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This dataset provides timeseries data on water quality and quantity, as collected or computed from outside sources. The format is many tables with one row per time series observation (1 tab-delimited file per site-variable combination, 1 zip file per site). This compilation of data is intended for use in estimating or interpreting metabolism. Sites were included if they met the initial criteria of having at least 100 dissolved oxygen observations and one of the accepted NWIS site types ('ST','ST-CA','ST-DCH','ST-TS', or 'SP'). 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...
Tags: 007, 012, AK, AL, AR, All tags...
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This dataset provides input data formatted for use in estimating metabolism. The format is tables of prepared time series inputs (1 tab-delimited file per site, in 1 zip file per site). 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.
Tags: 007, 012, AK, AR, Aerobic respiration, All tags...
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Daily maximum water temperature predictions in the Delaware River Basin (DRB) can inform decision makers who can use cold-water reservoir releases to maintain thermal habitat for sensitive fish species. This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the upper DRB. The modeling approach includes process-guided deep learning and data assimilation (Zwart et al., 2023). 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). In combination with data provided in Oliver et al. (2022),...
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This data release component contains mean daily stream water temperature observations, retrieved from the USGS National Water Information System (NWIS) and used to train and validate all temperature models. The model training period was from 2010-10-01 to 2014-09-30, and the test period was from 2014-10-01 to 2016-09-30.
Categories: Data; Tags: AL, AR, AZ, Alabama, Arizona, All tags...
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This dataset provides site identifiers, details, and quality indicators. The format is a table with 1 row per site (tab-delimited file). 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.
Tags: 007, 012, AK, AL, AR, All tags...
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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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This data release provides all data and code used in Rahmani et al. (2021b) to model stream temperature and assess results. Briefly, we modeled stream temperature at sites across the continental United States using deep learning methods. The associated manuscript explores the prediction challenges posed by reservoirs, the value of additional training sites when predicting in gaged vs ungaged sites, and the value of an ensemble of attribute subsets in improving prediction accuracy. The data are organized into these child items: Site Information - Attributes and spatial information about the monitoring sites and basins in this study Observations - Water temperature observations for the sites used in this study Model...
Tags: AL, AR, AZ, Alabama, Arizona, All tags...
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This data release and model archive provides all data, code, and modelling results used in Topp et al. (2023) to examine the influence of deep learning architecture on generalizability when predicting stream temperature in the Delaware River Basin (DRB). Briefly, we modeled stream temperature in the DRB using two spatially and temporally aware process guided deep learning models (a recurrent graph convolution network - RGCN, and a temporal convolution graph model - Graph WaveNet). The associated manuscript explores how the architectural differences between the two models influence how they learn spatial and temporal relationships, and how those learned relationships influence a model's ability to accurately predict...
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This model archive provides all data, code, and modeling results used in Barclay and others (2023) to assess the ability of process-guided deep learning stream temperature models to accurately incorporate groundwater-discharge processes. We assessed the performance of an existing process-guided deep learning stream temperature model of the Delaware River Basin (USA) and explored four approaches for improving groundwater process representation: 1) a custom loss function that leverages the unique patterns of air and water temperature coupling resulting from different temperature drivers, 2) inclusion of additional groundwater-relevant catchment attributes, 3) incorporation of additional process model outputs, and...
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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 dataset provides model specifications used to estimate metabolism. The format is a table with 1 row per model (1 tab-delimited file, compressed into zip file). The specific format of this configuration file is arbitrary and specific to this analysis, and the format need not be replicated to use streamMetabolizer; however, this tabular format is useful because it allows for the reading by both humans and computers of (1) the combinations of sites and temporal resolutions for which models were run, (2) the timeseries data that were selected and combined to prepare the input to each model, and (3) the model specifications and parameters that were used in each model application. This dataset is part of a larger...
Tags: 007, 012, AK, AR, Aerobic respiration, All tags...
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This dataset provides key diagnostics and overall assessments of metabolism model performance. The format is a table with 1 row per model (1 tab-delimited file, compressed into zip file). See the accompanying publication for rationale for the choices of specific diagnostics. 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;...
