Practice makes the model: A critical review of stormwater green infrastructure modelling practice. (1st June 2023)
- Record Type:
- Journal Article
- Title:
- Practice makes the model: A critical review of stormwater green infrastructure modelling practice. (1st June 2023)
- Main Title:
- Practice makes the model: A critical review of stormwater green infrastructure modelling practice
- Authors:
- Pons, Vincent
Abdalla, Elhadi Mohsen Hassan
Tscheikner-Gratl, Franz
Alfredsen, Knut
Sivertsen, Edvard
Bertrand-Krajewski, Jean-Luc
Muthanna, Tone Merete - Abstract:
- Highlights: The modelling practice of 270 green infrastructure modelling study were reviewed. Limitation of methods and datasets need more attention. Uncertainty assessments are properly done in less than 20% of the studies. The framework STAMP was developed to align objectives and methods. Modelling tools should be improved to enhance the practices. Abstract: Green infrastructures (GIs) have in recent decades emerged as sustainable technologies for urban stormwater management, and numerous studies have been conducted to develop and improve hydrological models for GIs. This review aims to assess current practice in GI hydrological modelling, encompassing the selection of model structure, equations, model parametrization and testing, uncertainty analysis, sensitivity analysis, the selection of objective functions for model calibration, and the interpretation of modelling results. During a quantitative and qualitative analysis, based on a paper analysis methodology applied across a sample of 270 published studies, we found that the authors of GI modelling studies generally fail to justify their modelling choices and their alignments between modelling objectives and methods. Some practices, such as uncertainty analysis, were also found to be limited, despite their necessity being widely acknowledged by the scientific community and their application in other fields. In order to improve current GI modelling practice, the authors suggest the following: i) a framework, calledHighlights: The modelling practice of 270 green infrastructure modelling study were reviewed. Limitation of methods and datasets need more attention. Uncertainty assessments are properly done in less than 20% of the studies. The framework STAMP was developed to align objectives and methods. Modelling tools should be improved to enhance the practices. Abstract: Green infrastructures (GIs) have in recent decades emerged as sustainable technologies for urban stormwater management, and numerous studies have been conducted to develop and improve hydrological models for GIs. This review aims to assess current practice in GI hydrological modelling, encompassing the selection of model structure, equations, model parametrization and testing, uncertainty analysis, sensitivity analysis, the selection of objective functions for model calibration, and the interpretation of modelling results. During a quantitative and qualitative analysis, based on a paper analysis methodology applied across a sample of 270 published studies, we found that the authors of GI modelling studies generally fail to justify their modelling choices and their alignments between modelling objectives and methods. Some practices, such as uncertainty analysis, were also found to be limited, despite their necessity being widely acknowledged by the scientific community and their application in other fields. In order to improve current GI modelling practice, the authors suggest the following: i) a framework, called STAMP, designed to promote the standardisation of the documentation of GI modelling studies, and ii) improvements in modelling tools for facilitating good practices, iii) the sharing of data for better model testing, iv) the evaluation of the suitability of hydrological equations for GI application, v) the publication of clear statements regarding model limitations and negative results. Graphical abstract: Image, graphical abstract … (more)
- Is Part Of:
- Water research. Volume 236(2023)
- Journal:
- Water research
- Issue:
- Volume 236(2023)
- Issue Display:
- Volume 236, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 236
- Issue:
- 2023
- Issue Sort Value:
- 2023-0236-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-06-01
- Subjects:
- Water -- Pollution -- Research -- Periodicals
363.7394 - Journal URLs:
- http://catalog.hathitrust.org/api/volumes/oclc/1769499.html ↗
http://www.sciencedirect.com/science/journal/00431354 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.watres.2023.119958 ↗
- Languages:
- English
- ISSNs:
- 0043-1354
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9273.400000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 27042.xml