Radar-raingauge data combination techniques : a revision and analysis of their suitability for urban hydrology
The applicability of the operational radar and raingauge networks for urban hydrology is insufficient. Radar rainfall estimates provide a good description of the spatiotemporal variability of rainfall; however, their accuracy is in general insufficient. It is therefore necessary to adjust radar meas...
| Veröffentlicht in: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 68(2013), 4 vom: 30., Seite 737-47 |
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| Weitere Verfasser: | , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2013
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| Zugriff auf das übergeordnete Werk: | Water science and technology : a journal of the International Association on Water Pollution Research |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't Review |
| Zusammenfassung: | The applicability of the operational radar and raingauge networks for urban hydrology is insufficient. Radar rainfall estimates provide a good description of the spatiotemporal variability of rainfall; however, their accuracy is in general insufficient. It is therefore necessary to adjust radar measurements using raingauge data, which provide accurate point rainfall information. Several gauge-based radar rainfall adjustment techniques have been developed and mainly applied at coarser spatial and temporal scales; however, their suitability for small-scale urban hydrology is seldom explored. In this paper a review of gauge-based adjustment techniques is first provided. After that, two techniques, respectively based upon the ideas of mean bias reduction and error variance minimisation, were selected and tested using as case study an urban catchment (∼8.65 km(2)) in North-East London. The radar rainfall estimates of four historical events (2010-2012) were adjusted using in situ raingauge estimates and the adjusted rainfall fields were applied to the hydraulic model of the study area. The results show that both techniques can effectively reduce mean bias; however, the technique based upon error variance minimisation can in general better reproduce the spatial and temporal variability of rainfall, which proved to have a significant impact on the subsequent hydraulic outputs. This suggests that error variance minimisation based methods may be more appropriate for urban-scale hydrological applications |
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| Beschreibung: | Date Completed 05.12.2013 Date Revised 02.12.2018 published: Print Citation Status MEDLINE |
| ISSN: | 0273-1223 |
| DOI: | 10.2166/wst.2013.300 |