Description
This dataset provides a comprehensive inventory of environmental mitigation measures required by Federal Energy Regulatory Commission (FERC) licensed hydropower facilities from 461 licenses that were issued from 1998 to 2023. These licenses constitute 446 of the 1015 FERC projects that were active at the end of 2023. 17,612 mentions of environmental mitigations were identified and categorized in 128 unique categories. Mitigations were identified using a Natural Language Processing (NLP) approach, specifically with a Bidirectional Encoder Representations from Transformer (BERT) model. Model-derived results were then reviewed and updated by a subject matter expert as needed. This dataset introduces important enhancements to previous efforts to inventory environmental mitigations, such as including associated license text for each mitigation, tracking the number of instances a mitigation was identified within a license, and providing improved location information. These enhancements significantly expand the dataset's utility, offering greater analytical capabilities and ensuring reproducibility. The dataset is downloadable as a zip file containing the metadata and dataset files.
| Date made available | Jun 30 2025 |
|---|---|
| Publisher | Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) |
Funding
| Funders | Funder number |
|---|---|
| USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Water Power Technologies Office | AC05-00OR22725 |
Research output
- 1 Conference contribution
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A Decision Support System to Compile Environmental Mitigations from Hydropower Licensing Documents
Yoon, H. J., Ruggles, T., Zhao, H. & Singh, D., 2024, Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024. Ding, W., Lu, C.-T., Wang, F., Di, L., Wu, K., Huan, J., Nambiar, R., Li, J., Ilievski, F., Baeza-Yates, R. & Hu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 4265-4268 4 p. (Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access
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