From qualitative to quantitative environmental scenarios: Translating storylines into biophysical modeling inputs at the watershed scale. (November 2016)

• Record Type: Journal Article
• Authors: Booth, Eric G.; Qiu, Jiangxiao; Carpenter, Stephen R.; Schatz, Jason; Chen, Xi; Kucharik, Christopher J.; Loheide, Steven P.; Motew, Melissa M.; Seifert, Jenny M.; Turner, Monica G.
• Is Part Of: Environmental modelling & software. Volume 85(2016:Nov.)
• Page Start: 80
• Page End: 97
• Publication Date: 2016-11
• Subjects: Scenarios -- Biophysical modeling -- Social-ecological systems -- Watershed -- Climate change -- Land use change; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.08.008
• Languages: English
• ISSNs: 1364-8152

Abstract

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. Highlights: Novel approach to determine spatiotemporally explicit biophysical model inputs. Inputs include climate, land use/land cover, and land nutrient applications. Communication between scenario narrative writers and modeling team is critical.