Search Results (15)

With accelerated urbanization and escalating severity and frequency of extreme precipitation events, urban flooding has become increasingly prevalent, posing significant threats to human life and economic well-being. Given the scarcity of land resources, the integration of flood mitigation measures into public spaces, particularly in the form of multi-functional storage spaces (MFSs), emerges as an effective strategy for rainwater retention. To assess the efficacy of MFS, a coupled modeling framework, comprising the Storm Water Management Model (SWMM) and the LISFLOOD-FP hydrodynamic model, was employed in the study. Under rainstorms of varying design characterized by diverse return periods and peak rainfall intensity locations, the study simulated and compared the performance of low-impact-development (LID) strategies, MFS, and a combined approach utilizing both LID and MFS (ALL). The findings indicate that the performance of these strategies significantly varies under diverse rainfall intensity and peak coefficients. Specifically, as the return period increases, the reduction rates of the three projects gradually diminish. For lower return periods (P ≤ 10), the order of reduction effectiveness was LID < MFS < ALL; whereas, for higher return periods (P ≥ 20), the order was LID < ALL < MFS. LID exhibited superior performance under low return periods with an early-peak-rainfall position, and under high return periods with a mid-peak position. MFS and the ALL approach achieved the most significant reduction effects under early-peak-rainfall positions. LID may introduce uncertainties into the performance of MFS during rainfall events with higher return periods and peak coefficients. The outcomes of this research offer valuable technical insights that can inform urban planning strategies and enhance the design of flood mitigation measures in urban environments. Full article

The present study investigates different combinations and methods for estimating the extreme Total Water Level (TWL) and its implications for predicting flood extension caused by coastal storms. This study analyses various TWL components and approaches and assesses how different methodologies alter flood predictions, with implications for warning systems and emergency responses. Using different combinations of individual TWL components, flood extension simulations were conducted using a hydrodynamic model in the Volano Beach area (Emilia-Romagna, Italy). A real coastal storm event was used as a reference for comparison. The findings indicate that the selection of individual TWL components and calculation methods significantly impacts flood extension predictions. The approaches, which involve calculating extreme values from a combined time series or the water level time series plus the extreme value of wave setup, yield the most realistic results, excluding the runup component. In comparison, the other combinations overestimate the flood. Incorporating hydromorphological models like XBeach could enhance the accuracy of runup estimations and improve the overall method reliability. Despite limitations such as runup estimation and the use of generic regional parameters, this study underscores the importance of the TWL combination selection in accurately predicting flood extents, emphasising the need for context-specific adaptations in environmental contexts. Full article

Cities with sloping terrain are more susceptible to flooding during heavy rains. Traditional hydraulic models struggle to meet computational demands when addressing such emergencies. This study presented an integration of the one-dimensional Storm Water Management Model (SWMM) and the two-dimensional LISFLOOD-FP model, where the head difference at coupled manholes between the two models functioned as the connection. Based on its calculation results, this study extracted the characteristic parameters of the rainfall data, simplified the SVR calculation method and developed a high-efficiency solution for determining the maximum ponding depth. The cost time of this model was stable at approximately 1.0 min, 95% faster compared to the one from the mechanism model for 5 h simulation under the same working conditions. By conducting this case study in Jiujiang, China, the feasibility of this algorithm was well demonstrated. Full article

Social activities have a significant impact on the rainstorm flood disaster risk. It is crucial to explore the dynamic changes of urban rainstorm flood disaster risk caused by crowd activities. In this study, a risk simulation method of urban rainstorm flood disasters is proposed, composed of an urban rainstorm flood model based on SWMM and LISFLOOD-FP and a crowd activities model based on ABM. Taking the Futian District of Shenzhen as an example, the temporal and spatial changes in rainstorm flood disaster risk for buildings and roads are analyzed under three scenarios: midnight, morning peak, and evening peak. The results show that: (1) Although the overall risk of urban rainstorm flood disasters increases as the inundation area expands, the average risks of roads and buildings increase rapidly and then stabilize during the morning peak due to commuting activities, while the average risk of roads remains high level during the evening peak due to commuting activities, while; (2) The risk of urban rainstorm flood varies significantly at different time periods. The average risk of buildings is the largest during the morning peak, about twice that during the evening peak. The number of high-risk roads during the evening peak is much higher than in the morning peak, and both buildings and roads have the least risk during midnight; (3) The spatial distribution of urban rainstorm flood disaster risk changes with the crowd activities, shifting from residential areas to industrial areas, schools, shopping malls, etc., during the morning peak, while the evening peak shows the reverse. Full article

