Analysis of Citizen Science Data Collection for River Flood Modelling

Doctoral Thesis (2026)
Author(s)

T. Herman Assumpção (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

D.P. Solomatine – Promotor (TU Delft - Civil Engineering & Geosciences)

I.I. Popescu – Promotor (TU Delft - Civil Engineering & Geosciences)

Research Group
Water Systems Monitoring & Modelling
DOI related publication
https://doi.org/10.4233/uuid:5e2c6444-7527-40d9-b740-f4363fd52cea Final published version
More Info
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Publication Year
2026
Language
English
Defense Date
28-01-2026
Awarding Institution
Delft University of Technology
Research Group
Water Systems Monitoring & Modelling
ISBN (print)
978-90-73445-76-5
Downloads counter
61
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Abstract

In the context of a changing climate and increasing environmental pressures, the demand for data to understand the mechanisms of change and their interactions with the hydrological cycle has grown significantly. Further, a gap in data availability remains between the Global North and the Global South. This thesis contributes to the research into the capabilities of citizen science as a recent approach to data collection in water resources. Data obtained via citizen contributions, mainly through social media mining, has been shown to achieve accuracy comparable to authoritative sources and provide valuable inputs for hydrodynamic modelling. Nonetheless, aligning the spatial and temporal resolution of citizen-generated data with modelling requirements remains a challenge.....