language:en license:cc-by-4.0 size_categories:100M<n<1B format:parquet modality:tabular library:datasets library:dask library:mlcroissant library:polars doi:10.57967/hf/3771 region:us ecology limnology
---
license: cc-by-4.0
language:
- en
tags:
- ecology
- limnology
size_categories:
- 100M<n<1B
pretty_name: 'LakeBeD-US: Computer Science Edition'
---

# Dataset Summary
LakeBeD-US: Computer Science Edition is a harmonized lake water quality dataset that includes 17 water quality parameters from 21 lakes in the United States of America that are monitored by 
long-term ecological research programs including the [North Temperate Lakes Long-Term Ecological Research program (NTL-LTER)](https://lter.limnology.wisc.edu/), [National Ecological Observatory Network (NEON)](https://www.neonscience.org/), [Niwot Ridge Long-Term Ecological Research program (NWT-LTER)](https://nwt.lternet.edu/), and
the [Carey Lab](https://carey.biol.vt.edu/) at Virginia Tech as part of the [Virginia Reservoirs Long-Term Research in Environmental Biology (LTREB)](https://www.ltreb-reservoirs.org/) 
site in collaboration with the [Western Virginia Water Authority](https://www.westernvawater.org/).

LakeBeD-US: Computer Science Edition is derived from LakeBeD-US: Ecology Edition, published in the Environmental Data Initiative repository. This Computer Science Edition is targeted towards members of the machine learning community for use in lake water quality and ecology prediction tasks. This dataset contains numerous missing values.

For more information about LakeBeD-US: Ecology Edition, please see the following:

B. J. McAfee et al., “LakeBeD-US: Ecology Edition - a benchmark dataset of lake water quality time series and vertical profiles.” Environmental Data Initiative, Dec. 03, 2024. doi: [10.6073/pasta/c56a204a65483790f6277de4896d7140](https://doi.org/10.6073/pasta/c56a204a65483790f6277de4896d7140).


<details>
  <summary>Click here for a full list of data sources used to build LakeBeD-US</summary>

Sources of observational data:

