• Energy Research

AbstractAdapting to climate change requires the production and use of climate information to inform adaptation decisions. By facilitating sustained interaction between science producers, boundary organizations narrow the gap between science and decision-making and foster the co-production of actionable knowledge. While traditional boundary organization approaches focused on intense one-on-one interactions between producers and users increases usability, this approach requires significant time and resources. Forming “boundary chains”, linking complimentary boundary organizations together, may reduce those costs. In this paper, we use longitudinal observations of a boundary chain, interviews and surveys to explore: (1) how producer-user interactions increase understanding and information usability and (2) if and how efficiencies in climate information production, dissemination and use arise as a result of the boundary chain. We find that forming and sustaining an effective boundary chain requires not only interest, commitment and investment from every link in the chain but also a level of non-overlapping mutual dependency and complementary skill sets. In this case, GLISA’s strength in producing scientific information and their credibility as climate scientists and HRWC’s strengths in facilitation, connection with potential information users, and their recognition and reputation in the watershed add value to the boundary chain enabling the boundary chain to accomplish more with greater efficiency than if each organization in the chain tried to work independently. Finally, data show how the boundary chain increased efficiencies in educating potential users about the strengths and limitations of climate science and improving the production, dissemination, and use of climate information.

Assessing global progress on human adaptation to climate change is an urgent priority. Although the literature on adaptation to climate change is rapidly expanding, little is known about the actual extent of implementation. We systematically screened >48,000 articles using machine learning methods and a global network of 126 researchers. Our synthesis of the resulting 1,682 articles presents a systematic and comprehensive global stocktake of implemented human adaptation to climate change. Documented adaptations were largely fragmented, local and incremental, with limited evidence of transformational adaptation and negligible evidence of risk reduction outcomes. We identify eight priorities for global adaptation research: assess the effectiveness of adaptation responses, enhance the understanding of limits to adaptation, enable individuals and civil society to adapt, include missing places, scholars and scholarship, understand private sector responses, improve methods for synthesizing different forms of evidence, assess the adaptation at different temperature thresholds, and improve the inclusion of timescale and the dynamics of 536 responses.

As critical infrastructure systems consider whether and how to adapt and build resilience to climate variability and change, more research is needed to holistically explore the dynamics of resilience-building changes over time. We begin to fill this gap with a case study of the Rhode Island public wastewater sector. The Rhode Island Department of Environmental Management has invested significant funding, technical assistance, capacity building, and regulatory pressure to help publicly owned wastewater systems build resilience to climate challenges since 2010. To trace, assess, and understand the dynamics of resilience-building efforts over time, we interviewed wastewater utility and municipal personnel using event history calendars (EHCs). EHCs helped respondents recall details of relevant events, including potentially disruptive storms/incidents, and how they responded, including large- and small-scale adaptations, during the study period (2010-2023). We used EHCs to trace resilience and transformation capacities over time, and to analyze and predict movement toward transformational adaptation. We found that factors that best enable movement from incremental to transformational changes include unlocking capacity, or the organizational cultural value of in-depth learning/change, and a suite of contextual supports - new information, forward-looking collaborators, and stable funding sources - which require buy-in across levels of governance. We also found that, with organizational culture considered, experiencing disruption is not predictive of pursuing transformative adaptation. This suggests decision-making strategies for states, local jurisdictions, and utility managers to support climate adaptation and resilience in critical infrastructure, such as eliminating path-dependencies and silos, lowering thresholds for action, and leveraging networks to support moving toward transformation.

In the past 20 years, Lake Erie has experienced a resurgence of harmful algal blooms and hypoxia driven by increased nutrient loading from its agriculturally dominated watersheds. The increase in phosphorus loading, specifically the dissolved reactive portion, has been attributed to a combination of changing climate and agricultural management. While many management practices and strategies have been identified to reduce phosphorus loads, the impacts of future climate remain uncertain. This is particularly the case for the Great Lakes region because many global climate models do not accurately represent the land-lake interactions that govern regional climate. For this study, we used midcentury (2046-2065) climate projections from one global model and four regional dynamically downscaled models as drivers for the Soil and Water Assessment Tool configured for the Maumee River watershed, the source of almost 50% of Lake Erie's Western Basin phosphorus load. Our findings suggest that future warming may lead to less nutrient runoff due to increased evapotranspiration and decreased snowfall, despite projected moderate increases in intensity and overall amount of precipitation. Results highlight the benefits of considering multiple environmental drivers in determining the fate of nutrients in the environment and demonstrate a need to improve approaches for climate change assessment using watershed models.

Abstract Combined sewer overflows (CSOs) occur when untreated raw sewage mixed with rainwater, runoff, or snowmelt is released during or after a storm in any community with a combined sewer system (CSS). Climate change makes CSOs worse in many locales; as the frequency and severity of wet weather events increases, so do the frequency and volume of CSO events. CSOs pose risks to humans and the environment, and as such, CSS communities are under regulatory pressure to reduce CSOs. Yet, CSS communities lack the tools needed, such as performance indicators, to assess CSS performance. Using the city of Cumberland, Maryland as a case study, we use public data on CSOs and precipitation over a span of 16 years to identify a new critical rainfall intensity threshold that triggers likely CSO incidence, and a multiple linear regression model to predict CSO volume using rainfall event characteristics. Together, this indicator and modeling approach can help CSS communities assess the performance of their CSS over time, especially to evaluate the effectiveness of efforts to reduce CSOs.