Skip to main content
Advanced Search

Filters: partyWithName: Integrated Information Dissemination Division (X) > Categories: Data (X)

Folders: ROOT > ScienceBase Catalog ( Show direct descendants )

21 results (11ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep learning model. In-situ measurements used for model training and evaluation are from 12,227 lakes and are included as well as daily meteorological conditions and lake properties. Median per-lake estimated error found through cross validation on lakes with in-situ surface temperature observations was 1.24 °C. The generated dataset will be beneficial for a wide range of applications including estimations of thermal habitats and the impacts of climate change on inland lakes.
Categories: Data; Tags: AL, AR, AZ, Alabama, Aquatic Biology, All tags...
thumbnail
Using predicted lake temperatures from uncalibrated, process-based models (PB0) and process-guided deep learning models (PGDL), this dataset summarized a collection of thermal metrics to characterize lake temperature impacts on fish habitat for 881 lakes. Included in the metrics are daily thermal optical habitat areas and a set of over 172 annual thermal metrics.
This data release component contains water temperature predictions in 118 river catchments across the U.S. Predictions are from the four models described by Rahmani et al. (2020): locally-fitted linear regression, LSTM-noQ, LSTM-obsQ, and LSTM-simQ.
thumbnail
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).
thumbnail
Water temperature estimates from multiple models were evaluated by comparing predictions to observed water temperatures. The performance metric of root-mean square error (in degrees C) is calculated for each lake and each model type, and matched values for predicted and observed temperatures are also included to support more specific error estimation methods (for example, calculating error in a particular month). Errors for the process-based model are compared to predictions as shared in Model Predictions data since these models were not calibrated. Errors for the process-guided deep learning models were calculated from validation folds and therefore differ from the comparisons to Model Predictions because those...
This item contains data and code used in experiments that produced the results for Sadler et. al (2022) (see below for full reference). We ran five experiments for the analysis, Experiment A, Experiment B, Experiment C, Experiment D, and Experiment AuxIn. Experiment A tested multi-task learning for predicting streamflow with 25 years of training data and using a different model for each of 101 sites. Experiment B tested multi-task learning for predicting streamflow with 25 years of training data and using a single model for all 101 sites. Experiment C tested multi-task learning for predicting streamflow with just 2 years of training data. Experiment D tested multi-task learning for predicting water temperature with...
thumbnail
This data release contains records from research focused on understanding social vulnerability to water insecurity, resiliency demonstrated by institutions, and conflict or crisis around water resource management. This data release focuses on social vulnerability to water insecurity. The data were derived from a meta-analysis of studies in the empirical literature which measured factors of social vulnerability associated with conditions of water insecurity. In the water security context this data and associated study identify the indicators used to measure social vulnerability, the frequency at which indicators are used, and the uncertainty associated with measurements based on those indictors. Assessed studies...
thumbnail
The data in this data release are from an effort focused on understanding social vulnerability to water insecurity, resiliency demonstrated by institutions, and conflict or crisis around water resource management. This data release focuses on definitions and metrics of resilience in water management institutions. Water resource managers, at various scales, are tasked with making complex and time-sensitive decisions in the face of uncertainty, competing objectives, and difficult tradeoffs. To do this, they must incorporate data, tacit knowledge, cultural and organizational norms, and individual or institutional values in a way that maintains consistent and predictable operations under normal circumstances, while...
thumbnail
Harmful algal blooms (HABs) are overgrowths of algae or cyanobacteria in water and can be harmful to humans and animals directly via toxin exposure or indirectly via changes in water quality and related impacts to ecosystems services, drinking water characteristics, and recreation. While HABs occur frequently throughout the United States, the driving conditions behind them are not well understood, especially in flowing waters. In order to facilitate future national model development and characterization of HABs, this data release publishes a synthesized and cleaned collection of HABs-related water quality and quantity data for river and stream sites across the United States. It includes nutrients, major ions, sediment,...
thumbnail
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...
thumbnail
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...
This data release component contains evaluation metrics used to assess the predictive performance of each stream temperature model. For further description, see the metric calculations in the supplement of Rahmani et al. (2020), equations S1-S7.
thumbnail
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...
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.
thumbnail
This dataset provides model parameters used to estimate water temperature from a process-based model (Hipsey et al. 2019) using uncalibrated model configurations (PB0) and the trained model parameters for process-guided deep learning models (PGDL; Read et al. 2019). 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).
thumbnail
The data in this data release are from an effort focused on understanding social vulnerability to water insecurity, resiliency demonstrated by institutions, and conflict or crisis around water resource management. This data release focuses on the conflict in crisis aspects of work. To characterize crisis a dual-prong, qualitative triangulation was used to identify and provide context for water conflict and other water-related events in the Colorado River Basin. The first prong was observation by research team members of nine public, recorded meetings of water control boards and official organizations in the Colorado River Basin. Discourse analysis was then used to identify major themes in these meetings, and integrated...
thumbnail
Harmful algal blooms (HABs) are overgrowths of algae or cyanobacteria in water and can be harmful to humans and animals directly via toxin exposure or indirectly via changes in water quality and related impacts to ecosystems services, drinking water characteristics, and recreation. While HABs occur frequently throughout the United States, the driving conditions behind them are not well understood, especially in flowing waters. In order to facilitate future model development and characterization of HABs in the Illinois River Basin, this data release publishes a synthesized and cleaned collection of HABs-related water quality and quantity data for river and stream sites in the basin. It includes nutrients, major ions,...
thumbnail
Climate change and land use change have been shown to influence lake temperatures and water clarity in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles in 2,332 lakes during 1980-2019. The data are organized into these items: This research was funded by the Department of the Interior Northeast and North Central Climate Adaptation Science Centers, a Midwest Glacial Lakes Fish Habitat Partnership grant through F&WS Access to computing facilities was provided by USGS Advanced Research Computing, USGS Yeti Supercomputer (https://doi.org/10.5066/F7D798MJ)....
thumbnail
Harmful algal blooms (HABs) have recently been observed in rivers, including the Illinois River in the Midwest United States. The Illinois River Basin has a history of eutrophication issues, primarily caused by the excessive loading of nitrogen and phosphorus from urban and agricultural sources. Recent events have seen the emergence of cyanobacterial harmful algal blooms in the area. This data release provides early warning indicator (EWI) metrics derived from a continuous chlorophyll concentration dataset obtained from seven water quality monitoring sites along the Illinois River. These metrics include the first-order autoregressive process (Ar1) and the standard deviation (SD) of chlorophyll, which serve as leading...


