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http://dx.doi.org/10.7780/kjrs.2020.36.6.1.14

A Comparison between the Reference Evapotranspiration Products for Croplands in Korea: Case Study of 2016-2019  

Kim, Seoyeon (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Jeong, Yemin (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Cho, Subin (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Youn, Youjeong (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Kim, Nari (Geomatics Research Institute, Pukyong National University)
Lee, Yangwon (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.36, no.6_1, 2020 , pp. 1465-1483 More about this Journal
Abstract
Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.
Keywords
Reference evapotranspiration; Latent heat flux; Cropland; Machine learning;
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