Using knowledge-guided machine learning to assess patterns of areal change in waterbodies across the contiguous U.S.: Data

<p>Data used for generating figures in the knowledge-guided machine learning manuscript and supplemental info by Wander et al.</p><p>This repository contains three folders:</p><ul><li><strong>Results: </strong>csv file with the final KGML groups for each waterbody. Latitude, longitude, RealSAT (Khandelwal et al., 2022) waterbody id, and HydroLAKES (Messager et al., 2016) waterbody id are provided.</li><li><strong>Code_data</strong>: data used for generating figures in the knowledge-guided machine learning manuscript and supplemental info by Wander et al.</li><li><strong>prism</strong>: data from PRISM dataset (Matsuura and Willmott) used for preliminary driver analysis in Wander et al.</li></ul><p>Khandelwal, A.; Karpatne, A.; Ravirathinam, P.; Ghosh, R.; Wei, Z.; Dugan, H.; Hanson, P. C.; Kumar, V. ReaLSAT, a global dataset of reservoir and lake surface area variations. <i>Sci. Data</i> <strong>2022</strong>, <i>9</i>, 356. <a href="https://doi.org/10.1038/s41597-022-01449-5">https://doi.org/10.1038/s41597-022-01449-5</a></p><p>Messager, M. L.; Lehner, B.; Grill, G.; Nedeva, I.; Schmitt, O. Estimating the volume and age of water stored in global lakes using a geo-statistical approach. <i>Nat. Commun.</i> <strong>2016</strong>, <i>7</i>, 1–11. <a href="https://doi.org/10.1038/ncomms13603">https://doi.org/10.1038/ncomms13603</a><br><br>Willmott, C. J.; Matsuura, K. Terrestrial Air Temperature and Precipitation: 1900-2014 Gridded Monthly Time Series: NOAA Physical Sciences Laboratory Terrestrial Air Temperature and Precipitation: 1900-2014 Gridded Monthly Time Series, <strong>2015</strong>. <a href="https://psl.noaa.gov/data/gridded/data.UDel_AirT_Precip.html">https://psl.noaa.gov/data/gridded/data.UDel_AirT_Precip.html</a>. (Accessed Jan 2022).</p><p>Danielson, J. J.; Gesch, D. B. TEMIS -- GMTED2010 Elevation Data at Different Resolutions, <strong>2011</strong>. <a href="https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-global-multi-resolution-terrain-elevation">https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-global-multi-resolution-terrain-elevation</a>. (Accessed Jan 2022).</p>