| Author: | Tansar, Husnain |
| Title: | Sustainable stormwater control and management with resilience-based optimization framework of green-grey infrastructures under climate change uncertainties |
| Advisors: | Duan, Huan-feng (CEE) |
| Degree: | Ph.D. |
| Year: | 2023 |
| Subject: | Drainage Urban runoff -- Management Storm sewers Flood control Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Civil and Environmental Engineering |
| Pages: | xxix, 242 pages : color illustrations |
| Language: | English |
| Abstract: | Globally, the urban stormwater management problems have significantly been risen in recent years because of several uncertain threats including rapid urbanization growth, climate change impacts, traditional design and aging infrastructure, and consistent reduction in conveyance and storage capacities of grey infrastructures. Urbanization and climate change collectively cause to increase significant surface runoff during extreme rainfall storms, causing higher hydraulic burdens on urban drainage systems that mostly exceeds their design capacities, and resulting in functional failure of partial or entire drainage systems. The critical evaluation of functional failures of existing urban drainage systems owing to the exceptional uncertain threats is significantly essential for comprehensive planning, designing and optimization of green-grey infrastructures for maximum reduction of system malfunctioning. The first part of the thesis is based on local and global sensitivity analysis of bioretention cell design parameters. In this part, we comprehensively evaluated the performance of two global sensitivity analysis methods including the variogram analysis of response surfaces framework and Sobol’s method, and identified key design parameters of bioretention cell, quantified associated uncertainties with their parameter’s rankings, and estimated the reliability of their rankings. Furthermore, a simple and computationally efficient local sensitivity analysis method (i.e., one-factor-at-a-time) employed for the classification and evaluation of influential and non-influential design parameters of bioretention cells towards different model responses under different rainfall conditions at the unit-scale and catchment-scale. The second part of the thesis mainly represents optimal planning, designing, and optimization of green-grey infrastructures considering economic, hydraulic, and technical constraints under existing and climate change-based scenarios with physics-based and data-driven models for reduction of retrofit costs, urban flood damages, outlet peak flow and increase in UDS’s resilience, reliability, and sustainability. The three main contributions of the second part of the thesis are (1) to develop a multi-objective decision-making framework for implementing green-grey infrastructures to enhance UDS resilience, (2) a surrogate-based multi-objective optimization of green-grey infrastructures under climate change impacts, and (3) performance evaluation of green infrastructure (GI) under different spatial placement strategies at the catchment-scale and local-scale. The main findings drawn from the first part explained that six parameters out of the total seventeen including conductivity, berm height, vegetation volume, suction head, porosity and wilting point indicated their significant sensitivities to surface infiltration, surface outflow and peak flow. In addition, soil thickness, conductivity slope and field capacity were categorized as influential to storage outputs. In particular, it is concluded from this study that the VARS is preferred over other sensitivity analysis approaches including the Sobol method (i.e., variance-based method) because of its higher accuracy, reliability, and computational efficiency. The important results concluded from the second part demonstrate that optimal designs of grey infrastructure are more cost-effective and have a significant influence on the reduction of flood damages and outlet peak flow compared to GI from their individual evaluations, while GI improves UDS’ functionality performance indicators (e.g., resilience, reliability, and sustainability) better than grey infrastructure. However, a combined implementation of both infrastructures boosts their advantages because of the synchronization effect compared to individual scenarios, providing the most cost-effective optimal UDS designs. The research findings presented in this thesis contribute to improve the efficiency and effectiveness of green-grey infrastructures and better-informed decision-making for stormwater modelers, drainage engineers, and nature-based practitioners. |
| Rights: | All rights reserved |
| Access: | open access |
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