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190101 ||| eng |
| 020 |
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|a 9789811335075
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| 100 |
1 |
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|a Wijesiri, Buddhi
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| 245 |
0 |
0 |
|a Decision Making with Uncertainty in Stormwater Pollutant Processes
|h Elektronische Ressource
|b A Perspective on Urban Stormwater Pollution Mitigation
|c by Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
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| 250 |
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|a 1st ed. 2019
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| 260 |
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|a Singapore
|b Springer Nature Singapore
|c 2019, 2019
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| 300 |
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|a VIII, 82 p
|b online resource
|
| 505 |
0 |
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|a 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
|
| 653 |
|
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|a Engineering geology
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| 653 |
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|a Water
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| 653 |
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|a Pollution
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| 653 |
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|a Geoengineering
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| 653 |
|
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|a Hydrology
|
| 700 |
1 |
|
|a Liu, An
|e [author]
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| 700 |
1 |
|
|a Egodawatta, Prasanna
|e [author]
|
| 700 |
1 |
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|a McGree, James
|e [author]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
|
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|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
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|a SpringerBriefs in Water Science and Technology
|
| 028 |
5 |
0 |
|a 10.1007/978-981-13-3507-5
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-981-13-3507-5?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 363.73
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| 520 |
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|a 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 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
|