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Multisectoral models of regional bio-physical systems simulate policy responses to climate change and support climate mitigation and adaptation planning at multiple scales. Challenges facing these efforts include sometimes weak understandings of causal relationships, lack of integrated data streams, spatial and temporal incongruities with policy interests, and how to incorporate dynamics associated with human values, governance structures, and vulnerable populations. There are two general approaches to developing integrated models. The first involves stakeholder involvement in model design -- a participatory modeling approach. The second is to integrate existing models. This can be done in two ways: by integrating existing models or by a soft-linked confederation of existing models. A benefit of utilizing existing models is the leveraging of validated and familiar models that provide credibility. We report opportunities and challenges manifested in one effort to develop a regional food, energy, and water systems (FEWS) modeling framework using existing bio-physical models. The C-FEWS modeling framework (Climate-induced extremes on the linked food, energy, water system) is intended to identify and evaluate response options to extreme weather in the Midwest and Northeast United States thru the year 2100. We interviewed ten modelers associated with development of the C-FEWS framework and ten stakeholders from government agencies, planning agencies, and non-governmental organizations in New England. We inquired about their perspectives on the roles and challenges of regional FEWS modeling frameworks to inform planning and information needed to support planning in integrated food, energy, and water systems. We also analyzed discussions of meetings among modelers and among stakeholders and modelers. These sources reveal many agreements among modelers and stakeholders about the role of modeling frameworks, their benefits for policymakers, and the types of outputs they should produce. They also identify challenges to developing regional modeling frameworks that couple existing models and balancing model capabilities with stakeholder preferences for information. The results indicate the importance of modelers and stakeholders engaging in dialogue to craft modeling frameworks and scenarios that are credible and relevant for policymakers. We reflect on the implications for how FEWS modeling frameworks comprised of existing bio-physical models can be designed to better inform policy making at the regional scale. 

Change to global climate, including both its progressive character and episodic extremes, constitutes a critical societal challenge. We apply here a framework to analyze Climate-induced Extremes on the Food, Energy, Water System Nexus (C-FEWS), with particular emphasis on the roles and sensitivities of traditionally-engineered (TEI) and nature-based (NBI) infrastructures. The rationale and technical specifications for the overall C-FEWS framework, its component models and supporting datasets are detailed in an accompanying paper (Vörösmarty et al., this issue). We report here on initial results produced by applying this framework in two important macro-regions of the United States (Northeast, NE; Midwest, MW), where major decisions affecting global food production, biofuels, energy security and pollution abatement require critical scientific support. We present the essential FEWS-related hypotheses that organize our work with an overview of the methodologies and experimental designs applied. We report on initial C-FEWS framework results using five emblematic studies that highlight how various combinations of climate sensitivities, TEI-NBI deployments, technology, and environmental management have determined regional FEWS performance over a historical time period (1980–2019). Despite their relative simplicity, these initial scenario experiments yielded important insights. We found that FEWS performance was impacted by climate stress, but the sensitivity was strongly modified by technology choices applied to both ecosystems (e.g., cropland production using new cultivars) and engineered systems (e.g., thermoelectricity from different fuels and cooling types). We tabulated strong legacy effects stemming from decisions on managing NBI (e.g., multi-decade land conversions that limit long-term carbon sequestration). The framework also enabled us to reveal how broad-scale policies aimed at a particular net benefit can result in unintended and potentially negative consequences. For example, tradeoff modeling experiments identified the regional importance of TEI in the form wastewater treatment and NBI via aquatic self-purification. This finding, in turn, could be used to guide potential investments in point and/or non-point source water pollution control. Another example used a reduced complexity model to demonstrate a FEWS tradeoff in the context of water supply, electricity production, and thermal pollution. Such results demonstrated the importance of TEI and NBI in jointly determining historical FEWS performance, their vulnerabilities, and their resilience to extreme climate events. These infrastructures, plus technology and environmental management, constitute the “policy levers” which can actively be engaged to mitigate the challenge of contemporary and future climate change. 

Climate change continues to challenge food, energy, and water systems (FEWS) across the globe and will figure prominently in shaping future decisions on how best to manage this nexus. In turn, traditionally engineered and natural infrastructures jointly support and hence determine FEWS performance, their vulnerabilities, and their resilience in light of extreme climate events. We present here a research framework to advance the modeling, data integration, and assessment capabilities that support hypothesis-driven research on FEWS dynamics cast at the macro-regional scale. The framework was developed to support studies on climate-induced extremes on food, energy, and water systems (C-FEWS) and designed to identify and evaluate response options to extreme climate events in the context of managing traditionally engineered (TEI) and nature-based infrastructures (NBI). This paper presents our strategy for a first stage of research using the framework to analyze contemporary FEWS and their sensitivity to climate drivers shaped by historical conditions (1980–2019). We offer a description of the computational framework, working definitions of the climate extremes analyzed, and example configurations of numerical experiments aimed at evaluating the importance of individual and combined driving variables. Single and multiple factor experiments involving the historical time series enable two categories of outputs to be analyzed: the first involving biogeophysical entities (e.g., crop production, carbon sequestered, nutrient and thermal pollution loads) and the second reflecting a portfolio of services provided by the region’s TEI and NBI, evaluated in economic terms. The framework is exercised in a series of companion papers in this special issue that focus on the Northeast and Midwest regions of the United States. Use of the C-FEWS framework to simulate historical conditions facilitates research to better identify existing FEWS linkages and how they function. The framework also enables a next stage of analysis to be pursued using future scenario pathways that will vary land use, technology deployments, regulatory objectives, and climate trends and extremes. It also supports a stakeholder engagement effort to co-design scenarios of interest beyond the research domain. 

Abstract Carbon dioxide (CO₂) quantification is critical for assessing city‐level carbon emissions and sustainable urban development. While urban vegetation has the potential to provide environmental benefits, such as heat and carbon mitigation, the CO₂exchange from biogenic sectors and its impact from the environmental perturbations are often overlooked. It is also challenging to simulate the plant functions in the complex urban terrain. This study presents a processed‐based modeling approach to assess the biogenic carbon fluxes from the vegetated areas over the Chicago Metropolitan Area (CMA) using the Weather Research and Forecast—Urban Biogenic Carbon exchange model. We investigate the change of CO₂sink power in CMA under heatwaves and irrigation. The results indicate that the vegetation plays a significant role in the city's carbon portfolio and the landscaping management has the potential to reduce carbon emissions significantly. Furthermore, based on the competing mechanisms in the biogenic carbon balance identified in this study, we develop a novel Environmental Benefit Score metrics framework to identify the vulnerability and mitigation measures associated with nature‐based solutions (NbS) within CMA. By using the generalized portable framework and our science‐policy confluence analysis presented in this study, global cities can maximize the effectiveness of NbS and accelerate carbon neutrality.