All Issue

2020 Vol.25, Issue 3 Preview Page
Monthly Sediment Yield Estimation Based on Watershed-scale Application of ArcSATEEC with Correction Factor

보정계수 적용을 통한 유역에 대한 ArcSATEEC의 월별 토양유실량 추정 방안 연구

Eun Seok Kim1
,
Hanyong Lee1
,
Jae E Yang2
,
Kyoung Jae Lim3
,
Youn Shik Park1*
김 은석1
,
이 한용1
,
양 재의2
,
임 경재3
,
박 윤식1*
1Rural Construction Engineering, Kongju National University, Chungcheongnam-do 32439, Korea
2Department of Biological Environment, Kangwon National University, Gangwon-do 24341, Korea
3Department of Regional Infrastructure, Kangwon National University, Gangwon-do 24341, Korea
1공주대학교 지역건설공학과
2강원대학교 바이오자원환경학과
3강원대학교 지역건설공학과
*Corresponding Author
30 September 2020. pp. 52-64
PDF XML Citation
Abstract

The universal soil loss equation (USLE), a model for estimating the potential soil loss, has been used not only in research areas but also in establishing national policies in South Korea. Despite its wide applicability, USLE cannot adequately address the effect of seasonal variances. To overcome this limit, the ArcGIS-based Sediment Assessment Tool for Effective Erosion (ArcSATEEC) has been developed as an alternative model. Although the field-scale (< 100 m2) application of this model produced reliable estimation results, it is still challenging to validate accuracy of the model estimation because it only estimates potential soil losses, not the actual sediment yield. Therefore, in this study, a method for estimating actual soil loss based on the ArcSATEEC model was suggested. The model was applied to eight watersheds in South Korea to estimate sediment yields. Correction factor was introduced for each watershed, and the estimated sediment yield was compared with that of the estimated yield by LOAD ESTimator (LOADEST). Sediment yield estimation for all watersheds exhibited reliable results, and the validity of the proposed correction factor was confirmed, suggesting the correction factor needs to be considered in estimating actual soil loss.

Keywords
ArcSATEEC
sediment delivery ratio
soil loss, USLE
References
1

De Rosa P., Cencetti C., and Fredduzzi A., 2016, A GRASS tool for the Sediment Delivery Ratio mapping. Proceedings of the 4th Open Source Geospatial Research and Education Sympo-sium, In Marchesini I. & Pierleoni A. (Eds.), Perugia, Italy.

10.7287/peerj.preprints.2227v2
2

Duda, P.B., Hummel Jr., P.R., Donigian Jr., A.S., and Imhoff, J.C., 2012, BASINS/HSPF: Model use, calibration, and valida-tion. Trans. ASABE, 55(4), 1523-1547.

10.13031/2013.42261
3

Folle, S., Dalzell, B., and Mulla, D., 2007, Evaluation of best management practices (BMPs) in impaired watersheds using the SWAT model, Depart of Soil, Water and Climate, University of Minnesota, Minnesota, USA.

4

Herr, J.W. and Chen, C.W., 2012, WARMF: Model use, calibra-tion, and validation. Trans. ASABE, 55(4), 1385-1394.

10.13031/2013.42249
5

Jha, B. and Jha, M.K., 2013, Rating curve estimation of surface water quality data using LOADEST. J. Environ. Protect., 4(8), 849-856.

10.4236/jep.2013.48099
6

Jung, K.H., Kim, W.T., Hur, S.O., Ha, S.K., Jung, P.K., and Jung, Y.S., 2004, USLE/RUSLE factors for national scale soil loss estimation based on the digital detailed soil map. Korean J. Soil Sci. Fert., 37(4), 199-206.

7

Kim, J., Yang, J.E., Lim, K.J., Kim, S.C., Lee, G., Hwang, S., Yu, N., and Park, Y.S., 2017, A study to define area of concern for potential soil loss in Geumgang watershed by KORSLE-based GIS model, J. Soil Groundwater Environ., 22(6), 29-36.

10.7857/JSGE.2017.22.6.029
8

Kongju National University, 2016, Development of Topsoil Ero-sion Model for Korea. Yesan-gun: Republic of Korea.

9

Moriasi, D.N., Gitau, M.W., Pai, N., and Daggupati, P., 2015, Hydrologic and water quality models: performance measures and evaluation criteria. Am. Soc. Agric. Biol. Eng., 58(6), 1763-1785.

10.13031/trans.58.10715
10

Omani N., Srinivasan, R., and Lee, T., 2012, Estimating Sedi-ment and Nutrient Loads of Texas coastal watersheds with SWAT. Spatial Sciences Laboratory, Texas A&M University, Texas, USA.

11

Oh, J., Sinha, T., and Sankarasubramanian, A., 2014, The role of retrospective weather forecasts in developing daily forecasts of nutrient loadings over the Southeast US. Hydrol. Earth Syst. Sci., 18(8), 2885-2898.

10.5194/hess-18-2885-2014
12

Park, Y.S., Kim, J., Kim, N., Kim, K.S., Choi, J., and Lim, K.J., 2007, Analysis of sediment yields at watershed scale using area/ slope-based sediment delivery ratio in SATEEC, J. Korean Soc. Water Environ., 23(5), 650-658.

13

Park, Y.S., Engel, B.A., and Harbor, J., 2014. A web-based model to estimate the impact of best management practices. WATER, 6(3), 455-471.

10.3390/w6030455
14

Park, Y.S., Kim, J., Kim, N.W., Kim, S.J., Jeon, J.H., Engel, B.A., Jang, W., and Lim, K.J., 2010, Development of new R, C and SDR modules for the SATEEC GIS system, Comp. Geo., 36(6), 726-734.

