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• W4248711255 abstract "Abstract. This study attempts to characterize 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 realizations of possible combinations of normalized errors and normalized bias to reflect the identified radar error and temporal dependence. These realizations 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 model TOPMODEL and a lumped model PRTF. These models were built for this purpose and applied to the Upper Medway Catchment (220 km2) in South-East England. The results show that the normalized 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." @default.
• W4248711255 created "2022-05-12" @default.
• W4248711255 creator A5007077214 @default.
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• W4248711255 date "2012-09-10" @default.
• W4248711255 modified "2023-10-17" @default.
• W4248711255 title "Statistical analysis of error propagation from radar rainfall to hydrological models" @default.
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• W4248711255 doi "https://doi.org/10.5194/hessd-9-10277-2012" @default.
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