Automated Approach for Rainfall-Runoff Model Generation

Tero J. Niemi, Gerald Krebs, Teemu Kokkonen

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

Manually constructing hydrological model descriptions for urban areas tends to be laborious due to the detailed mosaic land cover and the required high-resolution model setup. Here, the performance of a novel automated subcatchment generator with a detailed DEM-based surface flow routing is assessed against observations and manually constructed models. In general, the auto-generated models perform well against observations and comparably to manually constructed models regardless of the detail of land cover information input. The introduced inter-subcatchment connections may require previously acquired model parameters to be re-calibrated. This is due to the calibrated parameters in manually constructed models, even with high-resolution landuse, partly compensating for missing flow routes due to the larger scale used in subcatchment description.
Original languageEnglish
Title of host publication New Trends in Urban Drainage Modelling, UDM 2018
Subtitle of host publicationGreen Energy and Technology
EditorsGiorgio Mannina
PublisherSpringer
Pages597-602
ISBN (Electronic)978-3-319-99867-1
ISBN (Print)978-3-319-99866-4
DOIs
Publication statusPublished - 2018

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    Niemi, T. J., Krebs, G., & Kokkonen, T. (2018). Automated Approach for Rainfall-Runoff Model Generation. In G. Mannina (Ed.), New Trends in Urban Drainage Modelling, UDM 2018: Green Energy and Technology (pp. 597-602). Springer. https://doi.org/10.1007/978-3-319-99867-1_103