The development of high spatial resolution digital elevation models takes place via the use of GeoEye-1 stereo-pair imagery, providing highly accurate geometrical representations of complex riverine ...systems. The combination of geographic information systems with hydraulic models facilitates the exploitation of satellite topographic information throughout the cross-section extraction process. One-dimensional HEC-RAS and combined 1D/2D HEC-RAS models are adjusted by making use of the resulting high-resolution input. Several hydraulic simulations are effectuated in order to test how significantly DEM resolution affects hydraulic modelling results, with regard also to the model dimensionality. The ability of the combined 1D/2D model, based mainly on the high-accuracy input data, provides an accurate estimate of the flood hazard area. Flood-prone areas could take advantage of high-accuracy results and facilitate the effective management of extreme events and sufficient decision making.
The simulation speed of two‐dimensional hydrodynamic flood models is a limiting factor when catchments are large, a considerable number of simulations is required (e.g., exploratory modeling, ...Monte‐Carlo flood simulations, or predicting probabilistic flood maps), or when there is a need for real‐time flood emergency management. Rapid Flood Models (RFMs) that rely only on topographic depressions and the water balance equation have been successfully implemented to predict maximum urban flood inundation depths within seconds to a few minutes. However, the preprocessing step (identification of depressions and their attributes) and the postprocessing step (marking up possible flow paths of flood water in between flooded depressions) of RFMs is time consuming. In this study, we developed a new fast flood inundation model based on the cellular automata (CA) approach. The new model does not require the preprocessing and postprocessing steps of RFMs and therefore can provide more simulation speed. The performance of our new model, referred to as Cellular Automata fast flood evaluation (CA‐ffé), was compared to two well‐known hydrodynamic flood models (HEC‐RAS and TUFLOW) in 20 simulation experiments conducted in five different urban subcatchments. CA‐ffé predicted maximum inundation depth with reasonable accuracy in a matter of seconds to a few minutes for a single rainfall event simulation. The CA‐ffé model performed exceptionally well in areas with low‐lying depressions. However, in areas where floodwaters had higher momentum and velocity, the model usually was not able to estimate inundation depths calculated by HEC‐RAS or TUFLOW. CA‐ffé's key drawback is also its inability to represent the temporal evolution of flooding and flow velocities. Nevertheless, its ability to provide spatial flood extents and depths in a fraction of the time compared to its hydrodynamic counterparts is a significant advancement toward exploratory approaches for water systems planning, model‐based predictive control, and real‐time flood management.
Key Points
A rapid urban flood inundation model was developed using a novel cellular automata approach and tested against detailed hydrodynamic models
Our model successfully predicted maximum inundation depth caused by excessive rain and stormwater surcharges within seconds to a few minutes
Selecting appropriate ranges for the model's parameters is crucial for model performance
Hydraulic models play an important role in determining flood inundation areas. When considering a wide array of one‐ (1D) and two‐dimensional (2D) hydraulic models, selecting an appropriate model and ...its calibration are crucial in an accurate prediction of flood inundation. This study compares the performance of four commonly used 1D and 2D hydraulic models, including HEC‐RAS 1D, HEC‐RAS 2D, LISFLOOD‐FP diffusive, and LISFLOOD‐FP subgrid, with respect to their model structure and their sensitivity to surface roughness characterisation. Application of these models to four study reaches with different river geometry and roughness characterisation shows that for a given set of roughness condition, the geometry, including the sinuosity, reach length and floodplain width, does not affect the performance of a 1D or 2D model. Overall, the performance of a 1D model is comparable to the 2D models used in the study, with the 2D models showing slightly better results. The performance of 2D models is affected by low channel roughness, and it improves with increasing channel roughness that enables more water to enter into the floodplain. On the contrary, the performance of 1D model is positively affected with increasing floodplain roughness. When the models are evaluated for uniform versus distributed roughness characterisation in the floodplain, the uniform surface characterisation provides the best results compared to the distributed roughness characterisation.