- C. C. Carey, A. Breef-Pilz, V. Daneshmand, A. D. Delany, and R. Q. Thomas, “Time series of high-frequency sensor data measuring water temperature, dissolved oxygen, pressure, conductivity, specific conductance, total dissolved solids, chlorophyll a, phycocyanin, fluorescent dissolved organic matter, and turbidity at discrete depths in Falling Creek Reservoir, Virginia, USA in 2018-2023.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/7541E8D297850BE7C613D116156735A9](http://doi.org/10.6073/PASTA/7541E8D297850BE7C613D116156735A9).
- C. C. Carey, A. Breef-Pilz, and A. D. Delany, “Discharge time series for the primary inflow tributary entering Falling Creek Reservoir, Vinton, Virginia, USA 2013-2023.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/510534CD94E9CBA40E2B0173E784C2B8](http://doi.org/10.6073/PASTA/510534CD94E9CBA40E2B0173E784C2B8).
- C. C. Carey et al., “Time series of high-frequency sensor data measuring water temperature, dissolved oxygen, conductivity, specific conductance, total dissolved solids, chlorophyll a, phycocyanin, fluorescent dissolved organic matter, turbidity at discrete depths, and water level in Beaverdam Reservoir, Virginia, USA in 2009-2023.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/31BB6047E0AC367C60A61884338799C4](http://doi.org/10.6073/PASTA/31BB6047E0AC367C60A61884338799C4).
- C. C. Carey et al., “Filtered chlorophyll a time series for Beaverdam Reservoir, Carvins Cove Reservoir, Claytor Lake, Falling Creek Reservoir, Gatewood Reservoir, Smith Mountain Lake, Spring Hollow Reservoir in southwestern Virginia, and Lake Sunapee in Sunapee, New Hampshire, USA during 2014-2023.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/BDEA148E951B2DD11C74B51854C3AAB5](http://doi.org/10.6073/PASTA/BDEA148E951B2DD11C74B51854C3AAB5).
- C. C. Carey et al., “Secchi depth data and discrete depth profiles of water temperature, dissolved oxygen, conductivity, specific conductance, photosynthetic active radiation, oxidation-reduction potential, and pH for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2023.” Environmental Data Initiative, Sep. 12, 2024. doi: [10.6073/PASTA/6C27A31ED56662C13016307D0BB99986](http://doi.org/10.6073/PASTA/6C27A31ED56662C13016307D0BB99986).
- C. C. Carey et al., “Water chemistry time series for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2023.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/7D7FDC5081ED5211651F86862E8B2B1E](http://doi.org/10.6073/PASTA/7D7FDC5081ED5211651F86862E8B2B1E).
- C. C. Carey, A. S. L. Lewis, and A. Breef-Pilz, “Time series of high-frequency profiles of depth, temperature, dissolved oxygen, conductivity, specific conductance, chlorophyll a, turbidity, pH, oxidation-reduction potential, photosynthetically active radiation, colored dissolved organic matter, phycocyanin, phycoerythrin, and descent rate for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2023.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/B406E9A104DAFB1B91E1AD85A19384DB](http://doi.org/10.6073/PASTA/B406E9A104DAFB1B91E1AD85A19384DB).
- J. Hart, H. Dugan, C. Carey, E. Stanley, and P. Hanson, “Lake Mendota Carbon and Greenhouse Gas Measurements at North Temperate Lakes LTER 2016.” Environmental Data Initiative, 2022. doi: [10.6073/PASTA/A2B38BC23FB0061E64AE76BBDEC656FD](http://doi.org/10.6073/PASTA/A2B38BC23FB0061E64AE76BBDEC656FD).
- P. T. J. Johnson, S. E. Yevak, S. Dykema, and K. A. Loria, “Dissolved oxygen data for the Green Lake 4 buoy, 2018 - ongoing.” Environmental Data Initiative, Aug. 26, 2024. doi: [10.6073/PASTA/DED48FA1E3851ADCD78B744E3D5B49DE](http://doi.org/10.6073/PASTA/DED48FA1E3851ADCD78B744E3D5B49DE).
- P. Johnson, S. Yevak, S. Dykema, and K. Loria, “Chlorophyll-a data for the Green Lake 4 buoy, 2018 - ongoing.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/2B90EB17F06898359280F68CE140EF47](http://doi.org/10.6073/PASTA/2B90EB17F06898359280F68CE140EF47).
