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Flood events are the most commonly occurring natural disaster, with over 5 million properties at risk in the UK alone. Changes in the global climate are expected to increase the frequency and magnitude of flood events. Flood hazard assessments, using climate projections as input, guide policy decisions and engineering projects to reduce the impact of large return period events. Probabilistic flood modeling is required to take into account uncertainties in climate model projections. However, the dichotomous relationship between probabilistic modeling, computational cost and model resolution limits the applicability of such techniques. This paper examines improvements to traditional Monte Carlo methods using Latin hypercube sampling (LHS) and Multi‐level Monte Carlo (MLMC) to quantify the uncertainty in flood extent resulting from input hydrograph uncertainty. The results demonstrate that MLMC is a more efficient modeling strategy than current methods (i.e., traditional Monte Carlo) with high resolution outputs produced in less time than previously possible. The novel application of MLMC technique to three Scottish case studies, demonstrating a variety of river characteristics, domain sizes and computational costs, using a high resolution 5 m grid resulted in a 99.2% reduction in computational cost compared to traditional Monte Carlo methods and up to 2.3 times speedup over Latin Hypercube Sampling. Key Points: Multi‐level Monte Carlo (MLMC) reduces the computational cost by 99.2% over traditional full Monte Carlo; tested across a range of case studiesProbabilistic flood hazard assessment accuracy can be increased by incorporating higher resolution models with minimal increase in costsMLMC allows realistic uncertainty quantification at previously unfeasible 5 m grid resolution, yielding converged estimates of flooded area [ABSTRACT FROM AUTHOR]

A wide range of nature‐based solutions for flood hazard management work by storing and slowing flow within catchments, and therefore, there is a need to identify the optimal locations for implementing these solutions. This paper presents a relative scoring‐based mapping of the likely locations that contribute to the flood peak. Targeting flow reduction and attenuating mitigation actions in these locations can be an effective way to reduce flood damages at impact points downstream. The presented tool, SCIMAP‐Flood, uses information on land cover, hydrological connectivity, flood generating rainfall patterns and hydrological travel time distributions to impacted communities to find the potential source areas of flood waters. The importance of each location in the catchment is weighted based on its contribution to the flood hazard at each of the downstream impact points. In the example application, SCIMAP‐Flood is applied at a 5‐m grid resolution for the River Eden catchment, Cumbria, England, to provide sub‐field scale information at the landscape extent. Therefore, the tool can identify sub‐catchments where more detailed work can test different mitigation measures. [ABSTRACT FROM AUTHOR]

Among several devastating natural hazards, flooding is a common and serious threat to society causing huge loss of lives, properties, and infrastructure throughout the world. The intensity and frequency of this extreme weather event are expected to increase due to significant changes in the present‐day climate and land use and land cover (LULC) pattern. India has a very systematic and organized structural program and policies but lacks proper implementations, and adverse effect of climate change and the extreme event goes on in society. This paper is an analysis of floods in India and hazards due to climate change and LULC change patterns. Three models, namely "Eco‐biogeography‐based optimization (EBO), Random forest (RF), and Support vector machine (SVM)" were used to obtain the final output to prepare a "Flood susceptibility map". The result was validated through the "Receiver operating characteristics (ROC)" with "Area under curve (AUC)" values. The future rainfall scenario has been estimated by considering the "General circulation models" through different "shared socioeconomic pathways (SSPs)". The values of AUC are 0.915 (EBO), 0.887 (RF), and 0.869 (SVM), respectively. After consideration of different SSPs, the result shows that there is an increasing tendency of flood hazards in the projected period. Among all the employed modelling approaches, the EBO model has notable potential in delineating the possible flood‐prone regions for effective flood planning and management. Decision‐makers can benefit from country‐specific information and regional planner to implement sustainable and long‐term measures to overcome this type of hazardous situation. [ABSTRACT FROM AUTHOR]

