Coastal Flood risk assessment using ensemble multi-criteria decision-making with machine learning approaches.

Coastal areas are at a higher risk of flooding, and novel changes in the climate are induced to raise the sea level. Flood acceleration and frequency have increased recently because of unplanned infrastructural conveniences and anthropogenic activities. Therefore, the assessment of flood susceptibility mapping is considered the most significant flood management model. In this paper, flood susceptibility identification is performed by applying the innovative Multi-criteria decision-making model (MCDM) called Analytical Hierarchy Process (AHP) by ensembles with Support vector machine (AHP-SVM) and Decision Tree (AHP-DT). This model combines two Representation concentration pathway (RCP) scenarios such as RCP 2.6 & RCP 8.5. The factors influencing the coastal flooding in Bandar Abbas, Iran, identified through Flood susceptibility mapping. Multi-criteria decision-making (MCDM) has been applied to evaluate the Coastal flood conditioning factors, and ensemble machine learning (ML) approaches are employed for Coastal risk factor (CRF) prediction and classification. The statistical variances are measured through Friedman and Wilcoxon signed rank tests and statistical metrics such as Accuracy, sensitivity, and specificity. Among the models, AHP-DT obtained an improved AUC value of ROC as 0.95. After applying the ML models, the northern and western park of Raidak Basin River recognises very low and low flood susceptibility because of their topographic characteristics. The eastern part of the middle section fell very high and high CFSM. Observed from this result analysis, the people living nearer to the coastline are distributed by the low to medium exposure in the region of the west and middle of the considered study area. The results of this study can help decision-makers take necessary risk reduction approaches in the high-risk flooding zones of the coastal system.

Heterogeneity of values for coastal flood risk management with nature-based solutions.

The purpose of this study was to understand preferences for different coastal flood protection measures and the factors that influence such preferences, to inform management and policy. The Discrete Choice Experiment applied to Wales residents revealed that there is willingness-to-pay for coastal flood protection, especially through Nature-based Solutions (NbS) including expanding saltmarsh area and increasing saltmarsh with high vegetation. The preference for NbS provides evidence for including specific coastal area targets in financial schemes initially aimed at other benefits from natural habitats, such as habitat creation for biodiversity. This joint action will maximise the benefits from NbS and ensure integrated and concerted efforts across, often disjointed, sectors. There were also high levels of heterogeneity for preferences in different groups of people. For instance, results support that direct flood experience and damage severity can give rise to behavioural intentions that support mitigation and adaptation measures. Findings also highlight how crucial environmental education and direct contact with the object of study are for securing support and buy-in for flood protection measures. This work is original in that it considers the different types of management for a habitat as NbS and the heterogeneity of preferences within a population. Results are significant in providing a basis for future NbS developments and in supporting flood risk policy and management.

Flooding trends and their impacts on coastal communities of Western Cape Province, South Africa.

Climate change-induced extreme weather events have been at their worst increase in the past decade (2010-2020) across Africa and globally. This has proved disruptive to global socio-economic activities. One of the challenges that has been faced in this regard is the increased coastal flooding of cities. This study examined the trends and impacts of coastal flooding in the Western Cape province of South Africa. Making use of archival climate data and primary data from key informants and field observations, it emerged that there is a statistically significant increase in the frequency of flooding and consequent human and economic losses from such in the coastal cities of the province. Flooding in urban areas of the Western Cape is a factor of human and natural factors ranging from extreme rainfall, usually caused by persistent cut off-lows, midlatitude cyclones, cold fronts and intense storms. Such floods become compounded by poor drainage caused by vegetative overgrowth on waterways and land pollution that can be traced to poor drainage maintenance. Clogging of waterways and drainage systems enhances the risk of flooding. Increased urbanisation, overpopulation in some areas and non-adherence to environmental laws results in both the affluent and poor settling on vulnerable ecosystems. These include coastal areas, estuaries, and waterways, and this worsens the risk of flooding. The study recommends a comprehensive approach to deal with factors that increase the risk of flooding as informed by the provisions of both the Sustainable Development Goals framework and the Sendai Framework for Disaster Risk Reduction 2015-2030 in a bid to de-risking human settlement in South Africa.

The Role of Intensifying Precipitation on Coastal River Flooding and Compound River-Storm Surge Events, Northeast Gulf of Mexico.

Destructive coastal floods are commonly increasing in frequency and may be caused by global precipitation intensification. Such connections through climate, watershed, and river processes are poorly understood because of complex interactions in transitional fluvial-marine environments where flooding is caused by rivers, marine storm surge, or both in compound events. To better understand river floods along the fluvial-marine transition, we study watersheds of the northeastern Gulf of Mexico using long-term observations. Results show intensifying precipitation decreased precipitation-discharge lag times, increasing river-flood frequency and the likelihood of compound events in fluvial-marine transitions. This reduction in lag time occurred when the Atlantic Multidecadal Oscillation and El Niño Southern Oscillation began strongly affecting river discharge through the advection of moist air, intensifying precipitation. Along the fluvial-marine transition, compound events were largest in inland reaches. However, for inland reaches, compound event water levels did not exceed the floods caused solely by river flooding, the largest flood hazard in these systems. Our results demonstrate precipitation and river discharge play critical roles in coastal flooding and will likely escalate flooding as the climate continues to warm and intensify precipitation.

A methodological framework for selecting an optimal sediment source within a littoral cell.

One of the most used measures to counteract coastal erosion is beach nourishment. It has advantages with respect to the use of rigid structures that sometimes entail non desired impacts on the surrounding areas. However, beach nourishments are often unsuccessful, requiring frequent refills due to the use of sediments that are not suitable. In this paper, a methodological framework for increasing the probability of success of beach nourishment projects is presented. First, this framework consists of detecting potential borrowing areas, by analysing shoreline evolution and selecting the stretch that shows a more accretive character. Once the borrowing area has been identified, several sand extraction options are defined. The beach response (in terms of erosion and flooding) to each sand extraction alternative is analysed by using two numerical models, which simulate the hydro-morphodynamic patterns in the studied area. The numerical model results allow to find the best extraction alternative, which is that producing the least impact in the borrow area. As an example, the methodology is applied to a stretch of the Catalan coast (NW Mediterranean) to illustrate its potential. The proposed methodology shows to be a useful tool for helping coastal managers to optimize their available resources.

Impact of climate change on New York City's coastal flood hazard: Increasing flood heights from the preindustrial to 2300 CE.

The flood hazard in New York City depends on both storm surges and rising sea levels. We combine modeled storm surges with probabilistic sea-level rise projections to assess future coastal inundation in New York City from the preindustrial era through 2300 CE. The storm surges are derived from large sets of synthetic tropical cyclones, downscaled from RCP8.5 simulations from three CMIP5 models. The sea-level rise projections account for potential partial collapse of the Antarctic ice sheet in assessing future coastal inundation. CMIP5 models indicate that there will be minimal change in storm-surge heights from 2010 to 2100 or 2300, because the predicted strengthening of the strongest storms will be compensated by storm tracks moving offshore at the latitude of New York City. However, projected sea-level rise causes overall flood heights associated with tropical cyclones in New York City in coming centuries to increase greatly compared with preindustrial or modern flood heights. For the various sea-level rise scenarios we consider, the 1-in-500-y flood event increases from 3.4 m above mean tidal level during 1970-2005 to 4.0-5.1 m above mean tidal level by 2080-2100 and ranges from 5.0-15.4 m above mean tidal level by 2280-2300. Further, we find that the return period of a 2.25-m flood has decreased from ∼500 y before 1800 to ∼25 y during 1970-2005 and further decreases to ∼5 y by 2030-2045 in 95% of our simulations. The 2.25-m flood height is permanently exceeded by 2280-2300 for scenarios that include Antarctica's potential partial collapse.