10.1016/j.cageo.2009.11.005
15

Ratner, B., 2009, The correlation coefficient: Its values range between +1/-1, or do they?. J. Target. Meas. Anal. Market., 17(2), 139-142.

10.1057/jt.2009.5
16

Risal, A., Bhattarai, R., Kum, D., Park, Y.S., Yang, J.E., and Lim, K.J., 2016, Application of Web ERosivity Module (WERM) for estimation of annual and monthly R factor in Korea. CATENA 147, 225-237.

10.1016/j.catena.2016.07.017
17

Runkel, R.L., Crawford, C.G., and Cohn, T.A., 2004, Load Esti-mator (LOADEST): A Fortran Program for Estimating Constit-uent Loads in Streams and Rivers; U.S. Geological Survey Techniques and Methods: Reston, VA, USA.

10.3133/tm4A5
18

Santos, J.C.N., Andrade, E.M., Medeiros, P.H.A., Palácio, H.A.Q., and Neto, J.R.A., 2017. Sediment delivery ration in a small semi-arid watershed under conditions of low connectivity. Rev. Ciênc. Agron., 48(1), 49-58.

10.5935/1806-6690.20170006
19

Skaggs, R., Youssef, M., and Chescheir, G., 2012, DRAIN-MOD: Model use, calibration, and validation. Trans. ASABE, 55(4), 1509-1522.

10.13031/2013.42259
20

Song, J. M., Yang, J. E., Lim, K. J., Park, Y. S., 2019. Applica-tion of KORSLE to estimate soil erosion at field scale. J. Soil Groundw. Envron., 24(5), 31-41.

21

Sun, C., Shen, Z., Liu, R., Xiong, M., Ma, F., Zhang, O., Li, Y., and Chen, L., 2013, Historical trend of nitrogen and phosphorus loads from the upper Yangtze River basin and their responses to the Three Gorges Dam. Environ. Sci. Pollut. Res., 20(12), 8871-8880.

10.1007/s11356-013-1859-7
22

Sung, Y.S., Jung, Y., Lim, K.J., Kim, J., Kim, K.S., Park, S.K., Shin, M., Kum, D.H., and Park, Y.S., 2016, A study to develop monthly cover management factor database for monthly soil loss estimation, J. Korean Soc. Ag. Eng., 58(6), 23-30.

10.5389/KSAE.2016.58.6.023
23

United States Department of Agriculture, 1972, National Engi-neering Handbook: Sediment Source, Yileds, and Delivery Ratios, Soil Conservation Service, Washington, DC., USA.

24

Vanoni, V.A., 1975, Sedimentation Engineering, Manual and Report No. 54, American Society of Civil Engineers, New York, USA.

25

Wang, X., Williams, J., Gassman, P., Baffaut, C., Izaurralde, R., Jeong, J., and Kiniry, J. (2012). EPIC and APEX: Model use, calibration, and validation. Trans. ASABE, 55(4), 1447-1462. http://dx.doi.org/10.13031/2013.42253.

10.13031/2013.42253
26

Wang, G., Jager, H.I., Baskaran, L.M., Baker, T.F., and Brandt, C.C., 2016. SWAT modeling of water quantity and quality in the Tennessee river basin: spatiotemporal calibration and valida-tion, Hydrol, Earth Syst. Sci. Discuss., 1-33.

10.5194/hess-2016-34
27

Williams, J.R., 1975, Sediment-yield Prediction with Universal Equation using Runoff Energy Factor. In Present and perspec-tive technology for predicting sediment yield and sources, 244-252. US Department of Agriculture, Washington, DC.

28

Williams, J.R. and Berndt, H.D., 1977, Sediment Yield Predic-tion Based on Watershed Hydrology, Trans. Am. Soc. Ag. Eng., 20(6), 1100-1104.

10.13031/2013.35710
29

Williams, J.R., 1977, Sediment Yield Prediction with Universal Equation using Runoff Energy Factor. In: Present and Prospec-tive Technology for Predicting Sediment Yield and Sources, USDA-ARS-S-40, U.S Department of Agriculture, Washing-ton, DC., USA.

30

Wischmeier, W.H. and Smith, D.D., 1965, Predicting Rainfall Erosion Losses from Cropland East of the Rocky Mountains: A guide for selection of practices for soil and water conservation Handbook No.282. U.S. Department of Agriculture.

31

Wischmeier, W. H. and Smith, D.D., 1978, Predicting rainfall erosion losses: A Guide to Conservation Planning Handbook No.537. U. S. Department of Agriculture.

32

Yu, N., Lee, D.J., Han, J.H., Lim, K.J., Kim, J., Kim, K.H., Kim, S., Kim, E.S., Park, Y.S., 2017, Development of ArcGIS-based model to estimate monthly potential soil loss. J. Korean Soc. Ag. Eng., 59(1), 21-30.

10.5389/KSAE.2017.59.1.021
33

Yu, N., Shin, M., Seo, J., Park, Y.S., Kim, J., 2018, A study to define USLE P factor from field survey in the four major water-sheds. J. Korean Soc. Ag. Eng., 60(2), 37-44.

Information
  • Publisher :The Korean Society of Soil and Groundwater Environment
  • Publisher(Ko) :한국지하수토양환경학회
  • Journal Title :Journal of Soil and Groundwater Environment
  • Journal Title(Ko) :지하수토양환경
  • Volume : 25
  • No :3
  • Pages :52-64
  • Received Date : 2020-08-31
  • Revised Date : 2020-09-11
  • Accepted Date : 2020-09-17
  • DOI :https://doi.org/10.7857/JSGE.2020.25.3.052
Journal Informaiton Journal of Soil and Groundwater Environment Journal of Soil and Groundwater Environment
Online Submission
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close