uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Assimilating flow and level data into an urban drainage surrogate model for forecasting flows and overflows
Tech Univ Denmark, Dept Environm Engn DTU Environm, Bldg 115, DK-2800 Lyngby, Denmark.
DHI, Agern Alle 5, DK-2970 Horsholm, Denmark.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. IHE Delft Inst Water Educ, Hydroinformat Chair Grp, Delft, Netherlands;Ctr Nat Hazards & Disaster Sci CNDS, Uppsala, Sweden.ORCID iD: 0000-0002-0913-9370
IHE Delft Inst Water Educ, Hydroinformat Chair Grp, Delft, Netherlands;Delft Univ Technol, Water Resources Sect, Delft, Netherlands;Russian Acad Sci, Inst Water Problems, Moscow, Russia.
Show others and affiliations
2019 (English)In: Journal of Environmental Management, ISSN 0301-4797, E-ISSN 1095-8630, Vol. 248, article id UNSP 109052Article in journal (Refereed) Published
Abstract [en]

It is crucial to be able to forecast flows and overflows in urban drainage systems to build good and effective real-time control and warning systems. Due to computational constraints, it may often be unfeasible to employ detailed 1D hydrodynamic models for real-time purposes, and surrogate models can be used instead. In rural hydrology, forecast models are usually built or calibrated using long historical time series of, for example, flow or level observations, but such series are typically not available for the ever-changing urban drainage systems. In the current study, we therefore used a fast, reservoir-based surrogate forecast model constructed from a 1D hydrodynamic urban drainage model. Thus, we did not rely directly on historical time series data. Forecast models should preferably be able to update their internal states based on observations to ensure the best initial conditions for each forecast. We therefore used the Ensemble Kalman filter to update the surrogate model before each forecast. Water level or flow observations were assimilated into the model either directly, or indirectly using rating curves. The model forecasts were validated against observed flows and overflows. The results showed that model updating improved the forecasts up to 2 h ahead, but also that updating using water level observations resulted in better flow forecasts than assimilation based on flow data. Furthermore, updating with water level observations was insensitive to changes in the noise formulation used for the Ensemble Kalman filter, meaning that the method is suitable for operational settings where there is often little time and data for fine-tuning.

Place, publisher, year, edition, pages
2019. Vol. 248, article id UNSP 109052
Keywords [en]
CSO, Data assimilation, Ensemble Kalman filter, Flow forecasts, Surrogate model, Urban drainage
National Category
Water Engineering
Identifiers
URN: urn:nbn:se:uu:diva-394946DOI: 10.1016/j.jenvman.2019.05.110ISI: 000485210300106PubMedID: 31466185OAI: oai:DiVA.org:uu-394946DiVA, id: diva2:1362792
Available from: 2019-10-21 Created: 2019-10-21 Last updated: 2019-10-21Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMed

Authority records BETA

Mazzoleni, Maurizio

Search in DiVA

By author/editor
Mazzoleni, Maurizio
By organisation
LUVAL
In the same journal
Journal of Environmental Management
Water Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf