H008-0002
A model combining modified satellite–based Priestley Taylor with the best–fit ecosystem–level conductance to partition evapotranspiration at flux tower sites

Monday, 7 December 2020
Poster
Jongjin Baik1, Minha Choi2, My Nguyen MS3, Hao Yuefeng4 and Hyunho Jeon3, (1)Sungkyunkwan University, Suwon, Gyeonggi-do, Korea, Republic of (South), (2)Sungkyunkwan University, Environment and Remote Sensing Laboratory, Department of Water Resources, Graduate School of Water Resources, Suwon, Gyeonggi-do, South Korea, (3)Civil, Architectural and Environmental System Engineering, Sungkyunkwan University, Suwon, South Korea, (4)Department of Water Resources, Graduate School of Water Resources, Sungkyunkwan University, Suwon, South Korea
Abstract:
Evapotranspiration (ET) is basically partitioned into three main components, including transpiration (T), soil evaporation (Esoil), and interception vegetation evaporation (Eic). ET was reported to account for 60% of terrestrial precipitation, emphasizing the central position of ET in the surface water balance. The ratio of T to ET, denoted T/ET, is further investigated for better understanding and prediction the hydrological cycle, but it is extremely challenging. Therefore, the ET partitioning models have been rapidly developed by employing remote sensing–based and ground–based assessments. However, previous models are likely to ignore Eic in estimation, leading to overestimate or underestimate of T/ET. To improve the accuracy of T/ET estimation, this study proposed a Modified Ecosystem Conductance model (MEC) to partition ET based on the conductance fraction. The MEC model can be simply processed by utilizing dataset of flux tower network. Additionally, proposed technique can provide an efficient performance in both vegetation and non–vegetation ecosystems. This study contributes a comprehensive knowledge of ET mechanism, helping to control the ecosystem dynamics and the variation of hydrological cycle under the climatic and environmental changes.

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07049029).This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2019R1A2B5B01070196).

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