• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.84-91
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• 2021

In the 21st century, a number of storm and flood disasters caused by rapidly changing climate change is increasing, and the number of flood accidents at construction sites is also increasing. However, no specific reduction measures have been presented and thereby safety management to prevent flood accident need to be improved. Therefore, in this study, the inundation pattern by downpour at the excavation site was interpreted and the inundation risk quantification method was used to classify the risk magnitude. Finally, using the fish-bone diagram, we derived the major reasons of inundation accident at construction site systematically. The simulation results showed that the inundation depths of small-scale excavation sites and excavation sites exceeded 3 m due to the fluid flowing through the excavation surface. In addition, depending on the excavation site, a high velocity temporarily observed and decreased due to the storage effect, or high velocity surpassing 10 m/s continued. Since this type of flooding can pose a risk to most or all workers, if proper management measures are insufficient, fatal damage to life and property could occur. Consideration of the roots of these disasters is judged to be helpful in understanding the causes of inundation accidents that result in casualties and presenting accident reduction measures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.549-557
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• 2013

An flood inundation map is able to convey spatial distribution of inundation to a decision maker for flood risk management. A roughness coefficient with unclear values and a discharge obtained from the stage-discharge rating equation are key sources of uncertainty in flood inundation mapping by using a hydraulic model. Also, the uncertainty analysis needs an observation for the flood inundation, and satellite images is useful to obtain spatial distribution of flood. Accordingly, the objective of this study is to quantify uncertainty arising roughness and discharge in flood inundation mapping by using a hydraulic model and a satellite image. To perform this, flood inundations were simulated by HEC-RAS and terrain analysis, and ISODATA (Iterative Self-Organizing Data Analysis) was used to classify waterbody from Landsat 5TM imagery. The classified waterbody was used as an observation to calculate F-statistic (likelihood measure) in GLUE (Generalized Likelihood Uncertainty Estimation). The results from GLUE show that flood inundation areas are 74.59 $km^2$ for lower 5 % uncertainty bound and 151.95 $km^2$ for upper 95% uncertainty bound, respectively. The quantification of uncertainty in flood inundation mapping will play a significant role in realizing the efficient flood risk management.