Urban flood modeling usually involves simulating drainage network runoff and overland flow. We describe a method for urban pluvial flood modeling by coupling the stormwater management model (SWMM) with a raster-based 2D hydrodynamic model, which is based on a simplified form of the shallow water equations. Then, the method is applied to a highly urbanized area in Nanjing City, China. The elevation of the raster-based 2D hydrodynamic model shows that the raster-based model has comparable capabilities to LISFLOOD-FP for surface flood modeling. The calibration and validation results of the coupled model show that the method is reliable. Moreover, simulation results under the six rainfall return periods, which include 1-, 5-, 10-, 20-, 50-, and 100-year return periods show that node overflow, water depth, and flooding area increase proportionately as the intensity of rainfall increases. Therefore, the coupling model provides a simplified and intuitive method for urban pluvial flood modeling, which can be used to detect flood-sensitive areas and elevate the capacity of urban drainage networks for urban pluvial flooding. Full article

Flooding events are becoming more frequent and the negative impacts that they are causing globally are very significant. Current predictions have confirmed that conditions linked with future climate scenarios are worsening; therefore, there is a strong need to improve flood risk modeling and to develop innovative approaches to tackle this issue. However, the numerical tools available nowadays (commercial and freeware) need essential data for calibration and validation purposes and, regrettably, this cannot always be provided in every country for dissimilar reasons. This work aims to examine the quality and capabilities of open-source numerical flood modeling tools and their data preparation process in situations where calibration datasets may be of poor quality or not available at all. For this purpose, EPA’s Storm Water Management Model (SWMM) was selected to investigate 1D modeling and LISFLOOD-FP was chosen for 2D modeling. The simulation results obtained with freeware products showed that both models are reasonably capable of detecting flood features such as critical points, flooding extent, and water depth. However, although working with them is more challenging than working with commercial products, the quality of the results relative to the reference map was acceptable. Therefore, this study demonstrated that LISFLOOD-FP and SWMM can cope with the lack of these variables as a starting point and has provided steps to undertake to generate reliable results for the need required, which is the estimation of the impacts of flooding events and the likelihood of their occurrence. Full article

In this paper, a network-flow model was constructed to simulate the performance of interdependent critical infrastructure systems during flood hazards, when there is shortage of commodities such as electrical power and water. The model enabled us to control the distribution of commodities among different consumers whose demand cannot be fully met. Incorporating time-variance in the model allowed for evaluating the time evolution of the functional level of the infrastructure systems and quantifying their resilience. As a demonstration of the model’s capability, the network model was coupled with a raster-based hydraulic flooding model in the way of Monte Carlo simulations. It was then used to investigate the cascading effects of flood-related failures of individual infrastructure assets on the performance of the critical infrastructure systems of a coastal community under different flooding scenarios and future climate impacts. The coupled modelling framework is essential for correctly assessing the interdependences and cascading effects in the infrastructure systems in the case of flood hazards. While in the considered example, the extent of inundation becomes less severe with a changing climate, the risk to infrastructure does not recede because of the cascading effects. This behaviour could not be captured by the flood model alone. Full article

