Spatial Distribution of Flood Incidents Along Urban Overland Flow-Paths

Abstract

An increase of urban flood risks is expected for the following decades not only because climate is becoming more extreme, but also because population and asset densities in cities are increasing. There is a need for models that can explain the damage process of urban flooding and support damage prevention. Recent improvements in flood modeling have highlighted the importance of urban topography to properly describe the built environment. While such modeling has mainly focused on the hazard components of urban pluvial floods, the understanding of damage processes remains poor, mainly due to a lack of flood impact information. Citizen's reports about flood incidents can be used to describe urban flooding impacts. In this study a database of such type of reports and a digital elevation model are used as main inputs to analyze the relationships between urban topography and occurrence of pluvial flood impacts. After a delineation of urban subwatersheds at a district level, the amount of reports along the overland flow-paths is studied. Then, the spatial distribution of reports is statistically assessed at district and neighborhood levels, in Euclidean and network-constrained spaces. This novel implementation computes the connections of a network of subwatersheds to calculate overland flow-path gradient distances, which are used to test whether the location of reports is constrained by those gradients. Results indicate that while reports have a clear clustered spatial distribution over the study area, they are randomly distributed along overland flow-path gradients, suggesting that factors different from topography influence the occurrence of incidents.

Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

“…If such grouping also happens to differentiate groups of sites with remarkably different report incidence, which is not included in the clustering computation, then the environmental configurations with higher urban flooding risks can be discriminated. An expected result is that groups characterized by sites with higher urban densities, and thus bigger number of inhabitants, display higher incidence of reports (Gaitan et al, 2015). Even though the focus of this paper is to present an overview of methods to explore multivariate spatial datasets, results of the clustering test are discussed in Sect.…”

“…Jacobs, 2012), are examples of such measures. However, their effectiveness depends on the available knowledge of the mechanisms leading to damage after heavy rains, which are still not completely understood (Gaitan et al, 2015;Spekkers et al, 2013Spekkers et al, , 2014ten Veldhuis et al, 2011).…”

“…Previous studies indicated that currently implemented drainage models do not provide realistic predictions of local flooding occurrence during heavy rain events (Fontanazza et al, 2011;Ochoa-Rodriguez et al, 2014;Gaitan et al, 2015). Studying the spatial distribution of possible explanatory variables may help to explain how a heavy rainfall event triggers occurrence of flooding impacts in a city.…”

“…Studying the spatial distribution of possible explanatory variables may help to explain how a heavy rainfall event triggers occurrence of flooding impacts in a city. Recent works have analyzed whether occurrence of citizens' complaints and insurance claim reports on rainfall-related incidents could be explained by variability in urban topography (Gaitan et al, 2015) and rainfall intensity (Spekkers et al, 2013). Response and explaining variables in those studies were selected apriori.…”

Scenario-Based Economic Impact Analysis for Bridge Closures Due to Flooding: A Case Study of North Gyeongsang Province, South Korea

“…Amongst the various types of natural disasters that can lead to bridge closures and failures, floods are a leading cause of bridge closures and failures [7,8]. More intense flooding is expected to occur in flood-prone areas in the future as more frequent and heavier periods of precipitation occur as a result of climate change [9][10][11]. As a result, flood-induced travel disruptions, including bridge closures, are expected to increase.…”