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) |
1 | Allen, R. G., L. S. Pereira, D. Raes, and M. Smith, 1998. Crop evapotranspiration-Guidelines for computing crop water requirements, FAO Irrigation and Drainage Paper 56, FAO, Rome, ITA. |
2 | Allen, R. G., M. Tasumi, and R. Trezza, 2007. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-Model, Journal of Irrigation and Drainage Engineering, 133(4): 380-394. DOI |
3 | Baik, J. and M. Choi, 2015. Evaluation of geostationary satellite (COMS) based Priestley-Taylor evapotranspiration, Agricultural Water Management, 159: 77-91. DOI |
4 | Kendy, E., P. Gerard-Marchant, M. T. Walter, Y. Zhang, C. Liu, and T. S. Steenhuis, 2003. A soil-water-balance approach to quantify groundwater recharge from irrigated cropland in the North China Plain, Hydrological Processes, 17(10): 2011-2031. DOI |
5 | Khan, M. S., U. W. Liaqat, J. Baik, and M. Choi, 2018. Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach, Agricultural and Forest Meteorology, 252: 256-268. DOI |
6 | Steduto P., T. C. Hsiao, E. Fereres, and D. Raes, 2012. Crop yield response to water, FAO Irrigation and Drainage Paper 66, FAO, Rome, ITA. |
7 | Kim, N., K. Kim, S. Lee, J. Cho, and Y. Lee, 2020. Retrieval of daily reference evapotranspiration for croplands in South Korea using machine learning with satellite images and numerical weather prediction data, Remote Sensing, 12(21): 3642. DOI |
8 | Lee S., K. Kim, Y. Kim, J. Kim, S. Park, Y. Yun, N. Kim, and Y. Lee, 2018. Deep learning-based estimation and mapping of evapotranspiration in cropland using local weather prediction model and satellite data, Journal of the Korean Cartographic Association, 18(3): 105-116 (in Korean with English abstract). DOI |
9 | Merlin, O., J. Chirouze, A. Olioso, L. Jarlan, G. Chehbouni, and G. Boulet, 2014. An image-based foursource surface energy balance model to estimate crop evapotranspiration from solar reflectance/thermal emission data (SEB-4S), Agricultural and Forest Meteorology, 184: 188-203. DOI |
10 | Sumner, D. M., 2001. Evapotranspiration from a Cypress and Pine Forest Subjected to Natural Fires, Volusia County, Florida, 1998-99. https://pubs.er.usgs.gov/publication/wri014245, Accessed on Dec. 22, 2020. |
11 | Thornthwaite, C. W., 1948. An approach toward a rational classification of climate, Geographical Review, 38(1): 55-94. DOI |
12 | Zhuang, Q. and B. Wu, 2015. Estimating evapotranspiration from an improved two-source energy balance model using ASTER satellite imagery, Water, 7(12): 6673-6688. DOI |