Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
권호 표지
DOI QR코드

DOI QR Code

The Correlation Analysis Between SWAT Predicted Forest Soil Moisture and MODIS NDVI During Spring Season

봄철 SWAT 모형의 산림 토양수분과 Terra MODIS 위성영상 NDVI와의 상관성 분석

  • 홍우용 (건국대학교 일반대학원) ;
  • 박민지 (건국대학교 일반대학원) ;
  • 박종윤 (건국대학교 일반대학원) ;
  • 하림 (건국대학교 일반대학원) ;
  • 박근애 (건국대학교 일반대학원) ;
  • 김성준 (건국대학교 생명환경과학대학)
  • Published : 2009.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this study is to identify how much the MODIS NDVI (Normalized Difference Vegetation Index) can explain the forest soil moisture simulated from SWAT (Soil and Water Assessment Tool) model. For ChungjuDam watershed ($6,661.3\;km^2$) which covers 82.2% of forest, the SWAT model was calibrated for four years (2003-2006) at two locations of the watershed using daily streamflow data and was verified for three years (2000-2002) with average Nash and Sutcliffe model efficiencies of 0.69 and 0.75 respectively. For the period from March to June, the average spatial correlation between 16 days composite MODIS NDVI and the corresponding SWAT forest soil moisture was 0.90. The two variables averaged for each data set during that period showed an inverse relation with the average coefficient of determination of 0.55.

Keywords

References

  1. Ahn, T. Y., 2003. Development of drought map based on climatic water balance using satellite data. Master thesis, Andong University
  2. Farrar, T. J., 1994. The influence of soil type on the relationships between NDVI, rainfall, and soil moisture in semiarid Botswana; . NDVI response to soil moisture, Remote Sensing of Environ., 50(2): 121-133 https://doi.org/10.1016/0034-4257(94)90039-6
  3. Huete, A. R., K. Didan, T. Miura, E. P. Rodriguez, X. Gao & L. G. Ferreira, 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sensing of Environment, 83: 195-213 https://doi.org/10.1016/S0034-4257(02)00096-2
  4. Hutchinson, J. M. S. & T. J. Vought, 2006. Continuous soil moisture mapping using MODIS NDVI and LST products, Papers of the Applied Geography Conferences, 29: 140-149
  5. Hwang, T. H., B. S. Kim, H. S. Kim & B. H. Seo, 2006. The Estimation of soil moisture index by SWAT model and drought monitoring, Journal of Korean Society of Civil Engineers, 26(4B): 345-354
  6. Jang, J. S., 2003. Introduction of hydrologic models and parameters, Korean Commission on Irrigation and Drainage Journal, 10(1): 95-102
  7. Nash, J. E. & J. E. Sutcliffe, 1970, River Flow Forecasting through conceptual models, Part I-A discussion of principles, Journal of Hydrology, 10(3): 282-290 https://doi.org/10.1016/0022-1694(70)90255-6
  8. Park, E. J., C. S. Hwang & J. C. Seong, 2002. The analysis of drought susceptivility using soil moisture information and spatial factor involved in satellite imagery, Journal of Korean Association of Geographic Information Studies, 10(3): 481-492
  9. Park, J. Y., M. S. Lee, Y. J. Lee & S. J. Kim, 2008. The analysis of future land use change impact on hydrology and water quality using SWAT model, Journal of Korean Society of Civil Engineers, 28(2B): 187-197
  10. Park, M. J., Y. J. Lee, H. J. Shin & S. J. Kim, 2008. Assessment of future climate and land use change impactson hydrological behavior of dam watershed using SWAT-K model, 2008 ASABE Annual International Meeting
  11. Rind, D., 1982. The influence of ground moisture conditions in North America on summer climate as modeled in the GISS GCM, Monthly Weather Rev., 100: 501-526
  12. Shin, S. C. & T. Y. An. 2007. 인공위성 자료를 활용한 광역증발산량의 산정방법 개발, The Journal of GIS Association of korea, 10(2): 70-80
  13. 기상청 홈페이지: http://www.kma.go.kr. Accessed 9 May 2008
  14. NASA WIST Primary Data Search: https://wist.echo.nasa.gov/api. Accessed 29 Apr. 2008

Cited by

  1. Evaluation of Evapotranspiration and Soil Moisture of SWAT Simulation for Mixed Forest in the Seolmacheon Catchment vol.12, pp.4, 2010, https://doi.org/10.5532/KJAFM.2010.12.4.289
  2. Assessing Climate Change Impact on Hydrological Components of Yongdam Dam Watershed Using RCP Emission Scenarios and SWAT Model vol.56, pp.3, 2014, https://doi.org/10.5389/KSAE.2014.56.3.019
  3. The Correlation Analysis Between SWAT Predicted Forest Soil Moisture and MODIS NDVI During Spring Season vol.51, pp.2, 2009, https://doi.org/10.5389/KSAE.2009.51.2.007
  4. Assessment of Climate Change Impact on Evapotranspiration and Soil Moisture in a Mixed Forest Catchment Using Spatially Calibrated SWAT Model vol.46, pp.6, 2013, https://doi.org/10.3741/JKWRA.2013.46.6.569