**3.5 SATEEC ver. 2.0 with L modules for topography changes due to forest roads**

The application of L module in SATEEC was applied to study watershed located at Haeanmyeon Yanggu-gun in South-Korea (Figure 12, Kang et al., 2009). 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. The interference to slope length in the watershed are the boundaries of agricultural areas and roads, the data was built based on Gangwon Development Research Institude's measured data in Haean-myeon watershed (Figure 18).

Fig. 18. Slope Length Segmentation due to Agricultural Field Boundaries (Kang et al., 2009)

Kang et al. (2009) developed the USLE K and P factor maps with similar method and process to previous one by SATEEC, but USLE R factor was estimated using Time-Variant R module with daily precipitation data from Jan/1/1993 to Jul/31/2007 (Figure 19 (a)), and USLE C factor was estimated using Time-Variant C module with SATEEC DB (Figure 19 (b)) and land use map (Figure 19 (c)).

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

**3.5 SATEEC ver. 2.0 with L modules for topography changes due to forest roads**  The application of L module in SATEEC was applied to study watershed located at Haeanmyeon Yanggu-gun in South-Korea (Figure 12, Kang et al., 2009). 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. The interference to slope length in the watershed are the boundaries of agricultural areas and roads, the data was built based on Gangwon Development Research Institude's measured data in Haean-myeon

Fig. 18. Slope Length Segmentation due to Agricultural Field Boundaries (Kang et al., 2009) Kang et al. (2009) developed the USLE K and P factor maps with similar method and process to previous one by SATEEC, but USLE R factor was estimated using Time-Variant R module with daily precipitation data from Jan/1/1993 to Jul/31/2007 (Figure 19 (a)), and USLE C factor was estimated using Time-Variant C module with SATEEC DB (Figure 19 (b))

result.

watershed (Figure 18).

and land use map (Figure 19 (c)).

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

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

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 estimation.

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 SATEEC L module.

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 GIS System for Spatiotemporal Analysis of Soil Erosion and Sediment Yield 277

Although, with integration of Time-Variant C and R modules, the SATEEC allows user to estimate monthly/yearly soil erosion and sediment yield, daily assessment of soil loss and sediment yield at the watershed outlet is in need due to the particularity of precipitation affecting to soil erosion in a single day or a few days, such as typhoon. Woo et al. (2010) applied SATEEC with R5 module to estimate daily USLE R factor to Imha watershed stated above (Figure 16). Most of input data was set with identical method to Park et al. (2010), but R5 module was applied to estimate daily USLE R factor, and to validate the module. As shown in Figures 22 (a) and (b), the estimated sediment yield by SATEEC ver. 2.1 using R5 module showed less difference than the estimated sediment yield by SATEEC ver. 2.0 using Time-Variant R module, compared to measured data in both calibration and validation

(a) Calibration Period (Jan/1999 – Dec/2004)

**3.6 SATEEC ver. 2.1 for daily sediment estimation using daily USLE R modules** 

periods.

(a) USLE L factor without L module (b) USLE L factor with L module Fig. 20. Comparison of USLE L factor with L module and without L module (Kang et al., 2009)

Fig. 21. Comparison of Annual Soil Erosion using SATEEC 2.0. with L Module and without L Module (Kang et al., 2009)

(a) USLE L factor without L module (b) USLE L factor with L module Fig. 20. Comparison of USLE L factor with L module and without L module (Kang et al., 2009)

Fig. 21. Comparison of Annual Soil Erosion using SATEEC 2.0. with L Module and without

L Module (Kang et al., 2009)

#### **3.6 SATEEC ver. 2.1 for daily sediment estimation using daily USLE R modules**

Although, with integration of Time-Variant C and R modules, the SATEEC allows user to estimate monthly/yearly soil erosion and sediment yield, daily assessment of soil loss and sediment yield at the watershed outlet is in need due to the particularity of precipitation affecting to soil erosion in a single day or a few days, such as typhoon. Woo et al. (2010) applied SATEEC with R5 module to estimate daily USLE R factor to Imha watershed stated above (Figure 16). Most of input data was set with identical method to Park et al. (2010), but R5 module was applied to estimate daily USLE R factor, and to validate the module. As shown in Figures 22 (a) and (b), the estimated sediment yield by SATEEC ver. 2.1 using R5 module showed less difference than the estimated sediment yield by SATEEC ver. 2.0 using Time-Variant R module, compared to measured data in both calibration and validation periods.

(a) Calibration Period (Jan/1999 – Dec/2004)

SATEEC GIS System for Spatiotemporal Analysis of Soil Erosion and Sediment Yield 279

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**4. References** 

(b) Validation Period (Jan/2005 – Dec/2008)

Fig. 22. Comparison in Time-Series Plot

R2 and NSE of the sediment yield by SATEEC ver. 2.1 were 0.776 and 0.776 in calibration, and 0.927 and 0.911 in validation (Figure 23). Compared to the criteria of SATEEC ver. 2.0 results, SATEEC ver. 2.1 showed more reasonable values for both R2 and NSE in calibration and validation, it is deemed as SATEEC ver. 2.1 allows the estimation considering more detailed precipitation characteristics.

Fig. 23. Calibration and Validation of SATEEC ver. 2.1

#### **4. References**

278 Soil Erosion Studies

(b) Validation Period (Jan/2005 – Dec/2008)

R2 and NSE of the sediment yield by SATEEC ver. 2.1 were 0.776 and 0.776 in calibration, and 0.927 and 0.911 in validation (Figure 23). Compared to the criteria of SATEEC ver. 2.0 results, SATEEC ver. 2.1 showed more reasonable values for both R2 and NSE in calibration and validation, it is deemed as SATEEC ver. 2.1 allows the estimation considering more

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

Fig. 22. Comparison in Time-Series Plot

detailed precipitation characteristics.

Fig. 23. Calibration and Validation of SATEEC ver. 2.1


**Part 3** 

**Other Applications in Engineering/Geoscience** 

