Sensible and latent heat flux at semi-arid and arid region, i.e., evapotranspiration, has been researched for long time because it serves an important role for water resource issues. However, the issues have not solved completely yet. Accordingly, by applying the Bowen ratio concept on the soil surface, the sensible and latent heat fluxes are reciprocally estimated using single height temperature (Tz) and humidity (rehz) with the net radiation (Rn) and heat flux into the ground (G). The procedure proposed by authors initially estimates the soil surface temperature (Ts) and the relative humidity (rehs) using optimization techniques. The method is remarkably effective to expand for estimating evapotranspiration at various regions. The validity of the method is confirmed by the latent heat flux (lE) and sensible heat flux (H) observed by the eddy covariance method. The hourly change of the lE, H, Ts and rehs on the soil surface, yearly change of lE and H and relationship of estimated lE and H versus observed are clarified. Yearly change of evapotranspiration is also estimated. The analysis is performed by general method (1), conventional method and general method (2). Above results are very useful for water resources issue and irrigation planning. The research is conducted using hourly data at eight globally dispersed sites using FLUXNET.
References
[1]
Maruyama, T. and Segawa, M. (2016) Reciprocal Analysis of Sensible and Latent Heat Fluxes in a Forest Region Using Single Height Temperature and Humidity Based on the Bowen Ratio Concept. Journal of Water Resource and Protection, 8, 724-742.
https://doi.org/10.4236/jwarp.2016.87059
[2]
Maruyama, T. and Segawa, M. (2016) Application of the Reciprocal Analysis for Sensible and Latent Heat Fluxes with Evapotranspiration at a Humid Region. Journal of Mordan Hydrology, 6, 230-252. https://doi.org/10.4236/ojmh.2016.64019
[3]
Kondo, J. (1996) Water and Heat Balance on Soil Surface. In: Kondo, J., Ed., Meteorology on Water Environment, Asakura Publishing Ltd., Tokyo, 128-159.
[4]
Twine, T.E., Kustas, W.P., Norman, J.M., Cook, D.R., Houser, P.R., Meyers, T.P., Prueger, J.H., Starks, P.J. and Wesely, M.L. (2000) Correcting Eddy-Covariance Flux Underestimates over a Grassland. Agricultural and Forest Meteorology, 103, 279-300.
https://doi.org/10.1016/S0168-1923(00)00123-4
[5]
Wilson, K., et al. (2002) Energy Balance Closure at FLUXNET Sites. Agricultural and Forest Meteorology, 113, 223-243. https://doi.org/10.1016/S0168-1923(02)00109-0
[6]
Allen, R. (2008) Quality Assessment of Weather Data and Micrometeorological Flux Impact on Evapotranspiration Calculation. Journal of Agricultural Meteorology, 64, 191-204.
https://doi.org/10.2480/agrmet.64.4.5
[7]
Beringer, J., Cunningham, S. and Hutley, L. (2014) Sturt Plains Ozflux L2 Data.
[8]
Billesbach, D.B., Torn, J.A. and Margaret, S. (2010) ARM USDA UNL OSU Woodward Switchgrass 2. US-Br3 AmeriFlux L2 Data.
http://cdiac.esd.ornl.gov/programs/ameriflux/data_system/aaARM_USDA_UNL_OSU_Woodward_
Switchgrass_2_pf.html
[9]
Ceschia, E. and Tallec, T. (2008) Lamasquere (FR-Lam) European Fluxes Database Cluster L2 Data.
[10]
Eamus, D. and Cleverly, J. (2013) Ti Tree East Ozflux L2 Data.
[11]
Beringer, J. and Hutley, L. (2010) Dry River Ozflux L2 Data.