Found 453 datasets matching "process-based model".
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This dataset provides model specifications used to estimate water temperature from the process-based model, General Lake Model verion 2 (Hipsey et al. 2019) using calibrated model configurations...
Search relevance: 114.58 | Views last month: 0 -
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. General Lake Model verion 2...
Search relevance: 114.28 | Views last month: 1 -
These NetCDF data were compiled to investigate how two complementary models can contribute to our understanding of contemporary and future big sagebrush regeneration across the historical and...
Search relevance: 74.25 | Views last month: 0 -
This dataset includes model inputs (specifically, weather and flags for predicted ice-cover) and is part of a larger data release of lake temperature model inputs and outputs for 7,150 lakes in...
Search relevance: 64.55 | Views last month: 0 -
This is benchmark model for wastewater treatment using an activated sludge process. The activated sludge process is a means of treating both municipal and industrial wastewater. The activated...
Search relevance: 52.96 | Views last month: 1 -
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...
Search relevance: 52.35 | Views last month: 0 -
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...
Search relevance: 51.38 | Views last month: 0 -
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 indexed for each lake based on the...
Search relevance: 50.55 | Views last month: 1 -
Process-guided deep learning water temperature predictions: 5a Lake Mendota detailed prediction data
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models...
Search relevance: 50.12 | Views last month: 0 -
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models...
Search relevance: 49.93 | Views last month: 1 -
The Dairy Gas Emissions Model (DairyGEM) uses process level simulation and process related emission factors to predict ammonia, hydrogen sulfide, VOC and greenhouse gas emissions along with the...
Search relevance: 48.80 | Views last month: 0 -
This research software package contains Python code to execute experiments on deep generative modeling of classical random process models for noise time series. Specifically, it includes Pytorch...
Search relevance: 48.76 | Views last month: 1 -
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models...
Search relevance: 48.51 | Views last month: 1 -
Carbon and oxygen isotope data from annual tree rings in Ponderosa Pine collected in Oregon. The data was used in Ulrich, D. E. M., C. J. Still, J. R. Brooks, Y. Kim, and F. C. Meinzer. 2019....
Search relevance: 47.94 | Views last month: 0 -
This data release contains a database reviewing the state of the science for physically based distributed hydrologic model applications for post-fire hydrologic response. The database covers the...
Search relevance: 47.07 | Views last month: 0 -
This dataset contains the reef profiles and resulting hydrodynamic outputs of the "Broad-range Estimator of Wave Attack in Reef Environments" (BEWARE-2) meta-process modeling system. A...
Search relevance: 46.93 | Views last month: 0 -
In this paper, a maximum entropy-based general framework for probabilistic fatigue damage prognosis is investigated. The proposed methodology is based on an underlying physics-based crack growth...
Search relevance: 46.59 | Views last month: 0 -
This dataset holds modeled estimates of soil accretion for the Atchafalaya and Terrebonne basins in the Mississippi River Delta of coastal Louisiana, U.S. Soil accretion was predicted from...
Search relevance: 46.23 | Views last month: 0 -
The Innovation Center Model Awardees dataset provides information about institutions that have participated in the model process, and have been awarded funding based on their efforts to design,...
Search relevance: 46.23 | Views last month: 0 -
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB) models were configured and...
Search relevance: 46.04 | Views last month: 0