Various factors, such as the physical condition of the area, nature, and humans, influence the phenomenon of flooding. Thus, the flood control application model will differ in each region. The ...application of flood control structurally lowers the flood water level significantly, but it changes the ecosystem around the river. The eco-hydraulic concept is a new paradigm in watershed management to reduce the impact of floods while still paying attention to river ecosystems. This study aims to integrate structural methods with eco-hydraulic concepts in flood control in small-scale watersheds. The locus is the Akelaka watershed on Halmahera Island. Watershed morphometric analysis using the ArcGIS application, hydrological analysis for five and 25-year return floods, and hydraulics testing using the HecRAS application are used. The application of this concept uses vegetation on river slopes after normalization. The results showed that flood control which combined normalization, eco-hydraulic and structural ideas in Akelaka village, showed excellent results. The potential for inundation is reduced by up to 93% for a five-year return period flood discharge and 89% for a 25-year return period flood discharge.
Abstract The Egyptian Ministry of Water Resources and Irrigation launched in 2020 the national project to rehabilitate the canals network to rationalize the use of water resources to face the ...scarcity problems. The aim of study is to evaluate the impact of canal rehabilitation on the performance of irrigation water delivered laterally to Mesqa’s and longitudinally to the end of canal. Qaraqoul Canal et al.-Mallah Area, Alexandria, Egypt, was modeled using Hydrologic Engineering Center's-River Analysis System (HEC-RAS) to simulate water levels in the canal before and after rehabilitation using four discharge scenarios: 1.82, 3.7, 2.2, 7.87 m 3 /s. The calibration before rehabilitation shows that HEC-RAS simulated water levels corresponding to a discharge of 2.2 m 3 /s were in a good agreement with the actual field measured water levels. HEC-RAS results demonstrated that rehabilitation hydraulically improved the efficiency and performance of water conveyed by the canal. On the other hand, second scenario can be considered as suitable to keep water to reach the canal downstream with minimum suitable discharge, providing the need of two emergency pumps at last two branch canals called Mesqa’s. An ideal cross-section is also simulated using HEC-RAS which produced an efficient alternative with 40% less cost than the constructed alternative.
•Accurate, fast-running 1D model can predict backwater flooding in urban area.•1D model can quickly help/inform local policies to reduce flood risk.•Morris Method ranks the most influential ...parameters affecting flood damage.•Po River flood attenuation would be most helpful for flood reduction in Borgo Basso.•Roughness of the floodplain has a key role on the predicted flood damage.
Recent flood-related disasters, which affect many areas of the world due to a combination of climate change and increasing urbanization, have prompted researchers to study catastrophic phenomena for which large-scale mitigation strategies are needed. However, lower impact flood events occur more frequently, and although these floods are relatively less destructive, they can be effectively mitigated with local protection measures. This work focuses on understanding the factors that influence the reliable modeling of these lower impact - and less studied - flood events. We propose a procedure that combines the use of a simple but effective numerical model of the last segment of Ticino River with a Global Sensitivity Analysis for an in-depth evaluation of: i) the backwater-induced flooding of an urban area in the historical city of Pavia (Northern Italy) and ii) the potential flood damage due to such events. A 1D, unsteady HEC-RAS model (termed the 3R Model) was set up and validated against historical floods. Then, the 3R Model output was compared with a hybrid 1D/2D model of the same area. Both model schemes provide reliable results and similar predictions of the flood depth and its spatial extent. The 3R Model is demonstrated to be a successful modeling approach, providing a computational cost that is always less than one-tenth of the cost of the hybrid 1D/2D for the simulated floods. The Morris method of sensitivity analysis was performed to identify the most influential factors affecting the results of the 3R Model to help inform local policies aimed at flood risk reduction. The Morris results highlight that the maximum water level of the Po river has a dominant role in determining the flood magnitude for the whole area, with an influence at the control points in the floodplain that is more than triple that of the Ticino maximum flow rate. A Damage Index quantifying the housing loss due to the urban flood extent was introduced and analyzed using the Morris method. The results show that the predicted flood damage is strongly influenced by the uncertainty in the roughness coefficient of the floodplains. The contemporaneity of the floods on the Ticino and Po Rivers was also influential, playing a key role in flood severity within the urban area. A 5-hour delay of the Ticino flood wave (maximum flow rate of 2000 m3/s) with respect to that of the Po River (maximum stage level of 59.8 m a.s.l.) reduces the water level in the flooded area by 8 cm. These results will help the development of flood risk reduction strategies.
