[ESIP-all] NOAA Physical Sciences Lab Seminar on Hydrologic Modeling with Deep Learning

Tue Mar 30 13:26:39 EDT 2021

A webinar many of you might be interested in. Find the connection
information below.

*Hydrological Modeling with Deep Learning*

_

Annie Burgess, PhD

Lab Director | Earth Science Information Partners (ESIP)

*esipfed.org/lab <http://esipfed.org/lab>* | 585.738.7549

*From:* Trusted OAR ESRL DO Sender - NOAA Service Account <
trusted.oar.esrl.do.sender at noaa.gov>
*Date:* March 30, 2021 at 07:25:58 MDT
*To:* _NOAA Boulder Broadway Campus Staff <brdwy at noaa.gov>
*Subject:* *PSL Seminar: Nearing, Tue., Apr. 6, 2pm MT*

*NOAA Physical Sciences Laboratory Seminar*

*Tue., Apr. 6, 2021, 2pm MT*

Online Only

Connection Information Below

‌

*Grey Nearing*

University of California Davis

*Hydrological Modeling with Deep Learning*

The Hydrology community has known for several decades that machine learning
provides better predictions of most hydrological states and fluxes than
both calibrated conceptual models and process-based models. This talk will
cover recent progress in developing hydrological modeling capacity with
deep learning, including: (1) prediction in extrapolation, (2) methods of
uncertainty quantification, (3) data assimilation, (4) multi-timescale
modeling, (5) leveraging ensembles of forcing products, (6)
interpretability of deep learning models, and (7) knowledge-guided machine
learning for hydrological modeling.

__________

*Speaker Bio:* Grey Nearing received a PhD in Hydrology and Water Resources
from the University of Arizona in 2013. He was formerly part of model
development teams as NASA and NCAR, and an assistant Professor at the
University of Alabama. He is currently an Assistant Professor at the
University of California Davis and visiting faculty at Google Research.

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*Access Code: 343-392-437 *

*For a list of our seminars, visit:* *https://psl.noaa.gov/seminars/*
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*Seminar Contact:* *psl.seminars at noaa.gov * <psl.seminars at noaa.gov>

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