Adequacy evaluation of the GLDAS and GLEAM evapotranspiration by eddy covariance method

Yeongil Lee; Baeseok Im; Kiyoung Kim; Kyounghoon Rhee

doi:10.3741/JKWRA.2020.53.10.889

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2020 Vol.53, Issue 10 Preview Page Next Page

Research Article

Adequacy evaluation of the GLDAS and GLEAM evapotranspiration by eddy covariance method 에디공분산 방법에 의한 GLDAS와 GLEAM 증발산량의 적정성 평가

31 October 2020. pp. 889-902

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Abstract

This study was performed in Seolmacheon basin to evaluate the adequacy of GLDAS (Global Land Data Assimilation System) and GLEAM (Global Land Evaporation Amsterdam Model) evapotranspiration data. The verification data necessary for the evaluation of adequacy were calculated after processing the latent heat flux data produced in the Seolmacheon basin with the Koflux program. In order to gap-fill the empty period, alternative evapotranspiration was calculated in three ways: FAO-PM (Food and Agriculture Organization-Penman Monteith), MDV (Mean Diurnal Variation) and Kalman Filter. This study selected Kalman Filter method as the data gap-filling method because it showed the best Bias and RMSE among the three methods. The amount of GLDAS spatial evapotranspiration was calculated as Noah (version 2.1) with a time interval of 3 hours and a spatial resolution of 0.25°. The amount of GLEAM spatial evapotranspiration was calculated using GLEAM (version 3.1a). This study evaluated the spatial evapotranspiration of GLDAS and GLEAM as the evapotranspiration based on eddy covariance. As a result of evaluation, GLDAS spatial evapotranspiration showed better results than GLEAM. Accordingly, in this study, the GLDAS method was proposed as a method for calculating the amount of spatial evapotranspiration in the Seolmacheon basin.

Keywords

GLDAS

GLEAM

FAO-PM

MDV

Kalman filter

본 연구에서는 GLDAS (Global Land Data Assimilation System)와 GLEAM (Global Land Evaporation Amsterdam Model) 증발산량의 적정성을 평가하기 위해 설마천 유역에서 관측된 에디공분산 기반의 잠열 플럭스를 검증자료로 활용하였다. 잠열 플럭스로부터 증발산량을 산정하기 위해 Koflux 프로그램으로 자료처리하였으며, 자료처리 후 발생된 빈구간을 보충(Gap-filling)하기 위해 FAO-PM (Food and Agriculture Organization-Penman Monteith), 평균 일변동(Mean Diurnal Variation, MDV), 칼만 필터(Kalman Filter)의 3가지 방법으로 대체 증발산량을 산정하였다. 본 연구에서는 3가지 방법 중 칼만 필터(Kalman Filter) 기반의 증발산량이 우수한 Bias와 RMSE를 보여 자료보충 방법으로 채택하였다. 공간증발산량은 GLDAS의 경우 Noah (version 2.1, 3시간, 공간해상도 0.25°)로 추출하였으며 GLEAM의 경우는 GLEAM(version 3.1a, 1일, 공간해상도 0.25°)를 이용하였다. GLDAS와 GLEAM의 공간증발산량을 에디공분산 기반의 증발산량으로 적정성을 평가한 결과, GLDAS의 증발산량이 에디공분산 기반과 비교적 적정한 결과를 나타내었다.

키워드

GLDAS

GLEAM

FAO-PM

MDV

Kalman Filter

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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 : 53
No :10
Pages :889-902
Received Date : 2020-07-29
Revised Date : 2020-09-02
Accepted Date : 2020-09-02
DOI :https://doi.org/10.3741/JKWRA.2020.53.10.889

Journal of Korea Water Resources Association ISSN:2799-8746(Print) 2799-8754(Online) 한국수자원학회 논문집

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