Jordan S. Read
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View article: Hierarchical Classification of the Hydrologic landscapes of the North American Continent (shapefile - v0)
Hierarchical Classification of the Hydrologic landscapes of the North American Continent (shapefile - v0) Open
View article: Predicting Minnesota lake ice phenology with deep learning, explainable methods, and a physically based benchmark, 1980-2018
Predicting Minnesota lake ice phenology with deep learning, explainable methods, and a physically based benchmark, 1980-2018 Open
View article: Enabling collaboration through data and model sharing with CUAHSI HydroShare; CIROH Science Meeting Poster
Enabling collaboration through data and model sharing with CUAHSI HydroShare; CIROH Science Meeting Poster Open
View article: Enabling collaboration through data and model sharing with CUAHSI HydroShare; CIROH Devcon 25 presentation
Enabling collaboration through data and model sharing with CUAHSI HydroShare; CIROH Devcon 25 presentation Open
View article: Climate‐driven alterations of lake thermal regimes
Climate‐driven alterations of lake thermal regimes Open
Temperate lakes are undergoing climate‐driven alterations in their thermal regimes, changing their ecology. Previous efforts to understand temperature changes have overlooked multi‐dimensional temperature dynamics, missing complex shifts a…
View article: Changes in neurotensin signalling drive hedonic devaluation in obesity
Changes in neurotensin signalling drive hedonic devaluation in obesity Open
Calorie-rich foods, particularly those that are high in fat and sugar, evoke pleasure in both humans and animals 1 . However, prolonged consumption of such foods may reduce their hedonic value, potentially contributing to obesity 2–4 . Her…
View article: Towards a synthesis of perceptual models of dominant hydrologic processes across North America
Towards a synthesis of perceptual models of dominant hydrologic processes across North America Open
There is increasing recognition that providing robust assessments of future water resource availability and water-related risks requires the use of the right models in the right places. Traditionally, selecting or developing an appropriate…
View article: Novel recurrent mutations and genetic diversity in Sudanese children with adrenal insufficiency
Novel recurrent mutations and genetic diversity in Sudanese children with adrenal insufficiency Open
Objective Studies of primary adrenal insufficiency (PAI) in African children are rare, but in Sudan, congenital adrenal hyperplasia (CAH) and triple A syndrome are the most common genetic causes. Differential diagnosis is challenging, espe…
View article: Dopamine D1 receptor activation in the striatum is sufficient to drive reinforcement of anteceding cortical patterns
Dopamine D1 receptor activation in the striatum is sufficient to drive reinforcement of anteceding cortical patterns Open
Timed dopamine signals underlie reinforcement learning, favoring neural activity patterns that drive behaviors with positive outcomes. In the striatum, dopamine activates five dopamine receptors (D1R-D5R), which are differentially expresse…
View article: Lessons Learned from Developing and Operating the Critical Zone Collaborative Network (CZNet) Data Cyberinfrastructure
Lessons Learned from Developing and Operating the Critical Zone Collaborative Network (CZNet) Data Cyberinfrastructure Open
View article: Developing perceptual models of hydrologic behavior across the North American continent
Developing perceptual models of hydrologic behavior across the North American continent Open
The North American continent is home to a wide range of different hydro-climates. A key research gap is that there is currently limited understanding on the spatial variability of dominant hydrologic processes across these different hydro-…
View article: Exploring Earth's Critical Zone Through the U.S. Critical Zone Collaborative Network
Exploring Earth's Critical Zone Through the U.S. Critical Zone Collaborative Network Open
The Critical Zone Collaborative Network (CZ Net) is a national research initiative in the United States supporting investigations of the Earth's critical zone (CZ) -- the vital near-surface environment extending from the top of the vegetat…
View article: Supporting Data Sharing and Discovery for the Earth's Critical Zone through Cross-Repository Interoperability
Supporting Data Sharing and Discovery for the Earth's Critical Zone through Cross-Repository Interoperability Open
Critical Zone (CZ) scientists study the coupled chemical, biological, physical, and geological processes operating across scales to support life at the Earth’s surface. In 2020, the U.S. National Science Foundation funded a network of Them…
View article: The CUAHSI HydroShare Platform for Hydrology Data and Model Sharing
The CUAHSI HydroShare Platform for Hydrology Data and Model Sharing Open
View article: CIROH: Enabling collaboration through data and model sharing with CUAHSI HydroShare
CIROH: Enabling collaboration through data and model sharing with CUAHSI HydroShare Open
View article: Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations
Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations Open
Deep learning (DL) models are increasingly used to forecast water quality variables for use in decision making. Ingesting recent observations of the forecasted variable has been shown to greatly increase model performance at monitored loca…
View article: Indicators of the effects of climate change on freshwater ecosystems
Indicators of the effects of climate change on freshwater ecosystems Open
View article: Connecting habitat to species abundance: the role of light and temperature on the abundance of walleye in lakes
Connecting habitat to species abundance: the role of light and temperature on the abundance of walleye in lakes Open
Walleye ( Sander vitreus) are an ecologically important species managed for recreational, tribal, and commercial harvest. Walleye prefer cool water and low light conditions, and therefore changing water temperature and clarity potentially …
View article: Near‐term forecasts of stream temperature using deep learning and data assimilation in support of management decisions
Near‐term forecasts of stream temperature using deep learning and data assimilation in support of management decisions Open
Deep learning (DL) models are increasingly used to make accurate hindcasts of management‐relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real‐tim…
View article: RF33 | PSAT69 A Combined Candidate Gene/Whole Exome Sequencing Approach Permits a Rapid Genetic Diagnosis for >81% Individuals with Primary Adrenal Insufficiency.
