Articles | Volume 26, issue 17
https://doi.org/10.5194/hess-26-4553-2022
https://doi.org/10.5194/hess-26-4553-2022
Research article
 | 
13 Sep 2022
Research article |  | 13 Sep 2022

Low-flow estimation beyond the mean – expectile loss and extreme gradient boosting for spatiotemporal low-flow prediction in Austria

Johannes Laimighofer, Michael Melcher, and Gregor Laaha

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Latest update: 04 Mar 2024
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Short summary
Our study uses a statistical boosting model for estimating low flows on a monthly basis, which can be applied to estimate low flows at sites without measurements. We use an extensive dataset of 260 stream gauges in Austria for model development. As we are specifically interested in low-flow events, our method gives specific weight to such events. We found that our method can considerably improve the predictions of low-flow events and yields accurate estimates of the seasonal low-flow variation.