Exploring uncertainty and model predictive performance concepts via a modular snowmelt-runoff modeling framework |
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| Authors: | Tyler Jon Smith Lucy Amanda Marshall |
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| Affiliation: | 1. Deutsches GeoForschungsZentrum GFZ, Telegrafenberg, D-14473 Potsdam, Germany;2. Landesanstalt für Landwirtschaftliche Chemie (710), Universität Hohenheim, Emil-Wolff-Str. 14, D-70593 Stuttgart, Germany;3. Institut für Mineralogie, Leibniz Universität Hannover, Callinstr. 3, D-30167 Hannover, Germany;4. Institute of Soil Landscape Research, Leibniz-Centre for Agricultural Landscape Research (ZALF) e.V., Eberswalder Strasse 84, D-15374 Müncheberg, Germany;5. University of Potsdam, Institute of Earth and Environmental Sciences, Karl-Liebknecht-Str. 24–25, D-14476 Potsdam, Germany;1. Key Laboratory of Digital Earth Science, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100094, PR China;2. Department of Geography, Queen''s University, Kingston, ON K7L3N6, Canada;3. Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, PR China;1. Univ. Grenoble Alpes, LTHE, F-38000 Grenoble, France;2. CNRS, LTHE, F-38000 Grenoble, France;3. IRD, LTHE, F-38000 Grenoble, France;4. Centre d''Etudes Spatiales de la BIOsphère (CESBIO), CNES CNRS IRD UPS, OMP, Toulouse, France;5. Météo-France – CNRS, CNRM-GAME UMR 3589, Centre d''Etudes de la Neige, Grenoble, France;6. Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland;7. Gamma Remote Sensing AG, Worbstrasse 225, 3073 Gümligen, Switzerland;8. Karlsruhe Institute of Technology, IMK-IFU, Germany |
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| Abstract: | Model selection is an extremely important aspect of many hydrologic modeling studies because of the complexity, variability, and uncertainty that surrounds the current understanding of watershed-scale systems. However, development and implementation of a complete precipitation-runoff modeling framework, from model selection to calibration and uncertainty analysis, are rarely confronted. This paper introduces a modular precipitation-runoff modeling framework that has been developed and applied to a research site in Central Montana, USA. The case study focuses on an approach to hydrologic modeling that considers model development, selection, calibration, uncertainty analysis, and overall assessment. The results of this case study suggest that a modular framework is useful in identifying the interactions between and among different process representations and their resultant predictions of stream discharge. Such an approach can strengthen model building and address an oft ignored aspect of predictive uncertainty; namely, model structural uncertainty. |
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