Boen Zhang
@zhangboenvip
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PostDoc researcher at Oxford University
Oxford, England
Joined November 2015
Research Associate in Hydrology at The University of Edinburgh
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River datasets often miss forks and branches found in highly populated floodplains and deltas. As flooding grows more severe, accurate mapping of these areas is more important than ever. https://t.co/BqEpWMlD1q
eos.org
GRIT provides a much more detailed look at how rivers merge and split, which could enhance hydrological modeling, flood forecasting, and water management efforts.
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Land subsidence isn’t just a coastal problem: All the biggest cities in the United States are sinking.
eos.org
The most populated cities in the country are slowly subsiding, posing risks to infrastructure and exacerbating flooding—and not just on the coasts.
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Windblown dust has heavy economic consequences. https://t.co/RIF4iOjfNA
eos.org
Data from 2017 show that costs associated with dust were second only to hurricanes when comparing billion-dollar disasters.
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Weather whiplash and inequality: Rainstorms after drought are increasing in poor regions Between 1980-2010, drought-to-downpour events increased by 24%–48% in the poorest 20% of the world's population. https://t.co/KFg3zWwPci
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We are excited to share our review of “Challenges and opportunities of ML and explainable AI in hydrology” on Earth ArXiv: https://t.co/1P0ZFQOh3V (currently under review at Philosophical Transactions of the Royal Society A)
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Daily Briefing | Huge COP29 climate deal too little too late, poorer nations say ➡️ https://t.co/2pk0TyWF7x
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Climate change impacts are not only greater in developing countries, they are also coming faster. Although COP28 have reached agreements to increase climate finance, these agreements must be implemented at a pace that exceeds the rate of increase of extreme weather events.
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I am excited to share our new study https://t.co/aOPiMqZu05 published on @CommsEarth. Our findings reveal that compound drought-heatwave events increase in low-income regions twice as fast as in high-income regions.
nature.com
Communications Earth & Environment - From 1981 to 2020, low-income regions experienced a faster increase in the frequency of compound drought-heatwaves events than high-income regions, and the...
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Delighted to share 'Challenges and opportunities of ML and explainable AI in large-sample hydrology,' accepted today @royalsociety. The revised manuscript is available at: https://t.co/RDAQxJLDLx Thanks to the reviewers, editor, conference organisers & a great team of co-authors!
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You can see in this video why flash floods are likened to inland tsunamis. Even with a warning it is difficult to get out of the way in time. The danger also comes from the amount of debris carried in the flow. Extreme rainfall can cause these walls of water. #Valencia
El comienzo de todo y aún no habíamos recibido la alerta.. Éste video es de mi hijo y no se puede compartir sin permiso #paiporta #dana #desastre
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New Publication: "Spatiotemporal Variability of Channel Roughness and its Substantial Impacts on Flood Modeling Errors" from @NOAA @nwsnwc SI2022 project! Article DOI: https://t.co/KB4TeAbYWQ
#Hydrology #FloodModeling #MachineLearning #BigData
agupubs.onlinelibrary.wiley.com
We developed a continental-scale dataset of Manning's channel roughness values and trained accurate random forest models to predict them Predictable time variability explains a large fraction (∼3...
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We are pleased to share our new preprint describing #GRIT, led by @MichelSJW on behalf of the @EvoFlood @NERCScience project! "Global River Topology (GRIT): A bifurcating river hydrography" Preprint: https://t.co/peRZQvkUkI Hydrography: https://t.co/0XDaO6xtmH
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After almost a year, our review paper on #Physics-Guided #DeepLearning finally appears at @PNASNews
https://t.co/rQ1wBoQLvJ! It is part of the special issue on #Physics Meet #MachineLearning
https://t.co/oIVGk5JI04 (1/3)
pnas.org
Modeling complex physical dynamics is a fundamental task in science and engineering. Traditional physics-based models are first-principled, explain...
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The ASCE/EWRI Risk & Uncertainty Committee is hosting a webinar series: Join us for an insightful presentation by Dr. Günter Blöschl on the topic- "Processes of River Flood Generation – Are They Changing?" 2-3 PM (EST), Wednesday, 19th June Zoom link: https://t.co/h0HlNlVq8y
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Can a DL emulator model learn continental scale hydrology? Yes it can. New paper out from our Hydro-ML team shows how! Nice work led by @arbennett_ and @LCofthedesert with @hoang_h2o @peter_melchior et al @EPrinceton @IGWMC
https://t.co/8aTrr9mEfn
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A hindcast experiment of the 2021 #EuropeanFlood unveils a 17-hour lead time for preparedness and advisable action, holding promise for impact-based #FloodForecasting of inundated roads, railways and building footprint in real-time. @ufz_de
nature.com
Nature Communications - A hindcast experiment of the 2021 summer flood in West Germany unveils a 17-hour lead time for preparedness and advisable action, holding promise for impact-based...
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