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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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The Surface Water and Ocean Topography Mission: Observing Terrestrial Surface Water and Oceanic Submesoscale Eddies

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.
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How much runoff originates as snow in the western United States, and how will that change in the future?

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.
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Estimation of bathymetric depth and slope from data assimilation of swath altimetry into a hydrodynamic model

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.
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Global Reconstruction of Naturalized River Flows at 2.94 Million Reaches

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.
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An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope

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.