Forensic engineering analysis applied to flood control

Delpasand, Mohammad; Fallah-Mehdipour, Elahe; Azizipour, Mohammad Javad; Jalali, Mohammadreza; Safavi, Hamid R.; Saghafian, Bahram; Loáiciga, Hugo A.; Babel, Mukand S.; Savić, Dragan; Bozorg‐Haddad, Omid

doi:10.1016/j.jhydrol.2021.125961

Cited by 6 publications

(1 citation statement)

References 61 publications

(37 reference statements)

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“…In order to ensure the effectiveness and safety of flood management strategies, simulation techniques were used to predict the flood diversion area under extreme weather conditions to assess the responsiveness of the flood diversion area in the face of these extremes, and to provide a more accurate estimate of the value of flood risk in the flood diversion area. While there is a lack of more specialized assessment methods and standards in hydrology for the design of artificial diversion lakes and the assessment of storage capacity, future work should introduce a standard assessment simulation system that will help us to assess the predischarge of reservoir storage based on forecasts [47,48] to improve the scientific and practical accuracy of the methodology.…”

Section: Discussionmentioning

confidence: 99%

A Sponge Village Flood Response Method Based on GIS and RS Analysis Formation—A Case Study of Jiangou Village

Liang,

Guo,

Wang

2024

Water

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This study was conducted in response to the Beijing–Tianjin–Hebei mega heavy rainfall event at the end of July 2023, and the severely affected and representative Jiangou village in Beijing was selected as the study area. A variety of methods were used to synthesize and analyze the situation and propose an adaptive response to heavy rainfall and flooding in the village. Based on multi-source remote sensing (RS) data, a comprehensive topographic and hydrological characterization was carried out, and the precipitation before and after the disaster was analyzed; the flood inundation area was extracted using the improved normalized water body index (MNDWI) and OTSU thresholding methods, and the changes of water bodies during the flooding period were quantitatively analyzed; and an improved convolutional-neural-network-based building identification and extraction model was constructed to extract the research distribution of buildings in the area. The sponge city construction (SPCC) method was improved to obtain a method that can mitigate flood risk and adapt to villages by constructing small artificial lakes and local topographic buffers to improve the water storage and drainage capacity of villages. The study shows that these methods are innovative in flood hazard analysis and mitigation but still need further improvement in data accuracy, simulation depth, and system evaluation.

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Section: Discussionmentioning

confidence: 99%