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Record Nr. |
UNINA9910350342503321 |
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Autore |
Wijesiri Buddhi |
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Titolo |
Decision Making with Uncertainty in Stormwater Pollutant Processes : A Perspective on Urban Stormwater Pollution Mitigation / / by Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (88 pages) |
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Collana |
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SpringerBriefs in Water Science and Technology, , 2194-7244 |
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Disciplina |
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Soggetti |
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Environmental pollution |
Hydraulic engineering |
Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution |
Water Quality/Water Pollution |
Geoengineering, Foundations, Hydraulics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Understanding uncertainty associated with stormwater quality modelling -- Pollutant build-up and wash-off processes variability -- Assessment of build-up and wash-off process uncertainty and its influence on stormwater quality modelling -- Case study – uncertainty assessment of heavy metals build-up and wash-off processes -- Practical implications and recommendations for future research. |
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Sommario/riassunto |
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This book presents new findings on intrinsic variability in pollutant build-up and wash-off processes by identifying the characteristics of underlying process mechanisms, based on the behaviour of various-sized particles. The correlation between build-up and wash-off processes is clearly defined using heavy metal pollutants as a case study. The outcome of this study is an approach developed to quantitatively assess process uncertainty, which makes it possible to mathematically incorporate the characteristics of variability in build-up and wash-off processes into stormwater quality models. In addition, the approach can be used to quantify process uncertainty as an integral |
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aspect of stormwater quality predictions using common uncertainty analysis techniques. The information produced using enhanced modelling tools will promote more informed decision-making, and thereby help to improve urban stormwater quality. |
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