Articles | Volume 26, issue 20
Hydrol. Earth Syst. Sci., 26, 5391–5410, 2022
Hydrol. Earth Syst. Sci., 26, 5391–5410, 2022
Research article
27 Oct 2022
Research article | 27 Oct 2022

A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records

Thea Roksvåg et al.

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Cited articles

Bakka, H., Rue, H., Fuglstad, G.-A., Riebler, A., Bolin, D., Illian, J., Krainski, E., Simpson, D., and Lindgren, F.: Spatial modeling with R-INLA: A review, WIREs Computational Statistics, 10, e1443,, 2018. a
Banerjee, S., Gelfand, A., and Carlin, B.: Hierarchical Modeling and Analysis for Spatial Data, vol. 101 of Monographs on Statistics and Applied Probability, Chapman & Hall, ISBN 978-1584884101, 2003. a
Beldring, S., Roald, L. A., and Voksø, A.: Arenningskart for Norge. Årsmiddelverdier for avrenning 1961–1990, Tech. Rep. Oslo: NVE, ISSN 1501-2840, (last access: last access: 19 October 2022), 2002. a, b, c
Beldring, S., Engeland, K., Roald, L. A., Sælthun, N. R., and Voksø, A.: Estimation of parameters in a distributed precipitation-runoff model for Norway, Hydrol. Earth Syst. Sci., 7, 304–316,, 2003. a
Bergström, S.: Development and Application of a Conceptual Runoff Model for Scandinavian Catchments, SMHI, Norrköping, Sweden, RHO 7, 134 pp., 1976. a, b
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.