Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 25, issue 9
Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-4773-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-4773-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 9
Research article
 | 
02 Sep 2021
Research article |  | 02 Sep 2021

Bias-correcting input variables enhances forecasting of reference crop evapotranspiration

Qichun Yang, Quan J. Wang, Kirsti Hakala, and Yating Tang

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Cited articles

Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: FAO Irrigation and drainage paper No.56, Crop evapotranspiration: guidelines for computing crop water requirements, Food and Agriculture Organization of the United Nations (FAO), Rome, Italy, 1998. 
Bachour, R., Maslova, I., Ticlavilca, A. M., Walker, W. R., and Mckee, M.: Wavelet-multivariate relevance vector machine hybrid model for forecasting daily evapotranspiration, Stoch. Environ. Res. Risk Assess., 30, 103–117, https://doi.org/10.1007/s00477-015-1039-z, 2016. 
Ballesteros, R., Ortega, F., and Angel, M.: FORETo: New software for reference evapotranspiration forecasting, J. Arid Environ., 124, 128–141, https://doi.org/10.1016/j.jaridenv.2015.08.006, 2016. 
Boe, J., Terray, L., Habets, F., and Martin, E.: Statistical and dynamical downscaling of the Seine basin climate for hydro-meteorological studies, Int. J. Clim., 27, 1463–1655, https://doi.org/10.1002/joc.1602, 2007. 
Cai, J., Liu, Y., Lei, T., and Pereira, S. L.: Estimating reference evapotranspiration with the FAO Penman – Monteith equation using daily weather forecast messages, Agric. For. Meteorol., 145, 22–35, https://doi.org/10.1016/j.agrformet.2007.04.012, 2007. 
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Forecasts of water losses from land surface to the air are highly valuable for water resource management and planning. In this study, we aim to fill a critical knowledge gap in the forecasting of evaporative water loss. Model experiments across Australia clearly suggest the necessity of correcting errors in input variables for more reliable water loss forecasting. We anticipate that the strategy developed in our work will benefit future water loss forecasting and lead to more skillful forecasts.
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