Chinese coastal topography has changed significantly over the last two decades due to human actions such as the development of extensive land reclamation projects. Newly-reclaimed lands typically have low elevations (<10 m) and often experience severe ground subsidence. These conditions, combined with the more frequent occurrence of extreme sea-level events amplified by global climate change, lead to an increased risk of flooding of coastal regions. This work focuses on twelve Chinese coastal areas that underwent significant changes from 2000 to 2015 in their environments, correlated to relevant land reclamation projects. First, the ground changes between 2000 and 2015 were roughly computed by comparing the TanDEM-X and the Shuttle Radar Topography Mission (SRTM) digital elevation models of the investigated areas. These results indicate that six of the analyzed coastal zones have reclaimed more than 200 km² of new lands from 2000 to 2015, with five of them in northern China. Second, we focused specifically on the city of Shanghai, and characterized the risk of flood in this area. To this purpose, two independent sets of synthetic aperture radar (SAR) data collected at the X- and C-band through the COSMO-SkyMed (CSK) and the European Copernicus Sentinel-1 (S-1) sensors were exploited. We assumed that the still extreme seawater depth is chi-square distributed, and estimated the probability of waves overtopping the coast. We also evaluated the impact on the territory of potential extreme flood events by counting the number of very-coherent objects (at most anthropic, such as buildings and public infrastructures) that could be seriously affected by a flood. To forecast possible inundation patterns, we used the LISFLOOD-FP hydrodynamic model. Assuming that an extreme event destroyed a given sector of the coastline, we finally computed the extent of the flooded areas and quantified its impact in terms of coherent structures potentially damaged by the inundation. Experimental results showed that two coastline segments located in the southern districts of Shanghai, where the seawalls height is lower, had the highest probability of wave overtopping and the most significant density of coherent objects potentially subjected to severe flood impacts. Full article

In this study, a new approach for rainfall spatial interpolation in the Luxembourgian case study is introduced. The method used here is based on a Fuzzy C-Means (FCM) clustering method. In a typical FCM procedure, there are a lot of available data and each data point belongs to a cluster, with a membership degree [0 1]. On the other hand, in our methodology, the center of clusters is determined first and then random data are generated around cluster centers. Therefore, this approach is called inverse FCM (i-FCM). In order to calibrate and validate the new spatial interpolation method, seven rain gauges in Luxembourg, Germany and France (three for calibration and four for validation) with more than 10 years of measured data were used and consequently, the rainfall for ungauged locations was estimated. The results show that the i-FCM method can be applied with acceptable accuracy in validation rain gauges with values for R² and RMSE of (0.94–0.98) and (9–14 mm), respectively, on a monthly time scale and (0.86–0.89) and (1.67–2 mm) on a daily time scale. In the following, the maximum daily rainfall return periods (10, 25, 50 and 100 years) were calculated using a two-parameter Weibull distribution. Finally, the LISFLOOD FP flood model was used to generate flood hazard maps in Dudelange, Luxembourg with the aim to demonstrate a practical application of the estimated local rainfall return periods in an urban area. Full article

The assessment of populations affected by urban flooding is crucial for flood prevention and mitigation but is highly influenced by the accuracy of population datasets. The population distribution is related to buildings during the urban floods, so assessing the population at the building scale is more rational for the urban floods, which is possible due to the abundance of multi-source data and advances in GIS technology. Therefore, this study assesses the populations affected by urban floods through population mapping at the building scale using highly correlated point of interest (POI) data. The population distribution is first mapped by downscaling the grid-based WorldPop population data to the building scale. Then, the population affected by urban floods is estimated by superimposing the population data sets onto flood areas, with flooding simulated by the LISFLOOD-FP hydrodynamic model. Finally, the proposed method is applied to Lishui City in southeast China. The results show that the population affected by urban floods is significantly reduced for different rainstorm scenarios when using the building-scale population instead of WorldPop. In certain areas, populations not captured by WorldPop can be identified using the building-scale population. This study provides a new method for estimating populations affected by urban flooding. Full article

Combination of uncertainties in water level and wave height predictions for extreme storms can result in unacceptable levels of error, rendering flood hazard assessment frameworks less useful. A 2D inundation model, LISFLOOD-FP, was used to quantify sensitivity of flooding to uncertainty in coastal hazard conditions and method used to force the coastal boundary of the model. It is shown that flood inundation is more sensitive to small changes in coastal hazard conditions due to the setup of the regional model, than the approach used to apply these conditions as boundary forcing. Once the threshold for flooding is exceeded, a few centimetres increase in combined water level and wave height increases both the inundation and consequent damage costs. Improved quantification of uncertainty in inundation assessments can aid long-term coastal flood hazard mitigation and adaptation strategies, to increase confidence in knowledge of how coastlines will respond to future changes in sea-level. Full article

