Articles | Volume 26, issue 20
https://doi.org/10.5194/hess-26-5391-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-5391-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Oct 2022
Research article |
| 27 Oct 2022
| 27 Oct 2022
A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records
Department of Mathematical Sciences, Norwegian University of Science and Technology, NTNU, Høgskoleringen 1, 7491 Trondheim, Norway
Norwegian Computing Center, NR, Postboks 114, Blindern, 0314 Oslo, Norway
Ingelin Steinsland
Department of Mathematical Sciences, Norwegian University of Science and Technology, NTNU, Høgskoleringen 1, 7491 Trondheim, Norway
Kolbjørn Engeland
The Norwegian Water Resources and Energy Directorate, NVE, Middelthuns gate 29, 0368 Oslo, Norway
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Estimating flood quantiles at data-scarce sites often involves single-duration regression models. However, floodplain management and reservoir design, for example, need estimates at several durations, posing challenges. Our flexible generalized additive model (GAM) enhances accuracy and explanation, revealing that single-duration models may underperform elsewhere, emphasizing the need for adaptable approaches.
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We combine systematic, historical, and paleo information to obtain flood information from the last 10 300 years for the Glomma River in Norway. We identify periods with increased flood activity (4000–2000 years ago and the recent 1000 years) that correspond broadly to periods with low summer temperatures and glacier growth. The design floods in Glomma were more than 20 % higher during the 18th century than today. We suggest that trends in flood variability are linked to snow in late spring.
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Short summary
The goal of this work was to make a map of the mean annual runoff for Norway for a 30-year period. We first simulated runoff by using a process-based model that models the relationship between runoff, precipitation, temperature, and land use. Next, we corrected the map based on runoff observations from streams by using a statistical method. We were also able to use data from rivers that only had a few annual observations. We find that the statistical correction improves the runoff estimates.
The goal of this work was to make a map of the mean annual runoff for Norway for a 30-year...
