Predicting daily streamflow using rainfall forecasts,a simple loss module and unit hydrographs: Two Brazilian catchments |
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| Affiliation: | 1. National Environmental Research Council (NERC), Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford, Oxon OX10 8BB, UK;2. Instituto de Pesquisas Hidráulicas, Porto Alegre, RS Brazil;3. Integrated Catchment Assessment and Management Centre, and Department of Mathematics, Australian National University, Canberra, Australia;1. Department of Physics, University of North Bengal, Siliguri 734013, West Bengal, India;2. Department of Computer and Information Sciences, SUNY at Fredonia, NY 14063, USA;1. Georgia Water Resources Institute, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA;2. Hydrologic Research Center, 12555 High Bluff Drive, Suite 255, San Diego, CA 92130, USA;3. Scripps Institution of Oceanography, University of California San Diego, USA;1. Department of Mechanical Engineering, Imperial College London, London SW7 2AZ, UK;2. Department of Materials, Imperial College London, London SW7 2AZ, UK;3. School of Materials, The University of Manchester, Manchester M1 7HS, UK;4. Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK;5. Tata Steel Research and Development, Swinden Technology Centre, Rotherham S60 3AR, UK;1. Consiglio Nazionale delle Ricerche, Istituto di Metodologie per l’Analisi Ambientale, C.da S. Loja, 85050 Tito (PZ), Italy;2. ARPAB, 85100 Potenza, Italy;3. Moldavian Academy of Sciences, Institute of Geology and Seismology, Academiei str. 3, Chisinau, Republic of Moldova;1. The Institute of Hydrodynamics of the Academy of Sciences of the Czech Republic, Pod Pat’ankou 30/5, Prague 166 12, Czech Republic;2. Czech Hydrometeorological Institute, Na ?abatce 2050/17, 143 06 Praha, Czech Republic |
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| Abstract: | The performance of a simple, spatially-lumped, rainfall–streamflow model is compared with that of a more complex, spatially-distributed model. In terms of two model-fit statistics it is shown that for two catchments in Brazil (about 30,000 km2 and 34,000 km2) with different flow regimes, the simpler catchment models, which are unit hydrograph-based and require only rainfall, streamflow and air temperature data for calibration, perform about as well as more complex catchment models that require additional information from satellite images and digitized maps of elevation, land-use and soils. Simple catchment models are applied in forecasting mode, using daily rainfall forecasts from a regional weather forecasting model. The value of the rainfall forecasts, relative to the case where rainfall is known, is assessed for both catchments. The results are discussed in the context of on-going work to compare different modelling approaches for many other Brazilian catchments, and to apply improved forecasting algorithms based on the simple modelling approach to the same, and other, catchments. |
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