Vulnerability assessment is an essential tool in mitigating the impact of urban flooding. To date, most flood vulnerability research has focused on one type of flood, such as a pluvial or fluvial flood. However, cities can suffer from urban flooding for several reasons, such as precipitation and river levee overtopping. Therefore, a vulnerability assessment considering different types of floods (pluvial floods, fluvial floods, and compound flooding induced by both rainfall and river overtopping) was conducted in this study. First, a coupled urban flood model, considering both overland and sewer network flow, was developed using the storm water management model (SWMM) and LISFLOOD-FP model to simulate the different types of flood and applied to Lishui, China. Then, the results of the flood modeling were combined with a vulnerability curve to obtain the potential impact of flooding on different land-use classes. The results indicated that different types of floods could have different influence areas and result in various degrees of flood vulnerability for different land-use classes. The results also suggest that urban flood vulnerability can be underestimated due to a lack of consideration of the full flood-induced factors. Full article

Levee failures due to floods often cause considerable economic damage and life losses in inundated dike-protected areas, and significantly change flood hazard upstream and downstream the breach location during the event. We present a new extension for the LISFLOOD-FP hydrodynamic model which allows levee breaching along embankments in fully two-dimensional (2D) mode. Our extension allows for breach simulations in 2D structured grid hydrodynamic models at different scales and for different hydraulic loads in a computationally efficient manner. A series of tests performed on synthetic and historic events of different scale and magnitude show that the breaching module is numerically stable and reliable. We simulated breaches on synthetic terrain using unsteady flow as an upstream boundary condition and compared the outcomes with an identical setup of a full-momentum 2D solver. The synthetic tests showed that differences in the maximum flow through the breach between the two models were less than 1%, while for a small-scale flood event on the Secchia River (Italy), it was underestimated by 7% compared to a reference study. A large scale extreme event simulation on the Po River (Italy) resulted in 83% accuracy (critical success index). Full article

In this paper, we assess the flood mapping capabilities of the X-band Synthetic Aperture Radar (SAR) imagery acquired by the bistatic pair TanDEM-X/TerraSAR-X (TDX/TSX). The main objective is to investigate the added value of the bistatic TDX/TSX Interferometric Synthetic Aperture Radar (InSAR) coherence in addition to the SAR backscatter in the context of inundation mapping. As a classifier, we consider a Random Forest (RF) classification scheme using TDX/TSX SAR intensities and their bistatic InSAR coherence to extract the flood extent map. To evaluate the classification results and as no “ground truth” was available at the SAR data acquisition time, we set up a LISFLOOD-FP hydraulic model for simulating the temporal evolution of the flood water. The flood map simulated by the model shows good performances with an Overall Accuracy (OA) of $97.92\%$ and a Critical Success Index (CSI) of $94.01\%$ . The SAR-derived flood map is then compared to the LISFLOOD-FP extent map simulated at the SAR data acquisition time. As a test case, we consider the flooding event of the Richelieu River that occurred in the Montérégie region of Quebec (Canada) from April to June 2011. Experimental results highlight the potential of the bistatic InSAR coherence for more accurate flood mapping in a complex landscape with urban and vegetation areas. The classification results of the SAR-derived flood map with respect to the LISFLOOD-FP flood map reach an OA of $78.65\%$ and a Precision of $82.08\%$ when integrating the bistatic InSAR coherence. These classification OA and Precision values are $69.63\%$ and $64.52\%$ , respectively, using only the TDX/TSX SAR intensity. Full article

Human populations are not static or uniformly distributed across space and time. This consideration has a notable impact on natural hazard analyses which seek to determine population exposure and risk. This paper focuses on the coupling of population and environmental models to address the effect of seasonally varying populations on exposure to flood risk. A spatiotemporal population modelling tool, SurfaceBuilder247, has been combined with LISFLOOD-FP flood inundation model outputs for a study area centred on the coastal resort town of St Austell, Cornwall, United Kingdom (UK). Results indicate strong seasonal cycles in populations and their exposure to flood hazard which are not accounted for in traditional population datasets and flood hazard assessments. Therefore, this paper identifies and demonstrates considerable enhancements to the current handling of spatiotemporal population variation within hazard exposure assessment and disaster risk management. Full article