TY - JOUR
T1 - Risk Modelling in Urban Coastal Areas to Support Adaptation to Climate Change and Extreme Weather Events: Early Warning, Emergency Planning and Risk Management Systems
AU - Duarte, Cláudio M.
AU - Ferreira, José Carlos
AU - Fortes, Juana C.
N1 - Fundação para a Ciência e Tecnologia (FCT)- funding conceded through the project 'To-SEAlert -Wave overtopping and flooding in coastal and port areas' (PTDC/EAM-OCE/31207/2017) and for the pluriannual funding programme to MARE (UID/MAR/04292/2019).
PY - 2020/3/1
Y1 - 2020/3/1
N2 - Duarte, C.M.; Ferreira, J.C., and Fortes, J., 2020. Risk modelling in urban coastal areas to support adaptation to climate change and extreme weather events: Early warning, emergency planning and risk management systems. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 785-789. Coconut Creek (Florida), ISSN 0749-0208. The Portuguese coast is exposed to the Atlantic high-energy storms, endangering populations and coastal infrastructures and causing economic and environmental losses. With climate change and the rise of sea-level, it is expected that these storms became more frequent and violent. For this reason, it is essential to provide the authorities with tools for managing the hazards and risks associated with coastal events. The purpose of the To-SEAlert project is to develop, implement, and validate a set of tools and methodologies based on a WebGIS to monitor, prevent and manage wave overtopping and flooding emergencies caused by coastal events. In this work, XBeach software was used to model the effects of storm induced wave overtopping and sea erosion in a low-lying sandy shore in Costa da Caparica, Portugal. Two experiments were carried out, simulating a storm event in a segment and in a grid area. Results show beach and dune erosion and wave overtopping, similar to recorded effects in past events, and important limitations are discussed. The improvement of these simulations can be essential to input data on the To-SEAlert project model, allowing its objectives accomplishment.
AB - Duarte, C.M.; Ferreira, J.C., and Fortes, J., 2020. Risk modelling in urban coastal areas to support adaptation to climate change and extreme weather events: Early warning, emergency planning and risk management systems. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 785-789. Coconut Creek (Florida), ISSN 0749-0208. The Portuguese coast is exposed to the Atlantic high-energy storms, endangering populations and coastal infrastructures and causing economic and environmental losses. With climate change and the rise of sea-level, it is expected that these storms became more frequent and violent. For this reason, it is essential to provide the authorities with tools for managing the hazards and risks associated with coastal events. The purpose of the To-SEAlert project is to develop, implement, and validate a set of tools and methodologies based on a WebGIS to monitor, prevent and manage wave overtopping and flooding emergencies caused by coastal events. In this work, XBeach software was used to model the effects of storm induced wave overtopping and sea erosion in a low-lying sandy shore in Costa da Caparica, Portugal. Two experiments were carried out, simulating a storm event in a segment and in a grid area. Results show beach and dune erosion and wave overtopping, similar to recorded effects in past events, and important limitations are discussed. The improvement of these simulations can be essential to input data on the To-SEAlert project model, allowing its objectives accomplishment.
KW - coastal inundation
KW - Costa da Caparica
KW - Portugal
KW - risk forecasting and warning
KW - Wave overtopping
UR - http://www.scopus.com/inward/record.url?scp=85085478493&partnerID=8YFLogxK
U2 - 10.2112/SI95-153.1
DO - 10.2112/SI95-153.1
M3 - Article
AN - SCOPUS:85085478493
SN - 0749-0208
VL - 95
SP - 785
EP - 789
JO - Journal Of Coastal Research
JF - Journal Of Coastal Research
IS - sp1
ER -