Large-scale Solar Developments and Protected Lands – Can We Have Them Both?

By Karen Janowitz, Washington State University Energy Program

View of shrubsteppe lands in the Columbia Plateau in Washington
The Columbia Plateau boasts important ranchlands and are important to many endangered and threatened species and habitats as well as Tribal cultural resources. Photo: Ferdi Businger.

The passage of Washington State’s Clean Energy Transformation Act in 2019 mandates an electricity supply free of greenhouse gas emissions by 2045. Large-scale renewable energy projects are one way to achieve this mandate. Solar companies see this as an opportunity and are pursuing projects in the sunniest, least developed part of the state—the Columbia Plateau region. As many of you know, the area boasts some of the most productive farmland and ranchland in the state, as well as many endangered and threatened species and habitats, and Tribal cultural resources.

Concerned about losing these values to large renewable energy developments while acknowledging the need for renewables, the 2019 Washington State Legislature directed the Washington State University Energy Program (WSUEP) to pursue a Least-Conflict Solar Siting project for the Columbia Plateau. The project must be completed by June 30, 2023, and we are in the midst of working with a wide-ranging and diverse set of interests to produce maps that can help us balance the need for renewable energy with protecting Washington State’s productive farmland and ranchland, Tribal rights and resources, and species and habitats. You can assist with the project by reviewing draft maps, which will be available soon. Read on to gain an understanding of this novel and important process.

Least-conflict Solar Siting

Least-conflict Solar Siting identifies areas of greatest value for farming, ranching, and environmental conservation (the greatest occurrence of important ecosystems, species and their habitats). The lands that are not of great value are considered to be least-conflict or less-conflict lands. These areas are where companies could build large-scale solar developments with the fewest potential disputes from those who live, work, recreate, and value the land, and help prevent or minimize loss of productive and important lands.

To answer some commonly asked questions: the project is landscape-based, does not identify specific sites for solar developments, and has no regulatory teeth. The project’s findings do not replace any of the due diligence and assessments that solar companies must carry out. We are not reviewing lands within Tribal reservations unless the Tribe requests we do, and we are discussing with Tribes how they want to participate. Information in the maps is at a scale of 500 meters (1640 feet) to a side. Agrivoltaics is not part of the mapping process, though we acknowledge its large potential, and will be compiling the latest information on this topic as also requested by the legislature.

With our geo-spatial partner, Conservation Biology Institute (CBI), we convened four mapping groups that have been meeting to create least-conflict models—farmland, ranchland, environmental conservation, and solar industry. Participation, which is voluntary, includes people knowledgeable about the land, such as folks from NGOs, state, federal, and local agencies, Tribes, conservation districts, and landowners.

Each group produces a separate map, which are combined to find the common least-conflict areas. The solar industry group maps areas of greatest suitability for large-scale solar development. Adding the solar industry map to the other three will show where the best solar opportunities match the least-conflict areas.

The Analysis – Maps and Data

Maps are created by using existing datasets and combining the information as they move up a hierarchical tree framework to the highest value. CBI is leading this work using a geo-spatial environmental decision support tool called EEMSOnline. Figure 1 shows the top snippet of the farmlands model, with some of the properties the mapping group uses to identify the highest value farmland. Good irrigation capability, high water storage, and high soil depth are combined to identify good irrigated farmland, which is used to identify high quality irrigated farmland, which is one of the components of the final farmland quality model. Data layers used for this branch (not visible in the Figure 1) include available water storage, average depth to resistant layers, and irrigated capability classes.

Hierarchy of farmland quality elements considered in the model
Figure 1. Top layers of the farmland quality model tree structure

The final result is a map showing varying degrees of productive farmland (see Figure 2). Reddest areas representative highest quality identified by this process, while less productive, and thus less-conflict, are represented by blue.

We Need to Hear From You  

Map of the Columbia Plateau in Washington color-coded from red to blue, except for Tribal reservation lands.
Figure 2. February 2023 draft of the Farmlands map. The redder areas indicate higher quality farmland.

We are now seeking your help. We want to know if these maps reflect what you know about the land. Having more people review the draft maps and provide feedback will provide the reality check that will make the project more successful. Live and recorded half-hour tutorials on how to read and review the four maps are taking place this March. The draft combined map of all the layers will be available for review at the next large meeting, April 12, 2023, which you are all welcome to attend.

Contact Karen Janowitz at janowitzk@energy.wsu.edu for more information and to sign up for the March tutorials. Information and registration for the April 12 gathering will be available soon on the website.