The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners.
As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.
i
Understanding New York City street flooding through 311 complaints
-
2022
-
-
Source: Journal of Hydrology, 605, 127300
[PDF-1.11 MB]
Details:
-
Journal Title:Journal of Hydrology
-
Personal Author:
-
NOAA Program & Office:
-
Description:Street flooding is problematic in urban areas, where impervious surfaces, such as concrete, brick, and asphalt prevail, impeding the infiltration of water into the ground. During rain events, water ponds and rise to levels that cause considerable economic damage and physical harm. Previous urban flood studies and models have evaluated the factors contributing to street flooding, such as precipitation, slope, elevation, and the drainage network. Yet, due to the complexity of the interconnectedness of these factors and lack of available data, difficulty remains in ascertaining the localized areas prone to and experiencing street flooding. Thus, residents and city management of problem areas are unaware and unable to prepare for street flooding events. This study presents an evaluation of New York City’s 311 street flooding reports, via an inference model, as a way to detect the zip codes where street flooding is prevalent. The potential explanatory variables for street flooding complaints were precipitation amounts and 311 sewer back up (water arising from home drains as a result of rainfall), manhole overflow (water arising from manhole covers on the street) and catch basin (a clogged basin preventing rainwater from entering storm drains) complaints. Using Stage IV radar precipitation data and 311 sewer reports, spanning a 10-year period, a Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, with an embedded Zero-Inflation model is used to detect the variables statistically significant as predictors of flood complaint counts, specific to each zip code. The model is also tested using an Out-of-Sample prediction scheme by training it with the detected explanatory variables. Precipitation was found to be a predictor in 81% of the zip codes. For the infrastructural variables, manhole overflow complaints were significant to street flood complaints in 21% of the zip codes, back up complaints were significant in 41% of the zip codes, and catch basin complaints were significant in 47% of the zip codes. Thus, for an appreciable number of zip codes, infrastructural complaints were found to be predictors of street flooding complaints. This is the first study of its kind to investigate the infrastructural contributions of street flooding by 311 analysis, thereby identifying factors of street flooding, aside from precipitation. Leading contributions of the study include the demonstration of infrastructural impact towards the occurrence of street flooding and also the circumscription to the zip code and borough levels, allowing for tailored preventative actions in critical areas.
-
Keywords:
-
Source:Journal of Hydrology, 605, 127300
-
DOI:
-
ISSN:0022-1694
-
Format:
-
Publisher:
-
Document Type:
-
Funding:
-
License:
-
Rights Information:CC BY-NC-ND
-
Compliance:Library
-
Main Document Checksum:
-
Download URL:
-
File Type:
