Evolutionary and Holistic Assessment of Green-Grey Infrastructure for CSO Reduction

Water 2016, 8(9), 402; doi:10.3390/w8090402

Author 

Alida Alves ^1,* , Arlex Sanchez ¹

, Zoran Vojinovic ¹

, Solomon Seyoum ²

, Mukand Babel ³

 and Damir Brdjanovic ¹

¹

Environmental Engineering and Water Technology Department, UNESCO-IHE, Westvest 7, 2611 AX Delft, The Netherlands

²

Hydroinformatics and Knowledge Management Department, UNESCO-IHE, Westvest 7, 2611 AX Delft, The Netherlands

³

School of Engineering and Technology, AIT Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand

^*

Author to whom correspondence should be addressed. 

Academic Editor: Ataur Rahman

Received: 11 August 2016 / Revised: 5 September 2016 / Accepted: 9 September 2016 / Published: 15 September 2016

(This article belongs to the Special Issue Hydroinformatics and Urban Water Systems)

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Abstract 

Recent research suggests future alterations in rainfall patterns due to climate variability, affecting public safety and health in urban areas. Urban growth, one of the main drivers of change in the current century, will also affect these conditions. Traditional drainage approaches using grey infrastructure offer low adaptation to an uncertain future. New methodologies of stormwater management focus on decentralized approaches in a long-term planning framework, including the use of Green Infrastructure (GI). This work presents a novel methodology to select, evaluate, and place different green-grey practices (or measures) for retrofitting urban drainage systems. The methodology uses a hydrodynamic model and multi-objective optimization to design solutions at a watershed level. The method proposed in this study was applied in a highly urbanized watershed to evaluate the effect of these measures on Combined Sewer Overflows (CSO) quantity. This approach produced promising results and may become a useful tool for planning and decision making of drainage systems. View Full-Text

Keywords: urban drainage;  green-grey infrastructure;  hydrodynamic models;  multi-objective optimization

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