0.818 and 0.800 of R2 and NSE in validation.

SATEEC requires USLE input data, though, it has various modules to estimate timevariant soil erosion and sediment yield at the outlet, and moreover it showed reasonable result.
