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Floods have always been associated with widespread devastation and destruction since the emergence of human civilization. The intensity of this disaster has been increasing due to accelerated impact of human activities. Flood vulnerability is very diverse in nature and is multidimensional and a topic of vital significance. Hence, flood vulnerability assessment assumes greater significance since magnitude of destructions varies over space and time. The study makes a credible attempt to present a coherent review on the approaches and methodologies used for assessing flood and its vulnerability. A time frame of 1990–2018 was chosen for analyzing varied works carried out flood vulnerability and susceptibility assessment. Articles from Scopus and other reputed journals were used to review the works on flood assessments. Methods and approaches were examined by considering most-cited authors and keywords used in their works. The study revealed a gap existing between methods and approaches for evaluating flood vulnerability which can be incorporated by using high-resolution data along with using multidimensional approach for assessing vulnerability. Furthermore, this study calls for comprehensive flood assessment using artificial neural network, hydrodynamic models and geospatial techniques to provide a vivid visualization of flood susceptibility. The study may prove helpful in analyzing different components of vulnerability and guiding research gaps in methodology to be used for assessing flood vulnerability at spatial scales.

Hydrodynamic models have been widely used in urban flood modelling. Due to the prohibitive computational cost, most of urban flood simulations have been currently carried out at low spatial resolution or in small localised domains, leading to unreliable predictions. With the recent advance in high-performance computing technologies, GPU-accelerated hydrodynamic models are now capable of performing high-resolution simulations at a city scale. This paper presents a multi-GPU hydrodynamic model applied to reproduce a flood event in a 267.4 km2 urbanised domain in Fuzhou, Fujian Province, China. At 2 m resolution, the simulation is completed in nearly real time, demonstrating the efficiency and robustness of the model for high-resolution flood modelling. The model is used to further investigate the effects of varying spatial resolution and using localised domains on the simulation results. It is recommended that urban flood simulations should be performed at resolutions higher than 5 m and localised simulations may introduce unacceptable numerical errors.

Flooding is a major threat that presents a significant risk to human survival and development worldwide. Regarding flood risk management, flood modeling enables understanding, assessing, and forecasting flood conditions and their impact. This paper gives an overview of prevailing flood simulation models given their potentials and limitations for reflecting pluvial floods in watershed settings. The existing models are categorized into hydrologic, hydrodynamic, and coupled hydrologic-hydrodynamic models. The coupled hydrologic-hydrodynamic model can be further classified into full, external, and internal coupling models. The definitions, advantages, and limitations of each coupling model are discussed. It is found that the existing coupling types cannot accurately reflect the flood evolution processes. A dynamic bidirectional coupled hydrologic-hydrodynamic model is then detailed, where the watershed is spatially divided into inundation and non-inundation regions. These two regions are connected by a coupling moving interface. Only 2D hydrodynamic models are applied to the local inundation regions to ensure numerical accuracy, whereas the fully distributed hydrologic model is applied to non-inundation regions to improve computational efficiency. Future investigation should focus on the development of a dynamic bidirectional coupling procedure that can accurately represent the complex physical interactions between upstream rainfall-runoff and the local inundation process. This paper would help flood managers and potential users undertake effective flood modeling tasks, balancing their needs, model complexity, and requirements of input data and time.

Floods are the most frequent natural disaster and pose a very challenging threat to many cities worldwide. Understanding the flood dynamic is essential for developing strategies to reduce its risk and damages, thus ensuring the cities’ protection. This study evaluated the Capibaribe River basin's hydrological response to extreme events and its impact on the city of Recife, in the northeast of Brazil. The CAWM IV and HEC-HMS models were coupled with a high-resolution 2D HEC-RAS model to simulate the flood events of 1975 and 2011 in Recife. CAWM IV is a newly developed hydrological model that presented very promising results for the data-scarce watersheds of the Brazilian semiarid region. For the 2D hydrodynamic modeling, 1-m LiDAR DEM was used. A reservoir operation model was also applied to assess the effect of the basin's main reservoirs on the water system upstream from Recife. Lastly, the 2011 flood event was simulated under the scenario of an absence of this reservoir system. The strategy used to address flooding simulation in an urban area proved to be satisfactory. Of the events simulated with CAWM IV, 60% have at least a satisfactory adjustment with NSEsqrtQ coefficients greater than 0.36 in 95% of cases. With the reservoir operation model, it was possible to calculate the peak flow of the events of 1975 and 2011 as being 2574 and 731 m3/s, respectively. The 2D HEC-RAS model presented a measure of fit of approximately 0.7. The study showed that the reservoir system was responsible for reducing flood extent by 70.3% in the 2011 event, but even with this system, this event still caused a flood covering an area of 6.01 km2. The results indicate that although the reservoirs prevent severe flooding in the lower course of the Capibaribe River, Recife is still vulnerable to flooding.

