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2019 Vol.52, Issue 1 Preview Page

Research Article

Merging technique for evapotranspiration based on in-situ, satellite, and reanalysis data using modifed KGE fusion method

수정된 KGE 방법을 활용한 지점, 인공위성, 재분석 자료 기반 증발산 융합 기술

Jongjin Baika
,
Jaehwan Jeongb
,
Jongmin Parkc
,
Minha Choid*
백 종진a
,
정 재환b
,
박 종민c
,
최 민하d*
aPh.D, Center for Built Environment, Sungkyunkwan University
bPh.D Candidate, Department of Water Resources, Sungkyunkwan University
cPh.D Candidate, Department of Civil and Environmental Engineering, University of Maryland
dProfessor, Department of Water Resources, Sungkyunkwan University
a성균관대학교 건설환경연구소 박사후연구원
b성균관대학교 수자원전문대학원 박사과정
c메릴랜드대학교 건설환경공학과 박사과정
d성균관대학교 수자원전문대학원 교수
* Corresponding Author
31 January 2019. pp. 61-70
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Abstract

The modified Kling-Gupta efficiency fusion method to merge actual evapotranspiration was proposed and compared with the simple Taylor skill’s score method using Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MODIS Global Evapotranspiration Project (MOD16), and the flux tower on three different land cover types over the Korean peninsula and China. In the results of the weights estimated from two actual evapotranspiration merging techniques (i.e., STS and KGF), the weights of reanalysis data (i.e, GLDAS and GLEAM) in cropland and grassland showed similar performance, while the results of weights are different according to the merging techniques in forest. Both two merging techniques showed better results than original dataset in grassland and forest. However, there were no improvement in cropland compared to the other land cover types. The results of the KGF method slightly improved compared to those of the STS in grassland and forest.

Keywords
Evapotranspiration
Satellite
Flux tower
Merging technique
Reanalysis dataset

실제증발산 자료를 융합하기 위한 Modified Kling-Gupta efficiency Fusion (KGF)방법을 제시하였고, 인공위성 및 재분석 증발산 자료인 Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MODIS Global Evapotranspiration Project (MOD16)를 활용하여 Simple Taylor skill’s Score (STS)와 비교하였다. 한반도와 중국의 세가지 land cover type(i.e., cropland, grassland, forest)을 가진 flux tower에서 비교 검증을 실시하였다. 실제증발산의 융합 방법인 STS와 KGF로 계산된 가중치의 결과를 확인하면, cropland와 grassland에서 재분석 자료(GLDAS, GLEAM)가 높은 가중치 영향을 나타내지만, forest에서 융합 방법에 따라 가중치 영향이 다르게 나타났다. 전반적으로 실제증발산 융합 방법 적용 결과의 비교에서는 cropland에서는 융합에 사용된 자료에 비하여 높은 개선이 이뤄지지 않았지만, grassland와 forest 에서는 개선이 이뤄졌다. 두 방법 중 KGF의 결과가 STS의 결과에 비하여 약간 개선되는 결과를 나타내었다.

키워드
증발산
인공위성
플럭스타워
융합방법
재분석자료
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Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 52
  • No :1
  • Pages :61-70
  • Received Date : 2018-10-08
  • Revised Date : 2018-11-26; 2018-12-04
  • Accepted Date : 2018-12-04
  • DOI :https://doi.org/10.3741/JKWRA.2019.52.1.61
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