Sensitivity analysis of permeable pavement hydrological modelling in the Storm Water Management Model
[EN] The Storm Water Management Model (SWMM), widely used by engineers to design or analyse stormwater networks, allows to model the so-called Low Impact Development (LID) controls, which reduce the flow conveyed to traditional networks. But, values for LID control parameters are often unknown. Furt...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/182862 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/182862 |
| Access Level: | acceso abierto |
| Palabra clave: | Permeable pavement SWMM Low impact development SUDS Sensitivity analysis, Calibration INGENIERIA HIDRAULICA 06.- Garantizar la disponibilidad y la gestión sostenible del agua y el saneamiento para todos 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación 11.- Conseguir que las ciudades y los asentamientos humanos sean inclusivos, seguros, resilientes y sostenibles 13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos |
| Sumario: | [EN] The Storm Water Management Model (SWMM), widely used by engineers to design or analyse stormwater networks, allows to model the so-called Low Impact Development (LID) controls, which reduce the flow conveyed to traditional networks. But, values for LID control parameters are often unknown. Furthermore, it is not always easy to link the cross-section materials to those provided by the model, particularly in the soil layer. This article provides a global sensitivity analysis for the PP type of LID control, in order to support practitioners in calibration tasks. The analysis explores what factors are the most influential and which can be fixed while calibrating a model. In particular, flow volume and peak are studied but the analysis also explores the influence of storm length and drain layer, which is optional. At the end, the most influential parameters, and those that can be neglected are presented, showing that we can focus on quite less parameters than initially given when calibrating a PP model in SWMM. |
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