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Abstract With mounting scientific evidence demonstrating adverse global climate change (GCC) impacts to water quality, water quality policies, such as the Total Maximum Daily Loads (TMDLs) under the U.S. Clean Water Act, have begun accounting for GCC effects in setting nutrient load‐reduction policy targets. These targets generally require nutrient reductions for attaining prescribed water quality standards (WQS) by setting safe levels of nutrient concentrations that curtail potentially harmful cyanobacteria blooms (CyanoHABs). While some governments require WQS to consider climate change, few tools are available to model the complex interactions between climate change and benthic legacy nutrients. We present a novel process‐based integrated assessment model (IAM) that examines the extent to which synergistic relationships between GCC and legacy Phosphorus release could compromise the ability of water quality policies to attain established WQS. The IAM is calibrated for simulating the eutrophic Missisquoi Bay and watershed in Lake Champlain (2001–2050). Water quality impacts of seven P‐reduction scenarios, including the 64.3% reduction specified under the current TMDL, were examined under 17 GCC scenarios. The TMDL WQS of 0.025 mg/L total phosphorus is unlikely to be met by 2035 under the mandated 64.3% reduction for all GCC scenarios. IAM simulations show that the frequency and severity of summer CyanoHABs increased or minimally decreased under most climate and nutrient reduction scenarios. By harnessing IAMs that couple complex process‐based simulation models, the management of water quality in freshwater lakes can become more adaptive through explicit accounting of GCC effects on both the external and internal sources of nutrients.
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Accounting for spatial economic interactions at local and meso scales in integrated assessment model (IAM) frameworks: challenges and recent progress
Abstract The scientific and policy needs to assess and manage climate change impacts have spawned new coupled, multi-scale integrated assessment model (IAM) frameworks that link global climate and economic processes with high-resolution data and models of human-environmental systems at local and meso scales (Fisher-Vanden and Weyant 2020Annu. Rev. Resour. Econ.12471–87). A central challenge is in accounting for the fundamental interdependence of people, firms, and economic activities across space at multiple scales. This requires modeling approaches that can incorporate the relevant spatial details at each scale while also ensure consistency with spatially varying feedbacks and interactions across scales—a condition economists refer to as spatial equilibrium. In this paper, we provide an overview of how economists think about and model spatial interactions, particularly those at the local level. We describe challenges and recent progress in accounting for greater spatial heterogeneity at individual (field, agent) scales and incorporating heterogeneous spatial interactions and dynamics into consistent IAM frameworks. We conclude that the most notable progress is in advancing global IAMs with spatial heterogeneity and dynamics embedded in spatial equilibrium frameworks and that less progress has been made in incorporating features of spatial equilibrium into highly detailed multi-scale IAMs.
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- Award ID(s):
- 1739909
- PAR ID:
- 10400955
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research Letters
- Volume:
- 18
- Issue:
- 3
- ISSN:
- 1748-9326
- Page Range / eLocation ID:
- Article No. 035009
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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