J. Zwart

发表

Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles

Anuj Karpatne, Vipin Kumar, Michael S. Steinbach, 2018, SDM.

Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles pdf

Anuj Karpatne, Xiaowei Jia, Vipin Kumar, 2020, Trans. Data Sci..

Process‐Guided Deep Learning Predictions of Lake Water Temperature

Anuj Karpatne, Xiaowei Jia, Jordan S. Read, 2019, Water Resources Research.

Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?

Aranildo R. Lima, J. Willard, J. Zwart, 2022, Hydrological Processes.

Measurement and Variability of Lake Metabolism

J. Zwart, L. S. Brighenti, 2021, Reference Module in Earth Systems and Environmental Sciences.

Global patterns and drivers of ecosystem functioning in rivers and riparian zones

Frank O. Masese, Shawn J. Leroux, J. Zwart, 2019, Science Advances.

Global Patterns and Controls of Nutrient Immobilization on Decomposing Cellulose in Riverine Ecosystems

J. Zwart, J. Webster, K. Capps, 2022, Global Biogeochemical Cycles.

Estimating pelagic primary production in lakes: Comparison of 14C incubation and free‐water O2 approaches

J. Zwart, S. Carpenter, P. Hanson, 2021, Limnology and Oceanography: Methods.

Spatially Explicit, Regional‐Scale Simulation of Lake Carbon Fluxes

J. Zwart, A. Hamlet, D. Bolster, 2018, Global Biogeochemical Cycles.

Hydrologic Regulation of Lake Carbon Cycling in Both Time and Space

J. Zwart, Jacob Aaron Zwart, 2017 .

Improving estimates and forecasts of lake carbon dynamics using data assimilation

J. Zwart, C. Solomon, S. Jones, 2019, Limnology and Oceanography: Methods.

Experimental whole‐lake increase of dissolved organic carbon concentration produces unexpected increase in crustacean zooplankton density

J. Zwart, C. Solomon, B. Weidel, 2016, Global change biology.

Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes

Kirsten M. Winters, Jessica R. Corman, J. Read, 2016 .

Metabolic and physiochemical responses to a whole‐lake experimental increase in dissolved organic carbon in a north‐temperate lake

J. Zwart, C. Solomon, S. Jones, 2016 .

Light climate and dissolved organic carbon concentration influence species-specific changes in fish zooplanktivory

J. Zwart, C. Solomon, B. Weidel, 2017 .

Hydrologic setting constrains lake heterotrophy and terrestrial carbon fate

J. Zwart, C. Solomon, Stuart E. Jones, 2018 .

Using near‐term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density

Whitney S. Beck, J. Zwart, K. Weathers, 2022, Ecological applications : a publication of the Ecological Society of America.

Integrated, Regional‐Scale Hydrologic Modeling of Inland Lakes

J. Zwart, A. Hamlet, D. Bolster, 2018, JAWRA Journal of the American Water Resources Association.

Machine learning for understanding inland water quantity, quality, and ecology

J. Read, J. Zwart, S. Oliver, 2022 .

Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks

X. Jia, J. Zwart, Shengyu Chen, 2022, KDD.

Support of Early‐Career Researchers Supports the Future of ASLO

Alli N. Cramer, J. Zwart, K. Hondula, 2019, Limnology and Oceanography Bulletin.

Near-term forecasts of stream temperature using process-guided deep learning and data assimilation

X. Jia, J. Read, J. Zwart, 2021 .

Near‐term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

X. Jia, J. Read, J. Zwart, 2022, JAWRA Journal of the American Water Resources Association.

LakeMetabolizer: an R package for estimating lake metabolism from free-water oxygen using diverse statistical models

Jordan S. Read, Luke A. Winslow, Paul C. Hanson, 2016 .

Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles

X. Jia, J. Willard, A. Karpatne, 2020, Trans. Data Sci..

The importance of lake-specific characteristics for water quality across the continental United States.