- P. Johnson, S. Yevak, S. Dykema, and K. Loria, “PAR data for the Green Lake 4 buoy, 2018 - ongoing.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/CD2A197B4297259428D67C97D32F25B4](http://doi.org/10.6073/PASTA/CD2A197B4297259428D67C97D32F25B4).
- P. Johnson, S. Yevak, S. Dykema, and K. Loria, “Temperature data for the Green Lake 4 buoy, 2018 - ongoing.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/5D1C305FDA142F2AF462DCDBF77B33AB](http://doi.org/10.6073/PASTA/5D1C305FDA142F2AF462DCDBF77B33AB).
- N. Lottig, “High Frequency Under-Ice Water Temperature Buoy Data - Crystal Bog, Trout Bog, and Lake Mendota, Wisconsin, USA 2016-2020.” Environmental Data Initiative, 2022. doi: [10.6073/PASTA/AD192CE8FBE8175619D6A41AA2F72294](http://doi.org/10.6073/PASTA/AD192CE8FBE8175619D6A41AA2F72294).
- J. Magnuson, S. Carpenter, and E. Stanley, “North Temperate Lakes LTER: Chlorophyll - Madison Lakes Area 1995 - current.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/DA59B1093236CEB67D2CF220B17E5658](http://doi.org/10.6073/PASTA/DA59B1093236CEB67D2CF220B17E5658).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: Chemical Limnology of Primary Study Lakes: Nutrients, pH and Carbon 1981 - current.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/325232E6E4CD1CE04025FA5674F7B782](http://doi.org/10.6073/PASTA/325232E6E4CD1CE04025FA5674F7B782).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: Chlorophyll - Trout Lake Area 1981 - current.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/4A110BD6534525F96AA90348A1871F86](http://doi.org/10.6073/PASTA/4A110BD6534525F96AA90348A1871F86).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Meteorological and Dissolved Oxygen Data - Sparkling Lake Raft 1989 - current.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/9D054E35FB0B8D3A36B49B5E7A35F48F](http://doi.org/10.6073/PASTA/9D054E35FB0B8D3A36B49B5E7A35F48F).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Meteorological and Metabolism Data - Crystal Bog Buoy 2005 - present.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/AA8D03B297CC86AAAB404E4D25179A1A](http://doi.org/10.6073/PASTA/AA8D03B297CC86AAAB404E4D25179A1A).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Meteorological and Metabolism Data - Trout Bog Buoy 2003 - present.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/6A281EE14843E7F80FFF07E31D6E9CB0](http://doi.org/10.6073/PASTA/6A281EE14843E7F80FFF07E31D6E9CB0).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Water Temperature Data - Crystal Bog Buoy 2005 - current.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/800E42BF5421EB3D601A07245FF5750E](http://doi.org/10.6073/PASTA/800E42BF5421EB3D601A07245FF5750E).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Water Temperature Data - Sparkling Lake Raft 1989 - current.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/52CEBA5984C4497D158093F32B23B76D](http://doi.org/10.6073/PASTA/52CEBA5984C4497D158093F32B23B76D).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Water Temperature Data - Trout Bog Buoy 2003 - current.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/9535BBC321EBD512CD0E8B0F1D7821BE](http://doi.org/10.6073/PASTA/9535BBC321EBD512CD0E8B0F1D7821BE).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: Secchi Disk Depth; Other Auxiliary Base Crew Sample Data 1981 - current.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/4C5B055143E8B7A5DE695F4514E18142](http://doi.org/10.6073/PASTA/4C5B055143E8B7A5DE695F4514E18142).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Data: Meteorological, Dissolved Oxygen, Chlorophyll, Phycocyanin - Lake Mendota Buoy 2006 - current.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/DAAD81BE7F12173E3AEFBF3DF5D6D2FE](http://doi.org/10.6073/PASTA/DAAD81BE7F12173E3AEFBF3DF5D6D2FE).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Meteorological and Dissolved Oxygen Data - Trout Lake Buoy 2004 - current.