DYNAMIC MODELING OF THE SUSTAINABILITY AND RESILIENCY OF URBAN WATER SUPPLY AND SEWAGE SERVICES

Date of Award

Winter 2020

Project Type

Dissertation

Program or Major

Civil Engineering

Degree Name

Doctor of Philosophy

First Advisor

Weiwei Mo

Second Advisor

Kevin Gardner

Third Advisor

Jennifer Jacobs

Abstract

Urban drinking water supply and wastewater services are highly energy dependent, contributing to the water-energy nexus phenomena. Future changes such as climate change and decentralized water system adoption is expected to influence the current water-energy nexus. In this dissertation, a modeling framework was developed to model the energy use and generation in urban water services under various decentralization and climate change scenarios. The model was demonstrated using the City of Boston as the testbed. The considered water cycle in this study starts from raw water acquisition, treatment and drinking water distribution to wastewater generation, collection, treatment, and discharge back to the environment. Life cycle energy assessment was used to quantify the energy usages and generations associated with centralized and decentralized systems, both separately and integrated. For simulating climate change’s impact on the energy implications of the centralized water systems, comprehensive multivariate and multilinear regression analyses were conducted. Hydrologic modeling was combined with reservoir operation and hydropower generation model to estimate energy generation in the centralized drinking water system. Household level decentralized systems of rainwater harvesting (RWH) and greywater recycling (GWR) adoption were also simulated through dynamic daily water balance modeling at different decentralized system adoption rates for each individual household in Boston city. The obtained results show 1,489 TJ/year of primary energy is currently used in the Boston city water cycle. This energy demand of the centralized water services will rise for 2 % under climate change condition. GWR system adoption can decrease this energy demand by 3 %, while RWH system adoption can increase it for 0.3 %. The developed modeling framework in this study can support decision-making about future development of urban water systems in a way to improve sustainability and resiliency of them.

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