Identification and Regionalization of Streamflow Routing Parameters Using Machine Learning for the HLM Hydrological Model in Iowa

Identification and Regionalization of Streamflow Routing Parameters Using Machine Learning for the HLM Hydrological Model in Iowa

Abstract We present a novel approach to determine spatially distributed routing parameters for the distributed hydrological Hillslope Link Model (HLM), an ordinary differential equations‐based streamflow forecasting model implemented and tested in Iowa. We being by developing a technique to determin...

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Bibliographic Details
Main Authors: Nicolás Velásquez, Ricardo Mantilla, Witold Krajewski, Felipe Quintero, André D. L. Zanchetta
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2022-07-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
hydrologic routing
random forest
hydrologic modeling
runoff
parameters
Online Access:https://doi.org/10.1029/2021MS002855

Internet

https://doi.org/10.1029/2021MS002855

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