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/1B66CE0B3F0CF7C3F5922FB320B5591E](http://doi.org/10.6073/PASTA/1B66CE0B3F0CF7C3F5922FB320B5591E).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Water Temperature Data - Lake Mendota Buoy 2006 - current.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/B6B6B2F2070500202E10E219044B547B](http://doi.org/10.6073/PASTA/B6B6B2F2070500202E10E219044B547B).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: High Frequency Water Temperature Data - Trout Lake Buoy 2004 - current.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/767E476FCA7BEDF46D4905517854C8F7](http://doi.org/10.6073/PASTA/767E476FCA7BEDF46D4905517854C8F7).
- J. J. Magnuson, S. R. Carpenter, and E. H. Stanley, “North Temperate Lakes LTER: Physical Limnology of Primary Study Lakes 1981 - current.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/BE287E7772951024EC98D73FA94EEC08](http://doi.org/10.6073/PASTA/BE287E7772951024EC98D73FA94EEC08).
- D. McKnight, P. Johnson, K. Loria, Niwot Ridge LTER, and S. Dykema, “Stream and lake water chemistry data for Green Lakes Valley, 1998 - ongoing.” Environmental Data Initiative, 2021. doi: [10.6073/PASTA/811E22E67AA850FA6C03148AB621E76E](http://doi.org/10.6073/PASTA/811E22E67AA850FA6C03148AB621E76E).
- D. M. McKnight, S. Yevak, S. Dykema, K. Loria, and Niwot Ridge LTER, “Water quality data for Green Lakes Valley, 2000 - ongoing.” Environmental Data Initiative, 2023. doi: [10.6073/PASTA/4835FFF2B96F16677AB1ABB9C46DB34B](http://doi.org/10.6073/PASTA/4835FFF2B96F16677AB1ABB9C46DB34B).
- National Ecological Observatory Network (NEON), “Chemical properties of surface water (DP1.20093.001), RELEASE-2024.” National Ecological Observatory Network (NEON), 2024. doi: [10.48443/FDFD-D514](http://doi.org/10.48443/FDFD-D514).
- National Ecological Observatory Network (NEON), “Depth profile at specific depths (DP1.20254.001), RELEASE-2024.” National Ecological Observatory Network (NEON), 2024. doi: [10.48443/VCT8-PR05](http://doi.org/10.48443/VCT8-PR05).
- National Ecological Observatory Network (NEON), “Nitrate in surface water (DP1.20033.001), RELEASE-2024.” National Ecological Observatory Network (NEON), 2024. doi: [10.48443/MVDB-K902](http://doi.org/10.48443/MVDB-K902).
- National Ecological Observatory Network (NEON), “Periphyton, seston, and phytoplankton chemical properties (DP1.20163.001), RELEASE-2024.” National Ecological Observatory Network (NEON), 2024. doi: [10.48443/25WY-9F31](http://doi.org/10.48443/25WY-9F31).
- National Ecological Observatory Network (NEON), “Photosynthetically active radiation at water surface (DP1.20042.001), RELEASE-2024.” National Ecological Observatory Network (NEON), 2024. doi: [10.48443/S71B-KK05](http://doi.org/10.48443/S71B-KK05).
- National Ecological Observatory Network (NEON), “Photosynthetically active radiation below water surface (DP1.20261.001), RELEASE-2024.” National Ecological Observatory Network (NEON), 2024. doi: [10.48443/JNWY-XY08](http://doi.org/10.48443/JNWY-XY08).
- National Ecological Observatory Network (NEON), “Secchi depth (DP1.20252.001), RELEASE-2024.” National Ecological Observatory Network (NEON), 2024. doi: [10.48443/DTR7-N376](http://doi.org/10.48443/DTR7-N376).
- National Ecological Observatory Network (NEON), “Temperature at specific depth in surface water (DP1.20264.001), RELEASE-2024.” National Ecological Observatory Network (NEON), 2024. doi: [10.48443/4WDS-5B25](http://doi.org/10.48443/4WDS-5B25).
- National Ecological Observatory Network (NEON), “Water quality (DP1.20288.001), RELEASE-2024.” National Ecological Observatory Network (NEON), 2024. doi: [10.48443/T7RJ-PK25](http://doi.org/10.48443/T7RJ-PK25).
- National Ecological Observatory Network (NEON), “Discharge field collection (DP1.20048.001), RELEASE-2024.” National Ecological Observatory Network (NEON), p. 17.8 MB, Jan. 26, 2024. doi: [10.48443/3746-1981](http://doi.org/10.48443/3746-1981).

