Ryan C. Cahalan Jeff D. Pepin Erick R. Burns Scott Mello Hyunjun Oh Whitney Trainor-Guitton 20250505 heat and groundwater flow simulation model publication Reston, VA, USA US Geological Survey https://doi.org/10.5066/P138XVEG This data release documents sixteen 5-year simulations using the USGS SUTRA groundwater flow modeling software and includes the full output from one 5-year simulation for verification that the model code runs properly. The most recent version of SUTRA (version 4.0) was used to evaluate aquifer (ATES) and reservoir (RTES) thermal energy storage performance to support economic analyses by simulating three-dimensional groundwater and heat transport for layered systems in the following eight metropolitan area cities: Albuquerque, New Mexico; Charleston, South Carolina; Chicago and Decatur, Illinois; Lansing, Michigan; Memphis, Tennessee; Phoenix, Arizona; and Portland, Oregon. ATES entails storing hot or cold water directly within aquifers that are often near the surface, contain high-quality groundwater, and are typically relied upon for groundwater production. RTES is a variant of ATES that targets deeper aquifers that are poorly connected with shallower fresh aquifers and surface water bodies, resulting in lower ambient groundwater flow rates and more geochemically evolved waters that tend to be used less for groundwater production. The provided ATES and RTES models permit comparison of the performance of both storage techniques. Estimated subsurface conditions beneath airports within each city are represented to serve as demonstrative conditions for the general area; airports were chosen because of their resource development advantages, including available development space, regular and long-term space cooling demand, and availability of hydrogeologic data that is critical to accurate modeling . Climate-based supply and demand inputs, derived from National Renewable Energy Laboratory ComStock models (Parker and others, 2023), are representative of the cooling load of seven medium-sized office buildings in each city. These hourly, year-long demand profiles are used to construct the simulated energy storage and production schedule. Although city airport locations were used to derive representative hydrothermal model parameters, the airport cooling energy demand was not considered in the ComStock models. The version of SUTRA utilized in these models is summarized in Voss and others, (2024). Details on the construction of similar thermal energy storage models is provided in Burns and others (2020) and Pepin and others (2025). The SUTRA (version 4.0) executable, python scripts to administer simulations, and example model inputs and outputs are provided in this data release. Further detail on each folder’s contents, including input and output files, and running a model can be found in “readme.txt” files located in the respective folders. Burns, E.R., Bershaw, J., Williams, C.F., Wells, R., Uddenberg, M., Scanlon, D., Cladouhos, T., van Houten, B., 2020, Using saline or brackish aquifers as reservoirs for thermal energy storage, with example calculations for direct-use heating in the Portland Basin, Oregon, USA: Geothermics, v. 88, p. 101877, https://doi.org/10.1016/j.geothermics.2020.101877. Parker, A., Horsey, H., Dahlhausen, M., Praprost, M., CaraDonna, C., LeBar, A., amd Klun, L., 2023, ComStock Reference Documentation. Golden, CO: National Renewable Energy Laboratory. NREL/TP-5500-83819. https://www.nrel.gov/docs/fy23osti/83819.pdf. Pepin, J.D., Burns, E.R., Cahalan, R.C., Hayba, D.O., Dickinson, J.E., Duncan, L.L., and Kuniansky, E.L., 2025, Reservoir Thermal Energy Storage Pre-Assessment for the United States: Geothermics, v. 129, no. 103256, 18 p., https://doi.org/10.1016/j.geothermics.2025.103256. Voss, C.I., Provost, A.M., McKenzie, J.M., and Kurylyk, B.L., 2024, SUTRA—A code for simulation of saturated-unsaturated, variable-density groundwater flow with solute or energy transport—Documentation of the version 4.0 enhancements—Freeze-thaw capability, saturation and relative-permeability relations, spatially varying properties, and enhanced budget and velocity outputs: U.S. Geological Survey Techniques and Methods, book 6, chap. A63, 91 p., https://doi.org/10.3133/tm6A63. Two hydrogeologic models were developed for each of the eight US cities to evaluate aquifer and reservoir thermal energy storage performance in representative climates and subsurface conditions. This archive provides the input and output for example simulations, along with the modeling software. The models were created with input from National Renewable Energy Laboratory co-authors as a product of the GEOTHERMICA FLXenabler project. Information on model development practices followed for the city models in this data release can be found in Burns and others (2020). Burns, E.R., Bershaw, J., Williams, C.F., Wells, R., Uddenberg, M., Scanlon, D., Cladouhos, T., van Houten, B., 2020, Using saline or brackish aquifers as reservoirs for thermal energy storage, with example calculations for direct-use heating in the Portland Basin, Oregon, USA: Geothermics, v. 88, p. 101877, https://doi.org/10.1016/j.geothermics.2020.101877. Support is provided for correcting errors in the data release and clarification of the modeling conducted by the U.S. Geological Survey. Users are encouraged to review the journal article (https://doi.org/10.1016/j.geothermics.2020.101877) to understand the purpose, construction, and limitations of simulations similar to those contained in this archive. The models will run successfully only if the original directory structure is correctly restored. Instructions for reconstructing the original directory structure and running the models included in this data release can be found in the readme.txt ASCII file which is contained in the highest level folder of this model archive. 2025 publication date Complete None planned -122.6373 -80.0085 45.6054 32.8725 ISO 19115 Topic Category geoscientificInformation USGS Thesaurus geologic energy storage energy resources energy storage groundwater groundwater flow mathematical modeling geothermal resources USGS Metadata Identifier USGS:6797f8ead34ea8c18376e10d Geographic Names Information System Albuquerque New Mexico Charleston South Carolina Chicago Decatur Illinois Lansing Michigan Memphis Tennessee Phoenix Arizona Portland Oregon None. Please see 'Distribution Info' for details. Acknowledgement of the U.S. Geological Survey would be appreciated in products derived from this data release. The models were simulated using SUTRA version 4.0, which is publicly available online at https://www.usgs.gov/software/sutra-a-model-2d-or-3d-saturated-unsaturated-variable-density-ground-water-flow-solute-or. Please contact Ryan Cahalan (rcahalan@usgs.gov) for model related inquiries. None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Ryan C. Cahalan U.S. Geological Survey Research Geologist physical

