A mechanistic, biophysical water-quality model (CE–QUAL–W2) was developed and calibrated for Lake St. Croix, Wisconsin and Minnesota. The Lake St. Croix CE–QUAL–W2 model was simulated and calibrated using data collected from April through November 2013. Loads developed for the model were based on water-quality data collected by various agencies, including the U.S. Geological Survey (USGS). The calibrated model was used to evaluate good- and optimal-growth habitat availability for lake sturgeon using coldwater fish oxygen and thermal requirements, as part of the associated report, U.S. Geological Survey Scientific Investigations Report 2017-5157 (http://dx.doi.org/10.3133/SIR20175157).

The U.S. Geological Survey (USGS), in cooperation with the St. Croix River Research Station – Science Museum of Minnesota, updated a previously developed CE-QUAL-W2 hydrodynamic and water-quality model of Madison Lake, Minnesota (Smith and others, 2017). The previous version simulated phytoplankton into four general algal communities or groups: (1) Bacillariophyta (diatoms) and Chrysophyta (chrysophytes); (2) Chlorophyta (green algae); (3) Cyanophyta (blue-green algae); and, (4) Haptophyta and Cryptophyta (flagellates). For the updated model, the Cyanophyta group (originally referred to as blue-green algae) has been divided into two groups: a nitrogen-fixing Cyanophyta group, generally representative of Anabaena, Dolichospermum, and Cylindrospermopsis, and a non-fixing, buoyant Cyanophyta group, generally representative of Planktothrix, Microcystis, and Woronichinia.

The U.S. Army Corps of Engineers is considering changing the operations of Berlin Lake, Lake Milton, Michael J Kirwan Reservoir, and Mosquito Creek Lake. The lakes in this study are all reservoirs, formed by dams. These models were constructed to simulate those operations and document possible water-quality effects in the lakes, the lake outflows, and the Mahoning River downstream of the lakes. This data release includes U.S. Army Corps of Engineers water-quality data and the input and output files from the mechanistic water-quality models (CE-QUAL-W2).

CE-QUAL-W2, a mechanistic, two-dimensional model of hydrodynamics and water quality (Portland State University, 2021), was developed and calibrated for J. Percy Priest Reservoir, Tennessee, a U.S. Army Corps of Engineers (USACE) reservoir on the Stones River, southeast of Nashville, Tennessee. The J. Percy Priest CE-QUAL-W2 model was simulated and calibrated using USACE data collected from January 2012 through May 2019. Constituent loads were developed for the CE-QUAL-W2 model using the LOAD ESTimator (LOADEST; U.S. Geological Survey, 2016) and were based on water-quality data collected by the USACE from January 2005 through May 2019. The calibrated model will be used by the Tennessee Department of Environmental Conservation and others as a water-quality diagnostic and predictive tool for water-resources management. References: Portland State University, 2021, CE-QUAL-W2 Hydrodynamic and Water Quality Model: Water Quality Research Group, accessed October 19, 2021, at http://www.cee.pdx.edu/w2/. U.S. Geological Survey, 2016, Load Estimator (LOADEST): A Program for Estimating Constituent Loads in Streams and Rivers: U.S. Geological Survey website, accessed February 8, 2022 at https://water.usgs.gov/software/loadest/.

CE-QUAL-W2, a mechanistic, two-dimensional model of hydrodynamics and water quality (Portland State University, 2021), was developed and calibrated for J. Percy Priest Reservoir, Tennessee, a U.S. Army Corps of Engineers (USACE) reservoir on the Stones River, southeast of Nashville, Tennessee. The J. Percy Priest CE-QUAL-W2 model was simulated and calibrated using USACE data collected from January 2012 through May 2019. Constituent loads were developed for the CE-QUAL-W2 model using the LOAD ESTimator (LOADEST; U.S. Geological Survey, 2016) and were based on water-quality data collected by the USACE from January 2005 through May 2019. The calibrated model will be used by the Tennessee Department of Environmental Conservation and others as a water-quality diagnostic and predictive tool for water-resources management. References: Portland State University, 2021, CE-QUAL-W2 Hydrodynamic and Water Quality Model: Water Quality Research Group, accessed October 19, 2021, at http://www.cee.pdx.edu/w2/. U.S. Geological Survey, 2016, Load Estimator (LOADEST): A Program for Estimating Constituent Loads in Streams and Rivers: U.S. Geological Survey website, accessed February 8, 2022 at https://water.usgs.gov/software/loadest/.

