108 datasets found
-
Federal
4 Model Code: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
Department of the Interior —
This data release component contains model code and configurations for the LSTM models used to predict stream temperature. -
Federal
GeoNatShapes: a natural feature reference dataset for mapping and AI training
Department of the Interior —
These data were compiled for the use of training natural feature machine learning (GeoAI) detection and delineation. The natural feature classes include the... -
Federal
Process-guided deep learning water temperature predictions: 4c All lakes historical training data
Department of the Interior —
Observed water temperatures from 1980-2018 were compiled for 68 lakes in Minnesota and Wisconsin (USA). These data were used as training data for process-guided deep... -
Federal
1. Model code for model archive: Identifying structural priors in a hybrid differentiable model for stream water temperature modeling
Department of the Interior —
This section provides model code described by Rahmani et al. (2023b). This code accepts basin attributes and forcings and predicts stream temperatures using a... -
Federal
Data to support near-term forecasts of stream temperature using process-guided deep learning and data assimilation
Department of the Interior —
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... -
Federal
4. Figure code for model archive: Identifying structural priors in a hybrid differentiable model for stream water temperature modeling
Department of the Interior —
This section provides code for reproducing the figures in Rahmani et al. (2023b). The full... -
Federal
Process-guided deep learning water temperature predictions: 2 Model configurations (lake metadata and parameter values)
Department of the Interior —
This dataset provides model specifications used to estimate water temperature from a process-based model (Hipsey et al. 2019). The format is a single JSON file... -
Federal
Process-guided deep learning water temperature predictions: 6c All lakes historical evaluation data
Department of the Interior —
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB)... -
Federal
Meta Learning Paper Supplemental Code
National Institute of Standards and Technology —
Meta learning with LLM: supplemental code for reproducibility of computational results for MLT and MLT-plus-TM. Related research paper: "META LEARNING WITH LANGUAGE... -
Federal
Process-guided deep learning water temperature predictions: 6b Sparkling Lake detailed evaluation data
Department of the Interior —
This dataset includes "test data" compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature... -
Federal
Predictions and supporting data for network-wide 7-day ahead forecasts of water temperature in the Delaware River Basin: 2) model driver data
Department of the Interior —
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... -
Federal
Utah FORGE: Focal Mechanism Catalog from Stage 3 of the April 2022 Stimulation Test
Department of Energy —
This submission includes focal-mechanism solutions derived from the Utah FORGE April 2022 Stage-3 stimulation. Waveforms were extracted around each event (short... -
Federal
Daily water column temperature predictions for thousands of Midwest U.S. lakes between 1979-2022 and under future climate scenarios
Department of the Interior —
Lake temperature is an important environmental metric for understanding habitat suitability for many freshwater species and is especially useful when temperatures are... -
Federal
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 4 Models
Department of the Interior —
This data release component contains model code and configurations for the LSTM and linear regression models used to predict stream temperature. -
Federal
Delaware River Basin Stream Salinity Machine Learning Models and Data
Department of the Interior —
This model archive contains the input data, model code, and model outputs for machine learning models that predict daily non-tidal stream salinity (specific... -
Federal
Predicting water temperature in the Delaware River Basin: 2 Water temperature and flow observations
Department of the Interior —
Observations related to water and thermal budgets in the Delaware River Basin. Data from reservoirs in the basin include reservoir characteristics (e.g., bathymetry),... -
Federal
Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs
Department of the Interior —
This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017)... -
Federal
Image dataset of plant-parasitic nematodes associated with cool-season turfgrass for machine learning and deep learning classification algorithms
Department of Agriculture —
The dataset contains micrographs of Hoplolaimus, Helicotylenchus, Meloidogyne, Mesocriconema, Pratylenchus, Trichodorus, and Tylenchorhynchus nematodes. The data were... -
Federal
RivNitrateLSTM
U.S. Environmental Protection Agency —
Real-time USGS nitrate data are collected to map short-term changes in nitrate concentrations across locations in the US:...
108 datasets found