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| Titel |
High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications |
| VerfasserIn |
Nadav Peleg, Frank Blumensaat, Peter Molnar, Simone Fatichi, Paolo Burlando |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250129343
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| Publikation (Nr.) |
 EGU/EGU2016-9441.pdf |
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| Zusammenfassung |
| Urban drainage response is highly dependent on the spatial and temporal structure of rainfall.
Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a
fundamental step to fully assess urban drainage system reliability and related uncertainties.
This is even more relevant when considering extreme rainfall events. However, the current
space-time rainfall models have limitations in capturing extreme rainfall intensity
statistics for short durations. Here, we use the STREAP (Space-Time Realizations
of Areal Precipitation) model, which is a novel stochastic rainfall generator for
simulating high-resolution rainfall fields that preserve the spatio-temporal structure of
rainfall and its statistical characteristics. The model enables a generation of rain
fields at 102 m and minute scales in a fast and computer-efficient way matching the
requirements for hydrological analysis of urban drainage systems. The STREAP
model was applied successfully in the past to generate high-resolution extreme
rainfall intensities over a small domain. A sub-catchment in the city of Luzern
(Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP
to disaggregate extreme rainfall intensities for urban drainage applications; (ii)
assessing the role of stochastic climate variability of rainfall in flow response and
(iii) evaluate the degree of non-linearity between extreme rainfall intensity and
system response (i.e. flow) for a small urban catchment. The channel flow at the
catchment outlet is simulated by means of a calibrated hydrodynamic sewer model. |
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