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© 2019

Decision Making with Uncertainty in Stormwater Pollutant Processes

A Perspective on Urban Stormwater Pollution Mitigation

Benefits

  • Reviews in detail the latest research on uncertainty associated with stormwater quality modelling, helping readers to understand the need to assess uncertainty for informed decision-making in stormwater pollution mitigation

  • Presents a novel approach to quantifying the uncertainty inherent to stormwater pollutant processes as an integral part of stormwater quality predictions

  • Includes a case study on heavy metal pollutants to establish the correlation between build-up and wash-off processes

Book

Part of the SpringerBriefs in Water Science and Technology book series (BRIEFSWATER)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
    Pages 1-13
  3. Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
    Pages 15-24
  4. Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
    Pages 25-36
  5. Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
    Pages 37-48
  6. Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
    Pages 49-55
  7. Back Matter
    Pages 57-82

About this book

Introduction

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.

Keywords

stormwater pollutant Urban Stormwater Pollution Mitigation Stormwater Quality Modelling heavy metals build-up heavy metals wash-off pollutant wash-off pollutant build-up

Authors and affiliations

  1. 1.Science and Engineering FacultyQueensland University of Technology (QUT)BrisbaneAustralia
  2. 2.College of Chemistry and Environmental EngineeringShenzhen UniversityShenzhenChina
  3. 3.Science and Engineering FacultyQueensland University of Technology (QUT)BrisbaneAustralia
  4. 4.Science and Engineering FacultyQueensland University of Technology (QUT)BrisbaneAustralia
  5. 5.Science and Engineering FacultyQueensland University of Technology (QUT)BrisbaneAustralia

Bibliographic information

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