An Approach Using a 1D Hydraulic Model, Landsat Imaging  and Generalized Likelihood Uncertainty Estimation for an Approximation of Flood Discharge

Jung, Younghun; Merwade, Venkatesh; Yeo, Kyu-Dong; Shin, Youngsoo; Lee, Seung Oh

doi:10.3390/w5041598

Cited by 18 publications

(9 citation statements)

References 68 publications

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“…Although ample literature has been discussed to identified the source of uncertainties in flood inundation mapping (Bales and Wagner, 2009;Domeneghetti et al, 2013;Dottori et al, 2013;Jung et al, 2013;, but to eliminate the uncertainties completely are impossible due to various limitations such as computational times, cost, technology and knowledge of the flood science itself.…”

Section: Uncertainty In Flood Hazard Mappingmentioning

confidence: 99%

Flood Inundation Modeling and Hazard Mapping Under Uncertainty in the Sungai Johor Basin, Malaysia

Ali¹

2018

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Although all care is taken to ensure integrity and the quality of this publication and the information herein, no responsibility is assumed by the publishers, the author nor UNESCO-IHE for any damage to the property or persons as a result of operation or use of this publication and/or the information contained herein. A pdf version of this work will be made available as Open Access via http://repository.tudelft.nl/ihe This version is licensed under the Creative CommonsIn using 1-D hydraulic models, the geometric description of rivers and floodplains is performed by using a number of cross-sections, which play an important role in the accuracy of model results. In this work, criteria for cross-section spacing were tested and verified via numerical experiments.Similarly, digital elevation models (DEMs) used as geometrical input significantly affect the results of flood inundation modelling exercises. DEM is essential input that This study also explored the differences arising from the use of deterministic and uncertainty approaches in deriving design flood profiles and flood inundation maps.To this end, the generalized likelihood uncertainty estimation (GLUE) technique was used and the uncertainty in model predictions was derived through Monte Carlo analysis. In particular, this work focused on impact of uncertain inflow data and roughness coefficients in the accuracy of flood inundation models.As part of this research, 2-D hydraulic modelling software (LISFLOOD-FP) was also used to assess the effect of spatial data re-sampling (e.g. from high to low resolution) on model outcomes. This study evaluated two re-sampling techniques with combination of three different aggregation functions, i.e. minimum, maximum and mean values.This research work has not only provided useful results, but has also suggested further research and improvement of flood risk and mapping practices. The knowledge generated by, as well as the findings of this thesis, will be transferred to other study areas in Malaysia.

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Section: Uncertainty In Flood Hazard Mappingmentioning

confidence: 99%

Flood Inundation Modeling and Hazard Mapping Under Uncertainty in the Sungai Johor Basin, Malaysia

Ali¹

2018

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“…The flood hazard assessment tools mainly include Geographic Information System (GIS)-based hydrological analysis models [16,17], one-dimensional (1D) hydrodynamic models [18,19], dual one-dimensional (1D/1D) models [20,21] and 1D/2D-coupled models [22,23]. GIS-based models can be employed to quickly capture the local depressions, main flow paths and overland discharge/accumulations.…”

Section: Introductionmentioning

confidence: 99%

A GIS-Based Hydrological Modeling Approach for Rapid Urban Flood Hazard Assessment

Zhou

Arnbjerg‐Nielsen

et al. 2021

Water

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Urban floods are detrimental to societies, and flood mapping techniques provide essential support for decision-making on the better management of flood risks. This study presents a GIS-based flood characterization methodology for the rapid and efficient identification of urban flood-prone areas, which is especially relevant for large-scale flood hazards and emergency assessments for data-scarce studies. The results suggested that optimal flood mapping was achieved by adopting the median values of the thresholds for local depression extraction, the topographic wetness index (TWI) and aggregation analyses. This study showed the constraints of the depression extraction and TWI methods and proposed a methodology to improve the performance. A new performance indicator was further introduced to improve the evaluation ability of hazard mapping. It was shown that the developed methodology has a much lower demand on the data and computation efforts in comparison to the traditional two-dimensional models and, meanwhile, provides relatively accurate and robust assessments of flood hazards.

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“…The decomposition of polarimetric synthetic aperture radar (SAR) data greatly affected the robustness and reliability of the change detection method in wetland mapping. Taking advantage of the HEC-RAS (Hydrologic Engineering Center-River Analysis System, US Army Corps of Engineering, [12]) model development, and of the advances in data acquisition and GIS, Jung et al [13] reduced the uncertainty in the estimation of the flood discharge. Therefore, the exploration of the technological means and combined use of multiple remotely sensed datasets improved the mapping results of flood events, and advanced our understanding of the flood vulnerability in local communities.…”

Section: Better Remotely Sensed and Geospatial Datasets For Flood Rismentioning

confidence: 99%

Advances in Remote Sensing of Flooding

Wang¹

2015

Water

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Abstract:With the publication of eight original research articles, four types of advances in the remote sensing of floods are achieved. The uncertainty of modeled outputs using precipitation datasets derived from in situ observations and remote sensors is further understood. With the terrestrial laser scanner and airborne light detection and ranging (LiDAR) coupled with high resolution optical and radar imagery, researchers improve accuracy levels in estimating the surface water height, extent, and flow of floods. The unmanned aircraft system (UAS) can be the game changer in the acquisition and application of remote sensing data. The UAS may fly everywhere and every time when a flood event occurs. With the development of urban structure maps, the flood risk and possible damage is well assessed. The flood mitigation plans and response activities become effective and efficient using geographic information system (GIS)-based urban flood vulnerability and risk maps.Keywords: flood; flood risk analyses and mitigation; geographic information system (GIS); mapping flood extent and assessing flood damage; remote sensing and geospatial technologies and datasets

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An Approach Using a 1D Hydraulic Model, Landsat Imaging and Generalized Likelihood Uncertainty Estimation for an Approximation of Flood Discharge

Cited by 18 publications

References 68 publications

Flood Inundation Modeling and Hazard Mapping Under Uncertainty in the Sungai Johor Basin, Malaysia

Flood Inundation Modeling and Hazard Mapping Under Uncertainty in the Sungai Johor Basin, Malaysia

A GIS-Based Hydrological Modeling Approach for Rapid Urban Flood Hazard Assessment

Advances in Remote Sensing of Flooding

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