Modeling Flood Stage-Duration-Frequency: A Risk Assessment of Critical Infrastructure in the Tidal Potomac


Autoria(s): Feng, Yilu
Contribuinte(s)

Brubaker, Kaye L

Digital Repository at the University of Maryland

University of Maryland (College Park, Md.)

Civil Engineering

Data(s)

15/09/2016

15/09/2016

2016

Resumo

The service of a critical infrastructure, such as a municipal wastewater treatment plant (MWWTP), is taken for granted until a flood or another low frequency, high consequence crisis brings its fragility to attention. The unique aspects of the MWWTP call for a method to quantify the flood stage-duration-frequency relationship. By developing a bivariate joint distribution model of flood stage and duration, this study adds a second dimension, time, into flood risk studies. A new parameter, inter-event time, is developed to further illustrate the effect of event separation on the frequency assessment. The method is tested on riverine, estuary and tidal sites in the Mid-Atlantic region. Equipment damage functions are characterized by linear and step damage models. The Expected Annual Damage (EAD) of the underground equipment is further estimated by the parametric joint distribution model, which is a function of both flood stage and duration, demonstrating the application of the bivariate model in risk assessment. Flood likelihood may alter due to climate change. A sensitivity analysis method is developed to assess future flood risk by estimating flood frequency under conditions of higher sea level and stream flow response to increased precipitation intensity. Scenarios based on steady and unsteady flow analysis are generated for current climate, future climate within this century, and future climate beyond this century, consistent with the WWTP planning horizons. The spatial extent of flood risk is visualized by inundation mapping and GIS-Assisted Risk Register (GARR). This research will help the stakeholders of the critical infrastructure be aware of the flood risk, vulnerability, and the inherent uncertainty.

Identificador

doi:10.13016/M2SR58

http://hdl.handle.net/1903/18810

Idioma(s)

en

Palavras-Chave #Water resources management #Civil engineering #Statistics #Bivariate joint probability distribution #Expected Annual Damage (EAD) #Flood duration #Flood risk #HEC-RAS #Sea level rise
Tipo

Dissertation