Department of Landscape, Spatial and Infrastructure Sciences, Institute of Statistics, University of Natural Resources and Life Sciences, Vienna, Peter-Jordan-Strasse 82/I, 1190 Vienna, Austria
Michael Melcher
Institute of Information Management, FH JOANNEUM – University of Applied Sciences, Graz, Austria
Department of Landscape, Spatial and Infrastructure Sciences, Institute of Statistics, University of Natural Resources and Life Sciences, Vienna, Peter-Jordan-Strasse 82/I, 1190 Vienna, Austria
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Total article views: 3,767 (including HTML, PDF, and XML)
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2,911
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3,767
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Total: 3,767
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EndNote: 93
Views and downloads (calculated since 10 May 2022)
Cumulative views and downloads
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Total article views: 2,683 (including HTML, PDF, and XML)
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2,071
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2,683
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HTML: 2,071
PDF: 551
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Total: 2,683
BibTeX: 72
EndNote: 86
Views and downloads (calculated since 13 Sep 2022)
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840
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1,084
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HTML: 840
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BibTeX: 11
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Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 3,767 (including HTML, PDF, and XML)
Thereof 3,666 with geography defined
and 101 with unknown origin.
Total article views: 2,683 (including HTML, PDF, and XML)
Thereof 2,663 with geography defined
and 20 with unknown origin.
Total article views: 1,084 (including HTML, PDF, and XML)
Thereof 1,003 with geography defined
and 81 with unknown origin.
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.
Our study uses a statistical boosting model for estimating low flows on a monthly basis, which...
