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Remote sensing technology and the resulting high resolution geospatial data now allow for a detailed description of urban landscape, advancing the development of raster-based flood models. Previous studies have highlighted the critical role of finely resolved and accurate terrain data (5m or less) in capturing flow patterns in urban areas. However, using a uniform fine grid resolution over a rectangular domain generally results in dense grids and leads to large computational costs. The small cell size is often an overspecification for rural regions where the flow processes are changing much less rapidly. Unstructured grid models resolve this issue and trade off more complex programming and slower operation against being able to represent a given problem with fewer computational elements. An alternative solution has been recently proposed to apply the non-uniform structured grid, with fine grids covering only the regions where this detail is a necessity, for example to capture the preferential flow paths influenced by small-scale topographic features or man-made structures (river channels, buildings, roads, defences, etc.). Without this, the smoothing effect of mesh coarsening upon input topographical data in urban areas leads to a uncertain prediction of the inundation extent and the timing of inundation due to the simplified wetting process. Flow connectivity formed by the river channels and the road network, which has a strong control on urban floodplain hydraulics, is also better represented by mixing grid resolutions. Considering the large consequences in terms of economic losses caused by urban flooding, here we develop a GPU-accelerated non-uniform sub-/super-grid channel model (river channels with width below or above the fine grid resolution) for accurate and efficient urban flood modelling. Urban areas and the river channel network are forced to keep fine resolution, while a coarse representation, depending on the terrain gradient, is allowed for rural regions. This model allows the utilization of available sub-/super-grid scale bathymetric information for 1D in-channel flow representation, and a 2D model for floodplain with variable grid resolution, minimising the computational costs and below water line data requirements in the river channel. Three tests are set up to validate the model performance, and the results show that modelling the urban area with fine resolution improved the model reliability and accuracy, and reduces computational cost in rural areas where a coarse grid may be used.

An accurate estimation of river channel conveyance capacity and the water exchange at the river-floodplain interfaces is pivotal for flood modelling. However, in large-scale models limited grid resolution often means that small-scale river channel features cannot be well represented in traditional 1D/2D schemes. As a result instability over river and floodplain boundaries can occur, and flow connectivity, which has a strong control on the floodplain hydraulics, is not well-approximated. A subgrid channel model (SGC) based on the local inertial form of the shallow water equations, which allows utilization of approximated sub-grid scale bathymetric information while performing very efficient computations has been proposed as a solution, and it has been widely applied to calculate the wetting and drying dynamics in river-floodplain systems at regional scales. Unfortunately, SGC approaches to date have not included latest developments in numerical solutions of the local inertial equations, and the original solution scheme was reported to suffer from numerical instability in low friction regions such as urban areas. In this paper, for the first time, we implement a newly developed diffusion and explicit adaptive weighting factor in the SGC model. An adaptive artificial diffusion is explicitly included in the form of an upwind solution scheme based on the local flow status to improve the numerical flux estimation. A structured sequence of numerical experiments is performed, and the results confirm that the new SGC model improved the model performance in terms of water level and inundation extent, especially in urban areas where the Manning parameter is less than 0.03 m−1/3 s. By not compromising computational efficiency, this improved SGC model is a compelling alternative for river-floodplain modelling, particularly in large-scale applications.

Extreme precipitation events are expected to intensify with global warming, and naturally a widespread assumption is that the intensity and frequency of flooding will grow with the heavier downpours under climate change. However, flood magnitude is not only dependent on the spatial distribution, time evolution and rarity of precipitation, antecedent soil moisture and snowmelt are also the potential controls on flood hazard. Few studies have jointly quantified the influence of soil moisture dynamics and spatiotemporal distribution of precipitation on flood amplitude, though many research attempted to explain the elusive relationship between rainfall and flood conceptually. Here, the connections of changes in extreme precipitation and direct surface water flooding intensities in the periods of 1981-2000, 2021-2040 and 2061-2080 are quantified in 6 study areas in the UK, with high-resolution spatial and temporal characteristics of hourly rainfall data from UKCP Local 2.2 km. Dynamic soil moisture is modeled empirically and continuously to capture the moisture variation and infiltration loss, and distributed rainfall-runoff is calculated on the uneven terrain with the sub-grid river channel model in LISFLOOD-FP. Results indicate a strong correlation of the extreme rainfall and flood magnitude changes with the capacity of the soil moisture. Extreme precipitation can be magnified in rainy seasons due to amplified moisture convergence, while in dry periods limited moisture availability may offset extreme precipitation increases.