Sources of static lake attributes in Lake_Info.csv:

- K. S. Aho, T. Maavara, K. M. Cawley, and P. A. Raymond, “Inland Waters can Act as Nitrous Oxide Sinks: Observation and Modeling Reveal that Nitrous Oxide Undersaturation May Partially Offset Emissions,” Geophysical Research Letters, vol. 50, no. 21, p. e2023GL104987, 2023, doi: [10.1029/2023GL104987](http://doi.org/10.1029/2023GL104987).
- J. S. Baron and N. Caine, “Temporal coherence of two alpine lake basins of the Colorado Front Range, USA,” Freshwater Biology, vol. 43, no. 3, pp. 463–476, 2000, doi: [10.1046/j.1365-2427.2000.00517.x](http://doi.org/10.1046/j.1365-2427.2000.00517.x).
- C. C. Carey et al., “Bathymetry and watershed area for Falling Creek Reservoir, Beaverdam Reservoir, and Carvins Cove Reservoir.” Environmental Data Initiative, 2022. doi: [10.6073/PASTA/352735344150F7E77D2BC18B69A22412](http://doi.org/10.6073/PASTA/352735344150F7E77D2BC18B69A22412).
- R. M. Cory, D. M. McKnight, Y.-P. Chin, P. Miller, and C. L. Jaros, “Chemical characteristics of fulvic acids from Arctic surface waters: Microbial contributions and photochemical transformations,” Journal of Geophysical Research: Biogeosciences, vol. 112, no. G4, 2007, doi: [10.1029/2006JG000343](http://doi.org/10.1029/2006JG000343).
- J. P. Doubek et al., “The effects of hypolimnetic anoxia on the diel vertical migration of freshwater crustacean zooplankton,” Ecosphere, vol. 9, no. 7, p. e02332, 2018, doi: [10.1002/ecs2.2332](http://doi.org/10.1002/ecs2.2332).
- C. M. Flanagan, D. M. McKnight, D. Liptzin, M. W. Williams, and M. P. Miller, “Response of the Phytoplankton Community in an Alpine Lake to Drought Conditions: Colorado Rocky Mountain Front Range, U.S.A,” Arctic, Antarctic, and Alpine Research, vol. 41, no. 2, pp. 191–203, May 2009, doi: [10.1657/1938.4246-41.2.191](http://doi.org/10.1657/1938.4246-41.2.191).
- J. W. Gaeta, T. R. Hrabik, G. G. Sass, B. M. Roth, S. J. Gilbert, and M. J. Vander Zanden, “A whole-lake experiment to control invasive rainbow smelt (Actinoperygii, Osmeridae) via overharvest and a food web manipulation,” Hydrobiologia, vol. 746, no. 1, pp. 433–444, Mar. 2015, doi: [10.1007/s10750-014-1916-3](http://doi.org/10.1007/s10750-014-1916-3).
- A. B. Gerling, R. G. Browne, P. A. Gantzer, M. H. Mobley, J. C. Little, and C. C. Carey, “First report of the successful operation of a side stream supersaturation hypolimnetic oxygenation system in a eutrophic, shallow reservoir,” Water Research, vol. 67, pp. 129–143, Dec. 2014, doi: [10.1016/j.watres.2014.09.002](http://doi.org/10.1016/j.watres.2014.09.002).
- R. C. Lathrop et al., “Stocking piscivores to improve fishing and water clarity: a synthesis of the Lake Mendota biomanipulation project,” Freshwater Biology, vol. 47, no. 12, pp. 2410–2424, 2002, doi: [10.1046/j.1365-2427.2002.01011.x](http://doi.org/10.1046/j.1365-2427.2002.01011.x).
- R. C. Lathrop and S. R. Carpenter, “Water quality implications from three decades of phosphorus loads and trophic dynamics in the Yahara chain of lakes,” Inland Waters, vol. 4, no. 1, pp. 1–14, Jan. 2014, doi: [10.5268/IW-4.1.680](http://doi.org/10.5268/IW-4.1.680).
- Z. J. Lawson, M. J. Vander Zanden, C. A. Smith, E. Heald, T. R. Hrabik, and S. R. Carpenter, “Experimental mixing of a north-temperate lake: testing the thermal limits of a cold-water invasive fish,” Can. J. Fish. Aquat. Sci., vol. 72, no. 6, pp. 926–937, Jun. 2015, doi: [10.1139/cjfas-2014-0346](http://doi.org/10.1139/cjfas-2014-0346).
- Y.-T. Lin and C. H. Wu, “Response of bottom sediment stability after carp removal in a small lake,” Ann. Limnol. - Int. J. Lim., vol. 49, no. 3, Art. no. 3, 2013, doi: [10.1051/limn/2013049](http://doi.org/10.1051/limn/2013049).
- N. R. Lottig and H. A. Dugan, “North Temperate Lakes-LTER Core Research Lakes Information.” Environmental Data Initiative, 2024. doi: [10.6073/PASTA/B9080C962F552029EE2B43AEC1410328](http://doi.org/10.6073/PASTA/B9080C962F552029EE2B43AEC1410328).
- J. T. Mrnak, L. W. Sikora, M. J. V. Zanden, and G. G. Sass, “Applying Panarchy Theory to Aquatic Invasive Species Management: A Case Study on Invasive Rainbow Smelt Osmerus mordax,” Reviews in Fisheries Science & Aquaculture, vol. 31, no. 1, pp. 66–85, Jan. 2023, doi: [10.1080/23308249.2022.2078951](http://doi.org/10.1080/23308249.2022.2078951).
- K. M. Perales et al., “Spatial and temporal patterns in native and invasive crayfishes during a 19-year whole-lake invasive crayfish removal experiment,” Freshwater Biology, vol. 66, no. 11, pp. 2105–2117, 2021, doi: [10.1111/fwb.13818](http://doi.org/10.1111/fwb.13818).
- W. Rast and G. F. Lee, “Report on Nutruent Load - Eutrophication Response of Lake Wingra, Wisconsin,” Environmental Research Laboratory-Corvallis, Office of Research and Development, U.S. Environmental Protection Agency, 1977.
- R. Q. Thomas et al., “Near-term forecasts of NEON lakes reveal gradients of environmental predictability across the US,” Frontiers in Ecology and the Environment, vol. 21, no. 5, pp. 220–226, 2023, doi: [10.1002/fee.2623](http://doi.org/10.1002/fee.2623).
- United States Geological Survey, “The National Map Bulk Point Query Service.” Accessed: Jun. 13, 2024. [Online]. Available: https://apps.nationalmap.gov/bulkpqs/
- S. Upadhyay, K. A. Bierlein, J. C. Little, M. D. Burch, K. P. Elam, and J. D. Brookes, “Mixing potential of a surface-mounted solar-powered water mixer (SWM) for controlling cyanobacterial blooms,” Ecological Engineering, vol. 61, pp. 245–250, Dec. 2013, doi: [10.1016/j.ecoleng.2013.09.032](http://doi.org/10.1016/j.ecoleng.2013.09.032).
- C. J. Watras and P. C. Hanson, “Ecohydrology of two northern Wisconsin bogs,” Ecohydrology, vol. 16, no. 8, p. e2591, 2023, doi: [10.1002/eco.2591](http://doi.org/10.1002/eco.2591).
- K. E. Webster, T. K. Kratz, C. J. Bowser, J. J. Magnuson, and W. J. Rose, “The influence of landscape position on lake chemical responses to drought in northern Wisconsin,” Limnology and Oceanography, vol. 41, no. 5, pp. 977–984, 1996, doi: [10.4319/lo.1996.41.5.0977](http://doi.org/10.4319/lo.1996.41.5.0977).
</details>

