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Sewer Flow Prediction at a Large Urban Scale: Influence of Radar Rainfall Spatial Resolution

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New Trends in Urban Drainage Modelling (UDM 2018)

Part of the book series: Green Energy and Technology ((GREEN))

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Abstract

There is a growing interest in using radar rainfall data to evaluate the performance of urban drainage systems in near real time. This paper describes a study based on a large (55 km2) urban catchment in northern Italy. Different spatial resolutions of radar data have been compared and used as input to a numerical hydrological-hydraulic model of the drainage system, constructed by means of Infoworks CS software. The results show that the spatial resolution of weather radar data plays a significant role when modelling the hydrological behaviour of the drainage system and using different resolutions may result in significant differences in peak flows and runoff volumes.

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Author information

Authors and Affiliations

  1. CIRI-EC Interdepartmental Centre for Industrial Research in Building and Construction, University of Bologna, Bologna, Italy

    Sara Simona Cipolla

  2. DICAM Department of Civil, Chemical, Environmental, and Materials Engineering, University of Bologna, Bologna, Italy

    Giulia Paola Di Ventura, Marco Maglionico & Attilio Castellarin

  3. ARPAE Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, Emilia-Romagna, Italy

    Pier Paolo Alberoni

Authors
  1. Sara Simona Cipolla
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  2. Giulia Paola Di Ventura
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  3. Marco Maglionico
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  4. Pier Paolo Alberoni
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  5. Attilio Castellarin
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Corresponding author

Correspondence to Sara Simona Cipolla .

Editor information

Editors and Affiliations

  1. Ingegneria Civile, Ambientale, Aerospaziale, dei Materiali, University of Palermo, Palermo, Italy

    Giorgio Mannina

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Cipolla, S.S., Di Ventura, G.P., Maglionico, M., Alberoni, P.P., Castellarin, A. (2019). Sewer Flow Prediction at a Large Urban Scale: Influence of Radar Rainfall Spatial Resolution. In: Mannina, G. (eds) New Trends in Urban Drainage Modelling. UDM 2018. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-99867-1_137

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  • DOI: https://doi.org/10.1007/978-3-319-99867-1_137

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99866-4

  • Online ISBN: 978-3-319-99867-1

  • eBook Packages: EnergyEnergy (R0)

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