Turbulent heat fluxes are affected by and influence the temperature dynamics and ice conditions of lakes. Significant efforts have been made to develop operational hydrodynamic and ice models for large lakes such as the North American Great Lakes. However, the behavior of surface fluxes in these lakes has previously focused on the ice‐free season and has not yet been fully assessed during winter conditions in the presence of ice. Given the importance of navigation support and regional weather forecasting, we therefore analyze operational configurations of the Great Lakes for modeled fluxes to evaluate them for open water, ice‐covered, and partial ice conditions. We compare the modeled fluxes with eddy covariance‐based observed fluxes from the Great Lakes Evaporation Network. While observed latent heat fluxes have periods of high values both during ice‐free and ice‐covered periods, we find that elevated open water fluxes in early winter can be well modeled. However, the modeled fluxes during ice‐covered periods appear less accurate, where the errors are likely related to the simulated ice thickness. Thin ice has many small cracks, resulting in large fluxes nearly as high as over open water; very thick ice can reduce the latent fluxes to near zero, according to observations. Overall, the algorithms used in existing operational models show promise in resolving winter lake fluxes; however, further improvement may require adaptations to underlying ice and hydrodynamic model formulations.

This paper presents a new flood modelling tool developed by coupling a full 2D hydrodynamic model with hydrological models. The coupled model overcomes the main limitations of the individual modelling approaches, i.e. high computational costs associated with the hydrodynamic models and less detailed representation of the underlying physical processes related to the hydrological models. When conducting a simulation using the coupled model, the computational domain (e.g. a catchment) is first divided into hydraulic and hydrological zones. In the hydrological zones that have high ground elevations and relatively homogeneous land cover or topographic features, a conceptual lumped model is applied to obtain runoff/net rainfall, which is then routed by a group of pre-acquired ‘unit hydrographs’ to the zone borders. These translated hydrographs will then be used to drive the full 2D hydrodynamic model to predict flood dynamics at high resolution in the hydraulic zones that are featured with complex topographic settings, including roads, buildings, etc. The new coupled flood model is applied to reproduce a major flood event that occurred in Morpeth, northeast England in September 2008. While producing similar results, the new coupled model is shown to be computationally much more efficient than the full hydrodynamic model.

In this paper, the catastrophic flash flood event which occurred in the western part of Attica (Greece) in November 2017 is reconstructed. The flood event hit the town of Mandra, causing 24 fatalities and huge damages in the properties and the infrastructure. The flood hydrograph was derived using the two-dimensional hydrodynamic model FLOW-R2D. Attention was drawn on the uncertainties of the model output due to the uncertainty of the estimated parameters such as infiltration, friction and the uncertainty of input data. Due to the computational burden related to the model, a global sensitivity analysis based on Morris method was performed. Then, a Monte Carlo-based uncertainty analysis was performed on the two most influential factors. It was concluded that even the results of the physically based hydrodynamic models are characterised by uncertainties. However, the capability of the hydrodynamic models to describe in detail the dynamics of the overland flow is the main advantage of these models against the conventional hydrological models. It is concluded that the rational use of physically based models for analysing complex storm phenomena with high variable spatial and temporal distribution can lead to a more accurate range of magnitudes of flood peak.

