Uncertainty analysis of urban sewer system using spatial simulation of radar rainfall fields: New York City case study

TitleUncertainty analysis of urban sewer system using spatial simulation of radar rainfall fields: New York City case study
Publication TypeJournal Article
Year of Publication2018
AuthorsHamidi A., Farnham D.J, Khanbilvardi R.
JournalStochastic Environmental Research and Risk Assessment
Date Published2018/08
Type of ArticleArticle
ISBN Number1436-3240
Accession NumberWOS:000440089100006
Keywordsclimate-change; dependence; drainage; Engineering; Environmental Sciences & Ecology; Extreme rainfall; generation; Hydrology; life-cycle assessment; Mathematics; NYC sewer; prediction; Radar rainfall data; resources; risk; Spatial simulator; system; water; weather radar

The goal of this study is to investigate the uncertainty of an urban sewer system's response under various rainfall and infrastructure scenarios by applying a recently developed nonparametric copula-based simulation approach to extreme rainfall fields. The approach allows for Monte Carlo simulation of multiple variables with differing marginal distributions and arbitrary dependence structure. The independent and identically distributed daily extreme rainfall events of the corresponding urban area, extracted from nationwide high resolution radar data stage IV, are the inputs of the spatial simulator. The simulated extreme rainfall fields were used to calculate excess runoff using the Natural Resources Conservation Service's approach. New York City is selected as a case study and the results highlight the importance of preserving the spatial dependence of rainfall fields between the grids, even for simplified hydrologic models. This study estimates the probability of combined sewer overflows under extreme rainfall events and identifies the most effective locations in New York City to install green infrastructure for detaining excess stormwater runoff. The results of this study are beneficial for planners working on stormwater management and the approach is broadly applicable because it does not rely on extensive sewer system information.

Short TitleStoch. Environ. Res. Risk Assess.
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