Precipitation threshold for urban flood warning - an analysis using the satellite-based flooded area and radar-gauge composite rainfall data

Dao, Duc Anh; Kim, Dongkyun; Park, Jeongha; Kim, Tae‐Woong

doi:10.1016/j.jher.2020.08.001

Cited by 23 publications

(10 citation statements)

References 69 publications

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“…They discovered that the RTFW is strongly influenced by the temporal variability of the rainfall. A similar conclusion was found as Dao et al (2020b) performed an analysis on Busan, Korea based on the flooded area data derived from Sentinel-1 synthetic aperture radar images.…”

Section: Introductionsupporting

confidence: 80%

“…If the warning system runs on the merged watersheds with greater size, the rate of false alarm would significantly decrease and the rate of hit would also significantly increase (Dao et al, 2020b). Here, it is worth noting that the system failed to issue flood warning only for the 6.5 percent of all flood events in spite of the high spatial precision.…”

Section: Determination Of Rtfwmentioning

confidence: 96%

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Estimation of rainfall threshold for flood warning for small urban watersheds based on the 1D–2D drainage model simulation

Dao

Kim

Tran

2021

Stoch Environ Res Risk Assess

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This study proposed an equation for Rainfall Threshold for Flood Warning (RTFW) for small urban watersheds based on computer simulations. First, a coupled 1D-2D dual-drainage model was developed for nine watersheds in Seoul, Korea. Next, the model simulation was repeated for a total of 540 combinations of the synthetic rainfall events and watershed imperviousness (9 watersheds x 4 NRCS Curve Number (CN) values x 15 rainfall events). Then, the results of the 101 simulations that caused the critical flooded depth (0.25m-0.35m) were used to develop the equation that relates the value of RTFW to the rainfall event temporal variability (represented as coefficient of variation or CV) and the watershed Curve Number. The results suggest that (1) RTFW exponentially decreases as the rainfall CV increases; (2) RTFW linearly decreases as the watershed CV increases; and that (3) RTFW is dominated by CV when the rainfall has low temporal variability (e.g., CV<0.2) while RTFW is dominated by CN when the rainfall has high temporal variability (e.g., CV>0.4). For validation, the proposed equation was applied for the flood warning system with two storm events occurred in 2010 and 2011 over 239 watersheds in Seoul. The system showed the the hit, false and missed alarm rates at 69% (48%), 31% (52%) and 6.7% (4.5%), respectively for the 2010 (2011) event.

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Section: Introductionsupporting

confidence: 80%

Section: Determination Of Rtfwmentioning

confidence: 96%

Estimation of rainfall threshold for flood warning for small urban watersheds based on the 1D–2D drainage model simulation

Dao

Kim

Tran

2021

Stoch Environ Res Risk Assess

Self Cite

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“…They also suggest that 0.747 to 0.880 ranges are good for internal consistency reliability. Some researchers also argue that a fair threshold may be anywhere between .60 and up (Dao et al, 2020). Table 4 identifies the CR of the present study that satisfies the demanded range of internal consistency.…”

Section: Measuring Modelmentioning

confidence: 67%

User Attitude and Intentions Towards FinTech in Bangladesh

Ayoungman

Chowdhury

Hussain

et al. 2021

International Journal of Asian Business and Information Management

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FinTech is considered as a need for modern financial methods to compete with traditional financial methods. The combination of innovation, technology and finance develop a unique method that could be a source of economic development in developing countries. Modern technologies are essential to recognize the user attitude, behaviour and intentions towards FinTech. Hence, the key objective of the study is to investigate the user attitude and intentions towards the adoption of FinTech in Bangladesh. Under the light of the Technology Acceptance Model and Theory of Planned Behaviour, the following study used Perceived Trust, Perceived Usefulness, Perceived Compatibility, Perceived Cost Efficiency and Perceived Risk as an independent variable towards attitude and intentions of the users towards FinTech products. The study collected data from 450 FinTech users from Bangladesh and the proposed relationship among variables were measured by Structural Equation Model by using SMART-PLS. The research findings will benefit FinTech operators to create more customized services for local consumers.

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“…Synthetic aperture radar (SAR) stands for synthetic aperture radar. It is a technique for generating high‐resolution images from a resolution‐limited radar system (Kim & Duc, 2020; Giustarini et al, 2013; Mason et al, 2010, 2012; Pelich et al, 2022; Pulvirenti et al, 2016). Any imaging radar operates on the fundamental premise of emitting an electromagnetic signal toward a surface and measuring the amount of signal backscattered and its time delay.…”

Section: Overview Of Satellite Imagesmentioning

confidence: 99%

A review of intelligent models for mapping city development and urban flooding

Senthilkumar

Arthur

2023

Land Degrad Dev

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With urbanization is on the rise, it wreaks havoc on the hydrological processes within a catchment, resulting in a deteriorating water environment. Floods can greatly raise the cost of mitigation efforts due to their damaging consequences. The natural water balance is disrupted by an increase in impermeable areas. As runoff rises, so do flood peaks and volumes even in short, low‐intensity showers. Urban flooding is a significant impact of urbanization that has drawn the attention of experts. Currently, there are techniques based on distributed hydrologic modeling and Geographic Information Systems (GIS) used to assess the influence of land use for urbanization on the environment. Deep learning techniques with their immense performance in Computer Vision and Image Processing fields have been extended to the problem of urban floods by integrating them with a GIS‐based methodology. This study outlines multiple techniques that have been used to address urban floods.

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Precipitation threshold for urban flood warning - an analysis using the satellite-based flooded area and radar-gauge composite rainfall data

Cited by 23 publications

References 69 publications

Estimation of rainfall threshold for flood warning for small urban watersheds based on the 1D–2D drainage model simulation

Estimation of rainfall threshold for flood warning for small urban watersheds based on the 1D–2D drainage model simulation

User Attitude and Intentions Towards FinTech in Bangladesh

A review of intelligent models for mapping city development and urban flooding

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