River flooding has been causing extensive losses to life and property, which is a serious concern worldwide. To minimize these losses, suitable planning and management practices are required for the floodplain mapping. Flash floods occur almost every year in the deltaic region of Brahmani and Baitarani river basins in India, during the monsoon season. Generally, 1D modelling is considered as a regular practice. But nowadays, model formulations include 1D for the representation of river channels and 2D for representing river floodplains. In the absence of uniform observations, a hybrid model (1D–2D coupled model) has been developed for this deltaic region to identify the extent of inundation and its depth during the flooding, since 1D models alone do not provide detailed information of flooding. Thus, a well-known 2D river hydrodynamic model iRIC was externally coupled with 1D (SWAT and SWMM) models to simulate and visualize flood scenarios and to identify the flood-prone areas. The hydrological model SWAT was calibrated and validated for Brahmani river deltaic basin, with the observed discharge data available. However for Baitarani river basin, observed flow data were missing and only gauge data were available at few monitoring stations. Hence, for Baitarani river basin, the SWMM model was developed and calibrated with the help of Monte Carlo method. Finally, the SWAT- and SWMM-based tributary stream flow outputs were fed together into the iRIC hydrodynamic model as input for flood inundation mapping. The discharge and water gauge data were used for the calibration and validation. The results obtained from the coupled model were found to be in good agreement with the observed data (RMSE value is 0.77 and 0.79 during calibration and validation, respectively), which enabled identification of the flood-prone areas. The developed model may be used as a tool for effective planning and management of natural disasters such as flash floods.

Wind is a critical driving force in hydrodynamic and water quality modeling of large shallow lakes, and is characterized by the wind drag coefficient Cd, representing the momentum transfer at the air‐water interface. Contemporary empirical formulae for Cd estimation were derived over oceans and some of which are solely wind velocity U10 dependent. These formulae were previously found to be inadequate in inland lake models often resulting in the water velocity underestimation. To address this problem, a physical scale experiment was designed, in which Cd was measured using a wind profile and eddy covariance methodology. A new wind‐induced wave‐dependent Cd parameterization was also established and validated in two lake studies. The driving force was modified by the wave‐dependent Cd formula in a hydrodynamic model of the shallow Upper Klamath Lake (UKL), OR, USA. The experimental Cd was negatively correlated to the wind velocity up until the critical U10 = 1.6 m s−1 which was 1.0~3.1 times previous empirical extrapolations at light winds. The variation partitioning results showed that wave parameters contributed to more than 30% of Cd variation combined with wind parameters. The modified wind stress field was spatially heterogeneous and the modeled water velocity was closer to the observations at two sites. Significant main circulation and outer bank circulation were modeled accompanied by higher surface vorticity, compared to the original UKL model. Overall, the wave‐dependent Cd formula provided an improvement of the surface flow field in the UKL model and will improve the management of the lake ecosystems. Plain Language Summary As a critical driving force in large shallow lakes, wind parameterization is of great importance for accurate hydrodynamic modeling. Previous wind‐dependent wind drag formulae over oceans usually generate large underestimates of water velocity in lakes. We thus propose a new wave‐dependent Cd parameterization based on an experimental study to improve the Cd parameterization in lakes. The Cd measurements were compared and confirmed by two typical methodologies of wind profile and eddy covariance. The newly derived wave‐dependent Cd parameterization was validated in two lake studies and adapted to a hydrodynamic model of the Upper Klamath Lake, OR, USA. Results showed an improved representation of the wind stress field, surface water velocity, and surface circulation. Our work should therefore be useful when using mechanistic models to manage hydrodynamics and water quality in large shallow lakes. Key Points A wave‐dependent Cd formula was developed based on an experimental study, indicating a negative correlation of Cd with U10 at light winds Spatial heterogeneity of the wind stress field and surface circulation was identified in lake hydrodynamic modeling The adaptation of Cd parameterization in a hydrodynamic model was improved through the wave‐dependent Cd formula

Flooding is now becoming one of the most frequent and widely distributed natural hazards, with significant losses to human lives and property around the world. Evacuation of pedestrians during flooding events is a crucial factor in flood risk management, in addition to saving people’s lives and increasing time for rescue. The key objective of this work is to propose a shortest evacuation path planning algorithm by considering the evacuable areas and human instability during floods. A shortest route optimization algorithm based on cellular automata is established while using diagonal distance calculation methods in heuristic search algorithms. The Morpeth flood event that occurred in 2008 in the UK is used as a case study, and a highly accurate and efficient 2D hydrodynamic model is adopted to discuss the flood characteristics in flood plains. Two flood hazard assessment approaches [i.e., empirical and mechanics-based and experimental calibrated (M&E)] are chosen to study human instability. A comprehensive analysis shows that extreme events are better identified with mechanics-based and experimental calibration methods than with an empirical method. The result of M&E is used as the initial condition for the Morpeth evacuation scenario. Evacuation path planning in Morpeth shows that this algorithm can realize shortest route planning with multiple starting points and ending points at the microscale. These findings are of significance for flood risk management and emergency evacuation research.