632 SW Hall St

Portland OR 97201 USA n/a rcahalan@usgs.gov This project has been subsidized through the Cofund GEOTHERMICA by the Department of Energy Office of Energy Efficiency and Renewable Energy Geothermal Technologies Office (GTO). Alden M. Provost Clifford I. Voss Jeffrey M. McKenzie Barrett L. Kurylyk 2024 publication Reston, VA U.S. Geological Survey https://doi.org/10.3133/tm6A63 Clifford I. Voss Alden M. Provost Jeffrey M. McKenzie Barrett L. Kurylyk 20241220 software software https://www.usgs.gov/software/sutra-a-model-2d-or-3d-saturated-unsaturated-variable-density-ground-water-flow-solute-or Jeffrey D. Pepin Erick R. Burns Ryan C. Cahalan Daniel O. Hayba Jesse E. Dickinson Leslie L. Duncan Eve L. Kuniansky 2025 publication United Kingdom Geothermics The accompanying data release is found at: https://doi.org/10.5066/P9JPJQS1 Erick R. Burns John Bershaw Colin F. Williams Ray Wells Matt Uddenberg Darby Scanlon Trenton Cladouhos Boz van Houten 202011 heat and groundwater flow simulation model publication Geothermics vol. 88 n/a Elsevier BV Accompanying data release is found at: https://doi.org/10.5066/P9A6D6XM https://doi.org/10.1016/j.geothermics.2020.101877 The model represents simplified general conditions for the geology, hydrology, and climate at each airport location. Please see Pepin and others (2025) for an explanation of similar model building practices followed in this study. No formal logical accuracy tests were conducted. Dataset is considered complete for the information presented. The hydrogeological models are complete and can be used either with the included stress conditions or others tests of cooling loads and climate inputs. No formal positional accuracy tests were conducted. No formal positional accuracy tests were conducted. The process used to develop and run the simulation models is similar to that described in the referenced article Pepin and others (2025). The process here differs in that this model is three-dimensional, considers ambient groundwater flow (for ATES), has a more complex weather- and demand-based pumping schedule (stressing schedule from ComStock), and does not include surface to ground in-pipe flow. Please refer to the readme.txt files for further details about the model files and instructions on how to run the model. 2025 Vector G-polygon 8 Loose outline of airport extent, bounding box within 0.5 km of airport footprint. World Geodetic System 1984 (WGS 84) WGS_1984 6378137.000000 298.257224 cahalan2025_data_release.shp Table containing attribute information associated with the data set. Producer Defined FID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Shape Feature geometry. ESRI Shape type. NAME Airport name, abbreviation, and city Producer Defined Portland International Airport (PDX), Portland, OR Airport name Producer defined Memphis International Airport (MEM), Memphis, TN Airport name Producer defined Charleston International Airport (CHS), Charleston, SC Airport name Producer defined Decatur Airport (DEC), Decatur, IL Airport name Producer defined Chicago Midway International Airport (MDW), Chicago, IL Airport name Producer defined Capital Region International Airport (LAN), Lansing, MI Airport name Producer defined Phoenix Sky Harbor International Airport (PHX), Phoenix, AZ Airport name Producer defined Albuquerque International Sunport Airport (ABQ), Albuquerque, NM Airport name Producer defined This shapefile contains the areal extent of each airport used in the models included within this data release. The polygons represent the airport model locations, while the simulation domain extent is either manually input or internally calculated from the annual energy demand. The airport polygons are not meant to represent the simulation domain, but rather the area from where the model parameters are taken. ArcGIS (Esri) and Google Earth readable. GS ScienceBase U.S. Geological Survey mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Digital Data https://doi.org/10.5066/P138XVEG None 20250505 Ryan Cahalan physical

632 SW Hall St

Portland OR 97201 n/a rcahalan@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998