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2019 | Book

Understanding Uncertainty Associated with Stormwater Quality Modelling Read chapter Read first chapter

Decision Making with Uncertainty in Stormwater Pollutant Processes

A Perspective on Urban Stormwater Pollution Mitigation

Authors: Buddhi Wijesiri, Dr. An Liu, Dr. Prasanna Egodawatta, James McGree, Prof. Dr. Ashantha Goonetilleke

Publisher: Springer Singapore

Book Series : SpringerBriefs in Water Science and Technology

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

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.

Table of Contents

Frontmatter
Chapter 1. Understanding Uncertainty Associated with Stormwater Quality Modelling
Abstract
Stormwater quality modelling is the common practice for generating information necessary for decision making in the design of stormwater pollution mitigation measures. However, the reliability of modelling outcomes largely depends on two types of uncertainty, namely, uncertainty inherent to stormwater pollutant processes and process modelling uncertainty. The inherent process uncertainty arises due to the intrinsic variability in stormwater pollutant processes. The modelling uncertainty arises from model structure and parameters, and input data and calibration data. The chapter establishes the context for defining and quantifying the uncertainty inherent to pollutant build-up and wash-off processes by bringing together current scientific knowledge from research literature. The temporal changes in particle size results in different particle behaviour during build-up and wash-off, leading to variations in particle-bound pollutant load and composition. Accordingly, the variation in particle size over time can be used as a basis for accounting for process variability in stormwater quality modelling, and thereby assessing process uncertainty.
Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
Chapter 2. Pollutant Build-up and Wash-off Process Variability
Abstract
The outcomes of a series of mathematical simulations of pollutant build-up and wash-off are presented in this chapter, strengthening the knowledge base on process variability. It was found that the build-up of particles <150 µm and >150 µm have different temporal patterns. These patterns could be used to differentiate between the behaviour of particles. The behaviour of particles <150 µm was found to play a key role in creating build-up process variability. On the other hand, the load and composition of different sized particles available on urban surfaces prior to a rainfall event were found to significantly influence the wash-off process. Similar to build-up, wash-off process variability is largely dependent on the behaviour of particles <150 µm, although the contribution from particles >150 µm is significant during rainfall events with relatively shorter duration.
Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
Chapter 3. Assessment of Build-up and Wash-off Process Uncertainty and Its Influence on Stormwater Quality Modelling
Abstract
Current practice in stormwater quality modelling constraints the generation of reliable information about catchment scale stormwater quality due to the lack of robust methods to assess the inherent uncertainty in pollutant build-up and wash-off processes. This chapter presents an approach to quantify process uncertainty as an integral part of stormwater quality predictions. The approach primarily aims to mathematically incorporate the characteristics of process variability into stormwater quality models, and thus quantifying the resulting uncertainty. The application of the new approach revealed that compared to wash-off process uncertainty, the build-up process uncertainty has a greater influence on the prediction of event mean concentrations (EMCs) of particulate solids in urban catchments. Further, it was found that process uncertainty differently influences stormwater quality predictions corresponding to storm events with different intensities, durations and resulting runoff volumes. Planning and management decision making needs to specifically address the changes in the load and composition of particulate solids and associated pollutants during dry weather periods and the storm events that can potentially influence high variations in stormwater quality.
Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
Chapter 4. Case Study—Uncertainty Inherent in Metals Build-up and Wash-off Processes
Abstract
This chapter presents the outcomes from a case study which investigated how uncertainty inherent in build-up and wash-off of metals commonly present in urban catchments, could influence stormwater quality. The investigation found consistent and significantly high concentrations of Al, Cr, Mn, Fe, Ni, Cu, Zn, Cd and Pb in the particle size fraction <150 µm than in the particle size fraction >150 µm. When considering consecutive events of build-up and wash-off, the temporal variations in the build-up loads of metals associated with particle size fractions <150 and >150 µm were not consistent with their wash-off loads. These inconsistencies could be potentially due to the interactions between metals and particles that are determined by the particle physico-chemical characteristics. While particle behaviour was found to drive the variability in metal build-up and wash-off, the need for characterising process variability in stormwater quality modelling was highlighted, enabling the quantitative assessment of process uncertainty associated with stormwater quality predictions.
Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
Chapter 5. Practical Implications and Recommendations for Future Research
Abstract
This chapter discusses implications of the outcomes of this research study in relation to stormwater pollution mitigation. It also presents a novel approach for implementing the research outcomes, using the concept of Logic Models. This approach is a logical sequence to a set of activities that enable the designing of effective stormwater pollution mitigation strategies utilising reliable information generated by stormwater quality models. The chapter further identifies opportunities for future research, namely, pollutant-particulate interactions, uncertainty assessment in relation to models with different complexity, and the need for integrating different modelling frameworks to improve the quantification of overall uncertainty associated with stormwater quality modelling outcomes.
Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke
Backmatter
Metadata
Title
Decision Making with Uncertainty in Stormwater Pollutant Processes
Authors
Buddhi Wijesiri
Dr. An Liu
Dr. Prasanna Egodawatta
James McGree
Prof. Dr. Ashantha Goonetilleke
Copyright Year
2019
Publisher
Springer Singapore
Electronic ISBN
978-981-13-3507-5
Print ISBN
978-981-13-3506-8
DOI
https://doi.org/10.1007/978-981-13-3507-5