Abstract
Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.
| Original language | English |
|---|---|
| Article number | 77 |
| Journal | Scientific Data |
| Volume | 11 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2024 |
Funding
We would like to thank Jennifer C. Adam, Julian J. Reyes, Paul C. Hanson, Austin P. Delany, and Cee Nell for diverse technical and creative support during the production of the LTS-US dataset. We would like to thank Joshua Culpepper and Lauren Koenig for reviewing the LTS-US data product’s data, code, and metadata. Additionally, we would like to thank John R. Gardner and Jida Wang for providing insightful comments and feedback on a previous version of this manuscript. MFM, SNT, and KCF were supported by Mendenhall Fellowships from the U.S. Geological Survey. RMP was supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Water Power Technologies Office, and Environmental Sciences Division at Oak Ridge National Laboratory (ORNL). ORNL is managed by UT-Battelle, LLC, for the U.S. DOE under contract DE-AC05-00OR22725. IAO was supported by NSF award #EPS-2019528. RIW was supported by a UKRI Natural Environment Research Council (NERC) Independent Research Fellowship [grant number NE/T011246/1]. The National Lakes Assessment 2007, 2012, and 2017 data were a result of the collective efforts of dedicated field crews, laboratory staff, data management and quality control staff, analysts and many others from the U.S. EPA, states, tribes, federal agencies, universities, and other organizations. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We would like to thank Jennifer C. Adam, Julian J. Reyes, Paul C. Hanson, Austin P. Delany, and Cee Nell for diverse technical and creative support during the production of the LTS-US dataset. We would like to thank Joshua Culpepper and Lauren Koenig for reviewing the LTS-US data product’s data, code, and metadata. Additionally, we would like to thank John R. Gardner and Jida Wang for providing insightful comments and feedback on a previous version of this manuscript. MFM, SNT, and KCF were supported by Mendenhall Fellowships from the U.S. Geological Survey. RMP was supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Water Power Technologies Office, and Environmental Sciences Division at Oak Ridge National Laboratory (ORNL). ORNL is managed by UT-Battelle, LLC, for the U.S. DOE under contract DE-AC05-00OR22725. IAO was supported by NSF award #EPS-2019528. RIW was supported by a UKRI Natural Environment Research Council (NERC) Independent Research Fellowship [grant number NE/T011246/1]. The National Lakes Assessment 2007, 2012, and 2017 data were a result of the collective efforts of dedicated field crews, laboratory staff, data management and quality control staff, analysts and many others from the U.S. EPA, states, tribes, federal agencies, universities, and other organizations. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
