Fachinformationsdienst BAUdigital

A platform for research: civil engineering, architecture and urbanism

    Information and disinformation in hydrological data across space: The case of streamflow predictions using machine learning

    New search for: Gupta, Abhinav

    Access

    Download

    Access

    Download

    Page navigation

    Document information
    Similar titles

    Export, share and cite

    Information and disinformation in hydrological data across space: The case of streamflow predictions using machine learning

    New search for: Gupta, Abhinav

    Access

    Download

    Information and disinformation in hydrological data across space: The case of streamflow predictions using machine learning

    New search for: Gupta, Abhinav

    Access

    Download

    Access

    Download

    Page navigation

    Document information
    Similar titles

    Export, share and cite

    Document information
    Title:

    Information and disinformation in hydrological data across space: The case of streamflow predictions using machine learning

    Additional title:

    Journal of Hydrology: Regional Studies

    Contributors:

    Gupta, Abhinav (author)

    Published in:

    Journal of Hydrology: Regional Studies ; 51

    Publication date:

    2024-02-01

    ISSN:

    2214-5818

    DOI:

    https://doi.org/10.1016/j.ejrh.2023.101607

    Type of media:

    Article (Journal)

    Type of material:

    Electronic Resource

    Language:

    English

    Licence:

    http://creativecommons.org/licenses/by-nc-nd/4.0/

    Similar titles

    Information and disinformation in hydrological data across space: The case of streamflow predictions using machine learning

    Abhinav Gupta | DOAJ | 2024

    Free access

    Improving streamflow predictions across CONUS by integrating advanced machine learning models and diverse data

    Kshitij Tayal / Arvind Renganathan / Dan Lu | DOAJ | 2024

    Free access

    Combining Postprocessed Ensemble Weather Forecasts and Multiple Hydrological Models for Ensemble Streamflow Predictions

    Zhang, Jianke / Chen, Jie / Li, Xiangquan et al. | ASCE | 2019

    Hybrid Hydrological Data-Driven Approach for Daily Streamflow Forecasting

    Ghaith, Maysara / Siam, Ahmad / Li, Zhong et al. | ASCE | 2019

    Incorporating IMERG satellite precipitation uncertainty into seasonal and peak streamflow predictions using the Hillslope Link hydrological model

    Samantha H. Hartke / Daniel B. Wright / Felipe Quintero et al. | DOAJ | 2023

    Free access
    Back to top