Green Peter Dam on the Middle Santiam River and the downstream Foster Dam on the South Santiam River in Oregon have altered natural seasonal temperature patterns in those rivers. In response, the U.S. Army Corps of Engineers is leading efforts to improve conditions for Chinook salmon upstream and downstream of these dams by considering structural alterations and by exploring changes to the way the dams are operated. This data release includes the input and output files from a mechanistic water-quality model (CE–QUAL–W2) that was developed for Green Peter and Foster Lakes and the South Santiam River downstream of Foster Dam. The model was used to estimate how operations at Green Peter and Foster Dams affect water temperature in Foster Lake and in the South Santiam River downstream of Foster Dam, and how the dams can be operated to produce more optimal water temperatures to support fish requirements. The model results provide guidance to reservoir operators and water-resource professionals who seek to manage the South Santiam River Basin for multiple purposes, including improved conditions for endangered anadromous fish.

Green Peter Dam on the Middle Santiam River and the downstream Foster Dam on the South Santiam River in Oregon have altered natural seasonal temperature patterns in those rivers. In response, the U.S. Army Corps of Engineers is leading efforts to improve conditions for Chinook salmon upstream and downstream of these dams by considering structural alterations and by exploring changes to the way the dams are operated. This data release includes the input and output files from a mechanistic water-quality model (CE–QUAL–W2) that was developed for Green Peter and Foster Lakes and the South Santiam River downstream of Foster Dam. The model was used to estimate how operations at Green Peter and Foster Dams affect water temperature in Foster Lake and in the South Santiam River downstream of Foster Dam, and how the dams can be operated to produce more optimal water temperatures to support fish requirements. The model results provide guidance to reservoir operators and water-resource professionals who seek to manage the South Santiam River Basin for multiple purposes, including improved conditions for endangered anadromous fish.

A hydrodynamic, water-temperature, and water-quality model (CE-QUAL-W2; Wells, 2020) of the Link-Keno reach of the Klamath River (Oregon) was used for calendar years 2006–15 to run a series of base and recirculation scenarios. These model runs were implemented to test alternative scenarios for routing some of the Klamath Straits Drain discharge into Ady Canal. The model scenarios were configured for baseline conditions and three different sets of recirculation scenarios, including the maximum year-round recirculation without discharge limits (scenario 1), limited year-round recirculation fixed by the current pipe flow configuration from Klamath Straits Drain into Ady Canal (scenario 2), and limited seasonal recirculation (May-September), also fixed by the current pipe flow configuration (scenario 3). For calendar years 2012–15, a separate CE-QUAL-W2 model for the Klamath Straits Drain was used in lieu of the Klamath Straits Drain as a tributary directly into the Link-Keno reach of the Klamath River CE-QUAL-W2 model. Original calibration and simulation of the Klamath Straits Drain model was documented in Sullivan and Rounds (2018). Original calibration and simulation of the Link-Keno reach of the Klamath River was documented in Sullivan and others (2011). These recirculation scenarios will be used by the United States Bureau of Reclamation to better understand the effects of recirculating Klamath Straits Drain discharge into Ady Canal on constituent loads of total nitrogen, total phosphorus, and the 5-day biochemical oxygen demand (BOD5).

This data release consists of a two-dimensional (laterally averaged) hydrodynamic water-quality model (CE-QUAL-W2; Wells, 2019) of Green Peter and Foster Lakes for the 2023 calendar year, and three theoretical deep drawdown operational scenarios that apply the 2023 model to calendar year 2024. The model and scenarios were used to gain insights into the thermal processes in Green Peter and Foster Lakes and downstream water release temperatures from Green Peter Dam to the Middle Santiam River and from Foster Lake to the South Santiam River during deep drawdown operations, and to investigate the effects of deep reservoir drawdown timing on water temperatures within and downstream of Green Peter and Foster Lakes. The model and scenarios documented here were modified from the Green Peter and Foster Lakes model documented in Stratton Garvin and Rounds (2023) and Stratton Garvin and others (2023), and are not appropriate for use other than the intended purpose of comparing various drawdown operational scenarios using 2023 deep drawdown conditions to inform potential management decisions.

It is well recognized that the climate is warming in response to anthropogenic emission of greenhouse gases. Over the last decade, this has had a warming effect on lakes. Water clarity is also known to effect water temperature in lakes. What is unclear is how a warming climate might interact with changes in water clarity in lakes. As part of a project at the USGS Office of Water Information, several water clarity scenarios were simulated for lakes in Wisconsin to examine how changing water clarity interacts with climate change to affect lake temperatures at a broad scale. This data set contains the following parameters: year, WBIC, durStrat, max_schmidt_stability, mean_schmidt_stability_JAS, mean_schmidt_stability_July, SthermoD_mean_JAS, SthermoD_mean, lake_average_temp, peak_lake_average_temp, lake_average_temp_JAS, mean_epi_temp, mean_hypo_temp, mean_surf_temp, mean_bottom_temp, peak_surf_temp, peak_bottom_temp, mean_surf_temp_JAS, mean_bottom_temp_JAS, mean_bottom_temp_365, mean_surf_temp_365, mean_1m_temp, mean_surf_JA, GDD_wtr_5c, GDD_wtr_10c, volume_mean_m_3, simulation_length_days, mean_volumetric_temp, kd, out_val calculated for 2210 lakes.