M
Michael Durand
Researcher at Ohio State University
Publications - 147
Citations - 5504
Michael Durand is an academic researcher from Ohio State University. The author has contributed to research in topics: Snow & Snowpack. The author has an hindex of 38, co-authored 136 publications receiving 4158 citations. Previous affiliations of Michael Durand include University of California, Los Angeles.
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Journal ArticleDOI
The Surface Water and Ocean Topography Mission: Observing Terrestrial Surface Water and Oceanic Submesoscale Eddies
Michael Durand,Lee-Lueng Fu,Dennis P. Lettenmaier,Douglas Alsdorf,Ernesto Rodriguez,Daniel Esteban-Fernandez +5 more
TL;DR: In this article, the Ka-band radar interferometer (KaRIN) is used to measure the water elevation along rivers, lakes, streams, and wetlands and over the ocean surface using swath altimetry.
Journal ArticleDOI
How much runoff originates as snow in the western United States, and how will that change in the future?
Dongyue Li,Dongyue Li,Melissa L. Wrzesien,Michael Durand,Jennifer C. Adam,Dennis P. Lettenmaier +5 more
TL;DR: In this article, the authors show that 53% of the total runoff in the western United States originates as snowmelt, despite only 37% of precipitation falling as snow.
Journal ArticleDOI
Estimation of bathymetric depth and slope from data assimilation of swath altimetry into a hydrodynamic model
Michael Durand,Konstantinos M. Andreadis,Douglas Alsdorf,Dennis P. Lettenmaier,Delwyn Moller,Matthew Wilson +5 more
TL;DR: In this paper, an ensemble-based data assimilation (DA) methodology for estimating bathymetric depth and slope from WSE measurements and the LISFLOOD-FP hydrodynamic model is presented.
Journal ArticleDOI
Global Reconstruction of Naturalized River Flows at 2.94 Million Reaches
Peirong Lin,Ming Pan,Hylke E. Beck,Yuan Yang,Yuan Yang,Dai Yamazaki,Renato Prata de Moraes Frasson,Cédric H. David,Michael Durand,Tamlin M. Pavelsky,George H. Allen,Colin J. Gleason,Eric F. Wood +12 more
TL;DR: A carefully designed modeling effort to estimate global river discharge at very high resolutions, thus named “Global Reach‐level A priori Discharge Estimates for Surface Water and Ocean Topography”, and can be used in other hydrologic applications requiring spatially explicit estimates of global river flows.
Journal ArticleDOI
An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope
Michael Durand,Colin J. Gleason,Pierre-André Garambois,David M. Bjerklie,Laurence C. Smith,Hélène Roux,Hélène Roux,Ernesto Rodriguez,Paul D. Bates,Tamlin M. Pavelsky,Jerome Monnier,Xiao-Ming Chen,G. Di Baldassarre,J. M. Fiset,Nicolas Flipo,Renato Prata de Moraes Frasson,John W. Fulton,Nicole Goutal,Faisal Hossain,E. Humphries,J. T. Minear,Micah Mukolwe,Jeffrey Neal,Sophie Ricci,Brett F. Sanders,Guy Schumann,Jochen E. Schubert,Lauriane Vilmin +27 more
TL;DR: In this article, the authors evaluated the possibility of estimating discharge in ungauged rivers using synthetic, daily "remote sensing" measurements derived from hydraulic models corrupted with minimal observational errors, and found at least one algorithm able to estimate instantaneous discharge to within 35% relative root-mean-squared error (RRMSE) on 14/16 nonbraided rivers despite out-ofbank flows, multichannel planforms, and backwater effects.