RF33 | PSAT69 A Combined Candidate Gene/Whole Exome Sequencing Approach Permits a Rapid Genetic Diagnosis for >81% Individuals with Primary Adrenal Insufficiency. Open
Introduction Mutations in MC2R causing familial glucocorticoid deficiency (FGD), a rare form of primary, isolated adrenal insufficiency, were first published in 1993, discovered by candidate gene sequencing (CGS). Through advances in genet…
View article: Machine learning for understanding inland water quantity, quality, and ecology
Machine learning for understanding inland water quantity, quality, and ecology Open
This chapter provides an overview of machine learning models and their applications to the science of inland waters. Such models serve a wide range of purposes for science and management: predicting water quality, quantity, or ecological d…
View article: Physics-Guided Neural Networks (PGNN): An Application in Lake Temperature Modeling
Physics-Guided Neural Networks (PGNN): An Application in Lake Temperature Modeling Open
This paper introduces a framework for combining scientific knowledge of physicsbased models with neural networks to advance scientific discovery.This framework, termed physics-guided neural networks (PGNN), leverages the output of physicsb…
View article: Daily surface temperatures for 185,549 lakes in the conterminous United States estimated using deep learning (1980–2020)
Daily surface temperatures for 185,549 lakes in the conterminous United States estimated using deep learning (1980–2020) Open
The dataset described here includes estimates of historical (1980–2020) daily surface water temperature, lake metadata, and daily weather conditions for lakes bigger than 4 ha in the conterminous United States ( n = 185,549), and also in s…
View article: Multi‐Task Deep Learning of Daily Streamflow and Water Temperature
Multi‐Task Deep Learning of Daily Streamflow and Water Temperature Open
Deep learning (DL) models can accurately predict many hydrologic variables including streamflow and water temperature; however, these models have typically predicted hydrologic variables independently. This study explored the benefits of m…
View article: Heterogeneous Stream-reservoir Graph Networks with Data Assimilation
Heterogeneous Stream-reservoir Graph Networks with Data Assimilation Open
Accurate prediction of water temperature in streams is critical for monitoring and understanding biogeochemical and ecological processes in streams. Stream temperature is affected by weather patterns (such as solar radiation) and water flo…
View article: Near-term forecasts of stream temperature using process-guided deep learning and data assimilation
Near-term forecasts of stream temperature using process-guided deep learning and data assimilation Open
Near-term forecasts of environmental outcomes can inform real-time decision making. Data assimilation modeling techniques can be used for forecasts to leverage real-time data streams, where the difference between model predictions and obse…
View article: Predicting Water Temperature Dynamics of Unmonitored Lakes With Meta‐Transfer Learning
Predicting Water Temperature Dynamics of Unmonitored Lakes With Meta‐Transfer Learning Open
Most environmental data come from a minority of well‐monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer‐learning fr…
View article: LakeEnsemblR: An R package that facilitates ensemble modelling of lakes
LakeEnsemblR: An R package that facilitates ensemble modelling of lakes Open
Model ensembles have several benefits compared to single-model applications but are not frequently used within the lake modelling community. Setting up and running multiple lake models can be challenging and time consuming, despite the man…
View article: Multi-task deep learning of daily streamflow and water temperature
Multi-task deep learning of daily streamflow and water temperature Open
Deep learning models can accurately predict many hydrologic variables including streamflow and water temperature; however, these models have typically predicted hydrologic variables independently. This study explored the benefits of modeli…
View article: Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles Open
Physics-based models are often used to study engineering and environmental systems. The ability to model these systems is the key to achieving our future environmental sustainability and improving the quality of human life. This article fo…