Tags: 007, 012, AK, AR, Aerobic respiration, All tags...
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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. Reservoirs in the DRB serve an important role as a source of drinking water, but also affect downstream water quality. Therefore, this data release includes data that characterize both rivers and a subset of reservoirs in the basin. This release provides an update to many of the files provided in a previous data release (Oliver et al., 2021). The data are stored in 3 child folders: 1) spatial information, 2) observations, and 3) model driver data. 1) Spatial Information...
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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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This dataset provides daily metabolism estimates and potential predictor variables to support further exploration. The format is a table with 1 row per site-date combination (1 tab-delimited file, compressed into a zip file). 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...
Tags: 007, 012, AK, AR, Aerobic respiration, All tags...
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Salinity dynamics in the Delaware Bay estuary are a critical water quality concern as elevated salinity can damage infrastructure and threaten drinking water supplies. Current state-of-the-art modeling approaches use hydrodynamic models, which can produce accurate results but are limited by significant computational costs. We developed a machine learning (ML) model to predict the 250 mg/L Cl- isochlor, also known as the salt front, using daily river discharge, meteorological drivers, and tidal water level data. We use the ML model to predict the location of the salt front, measured in river miles (RM) along the Delaware River, during the period 2001-2020, and we compare the ML model results to results from the hydrodynamic...
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This dataset provides complete fits from metabolism estimation models. The format is 5 files per model (text and tab-delimited files, packaged as 1 zip file per model): (1) estimates of daily gross primary productivity (GPP), ecosystem respiration (ER), and the gas exchange coefficient (K600), (2) parameters for the model overall, (3) estimates of the nodes defining the piecewise line relating K600 to discharge, (4) parameters for the overall relationship between K600 and discharge, and (5) any warnings returned by the model. 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...
Tags: 007, 012, AK, AR, Aerobic respiration, All tags...
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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...


map background search result map search result map Metabolism estimates for 356 U.S. rivers (2007-2017): 1. Site data Metabolism estimates for 356 U.S. rivers (2007-2017): 3. Timeseries data Metabolism estimates for 356 U.S. rivers (2007-2017): 5. Model configurations Metabolism estimates for 356 U.S. rivers (2007-2017): 4. Model inputs Metabolism estimates for 356 U.S. rivers (2007-2017): 6. Model outputs Metabolism estimates for 356 U.S. rivers (2007-2017): 7. Model diagnostics Metabolism estimates for 356 U.S. rivers (2007-2017): 8. Metabolism estimates and predictors 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 Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins 1 Site Information: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins 2 Observations: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins 3 Model Forcings: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins 4 Model Code: 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 Predictions and supporting data for network-wide 7-day ahead forecasts of water temperature in the Delaware River Basin Data to support water quality modeling efforts in the Delaware River Basin Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin Model Code, Outputs, and Supporting Data for Approaches to Process-Guided Deep Learning for Groundwater-Influenced Stream Temperature Predictions A deep learning model and associated data to support understanding and simulation of salinity dynamics in Delaware Bay Model predictions for heterogeneous stream-reservoir graph networks with data assimilation Predictions and supporting data for network-wide 7-day ahead forecasts of water temperature in the Delaware River Basin Data to support water quality modeling efforts in the Delaware River Basin Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin Model Code, Outputs, and Supporting Data for Approaches to Process-Guided Deep Learning for Groundwater-Influenced Stream Temperature Predictions A deep learning model and associated data to support understanding and simulation of salinity dynamics in Delaware Bay Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins 2 Observations: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins 3 Model Forcings: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins 4 Model Code: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins 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): 5. Model configurations Metabolism estimates for 356 U.S. rivers (2007-2017): 4. Model inputs Metabolism estimates for 356 U.S. rivers (2007-2017): 6. Model outputs Metabolism estimates for 356 U.S. rivers (2007-2017): 7. Model diagnostics Metabolism estimates for 356 U.S. rivers (2007-2017): 8. Metabolism estimates and predictors 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 Metabolism estimates for 356 U.S. rivers (2007-2017): 1. Site data Metabolism estimates for 356 U.S. rivers (2007-2017): 3. Timeseries data