Crowdsourcing and interactive modelling for urban flood management

Journal Article (2020)
Author(s)

Eskedar T. Gebremedhin (IHE Delft Institute for Water Education, Deltares)

Laura Basco-Carrera (Deltares)

Andreja Jonoski (IHE Delft Institute for Water Education)

Mark Iliffe (World Bank)

Hessel C. Winsemius (TU Delft - Water Resources, Deltares)

Research Group
Water Resources
Copyright
© 2020 Eskedar T. Gebremedhin, Laura Basco-Carrera, Andreja Jonoski, Mark Iliffe, H.C. Winsemius
DOI related publication
https://doi.org/10.1111/jfr3.12602
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Eskedar T. Gebremedhin, Laura Basco-Carrera, Andreja Jonoski, Mark Iliffe, H.C. Winsemius
Research Group
Water Resources
Issue number
2
Volume number
13
Pages (from-to)
1-15
Reuse Rights

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Abstract

Participatory modelling has become a growing concept in environmental modelling, as it allows stakeholders to be involved in various stages of model development. The majority of studies, however, have focused on the participation during model use for scenario analysis and strategy evaluation after the model has been developed. Large-scale community mapping efforts create new opportunities to establish, detail and improve flood models at the development stage by working together with local stakeholders. In this article, we propose a novel participatory modelling and mapping approach. It builds on the community mapping projects across the most vulnerable wards in Dar es Salaam, Tanzania, which uses OpenStreetMap as a data platform. The approach consists of community mapping, an automated flood inundation model development and facilitation of stakeholder involvement. The participation of stakeholders in data collection helped achieving a more accurate flood model. The participatory modelling approach made participants aware of the skills necessary to develop an urban flood model with OpenStreetMap, necessary for creating a resilient society. The level of improvement obtained through the applied participatory modelling and mapping approach demonstrates its value in hydrodynamic model development and its potential for application in data scarce areas prone to urban floods.