Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-4773-2021
https://doi.org/10.5194/hess-25-4773-2021
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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Latest update: 13 Dec 2024
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Short summary
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.