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Dirk Eilander

Researcher at VU University Amsterdam

Publications -  55
Citations -  1079

Dirk Eilander is an academic researcher from VU University Amsterdam. The author has contributed to research in topics: Flood myth & Coastal flood. The author has an hindex of 13, co-authored 34 publications receiving 608 citations.

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Dependence between high sea-level and high river discharge increases flood hazard in global deltas and estuaries

TL;DR: In this paper, the first assessment and mapping of the dependence between observed high sea-levels and high river discharge for deltas and estuaries around the globe was provided, and the dependence may influence the joint probability of floods exceeding both the design discharge and design sea-level.
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Measuring compound flood potential from river discharge and storm surge extremes at the global scale

TL;DR: In this article, the authors identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally, and provide preliminary insights on the implications of the bivariate dependence behavior on the flood hazard characterisation using Madagascar as a case study.
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Plastic in global rivers: Are floods making it worse?

TL;DR: In this paper, the role of floods in plastic mobilisation was investigated and it was shown that 10-year return-period floods already tenfold the global plastic mobilization potential compared to non-flood conditions.
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The effect of surge on riverine flood hazard and impact in deltas globally

TL;DR: In this paper, a global scale assessment of the joint influence of riverine and coastal drivers of flooding in deltas is presented, based on extreme water levels at 3433 river mouth locations as modeled by a state-of-the-art global river routing model, forced with a multi-model runoff ensemble and bounded by dynamic sea level conditions derived from a global tide and surge reanalysis.
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Harvesting Social Media for Generation of Near Real-time Flood Maps☆

TL;DR: The approach uses filtering and geo-statistical methods to take into account that observations in tweets are inherently unreliable, and developed a concept that exploits observed information of the physical characteristics of a flood, such as flood depth and the location.