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This dataset provides shapefile outlines of the 7,150 lakes that had temperature modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). A csv file of lake metadata is also included. This dataset is part of a larger data release of lake temperature model inputs and outputs for 7,150 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9CA6XP8).
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This dataset provides shapefile outlines of the 2,332 lakes that had temperature modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). A csv file of lake metadata is included, which includes lake metadata and all features that were considered for the meta transfer model (not all meta features were used). This dataset is part of a larger data release of lake temperature model inputs and outputs for 2,332 lakes in the U.S. (https://doi.org/10.5066/P9I00WFR).
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This dataset provides shapefile outlines of the 881 lakes that had temperature modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). A csv file of lake metadata is also included. This dataset is part of a larger data release of lake temperature model inputs and outputs for 881 lakes in the U.S. state of Minnesota (https://doi.org/10.5066/P9PPHJE2).
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This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning approaches to water quality modeling, including the prediction of stream temperature. This section provides spatial data files that describe the rivers, reservoirs, and observational data in the Delaware River Basin included in this release. One shapefile of polylines describes the 459 river reaches that define the modeling network, and another shapefile of polygons includes the three reservoirs (Pepacton, Cannonsville, and Neversink) for which data are included in this release. Additionally, a point shapefile contains locations of monitoring sites...
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This dataset provides shapefile of outlines of the 68 lakes where temperature was modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).
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This dataset provides site locations as shapefile points. The format is a shapefile for all sites combined (.shp, .shx, .dbf, and .prj files). This dataset is part of a larger data release of metabolism model inputs and outputs for 356 streams and rivers across the United States (https://doi.org/10.5066/F70864KX). The complete release includes: modeled estimates of gross primary productivity, ecosystem respiration, and the gas exchange coefficient; model input data and alternative input data; model fit and diagnostic information; site catchment boundaries and site point locations; and potential predictors of metabolism such as discharge and light availability.
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: 007, 012, AK, AL, AR, All tags...
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Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater species such as largemouth bass (Micropterus salmoides). Recent declines in walleye and increases in largemouth bass populations have raised questions regarding the future trajectories and appropriate management actions for these important species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, USA under contemporary (1989-2014) and future (2040-2064 and 2065-2089) conditions. We correlated contemporary walleye recruitment success and largemouth bass relative abundance...
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This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that made real-time predictions in the Delaware River Basin during 2021. The model is driven by weather forecasts and observed reservoir releases and produces maximum water temperature forecasts for the issue day (day 0) and 7 days into the future (days 1-7) at five sites. This data release captures the entire forecasting period that is reported in Zwart et al. 2022, and is an extension of a previous data release that contains all data needed to build these models but only extends to July 16, 2021 (Oliver et al. 2021). Additionally, this release contains a tidy version of the model predictions with paired...
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This data release provides the predictions from stream temperature models described in Chen et al. 2021. Briefly, various deep learning and process-guided deep learning models were built to test improved performance of stream temperature predictions below reservoirs in the Delaware River Basin. The spatial extent of predictions was restricted to streams above the Delaware River at Lordville, NY, and includes the West Branch of the Delaware River below Cannonsville Reservoir and the East Branch of the Delaware River below Pepacton Reservoir. Various model architectures, training schemes, and data assimilation methods were used to generate the table and figures in Chen et a.l (2021) and predictions of each model are...
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This data release component contains shapefiles of river basin polygons and monitoring site locations coincident with the outlets of those basins. A table of basin attributes is also supplied. Attributes, observations, and weather forcing data for these basins were used to train and test the stream temperature prediction models of Rahmani et al. (2021b).<\p>
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: AL, AR, AZ, Alabama, Arizona, All tags...
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Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum...
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This dataset provides shapefile outlines of the catchments contributing to sites where metabolism was or could have been estimated. The format is a shapefile for all sites combined (.shp, .shx, .dbf, and .prj files). This dataset is part of a larger data release of metabolism model inputs and outputs for 356 streams and rivers across the United States (https://doi.org/10.5066/F70864KX). The complete release includes: modeled estimates of gross primary productivity, ecosystem respiration, and the gas exchange coefficient; model input data and alternative input data; model fit and diagnostic information; site catchment boundaries and site point locations; and potential predictors of metabolism such as discharge and...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: 007, 012, AK, AL, AR, All tags...
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Stream networks with reservoirs provide a particularly hard modeling challenge because reservoirs can decouple physical processes (e.g., water temperature dynamics in streams) from atmospheric signals. Including observed reservoir releases as inputs to models can improve water temperature predictions below reservoirs, but many reservoirs are not well-observed. This data release contains predictions from stream temperature models described in Jia et al. 2022, which describes different deep learning and process-guided deep learning model architectures that were developed to handle scenarios of missing reservoir releases. The spatial extent of this modeling effort was restricted to two spatially disjointed regions...


    map background search result map search result map Spatial data: Projected shifts in fish species dominance in Wisconsin lakes under climate change Spatial data: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes Metabolism estimates for 356 U.S. rivers (2007-2017): 2b. Site catchment boundaries Metabolism estimates for 356 U.S. rivers (2007-2017): 2a. Site coordinates Process-guided deep learning water temperature predictions: 1 Spatial data (GIS polygons for 68 lakes) Process-based water temperature predictions in the Midwest US: 1 Spatial data (GIS polygons for 7,150 lakes) Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 1 Lake information for 881 lakes Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning: 1 Lake information for 2,332 lakes Predicting water temperature in the Delaware River Basin: 1 Waterbody information for 456 river reaches and 2 reservoirs 1 Site Information: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins Model predictions for heterogeneous stream-reservoir graph networks with data assimilation Data to support near-term forecasts of stream temperature using process-guided deep learning and data assimilation Stream temperature predictions in the Delaware River Basin using pseudo-prospective learning and physical simulations Data to support water quality modeling efforts in the Delaware River Basin: 1) Spatial data for rivers, reservoirs, and monitoring locations Data to support near-term forecasts of stream temperature using process-guided deep learning and data assimilation Model predictions for heterogeneous stream-reservoir graph networks with data assimilation Stream temperature predictions in the Delaware River Basin using pseudo-prospective learning and physical simulations Data to support water quality modeling efforts in the Delaware River Basin: 1) Spatial data for rivers, reservoirs, and monitoring locations Predicting water temperature in the Delaware River Basin: 1 Waterbody information for 456 river reaches and 2 reservoirs Spatial data: Projected shifts in fish species dominance in Wisconsin lakes under climate change Process-guided deep learning water temperature predictions: 1 Spatial data (GIS polygons for 68 lakes) Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 1 Lake information for 881 lakes Spatial data: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning: 1 Lake information for 2,332 lakes Process-based water temperature predictions in the Midwest US: 1 Spatial data (GIS polygons for 7,150 lakes) 1 Site Information: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins Metabolism estimates for 356 U.S. rivers (2007-2017): 2b. Site catchment boundaries Metabolism estimates for 356 U.S. rivers (2007-2017): 2a. Site coordinates