Hydrological modelling of urban catchments under climate change for the design of a spatial decision support system to mitigate flooding using pervious pavements meeting the principles of sustainability
ABSTRACT: Urbanisation and Climate Change (CC) are two phenomena which are producing hydrological variations in urban catchments that might exceed the capability of drainage systems. Pervious Pavement Structures (PPS) provide an opportunity to mitigate both these phenomena by helping to restore the...
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| Tipo de recurso: | tesis doctoral |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/9642 |
| Acceso en línea: | http://hdl.handle.net/10902/9642 |
| Access Level: | acceso abierto |
| Palabra clave: | Climate change Geographic Information Systems Multi-criteria decision analysis Pervious pavement structures Stormwater modelling Análisis multi-criterio Cambio climático Modelado de aguas pluviales Pavimentos permeables Sistemas de Información Geográfica |
| Sumario: | ABSTRACT: Urbanisation and Climate Change (CC) are two phenomena which are producing hydrological variations in urban catchments that might exceed the capability of drainage systems. Pervious Pavement Structures (PPS) provide an opportunity to mitigate both these phenomena by helping to restore the natural water cycle and contributing to make cities more resilient to CC. This thesis consisted of the design of a four-module methodology to model the drainage capability of urban catchments under extreme precipitation events caused by CC, in order to determine their flooding susceptibility and improve their hydrological response to severe storms through the implementation of PPS meeting the principles of sustainability. The methodology was successfully tested through an urban catchment located in Espoo (Finland), which validated its applicability under real conditions. The automation of the proposed methods and their extension to model water quality were identified as the main future lines of research to give continuity to this PhD thesis. |
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