The transition to renewable energy is essential for mitigating climate change, reducing air pollution, and enhancing energy security. Solar and wind energy with battery storage are now the most inexpensive and broadly available forms of new electricity generation and are thus projected to play a dominant role in a net-zero emissions future. However, solar and wind energy both require the semi-permanent transformation of land, a finite and valuable resource with opportunity costs. The tradeoffs of renewable energy landscapes depend on the siting, construction (and design), and management of the energy development, with key concerns including food security—when transforming agricultural land, habitat loss or fragmentation, reduction in property value, and land degradation. As land-use tradeoffs remain one of the most contentious aspects of renewable energy deployment for supporters and opponents alike, numerous approaches have emerged to mitigate the negative effects of land transformation and enhance the economic and ecosystem services provided. However, the rate of expansion has outpaced the availability of comprehensive spatial and temporal data, leaving knowledge gaps about the footprint of existing landscapes, what practices are being realized and where, and under what policies and incentives can influence the future of renewable energy landscapes. This dissertation addresses these gaps by leveraging remote sensing, geospatial analysis, and publicly available data to quantify the spatial footprint, land use patterns, and tradeoffs of renewable energy infrastructure in the United States (US).Chapter 1 provides a high-level overview of the motivation for this research, and a literature review on ways that ground-mounted solar photovoltaic (PV) installations alter the water cycle at local and regional scales. I compile available knowledge on the approach, scale, climate, limitations, and hydrological outcomes to identify gaps in study design and the data needed to upscale approaches. Together, the literature indicates that solar PV installations unequivocally alter local and regional hydrological processes, and the implications depend on the needs of a region. Importantly, the information needed to replicate many modeling approaches does not exist beyond these few well-studied installations, making it difficult to determine the effects of converting larger portions of watersheds to solar. Chapter 2 addresses this gap, introducing the Ground-Mounted Solar Energy in the United States (GM-SEUS) dataset, the most comprehensive publicly available repository of solar energy infrastructure in the US. Using a combination of high-spatial resolution machine learning and object-based approaches and high-temporal resolution time series segmentation approaches, this dataset cultivates over 15,000 arrays covering 3,000 km2 and nearly 3 million panel-row boundaries covering 470 km2, with standardized and new metadata attributes. Building on existing data sources, GM-SEUS standardizes the definition of an array footprint, improves the spatial accuracy of datasets with uncertainty, and includes under-represented commercial-scale installations, setting the foundation for landscape-scale assessment of the US solar energy landscape. Chapter 3 uses this new dataset to analyze land use and land management conditions of the existing US solar energy landscape through 2024. I find that most solar energy in the US occupies agricultural land and likely lacks a productive vegetation ground cover, presenting opportunities for dual-use practices to have broader adoption. Roughly one quarter of both commercial- and utility-scale solar installations were found to reside on economically marginal land, and commercial-scale installations were preferentially sited on land of significantly low-productivity. Together, these results emphasize the need for stronger policy incentives and improved land management practices to motivate broader development of vegetated and dual-use practices.Shifting to wind energy, Chapter 4 evaluates the agricultural footprint and impact of wind turbines on agricultural production in the US Corn Belt. Wind turbines reduce local crop yields and production, yet the overall effect on food security is small, and decreasing through time. Land leases more than compensate for lost production, increasing incomes for commodity crop farm landowners. These findings demonstrate that wind power can simultaneously support environmental goals and economic security for farmers, without jeopardizing food security. Chapter 5 pulls together the findings of these chapters and reiterates a need for comprehensive and publicly available data on a rapidly expanding renewable energy landscape. With such data, researchers, policymakers, and interest-holders have the opportunity to study the multi-scale tradeoffs and synergies of existing renewable energy land transformation and focus future efforts by investigating what incentives and policies will result in real changes across the landscape.
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