Evaluation of one-dimensional and two-dimensional HEC-RAS models to predict flood travel time and inundation area for flood warning system

Ghimire, Ekaraj; Sharma, Suresh; Lamichhane, Niraj

doi:10.1080/09715010.2020.1824621

Cited by 39 publications

(26 citation statements)

References 47 publications

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“…As per the literature review, it is observed that flood mapping is likely being done using HEC-RAS [14] (i) Steady Flow Surface Profiles: This section of the modeling method measures water surface profiles for a continuous, steadily changing flow. The system may handle a singular river reach, a dendritic grid, or a whole network of channels.…”

Section: Hec-ras (Hydraulic Engineering Centre-river Analysis System)mentioning

confidence: 99%

Advanced Techniques of Flood Forecasting, Flood Inundation Mapping and Flood Prioritization of Panam River Basin

Patel¹,

Parekh²

2022

cea

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Section: Hec-ras (Hydraulic Engineering Centre-river Analysis System)mentioning

confidence: 99%

Advanced Techniques of Flood Forecasting, Flood Inundation Mapping and Flood Prioritization of Panam River Basin

Patel¹,

Parekh²

2022

cea

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“…On the other hand, with the development of computer science, many software and numerical models have been presented for flood modeling. Among software models, HEC‐RAS (Ghimire et al, 2022; Namara et al, 2022; Sejati et al, 2022), HEC‐HMS (Altaf & Romshoo, 2022; Nadeem et al, 2022; Shah & Lone, 2022), MIKEs (Mike11, Mike21, Mike Flood, Mike Urban) (Dikici et al, 2022; Goumas et al, 2022; Li et al, 2022; Zhang et al, 2022; Zhou, Teng, et al, 2022; Zhou, Zheng, et al, 2022), Bentley Open Flow (de Andrade et al, 2022; Ellwood et al, 2022; Khakhar et al, 2022), Flo‐2D (Gerundo et al, 2022; Komolafe, 2022; Liu et al, 2022; Wang, Luo, et al, 2022), and CCHE (Lee et al, 2020; Kakati et al, 2022; Poorzaman et al, 2022) models can be mentioned. Also, the most applied numerical models include artificial neural network (Ahmad et al, 2022; Dahri et al, 2022; Wang, Yang, et al, 2022), random forest (Abedi et al, 2022; El‐Magd & Ahmed, 2022; Ha & Kang, 2022; Zhu & Zhang, 2022), and analytic hierarchy process (Bouamrane et al, 2022; Roy et al, 2023; Souissi et al, 2022; Vilasan & Kapse, 2022).…”

Section: Introductionmentioning

confidence: 99%

Using geomorphologic indicators in preparation for flood zoning and flood risk maps in the Kashafroud basin, Iran

Panahi,

Khodashenas,

Faridhosseini

2024

J Flood Risk Management

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The risk of flooding has become more significant in many parts of the world due to climate change and increased urbanization. Flood has devastating effects on infrastructure, and communities, causing damage to property and loss of life. Simulation of flood extent in a particular area is done by using various mathematical models, hydrologic‐hydraulic models, and datasets. Flood modeling using hydraulic‐hydrological models has many errors due to the lack of hydraulic‐hydrologic data and insufficient statistical period length. This study demonstrates the fact that the geomorphological index (GI) method, which is based on the digital elevation model and requires little hydraulic‐hydrologic data, is an effective method for flood modeling. Flood zoning based on GI was performed within the Kashafroud basin with 25, 100, and 200‐year return periods by using geomorphic flood area (GFA) plugin in QGIS software. The true positive rates were 0.985, 0.989, and 0.992, respectively, which showed the high accuracy of flood zoning based on the GI method. Here proposed method showed that using the GFA plugin offers a good way for the flood risk assessment in a basin with the lack of measured data as an alternative to the hydraulic‐hydrological methods.

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“…Ideally, a 2‐D model is expected to accurately simulate the flood inundation extent (Ghimire et al, 2020; Papaioannou et al, 2016; Vojinovic & Tutulic, 2009). However, other sources of uncertainty, such as parameter and input values, still remain in the case of a 2‐D model.…”

Section: Introductionmentioning

confidence: 99%

Impact of cross‐sectional orientation in one‐dimensional hydrodynamic modeling on flood inundation mapping

Jesna

Bhallamudi

Sudheer

2023

J Flood Risk Management

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Flood management activities require development of flood maps that depict the spatial and temporal extent of floods with the help of hydrodynamic models. Two‐dimensional (2‐D) hydrodynamic models are frequently employed for flood inundation modeling and mapping with the help of high‐end computational resources and high‐resolution terrain information such as LiDAR (light detection and ranging) data. However, LiDAR data are either unavailable or not freely accessible in many parts of the world, especially in nations belonging to Global South. Hence, one‐dimensional (1‐D) models are still in practice owing to their lesser computational cost and data requirement. Nonetheless, the successful application of a 1‐D model depends mainly on the representation of the natural river and floodplain geometry, which is the primary input in the form of discrete cross‐sections. The assumed flow directions on floodplains while orienting the cross‐sections in 1‐D models induce some uncertainty in the model simulations. This study aims to evaluate the variability in the model simulations caused by the cross‐sectional orientations. Flood simulations were performed using a 1‐D hydrodynamic model for six different cross‐sectional realizations for three river reaches, having distinct morphological and topographical characteristics, and were compared with the simulations of a 2‐D hydrodynamic model and available reference inundation maps. The study suggests that the simulations of flood inundation extent and maximum flow depth variation are influenced by the cross‐sectional orientation on flood plains in river reaches characterized by broad flood plains with complex local topographical variations. In contrast, for reaches with relatively less wide and complex terrains, 1‐D models can generate robust simulations of flood inundation extent and spatial variation in maximum flood depth (R2 and NSE greater than 0.89) for high flood events.

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Evaluation of one-dimensional and two-dimensional HEC-RAS models to predict flood travel time and inundation area for flood warning system

Cited by 39 publications

References 47 publications

Advanced Techniques of Flood Forecasting, Flood Inundation Mapping and Flood Prioritization of Panam River Basin

Advanced Techniques of Flood Forecasting, Flood Inundation Mapping and Flood Prioritization of Panam River Basin

Using geomorphologic indicators in preparation for flood zoning and flood risk maps in the Kashafroud basin, Iran

Impact of cross‐sectional orientation in one‐dimensional hydrodynamic modeling on flood inundation mapping

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