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| Titel |
Singularity-sensitive gauge-based radar rainfall adjustment methods for urban hydrological applications |
| VerfasserIn |
L.-P. Wang, S. Ochoa-Rodríguez, C. Onof, P. Willems |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 9 ; Nr. 19, no. 9 (2015-09-29), S.4001-4021 |
| Datensatznummer |
250120816
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| Publikation (Nr.) |
 copernicus.org/hess-19-4001-2015.pdf |
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| Zusammenfassung |
| Gauge-based radar rainfall adjustment techniques have been widely used
to improve the applicability of radar rainfall estimates to
large-scale hydrological modelling. However, their use for urban
hydrological applications is limited as they were mostly developed
based upon Gaussian approximations and therefore tend to smooth off
so-called "singularities" (features of a non-Gaussian field) that
can be observed in the fine-scale rainfall structure. Overlooking the
singularities could be critical, given that their distribution is
highly consistent with that of local extreme magnitudes. This
deficiency may cause large errors in the subsequent urban hydrological
modelling. To address this limitation and improve the applicability of
adjustment techniques at urban scales, a method is proposed herein
which incorporates a local singularity analysis into existing
adjustment techniques and allows the preservation of the singularity
structures throughout the adjustment process. In this paper the
proposed singularity analysis is incorporated into the Bayesian
merging technique and the performance of the resulting
singularity-sensitive method is compared with that of the original
Bayesian (non singularity-sensitive) technique and the commonly used
mean field bias adjustment. This test is conducted using as case study
four storm events observed in the Portobello catchment
(53 km2) (Edinburgh, UK) during 2011 and for which radar
estimates, dense rain gauge and sewer flow records, as well as
a recently calibrated urban drainage model were available. The results
suggest that, in general, the proposed singularity-sensitive method
can effectively preserve the non-normality in local rainfall
structure, while retaining the ability of the original adjustment
techniques to generate nearly unbiased estimates. Moreover, the
ability of the singularity-sensitive technique to preserve the
non-normality in rainfall estimates often leads to better reproduction
of the urban drainage system's dynamics, particularly of peak runoff flows. |
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