edu.ucar.opensky::articles:25686 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T20:03:46.880806 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7df6w1t Generalization of runoff risk prediction at field scales to a continental-scale region using cluster analysis and hybrid modeling 2022-09-16T00:00:00Z publication https://n2t.org/ark:/85065/d7df6w1t https://doi.org/10.1029/2022GL100667 Ford, C. M. author Hu, Y. author Ghosh, C. author Fry, L. M. author Malakpour-Estalaki, S. author Mason, L. author Fitzpatrick, L. author Mazrooei, Amirhossein author Goering, D. C. author UCAR/NCAR - Library publisher As surface water resources in the U.S. continue to be pressured by excess nutrients carried by agricultural runoff, the need to assess runoff risk at the field scale continues to grow in importance. Most landscape hydrologic models developed at regional scales have limited applicability at finer spatial scales. Hybrid models can be used to address the scale mismatch between model simulation and applicability, but could be limited by their ability to generalize over a large domain with heterogeneous hydrologic characteristics. To assist the generalization, we develop a regionalization approach based on the principal component analysis and K-means clustering to identify the clusters with similar runoff potential over the Great Lakes region. For each cluster, hybrid models are developed by combining National Oceanic and Atmospheric Administration's National Water Model and a data-driven model, eXtreme gradient boosting with field-scale measurements, enabling prediction of daily runoff risk level at the field scale over the entire region. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright 2022 American Geophysical Union (AGU). None eng geoscientificInformation