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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 were configured and calibrated with training data to reduce root-mean squared error. Uncalibrated models used default configurations (PB0; see Winslow et al. 2016 for details) and no parameters were adjusted according to model fit with observations. Deep Learning (DL) models were Long Short-Term Memory artificial recurrent neural network models which used training data to adjust model structure and weights for temperature predictions (Jia et al. 2019). Process-Guided Deep Learning (PGDL) models were DL models with an added...
Categories: Data;
Tags: 007,
012,
Fish,
MN,
Minnesota, All tags...
Northeast CASC,
Rivers, Streams and Lakes,
US,
United States,
WI,
Water, Coasts and Ice,
Wildlife and Plants,
Wisconsin,
climate change,
deep learning,
environment,
hybrid modeling,
inlandWaters,
machine learning,
modeling,
reservoirs,
temperate lakes,
temperature,
thermal profiles,
water, Fewer tags
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This dataset includes model inputs that describe weather conditions for the 68 lakes included in this study. Weather data comes from gridded estimates (Mitchell et al. 2004). There are two comma-separated files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of lake temperature model inputs and outputs...
Categories: Data;
Tags: 007,
012,
Fish,
MN,
Minnesota, All tags...
Northeast CASC,
Rivers, Streams and Lakes,
US,
United States,
WI,
Water, Coasts and Ice,
Wildlife and Plants,
Wisconsin,
climate change,
deep learning,
environment,
hybrid modeling,
inlandWaters,
machine learning,
modeling,
reservoirs,
temperate lakes,
temperature,
thermal profiles,
water, Fewer tags
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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 "site_id". 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).
Categories: Data;
Tags: 007,
012,
Fish,
MN,
Minnesota, All tags...
Northeast CASC,
Rivers, Streams and Lakes,
US,
United States,
WI,
Water, Coasts and Ice,
Wildlife and Plants,
Wisconsin,
climate change,
deep learning,
environment,
hybrid modeling,
inlandWaters,
machine learning,
modeling,
reservoirs,
temperate lakes,
temperature,
thermal profiles,
water, Fewer tags
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This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other time periods). There are two comma-delimited files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of...
Categories: Data;
Tags: 007,
012,
Fish,
Northeast CASC,
Rivers, Streams and Lakes, All tags...
US,
United States,
WI,
Water, Coasts and Ice,
Wildlife and Plants,
Wisconsin,
climate change,
deep learning,
environment,
hybrid modeling,
inlandWaters,
machine learning,
modeling,
reservoirs,
temperate lakes,
temperature,
thermal profiles,
water, Fewer tags
|
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 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).
Tags: 007,
012,
Fish,
MN,
Minnesota, All tags...
Northeast CASC,
Rivers, Streams and Lakes,
US,
United States,
WI,
Water, Coasts and Ice,
Wildlife and Plants,
Wisconsin,
climate change,
deep learning,
environment,
hybrid modeling,
inlandWaters,
machine learning,
modeling,
reservoirs,
temperate lakes,
temperature,
thermal profiles,
water, Fewer tags
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