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제한적인 기상자료 조건에서의 잠재증발산량 추정을 위한 FAO56 Penman-Monteith 방법의 적용성 분석 - 안동댐 유역을 사례로 -Applicability Analysis of FAO56 Penman-Monteith Methodology for Estimating Potential Evapotranspiration in Andong Dam Watershed Using Limited Meteorological Data

Other Titles
Applicability Analysis of FAO56 Penman-Monteith Methodology for Estimating Potential Evapotranspiration in Andong Dam Watershed Using Limited Meteorological Data
Authors
김세진김문일임철희이우균김백조
Issue Date
2017
Publisher
한국기후변화학회
Keywords
Potential Evapotranspiration; FAO56 Penman-Monteith Methodology; Hargreaves Equation; Limited Data
Citation
한국기후변화학회지, v.8, no.2, pp.125 - 143
Indexed
KCI
OTHER
Journal Title
한국기후변화학회지
Volume
8
Number
2
Start Page
125
End Page
143
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/86051
DOI
10.15531/KSCCR.2017.8.2.125
ISSN
2093-5919
Abstract
This study is conducted to estimate potential evapotranspiration of 10 weather observing systems in Andong Dam watershed with FAO56 Penman-Monteith (FAO56 PM) methodology using the meteorological data from 2013 to 2014. Also, assuming that there is no solar radiation data, humidity data or wind speed data, the potential evapotranspiration was estimated by FAO56 PM and the results were evaluated to discuss whether the methodology is applicable when meteorological dataset is not available. Then, the potential evapotranspiration was estimated with Hargreaves method and compared with the potential evapotranspiration estimated by FAO56 PM only with the temperature dataset. As to compare the potential evapotranspiration estimated from the complete meteorological dataset and that estimated from limited dataset, statistical analysis was performed using the Root Mean Square Error (RMSE), the Mean Bias Error (MBE), the Mean Absolute Error (MAE) and the coefficient of determination (R2). Also the Inverse Distance Weighted (IDW) method was performed to conduct spatial analysis. From the result, even when the meteorological data is limited, FAO56 PM showed relatively high accuracy in calculating potential evapotranspiration by estimating the meteorological data.
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