Compounding effects of sea level rise and fluvial flooding.

Sea level rise (SLR), a well-documented and urgent aspect of anthropogenic global warming, threatens population and assets located in low-lying coastal regions all around the world. Common flood hazard assessment practices typically account for one driver at a time (e.g., either fluvial flooding only or ocean flooding only), whereas coastal cities vulnerable to SLR are at risk for flooding from multiple drivers (e.g., extreme coastal high tide, storm surge, and river flow). Here, we propose a bivariate flood hazard assessment approach that accounts for compound flooding from river flow and coastal water level, and we show that a univariate approach may not appropriately characterize the flood hazard if there are compounding effects. Using copulas and bivariate dependence analysis, we also quantify the increases in failure probabilities for 2030 and 2050 caused by SLR under representative concentration pathways 4.5 and 8.5. Additionally, the increase in failure probability is shown to be strongly affected by compounding effects. The proposed failure probability method offers an innovative tool for assessing compounding flood hazards in a warming climate.

Assessing and managing design storm variability and projection uncertainty in a changing coastal environment.

Coastal urban infrastructure and water management programs are vulnerable to the impacts of long-term hydroclimatic changes and to the flooding and physical destruction of disruptive hurricanes and storm surge. Water resilience or, inversely, vulnerability depends on design specifications of the storm and inundation, against which water infrastructure and environmental assets are planned and operated. These design attributes are commonly derived from statistical modeling of historical measurements. Here we argue for the need to carefully examine the approach and associated design vulnerability in coastal areas because of the future hydroclimatic changes and large variability at local coastal watersheds. This study first shows significant spatiotemporal variations of design storm in the Chesapeake Bay of the eastern U.S. Atlantic coast, where the low-frequency high-intensity precipitations vary differently to the tropical cyclones and local orographic effects. Average and gust wind speed exhibited much greater spatial but far less temporal variability than the precipitation. It is noteworthy that these local variabilities are not fully described by the regional gridded precipitation used in CMIP5 climate downscaling and by NOAA's regional design guide Atlas-14. Up to 46.4% error in the gridded precipitation for the calibration period 1950-1999 is further exacerbated in the future design values by the ensemble of 132 CMIP5 projections. The total model projection error (δM) up to -61.8% primarily comes from the precipitation regionalization (δ1), climate downscaling (δ2), and a fraction from empirical data modeling (δE). Thus, a post-bias correction technique is necessary. The bias-corrected design wind speed for 10-yr to 30-yr storms has small changes <20% by the year 2100, but contains large spatial variations even for stations of close proximity. Bias-corrected design precipitations are characteristic of large spatial variability and a notable increase of 2-5 year precipitation in the future along western shores of the Lower and Middle Chesapeake Bay. All these accounts point to the potential vulnerability of water infrastructure and water program in coastal areas, when the hydrological design basis using regional values fails to account for significant spatiotemporal precipitation variations in local coastal watersheds.

Coastal flood damage and adaptation costs under 21st century sea-level rise.

Coastal flood damage and adaptation costs under 21st century sea-level rise are assessed on a global scale taking into account a wide range of uncertainties in continental topography data, population data, protection strategies, socioeconomic development and sea-level rise. Uncertainty in global mean and regional sea level was derived from four different climate models from the Coupled Model Intercomparison Project Phase 5, each combined with three land-ice scenarios based on the published range of contributions from ice sheets and glaciers. Without adaptation, 0.2-4.6% of global population is expected to be flooded annually in 2100 under 25-123 cm of global mean sea-level rise, with expected annual losses of 0.3-9.3% of global gross domestic product. Damages of this magnitude are very unlikely to be tolerated by society and adaptation will be widespread. The global costs of protecting the coast with dikes are significant with annual investment and maintenance costs of US$ 12-71 billion in 2100, but much smaller than the global cost of avoided damages even without accounting for indirect costs of damage to regional production supply. Flood damages by the end of this century are much more sensitive to the applied protection strategy than to variations in climate and socioeconomic scenarios as well as in physical data sources (topography and climate model). Our results emphasize the central role of long-term coastal adaptation strategies. These should also take into account that protecting large parts of the developed coast increases the risk of catastrophic consequences in the case of defense failure.

