Browse > Article
http://dx.doi.org/10.7780/kjrs.2019.35.6.1.1

A Study on the Calculation of Evapotranspiration Crop Coefficient in the Cheongmi-cheon Paddy Field  

Kim, Kiyoung (Research & Development Division, Korea Institute of Hydrological Survey)
Lee, Yongjun (Research & Development Division, Korea Institute of Hydrological Survey)
Jung, Sungwon (Korea Institute of Hydrological Survey)
Lee, Yeongil (Research & Development Division, Korea Institute of Hydrological Survey)
Publication Information
Korean Journal of Remote Sensing / v.35, no.6_1, 2019 , pp. 883-893 More about this Journal
Abstract
In this study, crop coefficients were calculated in two different methods and the results were evaluated. In the first method, appropriateness of GLDAS-based evapotranspiration was evaluated by comparing it with observed data of Cheongmi-cheon (CMC) Flux tower. Then, crop coefficient was calculated by dividing actual evapotranspiration with potential evapotranspiration that derived from GLDAS. In the second method, crop coefficient was determined by using MLR (Multiple Linear Regression) analysis with vegetation index (NDVI, EVI, LAI and SAVI) derived from MODIS and in-situ soil moisture data observed in CMC, In comparison of two crop coefficients over the entire period, for each crop coefficient GLDAS Kc and SM&VI Kc, shows the mean value of 0.412 and 0.378, the bias of 0.031 and -0.004, the RMSE of 0.092 and 0.069, and the Index of Agree (IOA) of 0.944 and 0.958. Overall, both methods showed similar patterns with observed evapotranspiration, but the SM&VI-based method showed better results. One step further, the statistical evaluation of GLDAS Kc and SM&VI Kc in specific period was performed according to the growth phase of the crop. The result shows that GLDAS Kc was better in the early and mid-phase of the crop growth, and SM&VI Kc was better in the latter phase. This result seems to be because of reduced accuracy of MODIS sensors due to yellow dust in spring and rain clouds in summer. If the observational accuracy of the MODIS sensor is improved in subsequent study, the accuracy of the SM&VI-based method will also be improved and this method will be applicable in determining the crop coefficient of unmeasured basin or predicting the crop coefficient of a certain area.
Keywords
crop coefficient; evapotranspiration; soil moisture; vegetation index;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Allen, R. G., L. S. Pereira, D. Raes, and M. Smith, 1998. FAO Irrigation and drainage paper No. 56, Rome: Food and Agriculture Organization of the United Nations, 56(97): e156.
2 Allen, R. G., L. S. Pereira, M. Smith, D. Raes, and J. L. Wright, 2005. FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions, Journal of Irrigation and Drainage Engineering, 131(1): 2-13.   DOI
3 Allen, R. G., M. Smith, A. Perrier, and L. S. Pereira, 1994. An update for the definition of reference evapotranspiration, ICID Bulletin, 43(2): 1-34.
4 Baumgartner, A. and E. Reichel, 1975. The World Water Balance; Mean Annual Global, Continental and Maritime Precipitation, Evaporation and Run-Off, Elsevier, Amsterdam, Netherlands, p. 179.
5 Baik, J., J. Jeong, J. Park, and M. Choi, 2019. A study on the analyzing of uncertainty for actual evapotranspiration: Flux tower, satellite-based and reanalysis based dataset, Journal of Korea Water Resource Association, 52(1): 11-19.
6 Baldocchi, D. D., S. Ma, S. Rambal, L. Misson, J. M. Ourcival, J. M. Limousin, and D. Papale, 2010. On the differential advantages of evergreenness and deciduousness in mediterranean oak woodlands: a Flux perspective, Ecological Applications, 20(6): 1583-1597.   DOI
7 Byun, K., J. Shin, Y. Lee, and M. Choi, 2013. Validation of Net Radiation Measured from Fluxtower Based on Eddy Covariance Method: Case Study in Seolmacheon and Cheongmicheon Watersheds, Journal of Korea Water Resources Association, 46(2): 111-122.   DOI
8 Doorenbos, J. and W. O. Pruitt, 1977. Crop Water Requirement: Food and Agriculture Organization of the United Nations, FAO Irrigation and Drainage Paper 24, Rome, Italy, p. 144.
9 Jung, M. and E. Chang, 2013. Land-Cover Vegetation Change Detection based on Harmonic Analysis of MODIS NDVI Time Series Data, Korean Journal of Remote Sensing, 29(4): 351-360 (in Korean with English abstract).   DOI
10 Jensen, M. E. and R. G. Allen, 2000. Evolution of practical ET estimating methods. In National irrigation symposium, Proc. of the 4th Decennial Symposium, Arizona, USA, Nov. 14-16, pp. 52-65.
11 Jiang, Z., A. R. Huete, K. Didan, and T. Miura, 2008. Development of a two-band enhanced vegetation index without a blue band, Remote Sensing of Environment, 112(10): 3833-3845.   DOI
12 Huete, A. R., 1988. A soil-adjusted vegetation index (SAVI), Remote Sensing of Environment, 25(3): 295-309.   DOI
13 Kwon, H. J. and J. Kim, 2010. KoFlux's progress: background, status and direction, Korean Journal of Agricultural and Forest Meteorology, 12(4): 241-263.   DOI
14 Kamble, B., A. Kilic, and K. Hubbard, 2013. Estimating crop coefficients using remote sensing-based vegetation index, Remote Sensing, 5(4): 1588-1602.   DOI
15 Ko, J., G. Piccinni, T. Marek, and T. Howell, 2009. Determination of growth-stage-specific crop coefficients (Kc) of cotton and wheat, Agricultural Water Management, 96(12): 1691-1697.   DOI
16 Kim, K., J. Baik, J. Lee, Y. Lee, S. Jung, and M. Choi, 2016. An assessment and analysis of the gap-filling techniques for revising missing data of Flux tower based Evapotranspiration-FAO-PM, MDV, and Kalman filter, Journal of Korean Society of Hazard Mitigation, 16(6): 95-107.   DOI
17 Park, J., J. Baik, and M. Choi, 2017. Satellite-based crop coefficient and evapotranspiration using surface soil moisture and vegetation indices in Northeast Asia, Catena, 156: 305-314.   DOI
18 Qi, J., A. Chehbouni, A. R. Huete, Y. H. Kerr, and S. Sorooshian, 1994. A modified soil adjusted vegetation index, Remote Sensing of Environment, 48(2): 119-126.   DOI