Probabilistic methods are widely adopted for residual flood hazard assessment in flood‐prone areas protected by levees. Such methods can consider various sources of uncertainty, including breach location and flood event characteristics, and allow for the quantification of the result confidence. However, the possible occurrence of multiple levee breaches during the same flood event is usually disregarded. This paper presents a probabilistic method based on levee fragility functions and basic probability rules to estimate the probability of selected breach scenarios, including multiple breaching events. The flood hazard classification is based on inundation variables calculated for flood events of different return periods. A combined 1D‐2D hydrodynamic model is used for flood simulations. Probabilistic inundation extent maps and probabilistic flood hazard level maps are then created. Finally, probabilistic flood hazard estimates are summarized in a map of a suitable central tendency of the hazard level, coupled with a map of the Shannon entropy as an uncertainty indicator. This pair of statistical maps provides concise and effective information on a reference flood hazard along with the associated uncertainty. The method was applied to a region located along the middle reach of the Po River (northern Italy). Comparable central flood hazard estimates are obtained for the two sets of breaching events including or not including multiple breaches, with higher uncertainty if multiple breaches are considered. This result highlights the importance of considering multiple breaching events in flood risk management. Key Points: A probabilistic method is presented for flood hazard mapping in flood‐prone areas protected by levees, considering multiple breachesBreach scenario probabilities for selected return periods are estimated using levee fragility functions and basic probability rulesA "central" hazard level map and an entropy index map are introduced to summarize probabilistic information on flood hazard [ABSTRACT FROM AUTHOR]

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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. [ABSTRACT FROM AUTHOR]

Land use changes, landscape modifications and changing climate have resulted in local to regional flood risk increases in recent decades. As an alternative to traditional engineering approaches, there has been a movement towards catchment‐based flood risk management, a subset of which is natural flood management (NFM). NFM aims to enhance flood resilience through the slowing and storing of runoff and flow, based on the restoration and augmentation of hydrological and morphological catchment features. However, despite research highlighting their potential benefits, there is a limited quantity of robust and science‐based empirical evidence on how these structures function in the landscape and their efficacy in reducing flood hazards. To address this knowledge gap and contribute to the growing NFM evidence base, this study evaluates the efficacy of offline water storage ponds for flow attenuation. Two contrasting pond sites in the Tone and Parrett catchment headwaters (SW‐England) were monitored from April 2018 to December 2020 for channel flow, pond volume, and rainfall. Field‐scale, high resolution (1.61 cm spatial support) digital elevation models from Structure‐from‐Motion and manual surveys were collected to quantify pond dynamics and connectivity. A comprehensive, storm definition methodology was developed for event separation, to enable quantification of the impact of pond behaviour on stream flow, across storm hydrographs. Results show that where offline ponds function as designed, with direct pond filling from the channel, peak flow attenuation can reach 7% (maximum event AEP of 83%). Smaller events, where pond filling occurs directly from rainfall or runoff display only a maximum of 3% peak flow reduction (event AEP from 83% –>99%). The ability of ponds to attenuate flow is heavily reliant on sufficient structural conditions for ponds to fill directly from the channel and to drain slowly following event peaks. This study provides an empirical database for future NFM applications, including key criteria for future design and for use as observational data in modelling applications, by upscaling the efficacy of ponds to reduce flood impacts at larger scales. [ABSTRACT FROM AUTHOR]

We demonstrate that long‐term tidally induced changes in extreme sea levels affect estimates of major flood hazard in a predictable way. Long‐term variations in tides due to the 4.4 and 18.6‐year cycles influence extreme sea levels at 380 global tide gauges out of a total of 581 analyzed. Results show coherent regions where the amplitudes of the modulations are particularly relevant in the 100‐year return sea level, reaching more than 20 cm in some regions (western Europe, north Australia, and Singapore). We identify locations that are currently in a positive phase of the modulation and therefore at a higher risk of flooding, as well as when (year) the next peak of the long‐term tidal modulations is expected to occur. The timing of the peak of the modulation is spatially coherent and influenced by the relative importance of each cycle (4.4 or 18.6‐year) over the total amplitude. An evaluation of four locations suggests that the potentially flooded area in a 100‐year event can vary up to ∼45% (in Boston) as a result of the long‐term tidal cycles; however, the flooded area varies due to local topography and tidal characteristics (6%–13%). We conclude that tidally modulated changes in extreme sea levels can alter the potentially inundated area in a 100‐year event and that the traditional, fixed 100‐year floodplain is inadequate for describing coastal flood risk, even without considering sea‐level rise. Plain Language Summary: Interannual and decadal (long‐term) variations in tides modulate extreme sea levels, increasing the risk of flooding at specific and predictable times. Here, we use a data set of 581 tide gauges to estimate the magnitude of the long‐term tidally induced changes in extreme sea levels as well as to identify the timing of the peak of the modulations. We find significant amplitudes of the long‐term tidal modulations in extreme water levels. We conclude that the long‐term modulations in tides influence the total inundation area and, therefore, they should be taken into account when assessing coastal vulnerability. Key Points: Long‐term tidal cycles (4.4 and 18.6‐year) modulate extreme sea levels and affect estimates of flood riskThe timing of the peak of both modulations is influenced by the relative importance of each cycle over the total amplitudeTidally induced changes in extreme sea levels affect estimates of total inundation area [ABSTRACT FROM AUTHOR]