## **Difference Between LakeBeD-US Editions**

The original LakeBeD-US dataset is structured in a "long" format. In this 
format, columns representing different variables are stored in one column as 
multiple rows. This format makes the addition of new variables an easy process.

<img src="https://www.statology.org/wp-content/uploads/2021/12/wideLong3-1.png" alt="Depiction of a long format dataset" width="400">

However, machine learning tasks typically leverage a "wide" format.

LakeBeD-US: Computer Science Edition presents the original LakeBeD-US data in a 
tabular format where each column corresponds to a different variable and each 
row to a distinct observation.

<img src="https://www.statology.org/wp-content/uploads/2021/12/wideLong4.png" alt="Depiction of a wide format dataset" width="400">

## **LakeBeD-US: Computer Science Edition** Creation Workflow

### Process

The data preprocessing script takes the following steps to transform the 
LakeBeD-US: Ecology Edition into the Computer Science Edition.

1. **Data Imputation**

	The original LakeBeD-US dataset contains missing values, specifically in 
	the `depth` and `flag` column. These occur in one-dimensional variables' 
	observations (because there is no notion of depth for these variables) and 
	observations that are not erroneous. This step imputes missing values for 
	`flag` by assuming observations that are reported without a value for 
	`flag` should have a value of '0'. It does not impute values for `depth` 
	because we wish to leave the decision of whether to impute values for 
	`depth` to the end user or to omit `depth` entirely from one-dimensional 
	variables.
2. **Data Formatting**
	
	This step converts the columns in the long format of the data to the 
	appropriate types. The typecasts are given as follows:

	| Column        | Typecast          |
	| ------------- | ----------------- |
	| `source`      | `str`             |
	| `datetime`    | `pandas.datetime` |
	| `lake_id`     | `str`             |
	| `depth`       | `float`           | 
	| `variable`    | `str`             | 
	| `unit`        | `str`             | 
	| `observation` | `float`           | 
	| `flag`        | `int`             |

3. **Data Cleaning**

	1. **Erroneous Observation Removal**

		Some observations are reported with depth values of "-99". We omit 
		these values. 
		
		*Note: Depth is measured positively from the surface of 
		the water downwards. Negative depth implies an observation above 
		surface level. Observations with negative depth values are not 
		necessarily erroneous. The surface level of the water changes over 
		time, leading to situations where the sensor may be above the water 
		level.*

	2. **Variable Renaming**

		Chlorophyll a (`chla`) is reported in two units: micrograms per liter 
		and relative fluoresence units. Since we omit the `unit` column from 
		the final dataset, we create two variables: `chla_ugl` and `chla_rfu` 
		depending on the unit a particular `chla` observation was measured in.

4. **Data Structuring**

	1. **Lake Splitting**

		A dataframe read from a single file in the distribution of the data, 
		could contain data from multiple lakes. We split this dataframe into 
		multiple dataframes each with their own lake.

	2. **Deduplication**

		For a given datetime, depth, if applicable, and flag, there could be 
		multiple observations for a variable. We aggregate these into a single 
		observation using a median aggregation function.

	3. **Separating Variables**

		We separate the data into two dataframes which contain one-dimensional 
		and two-dimensional variables, respectively.

	4. **Pivoting**

		We perform a pivot of the two dataframes after separation into a wide 
		format. We pivot on `datetime` and `flag` for one-dimensional variables 
		and `datetime`, `depth`, and `flag` for two-dimensional variables.
	
### **Preprocessing Usage**

To run the preprocessing script, located in `src/`, simply unzip the original 
LakeBeD-US zip file into a directory and use the following command

```bash
$ python3 preprocess.py [LAKEBED-US DIRECTORY]/
```

# Dataset Metadata and Usage

## Folder and File Structure

LakeBeD-US: Computer Science Edition is organized into multiple levels. At the top level, we seperate high-frequency and low-frequency data. High-frequency data are data that are collected by automated sensors, typically mounted to a buoy on the lake. Low-frequency data is collected manually. The temporal frequency of these data vary greatly, and should be considered before use.