Hydrodynamic models play a key role in simulating total water level (TWL), that is, a combination of river flow, tide, surge, wind and wave‐induced water level, and representing flood inundation ...dynamics in coastal areas. An appropriate selection of two‐dimensional (2D) models that integrate riverine and estuarine interactions with ocean dynamics is crucial to generate accurate TWL predictions and assist stakeholders and federal agencies in decision making and flood emergency responses. In this study, we compare the performance of two widely used hydrodynamic models (e.g., 2D HEC‐RAS and Delft3D‐Flexible Mesh FM) with respect to their ability of predicting TWL in Delaware Bay, United States. Based on a previously established model configuration, we simulate Hurricane Sandy and Isabel that affected the Bay and led to considerable damages and economic losses. We then evaluate model capabilities with tidal analysis, compare observed vs. simulated TWL and analyze spatiotemporal variations of TWL through scenario‐based simulations. Our results suggest that atmospheric forcing input in Delft3D‐FM significantly improves TWL predictions as compared to those of 2D HEC‐RAS. Furthermore, model simulations with Delft3D‐FM can be faster than 2D HEC‐RAS by a factor of 6–10. Despite these advantages, 2D HEC‐RAS (version 5.07) is a noncommercial software easier to implement and can be a simpler alternative for modeling extreme events when atmospheric forcing is not relevant in the model domain.
Tigris River is an important water body in Iraq for drinking, agricultural, industrial, and livestock uses. The river flows from Turkey to the Iraqi land at Fiesh-khabour district in the northern ...part of Iraq and flows into Mosul city. Therefore, this study aims to simulate the flow in the Tigris River using the latest version of the HEC-RAS model (v5.0.7). The calibration and verification of the model showed that the final Manning’s roughness coefficients (n) of the main channels for the Tigris River were 0.036 and 0.026 for Mosul and Tikrit sites respectively. The Results illustrated a very good agreement between the simulated and measured stages. The Root Mean Square Error RMSE, MAE, and Nash-Sutcliffe Efficiency Criteria NSE, tests were used for calibrating the unsteady state flow model where it served as a comparison of calculated water levels by the model for each of the Manning index values ‘n’ with the observed water levels as a function. The final Manning’s roughness coefficients (n) of the main channels for the Mosul and Tikrit sites were 0.036 and 0.026 respectively. It's suggested to construct of hydraulic structures such as a dam with a reservoir beside this area to operate water stations and electric turbinate’s and other projects built next to the river, such as irrigation projects. Recommended using the simulation of the present study in the future to study the effect of constructing a dam in the Tikrit region. In addition, the current simulation can be used in the future to study the TDS, transportation of sediment loads, or pollution along the river.
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•The novelty of data-driven and HEC-RAS model for flood inundation is presented.•The accuracy in prediction and flood inundation is improved.•14 meteorological stations for 1999−2005 ...periods and TWI are used in ANN model.•Flood inundation obtained in HEC-RAS model is calibrated and validated in NDWI.
Lower Baro River, Ethiopia.
This paper presents the novelty of ANN and HEC-RAS model for flood inundation mapping in lower Baro Akobo Basin River, Ethiopia. ANN and HEC-RAS model is applied and successfully improves the accuracy of prediction and flood inundation in the region. This study uses 14 meteorological stations on a daily basis for 1999−2005 and 2006−2008 periods, and Topographical Wetness Index (TWI) to the train and test the model respectively. The runoff time series obtained in ANN model is linked to HEC-RAS and the flood depths were generated. The flood inundation generated in HEC-RAS model result was calibrated and validated in Normal Difference Water Index (NDWI).
As the inundation map generated from the runoff values of ANN model reveals, the lower Baro river forms huge inundation depth up to 250 cm. The performance the ANN model was evaluated using Nash-Sutcliffe Efficiency (NSE = 0.86), PBIAS = 8.2 % and R2 = 0.91 and NSE = 0.88, PBIAS = 8.5 % and R2 = 0.93 during the training and testing periods respectively. The generated inundation areas in HEC-RAS and the water bodies delineated in NDWI were covered with 94.6 % and 96 % as overlapping areas during the calibration and validation periods respectively. Therefore, it is concluded that the integration of the ANN approach with the HEC-RAS model has improved the prediction accuracy in traditional flood forecasting methods.
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