Byrne et al. (2026) Dataset for Geospatial Interpolation of Soil Profile Depth in the Magic Valley, Idaho, USA: Use of Publicly Available Well Report Data

Identification

• Journal: ScholarWorks (Boise State University)
• Year: 2026
• Date: 2026-03-10
• Authors: Akira Byrne, David P. Huber, Dylan Thompson, Josh Enterkine, Jennifer Pierce
• DOI: 10.18122/geo_data.10.boisestate

Research Groups

• Boise State University
• United States Department of Agriculture Agricultural Research Service, Northwest Irrigation and Soils Research Lab
• Boise Center Aerospace Laboratory (BCAL)
• University of Texas at El Paso
• University of Pennsylvania

Short Summary

This paper presents a dataset and methodology for creating a soil profile depth map for the Magic Valley, Idaho, USA, by manually extracting and geostatistically interpolating soil depths from approximately 5,700 publicly available well log reports. The study demonstrates the utility of this data source for mapping critical soil properties in dryland regions, essential for understanding ecosystem productivity and climate regulation.

Objective

• To generate a usable and high-quality soil depth map for the Magic Valley, Idaho, USA, using publicly available well log data.
• To demonstrate the effectiveness of leveraging well log data for geospatial interpolation of soil profile depth in a dryland agricultural region.

Study Configuration

• Spatial Scale: Magic Valley, south-central Idaho, USA, covering an intensive agricultural area of 931 km². The study area is bounded by the Snake River Canyon (north), High Line Canal (south), Salmon Falls Creek Canyon (west), and HUC 12 subwatersheds near Kimberly (east). A 1.5 km buffer was applied for interpolation.
• Temporal Scale: Well log data spans from 1939 to 2024.

Methodology and Data

• Models used: Standard kriging interpolation method with a Gaussian semivariogram model.
• Data sources:
  • Public well log (well driller’s report) data scraped from the Idaho Department of Water Resources (IDWR).
  • Manual extraction of soil depths from approximately 8,000 well sites, resulting in a refined dataset of ~5,700 high-confidence soil depth estimates.

Main Results

• A usable and high-quality soil depth map was successfully generated for the 931 km² Magic Valley study region.
• Soil depths within the study area were found to range up to 8.9 meters.
• Publicly available well log data was demonstrated to be a valuable and effective source for mapping soil depth in dryland environments.
• The resulting dataset provides approximately 5,700 high-quality soil depth estimates.

Contributions

• Provides a novel, high-resolution geospatial dataset and map of soil profile depth for the Magic Valley, Idaho, a region critical for agriculture and ecosystem services.
• Establishes a robust methodology for utilizing publicly available, often underutilized, well log data for detailed soil depth mapping.
• Offers a crucial resource for researchers and land managers studying water, nutrient, and carbon storage, and predicting ecosystem productivity and variability under climate and land-use change.
• Highlights the importance of soil depth as a fundamental control volume influencing landscape-scale hydrological and biogeochemical processes.

Funding

• National Science Foundation Critical Zone Collaborative Network, Dryland Thematic Cluster, Grant Award #2012475.

Citation

@article{Byrne2026Dataset,
  author = {Byrne, Akira and Huber, David P. and Thompson, Dylan and Enterkine, Josh and Pierce, Jennifer},
  title = {Dataset for Geospatial Interpolation of Soil Profile Depth in the Magic Valley, Idaho, USA: Use of Publicly Available Well Report Data},
  journal = {ScholarWorks (Boise State University)},
  year = {2026},
  doi = {10.18122/geo_data.10.boisestate},
  url = {https://doi.org/10.18122/geo_data.10.boisestate}
}