The identification of flood prone areas is essential for a range of engineering, risk reduction and research applications. Here, we describe a combined hydrological and hydraulic modelling approach for the assessment of flood‐prone areas and we present the results obtained over the Po river (Northern Italy). Runoff and river discharges are calculated through the hydrological model CHyM driven by GRIPHO, a new precipitation dataset for Italy. River flow data are used to obtain flood hydrographs for the CA2D hydraulic model, which calculates flood hazard maps at a resolution of 90 m. Flood simulations are run over a re‐shaped HydroSHEDS digital elevation model that includes information of the channel geometry. Modeled flood hydrographs are compared with observed data for a choice of gauging stations, showing a good performance of the CHyM model. We validate the flood hazard maps against observed flood events and official hazard maps. For high return periods, modelled maps can correctly identify up to 67% of the flood extent, both on the Po River and on smaller tributaries, while performances are more variable for lower return periods. Overall, the proposed approach suggests a strong potential for further applications, such as flood hazard assessment under future climate scenarios. [ABSTRACT FROM AUTHOR]

Understanding and modelling pluvial flood patterns is pivotal for the estimation of flood impacts in urban areas, especially in a climate change perspective. However, urban flood modelling under climate change conditions poses several challenges. On one hand, the identification and collection of climate change data suitable for flood‐related evaluations requires consistent computational and scientific effort. On the other hand, large difficulties can arise in the reproduction of the rainfall‐runoff transformation process in cases when only little information about the subsurface processes is known. In this perspective, a simplified approach is proposed to address the challenges regarding the quantitative estimation of climate change effects on urban flooding for real case applications. The approach is defined as "bottom‐up" because climate change information is not included in flood modelling, but it is only invoked for the interpretation of results. In other words, the challenge faced in this work is the development of a modelling strategy that is expeditious, because it does not require flood simulations for future rainfall scenarios, but only under current climate conditions, thus reducing the overall computational effort; and it is flexible, because results can be easily updated once new climate change data, scenarios or methods become available, without the need of additional flood simulations. To simulate real case applications, the approach is tested for a scenario analysis, where different return periods and hyetograph shapes are used as input for urban inundation modelling in Naples, Italy. The approach can support public and private stakeholders, such as land administrators and water systems managers; moreover, it represents a valuable and effective basis for climate change risk communication strategies. [ABSTRACT FROM AUTHOR]

Bridges are in direct interaction with the environment and thus are exposed to various natural hazards such as earthquakes and floods, that may result in severe damage and substantial direct and indirect losses. The multiple hazard events may be subsequent single events (e.g., a flood event followed by an earthquake) or combined multi‐hazard events (e.g., cascading ground failure event after an earthquake). The effect of multiple hazards on bridge fragility is related to the damage level of the bridge components and the associated failure mechanisms that may compromise the roadway network functionality. The scope of this work is to propose an approach for the multiple‐hazard assessment of bridges considering subsequent events and different damage scenarios of critical bridge components, i.e. piers, bearings and abutments. Therefore, the effect of the damage level of critical bridge components and their interdependence on the fragility assessment for subsequent hazard events is investigated. Different damage scenarios and hazard sequences are studied, providing insight into the damage mechanisms and the accumulation of damage. The approach is applied to the multiple hazard assessment of a case study typical riverine bridge in Greece and the results are comparatively discussed. [ABSTRACT FROM AUTHOR]