Initial abstraction (Ia) is a sensitive parameter in hydrological models, and its value directly determines the amount of runoff. Ia, which is influenced by many factors related to antecedent watershed condition (AWC), is difficult to estimate due to lack of observed data. In the Soil Conservation Service curve number (SCS-CN) method, it is often assumed that Ia is 0.2 times the potential maximum retention S. Yet this assumption has frequently been questioned. In this paper, Ia/S and factors potentially influencing Ia were collected from rainfall–runoff events. Soil moisture and evaporation data were extracted from GLDAS-Noah datasets to represent AWC. Based on the driving factors of Ia, identified using the Pearson correlation coefficient and maximal information coefficient, artificial neural network (ANN)-estimated Ia was applied to simulate the selected flood events in the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model. The results indicated that Ia/S varies over different events and different watersheds. Over 75% of the Ia/S values are less than 0.2 in the two study areas. The driving factors affecting Ia vary over different watersheds, and the antecedent precipitation index appears to be the most influential factor. Flood simulation by the HEC-HMS model using statistical Ia gives the best fitness, whereas applying ANN-estimated Ia outperforms the simulation with median Ia/S. For over 60% of the flood events, ANN-estimated Ia provided better fitness in flood peak and depth, with an average Nash–Sutcliffe efficiency coefficient of 0.76 compared to 0.71 for median Ia/S. The proposed ANN-estimated Ia is physically based and can be applied without calibration, saving time in constructing hydrological models.

The flood caused by a dam-break event generally contains a large amount of energy, and it can be destructive to the downstream buildings and structures. An experiment-validated three-dimensional numerical model was designed to investigate the impact of dam-break flood on structures with different arrangements. The Eulerian two-phase flow model and the smooth particle dynamics method are applied separately to solve the flow motion, and the deformation characteristics of buildings under the flood impact are evaluated by fluid-structure interaction model. An experiment is constructed to validate the numerical simulation. The results show that the structure suffers a large instantaneous impact pressure when the flood water first contacts the structure, and the value of this pressure can reach 1.5-3.0 times that of the maximum pressure after the first impact, and the maximum total pressure of the upstream building surface is about 1800N. The deformation near the door and windows is obvious, and the maximum deformation can reach 600μm, which further results in the large deformation of the gable and roof on both sides. Moreover, the arrangement of buildings has different blocking effect on flood. The back-row buildings arranged in alignment along the flow direction still has to bear 20% flood impact, and the front row buildings arranged alternately bear 90% high-speed flow impact. The structural damage is evaluated by the material failure criterion, and the weak position of buildings is identified, providing an optimal design of buildings.

The main objectives of the present work are to investigate the hydraulic characteristics of the dam discharge flow and its impact downstream. Building information modeling technology is adopted to generate the terrain entity and hydraulic structures. The calculation of the dam discharge and flood routing simulation is achieved by employing Reynolds-Averaged Navier-Stokes equations with the RNG k- eddy viscosity model for its turbulence closure, as well as the Volume of Fluid method. An urban flood experiment and the field measurement records are utilized and validated the model accuracy. The flow field is obtained to assess the dam working conditions under different water levels. The results show that the maximum downstream flow depth, the maximum discharge capacity and the hydraulic jump length under normal water level is 18.6 m, 13,800 m3/s, and 108 m, respectively. The dam satisfies the safety demand under different water levels but close attention should be paid to the dam foundation, especially around the incident points of the discharge flow. Complex turbulent flow patterns, including collision, reflection, and vortices, are captured by three-dimensional simulation. The numerical simulation can assist the reservoir management vividly, so as to guarantee the stability of the dam operation.

The flood caused by a dam-break event generally contains a large amount of energy, and it can be destructive to the downstream buildings and structures. In the present study, the evolution of a dam-break flood and its impact pressure on a structure are considered by performing a numerical simulation. A laboratory experiment is first performed to validate the numerical model. Subsequently, simulations are performed to investigate the impact pressure of the dam-break flood on a solitary structure in the downstream region. The flow regime near the structure, temporal variations and distributions of the impact pressure on the structure, and effects of the initial reservoir water depth on the peak pressures are discussed. It is observed that the profiles of the water surface at the cross-section upstream and downstream of the structure are completely different. In addition, the surface velocity distributions are significantly different. The structure suffers a large instantaneous impact pressure when the flood water first contacts the structure, and the value of this pressure can reach 1.5–3.0 times that of the maximum pressure after the first impact. The instantaneous impact pressure is proportional to the initial reservoir water depth. The distribution of the peak pressure acting on the wall on the upstream side of the structure is nonlinear in both the horizontal and vertical directions.

Intense storm surge can lead to severe coastal floods. Flood inundation simulation is useful to identify areas that are most vulnerable to severe storm surges and to address potential flooding hazards. In this paper, both 2D and 3D hydrodynamic models are built separately to quantify the flood danger to a coastal city. A digital city model is generated by integrating building information modeling (BIM) and geographic information systems (GIS) technology based on digital aerial photogrammetry for the 3D hydrodynamic model. The results reveal that 2D hydrodynamic assumptions and approximations weaken if the vertical fluctuations are enormous, especially in urban environments. In comparison, a 3D model coupled with high-resolution topographic data can provide a more realistic and accurate result for the complex flow field. Furthermore, a comparison between using the digital city model and a standard digital elevation model (DEM) in a 3D model has been conducted. The flood inundation is simulated step-wise using the standard DEM, while the wave front propagates in a more realistic manner based on high-resolution topography data. Thus, a 3D hydrodynamic model coupled with the digital city model is recommended for urban flood simulation, which is promising to improve the ability of flood prediction and prevention.