MSc Thesis

During my MSc Thesis, I did a research on the optimisation of Stormwater Best Management Practices (BMPs) implementation. Here is the abstract.
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Optimization of Implementing Best Management Practices (BMPs) in Urban Areas

Case Study in Surabaya City, Indonesia

Master Thesis by Badruz Zaman

Abstract

Runoff is the main source of urban flooding especially in the local drainage system. Urbanization, land use changes and climate changes are among the triggers that cause stormwater runoff increases. Conventionally problems of urban floods are solved by increasing the capacity of drainage networks in order to allow more stormwater runoff into the drainage system. However, this solution incurs high costs and not adaptable to the future uncertainties. US Environmental Protection Agency (USEPA) has promoted stormwater management in urban areas that more sustainable for future uncertainty which is called stormwater Best Management Practices (BMPs). The concept is utilizing the limited spaces in urban areas in mimicking predevelopment of hydrological site (natural condition). This research therefore aims to optimize the implementation of BMPs for retrofitting existing urban drainage network. Two conflicting objectives are solved in this research i.e. maximizing runoff reduction and minimizing BMP intervention costs. To evaluate the performance of BMP implementation, a case study in Puri Mas residential area of Surabaya in Indonesia has been developed. The final goal for this thesis is presenting optimal Pareto fronts of unit BMPs. This information is important for having a better decision making process.

The research is started by data collection and analysis. Rainfall data, subcatchment properties, and drainage networks are among data that have been analyzed. Those data are used to build a model of the drainage system in Puri Mas using SWMM 5.1. For implementing BMPs in the existing drainage system, 7 BMPs have been analyzed to see their feasibility to be implemented in the case study area. Finally, four BMPs have been selected and therefore detail design and costs estimation for each BMP are carried out. The selected BMPs are bio-retention cell, green roof, infiltration trench, and rain barrel. These BMPs then were applied in the existing drainage system of Puri Mas residential area. For optimizing the implementation of the BMPs, genetic algorithm based on NSGA-II was used to solve the multi-objective optimization. The result of optimization process is offset of solutions which indicate the areas implementation of BMPs.  With this information, it is expected that decision making process would be better.

Optimization process of implementation of BMPs in a case study area of Puri Mas has been performed and the result of the optimization process shows that BMP application has significantly reduced the peak flow. Within only occupied 15.43% of the total area, peak flow can be reduced by 27.74% which is from 130.20 litres per second to 94.08 litres per second with estimated costs of US$ 1.99 million. There are also varying solutions that are presented here to be chosen by decision makers. The results also showed that the optimized solutions provide valuable information for decision making process that commonly are not much easily identifiable by decision makers.

Keywords: runoff, stormwater, uncertainty, best management practices, hydrological, retrofitting, Pareto fronts, drainage networks, bio-retention cell, green roof, infiltration trench, rain barrel, genetic algorithm, NSGA-II, multi-objective obtimization, peak flow, decision making.   

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You caan download the MSc poster here and Full MSc Thesis Report here.