Stochastic Urban Pluvial Flood Hazard Maps Based upon a Spatial-Temporal Rainfall Generator

Abstract

It is a common practice to assign the return period of a given storm event to the urban pluvial flood event that such storm generates. However, this approach may be inappropriate as rainfall events with the same return period can produce different urban pluvial flooding events, i.e., with different associated flood extent, water levels and return periods. This depends on the characteristics of the rainfall events, such as spatial variability, and on other characteristics of the sewer system and the catchment. To address this, the paper presents an innovative contribution to produce stochastic urban pluvial flood hazard maps. A stochastic rainfall generator for urban-scale applications was employed to generate an ensemble of spatially-and temporally-variable design storms with similar return period. These were used as input to the urban drainage model of a pilot urban catchment (~9 km 2 ) located in London, UK. Stochastic flood hazard maps were generated through a frequency analysis of the flooding generated by the various storm events. The stochastic flood hazard maps obtained show that rainfall spatial-temporal variability is an important factor in the estimation of flood likelihood in urban areas. Moreover, as compared to the flood hazard OPEN ACCESSWater 2015, 7 3397 maps obtained by using a single spatially-uniform storm event, the stochastic maps generated in this study provide a more comprehensive assessment of flood hazard which enables better informed flood risk management decisions.

Towards identification of critical rainfall thresholds for urban pluvial flooding prediction based on crowdsourced flood observations

“…Strongest correlations were found with the variables d 0.25 and d 1 . This confirms the relevance of sub-daily temporal resolutions when investigating the impact of rainfall on urban hydrology (Blenkinsop et al, 2017;Ochoa-Rodriguez et al, 2015;Romero et al, 2011;Simões et al, 2015). It should be noted that relations found are strongly dependent on the spatial aggregation scale.…”

“…Research has shown that these variable resolutions 5 influence hydrodynamic model outputs (Ochoa-Rodriguez et al, 2015). A variable spatial resolution of rainfall also appears to be a significant parameter in the determination of flood probabilities (Simões et al, 2015). Recently, an alternative framework is proposed, in which the variable of interest is the time needed to accumulate a fixed amount of rainfall or flow instead of a variable amount over a fixed arbitrary time (Ten Veldhuis and Schleiss, 2017).…”

“…Heavy rainfall events, which are most relevant for flooding, are rare, limiting the type of observation-based analyses that can be performed. Numerous scientific investigations emphasize the importance of variable temporal resolutions when the urban hydrologic response is relevant (Blenkinsop et al, 2017;Ochoa-Rodriguez et al, 2015;Romero et al, 2011;Simões et al, 2015). In an urban environment, the critical response time is in the range of minutes to hours (Romero et al, 2011).…”

“…For the d 0.25 and d 1 variables, the maximum depth during an event was selected as a 10 characteristic rainfall value. It follows from other research that sub-daily durations are the most relevant for urban hydrologic response (Blenkinsop et al, 2017;Ochoa-Rodriguez et al, 2015;Romero et al, 2011;Simões et al, 2015). Report and OP data were plotted versus rainfall depth and Spearman's rank correlation coefficients were computed.…”

A Singular Spectrum Analysis Technique to Electricity Consumption Forecasting

“…Its aim is to decompose original series into small number of independent and interpretable components like oscillatory components, a structureless noise, and a slowly varying trend. Moreover, [4] also illustrate that SSA technique performs four steps. First, computing the trajectory matrix.…”