Within the `HighFrequency` and `LowFrequency` folders are folders dedicated to specific lakes. The 21 Lakes in LakeBeD-US are listed in the table below.
| Folder Name | Lake Name               | Long-Term Monitoring Program     | Location                     |
|-------------|-------------------------|----------------------------------|------------------------------|
| AL          | Allequash Lake          | NTL-LTER                         | Vilas County, WI, USA        |
| BARC        | Lake Barco              | NEON                             | Putman County, FL, USA       |
| BM          | Big Muskellunge Lake    | NTL-LTER                         | Vilas County, WI, USA        |
| BVR         | Beaverdam Reservoir     | Virginia Reservoirs LTREB        | Roanoke County, VA, USA      |
| CB          | Crystal Bog             | NTL-LTER                         | Vilas County, WI, USA        |
| CR          | Crystal Lake            | NTL-LTER                         | Vilas County, WI, USA        |
| CRAM        | Crampton Lake           | NEON                             | Vilas County, WI, USA        |
| FCR         | Falling Creek Reservoir | Virginia Reservoirs LTREB        | Roanoke County, VA, USA      |
| FI          | Fish Lake               | NTL-LTER                         | Dane County, WI, USA         |
| GL4         | Green Lake 4            | NWT-LTER                         | Boulder County, CO, USA      |
| LIRO        | Little Rock Lake        | NEON                             | Vilas County, WI, USA        |
| ME          | Lake Mendota            | NTL-LTER                         | Dane County, WI, USA         |
| MO          | Lake Monona             | NTL-LTER                         | Dane County, WI, USA         |
| PRLA        | Prairie Lake            | NEON                             | Stutsman County, ND, USA     |
| PRPO        | Prairie Pothole         | NEON                             | Stutsman County, ND, USA     |
| SP          | Sparkling Lake          | NTL-LTER                         | Vilas County, WI, USA        |
| SUGG        | Lake Suggs              | NEON                             | Putman County, FL, USA       |
| TB          | Trout Bog               | NTL-LTER                         | Vilas County, WI, USA        |
| TOOK        | Toolik Lake             | NEON                             | North Slope Borough, AK, USA |
| TR          | Trout Lake              | NTL-LTER                         | Vilas County, WI, USA        |
| WI          | Lake Wingra             | NTL-LTER                         | Dane County, WI, USA         |

For more information about these lakes, please refer to `Lake_Info.csv`.

Within the folder for each lake, multiple files are present. Files ending with `*_1D.parquet` contain the information for 1-dimensional variables. 1D variables change over time within each lake, but do not measured across discrete depths. Files ending with `*_2D.parquet` contain 2D variables that vary across time and across depths within the lake. Each file contains columns pertaining to only the variables measured for that specific lake, and each column refers to a specific water quality variable. The possible columns are listed in the table below.
| Column Name | Description/Water Quality Variable                  | Units                                  | Dimensionality |
|-------------|-----------------------------------------------------|----------------------------------------|----------------|
| datetime    | Time of the observation in the lake's local time    |                                        |                |
| flag        | Quality flag for the observed value                 |                                        |                |
| depth       | Depth of the observed value                         | Meters                                 |                |
| chla_rfu    | Chlorophyll a                                       | Relative Flourenscence Units           | 2D             |
| chla_ugl    | Chlorophyll a                                       | Micrograms per liter (µg/L)            | 2D             |
| do          | Dissolved oxygen                                    | Milligrams per liter (mg/L)            | 2D             |
| fdom        | Flourescent dissolved organic matter                | Relative Flourenscence Units           | 2D             |
| temp        | Temperature                                         | Degrees Celcius                        | 2D             |
| phyco       | Phycocyanin                                         | Relative Flourenscence Units           | 2D             |
| tp          | Total phosphorus                                    | Micrograms per liter (µg/L)            | 2D             |
| drp         | Dissolved reactive phosphorus                       | Micrograms per liter (µg/L)            | 2D             |
| tn          | Total nitrogen                                      | Micrograms per liter (µg/L)            | 2D             |
| no2         | Nitrite as nitrogen (NO<sub>2</sub>-N)              | Micrograms per liter (µg/L)            | 2D             |
| no3         | Nitrate as nitrogen (NO<sub>3</sub>-N)              | Micrograms per liter (µg/L)            | 2D             |
| no3no2      | Combined nitrite and nitrate as nitrogen (NO<sub>2</sub>+NO<sub>3</sub>-N) | Micrograms per liter (µg/L) | 2D |
| nh4         | Ammonium and nitrogen (NH<sub>4</sub>-N)            | Micrograms per liter (µg/L)            | 2D             |
| dic         | Dissolved inorganic carbon                          | Milligrams per liter (mg/L)            | 2D             |
| doc         | Dissolved organic carbon                            | Milligrams per liter (mg/L)            | 2D             |
| poc         | Particulate organic carbon                          | Milligrams per liter (mg/L)            | 2D             |
| par         | Photosynthetically active radiation (light)         | Micromoles per square meter per second | 2D             |
| secchi      | Secchi depth                                        | Meters                                 | 1D             |
| inflow      | Surface water inflow into the lake                  | Cubic meters per second                | 1D             |

