Development of Flood Nomograph for Inundation Forecasting in Urban Districts

Jo, Deok Jun; Jeon, Byeong Hoon

doi:10.9798/kosham.2013.13.3.037

Cited by 5 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among all the precipitation parameters tested, a few of them (duration, sum, mean and max intensity, and K 1 ) depicted significant (p < 0.05) negative and positive correlations with inundation parameters. In summary, it could be stated that, in general, rain events with a shorter duration, higher maximum intensity, and total sum will cause higher SWSS flooding time, discharge and total volume, which is in agreement with the findings of other studies [15,16] (partly, since no studies were found to cover correlation with all the used precipitation characteristics). An exclusion of KOSTRA design rain leads to an improvement of the correlation, while block-typed and natural rain events lead to a different response of the SWSS.…”

Section: Detection Of "System Overloading" Precipitation Thresholdsupporting

confidence: 90%

See 1 more Smart Citation

Urban Floods: Linking the Overloading of a Storm Water Sewer System to Precipitation Parameters

et al. 2020

View full text Add to dashboard Cite

The lack and inefficiency of urban drainage systems, as well as extreme precipitation, can lead to system overloading and, therefore, an urban pluvial flood. The study brings insights into this phenomenon from the perspective of the statistical relationship between precipitation and flooding parameters. The paper investigates the possibility of predicting sewer overloading based on the characteristics of the upcoming rain event using the Storm Water Management Model (SWMM) and statistical methods. Additionally, it examines the influence of precipitation resolution on the model sensitivity regarding floods. The study is set in a small urban catchment in Dresden (Germany) with a separated stormwater sewer system (SWSS). The flood-event-based calibrated model runs with observed and designed heavy rain events of various sums, durations, and intensities. Afterward, the analysis focuses on precipitation and model overloading parameters (total flood volume, maximum flooding time and flow rate, and maximum nodal water depth) with pairwise correlation and multi-linear regression (MLR). The results indicate that it is possible to define a certain threshold (or range) for a few precipitation characteristics, which could lead to an urban flood, and fitting MLR can noticeably improve the predictability of the SWSS overloading parameters. The study concludes that design and observed rain events should be considered separately and that the resolution of the precipitation data (1/5/10 min) does not play a significant role in SWSS overloading.

show abstract

Section: Detection Of "System Overloading" Precipitation Thresholdsupporting

confidence: 90%

“…Thus, various simpler data-driven approaches could be sometimes more beneficial and easier to implement and apply [7,14]. These could include empirical graphical/threshold methods [15,16], logistic and probabilistic regressions [17,18], and machine learning [19].…”

mentioning

confidence: 99%