@inproceedings{71272622c20746459c746c037f7a5256,
title = "An Agent-Based Model for Greening the City of Ravenna and Reducing Flooding at a Cultural Heritage Site",
abstract = "The paper presents an agent-based model exploring the impact of greening a city for groundwater flood risk reduction as a discussion tool to support urban planning decisions. The case study is an urban archaeological site in Ravenna, Italy. The model aimed to provide insights to generate discussion between researchers at the University of Bologna and the local authorities. The city map was divided into cells potentially suitable for modelled greening, combined with Ravenna precipitation and temperature data, and estimated scores for evapotranspiration and permeability. Generally, results indicate that more greening measures introduced correspond to a reduction in the volume of excess rainwater, with particular effectiveness in greened streets. Our results demonstrate the benefits of agent base modelling in the field of disaster risk management for testing measures prior to their implementation.",
keywords = "Agent-based modelling, Climate change, Cultural heritage, Disaster risk management, Flooding",
author = "Eleonora Melandri and Emily West and Angela Santangelo and Rembrandt Koppelaar and Aitziber Egusquiza",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 15th KES International Conference on Sustainability and Energy in Buildings, SEB 2023 ; Conference date: 18-09-2023 Through 20-09-2023",
year = "2024",
doi = "10.1007/978-981-99-8501-2\_60",
language = "English",
isbn = "9789819985005",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "697--707",
editor = "Littlewood, \{John R.\} and Lakhmi Jain and Howlett, \{Robert J.\}",
booktitle = "Sustainability in Energy and Buildings 2023",
address = "Germany",
}
