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Pan coefficient sensitivity to environment variables across China.

Authors :
Wang, Kaiwen
Liu, Xiaomang
Tian, Wei
Li, Yanzhong
Liang, Kang
Liu, Changming
Li, Yuqi
Yang, Xiaohua
Source :
Journal of Hydrology. May2019, Vol. 572, p582-591. 10p.
Publication Year :
2019

Abstract

• Pan coefficients (K p) of China D20 pans ranged from 0.29 to 0.91 across China. • The seasonal relationship of K p was Summer > Annual > Autumn ∼ Spring ∼ Winter. • K p of the China D20 pan was most sensitive to relative humidity. Data of open water evaporation (E ow), such as evaporation of lake and reservoir, have been widely used in hydraulic and hydrological engineering projects, and water resources planning and management in agriculture, forestry and ecology. Because of the low-cost and maneuverability, measuring the evaporation of a pan has been widely regarded as a reliable approach to estimate E ow through multiplying an appropriate pan coefficient (K p). K p is affected by geometry and materials of a pan, and complex surrounding environment variables. However, the relationship between K p and different environment variables is unknown. Thus, this study chose China D20 pan as an example, used meteorological observations from 767 stations and introduced the latest PenPan model to analyze the sensitivity of K p to different environment variables. The results show that, the distribution of annual K p had a strong spatial gradient. For all the stations, annual K p ranged from 0.31 to 0.89, and decreased gradually from southeast to northwest. The sensitivity analysis shows that for China as a whole, K p was most sensitive to relative humidity, followed by air temperature, wind speed and sunshine duration. For 767 stations in China, K p was most sensitive to relative humidity for almost all the stations. For stations north of Yellow River, wind speed and sunshine duration were the next sensitive variables; while for stations south of Yellow River, air temperature was the next sensitive variable. The method introduced in this study could benefit estimating and predicting K p under future changing environment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00221694
Volume :
572
Database :
Academic Search Index
Journal :
Journal of Hydrology
Publication Type :
Academic Journal
Accession number :
139236749
Full Text :
https://doi.org/10.1016/j.jhydrol.2019.03.039