Geographically paired lake-reservoir dataset derived from the 2007 USA EPA National Lakes Assessment
Abstract
Climate change poses a significant threat to lake and reservoir ecosystems, though the exact nature of these threats may differ between lakes and reservoirs. To assess differences between lakes and reservoirs that may influence their response to climate change, we compared catchment and waterbody attributes of 132 geographically paired lakes and reservoirs from the 2007 United States Environmental Protection Agencys National Lakes Assessment (NLA) dataset. The data include the NLA IDs of each waterbody and their elevation, catchment area, surface area, perimeter, maximum depth, residence time, Secchi disk depth, surface temperature, and bottom temperature. Residence time data was collected from estimates generated by Brooks, J.R., J.J. Gibson, S.J. Birks, M.H. Weber, K.D. Rodecap, J.L. Stoddard. 2014. Stable isotope estimates of evaporation: inflow and water residence time for lakes across the United States as a tool for national lake water quality assessments. Limnology and Oceanography 59(6):2150-2165.
Contact
Core Areas
Dataset ID
326
Data Sources
Date Range
-
LTER Keywords
Maintenance
completed
Methods
NLA data were obtained from US Environmental Protection Agency National Aquatic Resource Surveys website (https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys). We incorporated the NLAs definition of human-made lakes, lakes that did not exist prior to European settlement and resulted from impoundment, as reservoirs in our analysis. From this database, we identified geographically co-located lake and reservoir pairs. Pairs were defined as lakes and reservoirs within a 50 km radius of one another. We developed pairings using the near proximity analysis tool for Geographic Information Systems (ArcGIS 10.1). If more than one lake was found within 50 km of a reservoir, the closest lake was chosen for the analysis. We identified 66 lake-reservoir pairs and for each lake or reservoir, we consolidated its catchment and water body attributes from the NLA data onto our data spreadsheet.
Laboratory and field methods for the NLA data are reported by the US Environmental Protection Agency (https://www.epa.gov/national-aquatic-resource-surveys/national-lakes-assessment-2007-results). We used the NLA data directly to collect basic geographic and morphometric parameters (elevation, catchment area, lake area, lake perimeter, maximum depth) and physical parameters (Secchi disk depth, turbidity, chlorophyll, surface water temperature, bottom water temperature). Mean residence times were provided by Renée Brooks (pers. communication) and were estimated using stable isotopes of hydrogen and oxygen as described in Brooks et al. (2014). If more than one parameter was collected for a site, then the average among the values was used in the analysis. From these parameters, we also calculated the ratio of catchment area to surface area (CA:SA) and depth-corrected difference in temperature between the surface and bottom waters.
Laboratory and field methods for the NLA data are reported by the US Environmental Protection Agency (https://www.epa.gov/national-aquatic-resource-surveys/national-lakes-assessment-2007-results). We used the NLA data directly to collect basic geographic and morphometric parameters (elevation, catchment area, lake area, lake perimeter, maximum depth) and physical parameters (Secchi disk depth, turbidity, chlorophyll, surface water temperature, bottom water temperature). Mean residence times were provided by Renée Brooks (pers. communication) and were estimated using stable isotopes of hydrogen and oxygen as described in Brooks et al. (2014). If more than one parameter was collected for a site, then the average among the values was used in the analysis. From these parameters, we also calculated the ratio of catchment area to surface area (CA:SA) and depth-corrected difference in temperature between the surface and bottom waters.
Version Number
11