map background search result map search result map Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 1 Lake information for 881 lakes Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 3 Model configurations (lake model parameter values) Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 6 model evaluation Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 7 thermal and optical habitat estimates Data release: Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 2 Observations Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 3 Model inputs Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 5 Model predictions Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 6 Model evaluation Daily surface temperature predictions for 185,549 U.S. lakes with associated observations and meteorological conditions (1980-2020) Multi-task Deep Learning for Water Temperature and Streamflow Prediction (ver. 1.1, June 2022) 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 Harmonized discrete and continuous water quality data in support of modeling harmful algal blooms in the Illinois River Basin, 2005 - 2020 Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin Coded Water Conflict and Crisis Events in the Colorado River Basin, Derived from LexisNexis search 2005-2021 Literature Summary of Indicators of Water Vulnerability in the Western US 2000-2022 Harmonized continuous water quality data in support of modeling harmful algal blooms in the United States, 2005 - 2022 Metrics of Resilience in Water Management Institutions in the Upper Colorado and Delaware River Basins, United States 2022 Data release: early warning indicators for harmful algal bloom assessments in the Illinois River, 2013 - 2020 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 Data release: early warning indicators for harmful algal bloom assessments in the Illinois River, 2013 - 2020 Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin Harmonized discrete and continuous water quality data in support of modeling harmful algal blooms in the Illinois River Basin, 2005 - 2020 Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 3 Model configurations (lake model parameter values) Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 7 thermal and optical habitat estimates Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 1 Lake information for 881 lakes Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 6 model evaluation Data release: Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning Coded Water Conflict and Crisis Events in the Colorado River Basin, Derived from LexisNexis search 2005-2021 Metrics of Resilience in Water Management Institutions in the Upper Colorado and Delaware River Basins, United States 2022 Literature Summary of Indicators of Water Vulnerability in the Western US 2000-2022 Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 2 Observations Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 3 Model inputs Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 5 Model predictions Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 6 Model evaluation Multi-task Deep Learning for Water Temperature and Streamflow Prediction (ver. 1.1, June 2022) Daily surface temperature predictions for 185,549 U.S. lakes with associated observations and meteorological conditions (1980-2020) Harmonized continuous water quality data in support of modeling harmful algal blooms in the United States, 2005 - 2022