Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
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Development of Soil Moisture Data Assimilation Scheme for Predicting Effective Soil Characteristics Using Remotely Sensed Data

원격탐사자료 기반 유효토양특성 산정을 위한 토양수분자료동화기법 개발

  • Lee, Taehwa (School of Agricultual Civil & Bio-Industrial Engineering, Kyungpook National University) ;
  • Kim, Sangwoo (School of Agricultual Civil & Bio-Industrial Engineering, Kyungpook National University) ;
  • Lee, Sang-Ho (School of Agricultual Civil & Bio-Industrial Engineering, Kyungpook National University) ;
  • Choi, Kyung-Sook (School of Agricultual Civil & Bio-Industrial Engineering, Kyungpook National University) ;
  • Shin, Yongchul (School of Agricultual Civil & Bio-Industrial Engineering, Kyungpook National University) ;
  • Lim, Kyoungjae (Department of Regional Infrastructure Engineering, Kangwon National University) ;
  • Park, Younshik (Department of Rural Construction Engineering, Kongju National University)
  • Received : 2017.11.02
  • Accepted : 2017.11.22
  • Published : 2018.01.31
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Abstract

In this study, we developed the Soil Moisture Data Assimilation (SMDA) scheme to extract Effective Soil Characteristics-ESC (Sand, Silt, Clay %) from MODerate resolution Imaging Spectroradiometer (MODIS) products. The SMDA scheme was applied to the MODIS-based Soil Moisture (SM) data during the summer (July to September) period. Then the ESC and soil erosion factors (K) were predicted, respectively. Several numerical experiments were conducted to test the performance of SMDA at the study sites under the synthetic and field validation conditions. In the synthetic experiment, the estimated soil moistures values(R: >0.990 and RMSE: <0.005) were identified well with the synthetic observations. The field validation results at the Bangdongri and Chungmicheon sites were also comparable to the TDR-based measurements with the statistics (R: 0.772/0.000 and RMSE: 0.065/0.000). The estimated ESC values were also matched well with the measurements for the synthetic and field validation conditions. Then we tested the SMDA scheme to extract the ESC from the MODIS-based soil moisture products. Although uncertainties exist in the results, the estimated soil moisture and ESC based on the SMDA were comparable to the measurements. Overall, the K factors were similarly distributed based on the derived ESC. Also, the K factors in the mountainous regions were higher than those of the relatively flat areas. Thus, the newly developed SMDA scheme can be useful to estimate spatially and temporally-distributed soil erosion and establish soil erosion management plans.

Keywords

References

  1. Box. Jr. J. E., 1981. The effect of surface slaty fragment on soil erosion by water. Soil Science Society of America Journal, 43, 111-116. doi:10.2136/sssaj1981.03615995004500010024x.
  2. Cosby, B. J., G. M. Hornberger, R. B. Clapp, and T. R. Ginn, 1984. A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils. Water Resources Research, 20, 682-690. doi:10.1029/WR020i006p00682.
  3. Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003. Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, Journal of Geophysical Research, 108, 8851. doi:10.1029/2002JD003296.
  4. Erickson, A. J., 1997. A disforestimating soil erodibility - K value class and soil loss tolerance. U.S. Department of Agriculture. Soil Conservation Service. Salt Lake City, Utah.
  5. Jin-Kyu Choi, Ja-Woong Koo, and Jae-Gwon Son, 1998. Review on the unit conversion with the USLE application in Korea, Korean Journal of Soil Science and Fertilizer, 31(3): 301-308.
  6. Kang-Ho Jung, Won-Tae Kim, Seung-Oh Hur, Sang-Keon Ha, Pil-Kyun Jung, and Yeong-Sang Jung, 2004. USLE/RUSLE factors for national scale soil loss estimation based on the digital detailed soil map, Korean Journal of Soil Science and Fertilizer, 37(4): 199-206.
  7. Lee Geun Sang, Jang Yeong Lyul, and Jo Gi Seong, 2003. The analysis of optimum resolution with different scale of soil map for the calculation of soil loss. Journal of the Korean Association of Geographic Information Studies, 6(3): 1-10.
  8. Ministry of Construction and Transportation-MOCT, 1992. Investigation of sediment loads at watershed-scales for designing dam.
  9. Scott, C. A., W. G. M. Bastiaanssen, and M. D. Ahmad, 2003. Mapping root zone soil moisture using remotely sensed opticalimagery, Journal of Irrigation and Drainage Engineering, 129(5): 362-335.
  10. Sharpley, A. N., and J. R. Villiams, eds., 1990. EPIC--Erosion/Productivity Impact Calculator: 1. Model Documentation. U.S. Department of Agriculture Technical Bulletin No. 1768. pp. 235.
  11. Wischmeier, W. H. and Smith, D. D., 1965. Predicting rainfall-erosion losses from cropland east of the Rocky Mountains, Guide for selection of practices for soil and water conservation. Agriculture Handbook No. 282, Agricultural Research Service, U. S. Dept. of Agric, Washington DC, pp. 47.
  12. Wischmeier, W. H. and Smith, D. D., 1978. Predicting rainfall erosion losses. A Guide to Conservation Planning. The USDA Agricultural Handbook No.537.
  13. Wischmeier, W. H., John, C. B., and Cross, B. V., 1971. A Soil erodibility monograph for farm land and conservation sites. Journal of Soil and Water Conservation, vol.26.