From qualitative to quantitative environmental scenarios: Translating storylines into biophysical modeling inputs at the watershed scale |
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| Affiliation: | 1. School of Media and Journalism, University of North Carolina, Chapel Hill, USA;2. Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, USA;3. Stanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA;4. Institute for Disease Modeling, Bellevue, WA, USA;5. Department of Computer Science, Johns Hopkins University, USA;6. Graduate School of Public Health, San Diego State University, San Diego, USA;1. Delft University of Technology, Faculty of Applied Sciences, Department of Biotechnology, Section Biotechnology & Society, Julianalaan 67, 2628BC Delft, The Netherlands;2. CSG Centre for Society and the Life Sciences, PO Box 9010, 6500 GL Nijmegen, The Netherlands;3. Kluyver Centre for Genomics of Industrial Fermentation, PO Box 5057, 2600GA Delft, The Netherlands;4. Radboud University, Faculty of Science, Institute for Science, Innovation and Society, PO Box 9010, 6500GL Nijmegen, The Netherlands |
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| Abstract: | Scenarios are increasingly used for envisioning future social-ecological changes and consequences for human well-being. One approach integrates qualitative storylines and biophysical models to explore potential futures quantitatively and maximize public engagement. However, this integration process is challenging and sometimes oversimplified. Using the Yahara Watershed (Wisconsin, USA) as a case study, we present a transparent and reproducible roadmap to develop spatiotemporally explicit biophysical inputs climate, land use/cover (LULC), and nutrients] that are consistent with scenario narratives and can be linked to a process-based biophysical modeling suite to simulate long-term dynamics of a watershed and a range of ecosystem services. Our transferrable approach produces daily weather inputs by combining climate model projections and a stochastic weather generator, annual narrative-based watershed-scale LULC distributed spatially using transition rules, and annual manure and fertilizer (nitrogen and phosphorus) inputs based on current farm and livestock data that are consistent with each scenario narrative. |
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| Keywords: | Scenarios Biophysical modeling Social-ecological systems Watershed Climate change Land use change |
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