Statistical analysis of error propagation from radar rainfall to hydrological models
This study attempts to characterise the manner with which inherent error in radar rainfall estimates input influence the character of the stream flow simulation uncertainty in validated hydrological modelling. An artificial statistical error model described by Gaussian distribution was developed to...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2013-04-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | http://www.hydrol-earth-syst-sci.net/17/1445/2013/hess-17-1445-2013.pdf |
| _version_ | 1811204488025866240 |
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| author | D. Zhu D. Z. Peng I. D. Cluckie |
| author_facet | D. Zhu D. Z. Peng I. D. Cluckie |
| author_sort | D. Zhu |
| collection | DOAJ |
| description | This study attempts to characterise the manner with which inherent error in radar rainfall estimates input influence the character of the stream flow simulation uncertainty in validated hydrological modelling. An artificial statistical error model described by Gaussian distribution was developed to generate realisations of possible combinations of normalised errors and normalised bias to reflect the identified radar error and temporal dependence. These realisations were embedded in the 5 km/15 min UK Nimrod radar rainfall data and used to generate ensembles of stream flow simulations using three different hydrological models with varying degrees of complexity, which consists of a fully distributed physically-based model MIKE SHE, a semi-distributed, lumped model TOPMODEL and the unit hydrograph model PRTF. These models were built for this purpose and applied to the Upper Medway Catchment (220 km<sup>2</sup>) in South-East England. The results show that the normalised bias of the radar rainfall estimates was enhanced in the simulated stream flow and also the dominate factor that had a significant impact on stream flow simulations. This preliminary radar-error-generation model could be developed more rigorously and comprehensively for the error characteristics of weather radars for quantitative measurement of rainfall. |
| first_indexed | 2024-04-12T03:14:11Z |
| format | Article |
| id | doaj.art-4b5f76e362e1484abfb2ea2449c89ba5 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-04-12T03:14:11Z |
| publishDate | 2013-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-4b5f76e362e1484abfb2ea2449c89ba52022-12-22T03:50:13ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382013-04-011741445145310.5194/hess-17-1445-2013Statistical analysis of error propagation from radar rainfall to hydrological modelsD. ZhuD. Z. PengI. D. CluckieThis study attempts to characterise the manner with which inherent error in radar rainfall estimates input influence the character of the stream flow simulation uncertainty in validated hydrological modelling. An artificial statistical error model described by Gaussian distribution was developed to generate realisations of possible combinations of normalised errors and normalised bias to reflect the identified radar error and temporal dependence. These realisations were embedded in the 5 km/15 min UK Nimrod radar rainfall data and used to generate ensembles of stream flow simulations using three different hydrological models with varying degrees of complexity, which consists of a fully distributed physically-based model MIKE SHE, a semi-distributed, lumped model TOPMODEL and the unit hydrograph model PRTF. These models were built for this purpose and applied to the Upper Medway Catchment (220 km<sup>2</sup>) in South-East England. The results show that the normalised bias of the radar rainfall estimates was enhanced in the simulated stream flow and also the dominate factor that had a significant impact on stream flow simulations. This preliminary radar-error-generation model could be developed more rigorously and comprehensively for the error characteristics of weather radars for quantitative measurement of rainfall.http://www.hydrol-earth-syst-sci.net/17/1445/2013/hess-17-1445-2013.pdf |
| spellingShingle | D. Zhu D. Z. Peng I. D. Cluckie Statistical analysis of error propagation from radar rainfall to hydrological models Hydrology and Earth System Sciences |
| title | Statistical analysis of error propagation from radar rainfall to hydrological models |
| title_full | Statistical analysis of error propagation from radar rainfall to hydrological models |
| title_fullStr | Statistical analysis of error propagation from radar rainfall to hydrological models |
| title_full_unstemmed | Statistical analysis of error propagation from radar rainfall to hydrological models |
| title_short | Statistical analysis of error propagation from radar rainfall to hydrological models |
| title_sort | statistical analysis of error propagation from radar rainfall to hydrological models |
| url | http://www.hydrol-earth-syst-sci.net/17/1445/2013/hess-17-1445-2013.pdf |
| work_keys_str_mv | AT dzhu statisticalanalysisoferrorpropagationfromradarrainfalltohydrologicalmodels AT dzpeng statisticalanalysisoferrorpropagationfromradarrainfalltohydrologicalmodels AT idcluckie statisticalanalysisoferrorpropagationfromradarrainfalltohydrologicalmodels |