Combining Parametric Land Surface Models with Machine Learning

A hybrid machine learning and process-based-modeling (PBM) approach is proposed and evaluated at a handful of AmeriFlux sites to simulate the top-layer soil moisture state. The Hybrid-PBM (HPBM) employed here uses the Noah land-surface model integrated with Gaussian Processes. It is designed to corr...

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Veröffentlicht in:	arXiv.org 2020-05
Hauptverfasser:	Pelissier, Craig, Frame, Jonathan, Nearing, Grey
Format:	Artikel
Sprache:	eng
Schlagworte:	Autoregressive models Computer simulation Gaussian process Machine learning Modelling Soil layers Soil moisture Training
Online-Zugang:	Volltext
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