Aline Jaimes, Paul C Hanson, Kirsten M. Winters, 2015, Ecological applications : a publication of the Ecological Society of America.

Experimental whole-lake dissolved organic carbon increase alters fish diet and density but not growth or productivity

J. Zwart, C. Solomon, B. Weidel, 2018, Canadian Journal of Fisheries and Aquatic Sciences.

Phytoplankton traits predict ecosystem function in a global set of lakes.

J. Zwart, C. Solomon, Stuart E. Jones, 2015, Ecology.

Limnology and Oceanography Bulletin Volume 30 Number 4 November 2021 121–145

Laura J. Falkenberg, Jorrit P. Mesman, Alli N. Cramer, 2021, Limnology and Oceanography Bulletin.

Cross‐Scale Interactions Dictate Regional Lake Carbon Flux and Productivity Response to Future Climate

J. Read, J. Zwart, A. Hamlet, 2019, Geophysical Research Letters.

Projected changes of regional lake hydrologic characteristics in response to 21st century climate change

J. Zwart, A. Hamlet, D. Bolster, 2021, Inland Waters.

Multi-task deep learning of daily streamflow and water temperature

X. Jia, J. Read, J. Zwart, 2021 .

The Influence of Hydrologic Residence Time on Lake Carbon Cycling Dynamics Following Extreme Precipitation Events

J. Zwart, C. Solomon, S. Sebestyen, 2017, Ecosystems.

A Framework for Understanding Variation in Pelagic Gross Primary Production of Lake Ecosystems

J. Zwart, C. Solomon, Stuart E. Jones, 2018, Ecosystems.

Physics-Guided Machine Learning from Simulation Data: An Application in Modeling Lake and River Systems

X. Jia, J. Read, J. Zwart, 2021, 2021 IEEE International Conference on Data Mining (ICDM).

Partial Differential Equation Driven Dynamic Graph Networks for Predicting Stream Water Temperature

Taylor T. Johnson, X. Jia, J. Zwart, 2021, 2021 IEEE International Conference on Data Mining (ICDM).

Physics-Guided Recurrent Graph Model for Predicting Flow and Temperature in River Networks

Michael S. Steinbach, Jordan S. Read, Alison P. Appling, 2021, SDM.

Landscape patterns shape wetland pond ecosystem function from glacial headwaters to ocean

J. Zwart, G. Lamberti, Stuart E. Jones, 2017 .

Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks

X. Jia, J. Read, J. Zwart, 2020, SDM.

Delving deeper: Metabolic processes in the metalimnion of stratified lakes

J. Zwart, M. Honti, R. Woolway, 2017 .

Hacking Limnology Workshop and DSOS22: Creating a Community of Practice for the Nexus of Data Science, Open Science, and the Aquatic Sciences

Jorrit P. Mesman, Rachel M. Pilla, J. Zwart, 2022, Limnology and Oceanography Bulletin.

The AEMON‐J “Hacking Limnology” Workshop Series & Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research

Mridul K. Thomas, Jorrit P. Mesman, Alli N. Cramer, 2021, Limnology and Oceanography Bulletin.

Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research

J. Zwart, Michael F. Meyer, 2020, Limnology and Oceanography Bulletin.

Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations

Scott D. Hamshaw, X. Jia, J. Read, 2023, Frontiers in Water.

Physics-guided machine learning from simulated data with different physical parameters

X. Jia, J. Read, J. Zwart, 2023, Knowledge and Information Systems.

Heterogeneous Stream-reservoir Graph Networks with Data Assimilation

Jacob Zwart, Alison Appling, Samantha Oliver, 2021, 2021 IEEE International Conference on Data Mining (ICDM).

Model‐Data Fusion to Test Hypothesized Drivers of Lake Carbon Cycling Reveals Importance of Physical Controls

J. Zwart, C. Solomon, Y. Prairie, 2018 .