Abstract

Precipitation time series with high temporal resolution are desired for hydrological modelling and flood studies. Yet the choice of an appropriate resolution is not straightforward because the use of too high a temporal resolution increases the data requirements, computational costs and, presumably, associated uncertainty, while performance improvement may be indiscernible. In this study, the effect of averaging hourly precipitation on model performance and associated uncertainty is investigated using two data sources: station network precipitation (SNP) and radar-based precipitation (RBP). From these datasets, time series of different temporal resolutions were generated, and runoff was simulated for 13 pre-alpine catchments with a bucket-type model. Our results revealed that different temporal resolutions were required for an acceptable model performance depending on the catchment size and data source. These were 1-12h for small (16-59km(2)), 3-21h for medium (60-200km(2)), and 24h for large (200-939km(2)) catchments.

Keywords

radar-based precipitation; station network precipitation; averaging length; uncertainty; Bayesian methods; bucket-type model

Published in

Hydrological Sciences Journal
2018, Volume: 63, number: 1, pages: 1-16
Publisher: TAYLOR & FRANCIS LTD

UKÄ Subject classification

Oceanography, Hydrology, Water Resources


Publication identifier

DOI: https://doi.org/10.1080/02626667.2017.1410279

Permanent link to this page (URI)

https://res.slu.se/id/publ/98716