<details>
	<summary>A full list of the definitions for quality flags is listed if you click here. In summary, quality flags 0, 5, 10, 19, 23, 25, 32, 43, 47, 51, and 52 are generally acceptable but any other quality flag should be used with caution or removed.</summary>
	
| Flag | Definition                                                                                             |
|------|--------------------------------------------------------------------------------------------------------|
| 0    | No flag                                                                                                |
| 1    | Sample suspect                                                                                         |
| 2    | Standard curve/reduction suspect                                                                       |
| 3    | Sample not taken                                                                                       |
| 4    | Sample lost                                                                                            |
| 5    | Average of duplicate analyses                                                                          |
| 6    | Duplicate analyses in error                                                                            |
| 7    | Analysed late                                                                                          |
| 8    | Outside of standard range                                                                              |
| 9    | Outside of data entry constraints                                                                      |
| 10   | Nonstandard methods                                                                                    |
| 11   | Data suspect                                                                                           |
| 12   | Data point and blind value differ by more than 15%                                                     |
| 13   | More than four quality flags                                                                           |
| 14   | Sample retested                                                                                        |
| 15   | Value suspect but total pigment(chlorophyll + phaeophytin) value accurate                              |
| 16   | TPM (total particulate matter) uncorrected for humidity change between filter weighing                 |
| 17   | Quality control comments on SLOH (Wisconsin State Lab of Hygiene) lab sheet                            |
| 18   | Value between LOD (limit of detection) and LOQ (limit of quantification)                               |
| 19   | Value below detection limit; set to zero                                                               |
| 20   | Sample contaminated; data not reported                                                                 |
| 21   | Equipment malfunction produced bad value; value set to missing                                         |
| 22   | Could not be computed; set to missing                                                                  |
| 23   | negative value set to zero                                                                             |
| 24   | Value below detection limit                                                                            |
| 25   | Sensor was off during part of the averaged period                                                      |
| 26   | Data logger off                                                                                        |
| 27   | Sensor off                                                                                             |
| 28   | Sensor malfunction                                                                                     |
| 29   | Sensor calibration suspect                                                                             |
| 30   | Sensor has suspected biofouling                                                                        |
| 31   | Measurement removed (above water)                                                                      |
| 32   | Date is accurate but time is inaccurate                                                                |
| 33   | value corrected to account for artificial increase in pressure after sensor maintenance                |
| 34   | value of NA due to extremely low flows that are not well captured by rectangular or v-notch weir       |
| 35   | demonic intrusion                                                                                      |
| 36   | value of NA due to leaking at weir                                                                     |
| 37   | flow topping the v-notch weir                                                                          |
| 38   | missing observation/not recorded                                                                       |
| 39   | values removed because of maintenance                                                                  |
| 40   | value down corrected due to low flows on the rectangular weir                                          |
| 41   | value downcorrected due to flow overtopping the rectangular weir                                       |
| 42   | sensor malfunction and demonic intrusion                                                               |
| 43   | sample run using NPOC (non-purgeable organic carbon) method due to high inorganic carbon values        |
| 44   | Duplicate check failed                                                                                 |
| 45   | Pigment in extract below detection (<34 ug/L)                                                          |
| 46   | More than two quality flags                                                                            |
| 47   | Flagged with no explanation                                                                            |
| 48   | Value corrected using a constant offset due to two thermistor   malfunctions in Fall 2020              |
| 49   | negative or outlier value removed and set to NA, see Methods section for more detail on QAQC process   |
| 50   | buoy sink event                                                                                        |
| 51   | Secchi Depth hit bottom (calculated for NEON Lakes only)                                               |
| 52   | unknown depth near surface. Labeled as 0.5m                                                            |
	
</details>

## Citation
When using this data, please use the following Bibtex citation, and include the DOI for the version used:

```bibtex
@misc{lakebed-us-cs_2024,
	title = {{LakeBeD}-{US}: {Computer} {Science} {Edition} - a benchmark dataset for lake water quality time series and vertical profiles},
	url = {https://huggingface.co/datasets/eco-kgml/LakeBeD-US-CSE},
	language = {en},
	publisher = {Hugging Face},
	author = {Pradhan, Aanish and McAfee, Bennett J. and Neog, Abhilash and Fatemi, Sepideh and Lofton, Mary E. and Carey, Cayelan C. and Karpatne, Anuj and Hanson, Paul C.},
	year = {2024},
}
```

## Project Funding
Funding to create the LakeBeD-US datasets was provided by the U.S. National Science Foundation (grants no. DEB-2213549, DEB-2213550, DEB-2025982, DEB-2327030, EF-2318861, and DBI-2223103).

<img alt="USNSF_Logo_Lockup_hor_RGB_1200ppi.png" src="https://nsf.widen.net/content/oht0v7rx8o/png/USNSF_Logo_Lockup_hor_RGB_1200ppi.png?position=c&quality=80&x.portal_shortcode_generated=dnmqqhzz&x.collection_sharename=pyoiomsk&x.app=portals" width = 300>