Electronic Theses and Dissertations


Koorosh Azizi



Document Type


Degree Name

Doctor of Philosophy


Civil Engineering

Committee Chair

Claudio Meier

Committee Member

Arleen AH Hill

Committee Member

Stephen SKD Diko

Committee Member

Laura LS Saija


Urban pluvial flooding (UPF) resulting from localized, intense, rainfall‐generated ponding and overland flow causes a range of socio-environmental impacts. UPF is driven by a complex set of interconnected factors, including physical, historical, social, cultural, institutional, and economic conditions. Its impacts are increasing due to both biophysical change (e.g., global warming) and the interactions between the human and physical dimensions of the urban environment (e.g., land-use change). Notwithstanding its complexity and the rather low level of attention it has received in both research and practice, UPF is an issue that needs to be tackled from a comprehensive perspective. Although different integrated approaches such as citizen-science and socio-hydrology have tried to address UPF by coupling humans and environmental systems and reflecting on the possible outcomes from the interaction between disciplines, this study argues that these are not sufficient to fully understand and respond to UPF over a broad range of contexts and at multiple scales, because they engage little with the community and rarely interact with other disciplines. Moreover, simulating urban pluvial flooding is more complex than traditional watershed hydrological modeling. The typical lack of hydro-meteorological data and watershed information in urban areas further complicates the modeling process, especially when trying to simulate or predict extreme events. What is needed to improve the spatial resolution and accuracy of UPF models, reducing their uncertainty, is a systematic and multi-phase community-engagement process that collects detailed residents’ observations of UPF variables of interest. This study advances a generative citizen-science approach to better understand, characterize, and model the complex, integrated process that is UPF. The proposed framework provides an avenue to couple quantitative and qualitative community-based observations with traditional sources of hydro-information, to fill spatial and temporal data gaps, allow for a more accurate characterization of local watershed response, and improve rainfall-runoff modeling of UPF. The approach engaged researchers and residents in the definition of the problem, data sharing, co-analysis, and model development, within a more profound, reciprocal process of mutual learning and empowerment. Results of applying this framework indicate how community-based practices provide a bi-directional learning context between experts and residents, which should result in enhanced local resilience to extreme flooding events and allow residents to proactively participate in decision-making related to UPF risk management.


Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest.


Open access