Loading…

Sensitivity analysis of permeable pavement hydrological modelling in the Storm Water Management Model

•Global sensitivity analysis is firstly performed for permeable pavement in SWMM.•In-depth insight is provided into parameters influence on permeable pavement outflow.•Optional drain layer and event type influences are considered in the analysis.•Factor prioritization setting identified 5, out of 20...

Full description

Saved in:
Bibliographic Details
Published in:Journal of hydrology (Amsterdam) 2021-09, Vol.600, p.126525, Article 126525
Main Authors: Madrazo-Uribeetxebarria, Eneko, Garmendia Antín, Maddi, Almandoz Berrondo, Jabier, Andrés-Doménech, Ignacio
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Global sensitivity analysis is firstly performed for permeable pavement in SWMM.•In-depth insight is provided into parameters influence on permeable pavement outflow.•Optional drain layer and event type influences are considered in the analysis.•Factor prioritization setting identified 5, out of 20, most influencing parameters.•Factor fixing setting identified 4 parameters, out of 20, which may be fixed. 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.
ISSN:0022-1694
1879-2707
DOI:10.1016/j.jhydrol.2021.126525