Household-Level Coastal Adaptation and Its Drivers: A Systematic Case Study Review.

Evidence-based information on household-level adaptation is an important element of integrated management of vulnerable coastal regions. A growing number of empirical studies deal with household-level adaptation at the coast in different regions. This article provides a systematic review of these studies. We analyze studies according to how households in different parts of the world are currently adapting, or how they are intending to adapt, and identify explanatory factors for adaptation behavior and intention. We find that households implement a broad range of adaptation measures and that adaptation behavior is explained by individual factors such as socioeconomic and cognitive variables, experience, and perceived responsibilities. Nonpersonal characteristics have also been used to explain adaptation behavior and intention but have not been extensively investigated. Few studies employ qualitative research methods and use inductive approaches as well as models stemming from behavioral economics. Our findings suggest that coastal risk management policies should communicate the efficacy of household-level adaptation, in addition to information about flood risk, in order to encourage coastal households in their adaptation activities. In this context, we discuss the role of resources and responsibility of households for their adaptation behavior. We describe the lessons learnt and formulate a research agenda on household-level adaptation to coastal flood risk. In practice, coastal risk management policies should further promote individually driven adaptation by integrating it in adaptation strategies and processes.

Hurricane Recovery and Ecological Resilience: Measuring the Impacts of Wetland Alteration Post Hurricane Ike on the Upper TX Coast.

Recovery after hurricane events encourages new development activities and allows reconstruction through the conversion of naturally occurring wetlands to other land uses. This research investigates the degree to which hurricane recovery activities in coastal communities are undermining the ability of these places to attenuate the impacts of future storm events. Specifically, it explores how and to what extent wetlands are being affected by the CWA Section 404 permitting program in the context of post-Hurricane Ike 2008 recovery. Wetland alteration patterns are examined by selecting a control group (Aransas and Brazoria counties with no hurricane impact) vs. study group (Chambers and Galveston counties with hurricane impact) research design with a pretest-posttest measurement analyzing the variables such as permit types, pre-post Ike permits, land cover classes, and within-outside the 100-year floodplain. Results show that permitting activities in study group have increased within the 100-year floodplain and palustrine wetlands continue to be lost compare to the control group. Simultaneously, post-Ike individual and nationwide permits increased in the Hurricane Ike impacted area. A binomial logistic regression model indicated that permits within the study group, undeveloped land cover class, and individual and nationwide permit type have a substantial effect on post-Ike permits, suggesting that post-Ike permits have significant impact on wetland losses. These findings indicate that recovery after the hurricane is compromising ecological resiliency in coastal communities. The study outcome may be applied to policy decisions in managing wetlands during a long-term recovery process to maintain natural function for future flood mitigation.

The use of cartographic modeling to assess the impacts of coastal flooding: a case study of Port Said Governorate, Egypt.

Low-set coastal areas are expected to aggravate inundation on account of sea level rise (SLR). The present study is planned to appraise the impacts of coastal flooding in Port Said city, Egypt by using remote sensing, GIS, and cartographic modeling techniques. To accomplish this scope, Landsat 8-OLI image dated 2016 and SRTM 1Arc-Second Digital Elevation Model (DEM) data were used. Landsat image was classified into seven land use and land cover (LULC) classes by using remote sensing and GIS's software. Different inundation scenarios 1.0, 2.0, and 3.0-m coastal elevation were used to figure the influence of SLR on the study area. Estimation of potential losses under SLR was made by overlaying the expected scenarios on land use. The inundation areas under the expected SLR scenarios of 1.0, 2.0, and 3.0 m were estimated at 827.49, 1072.67, and 1179.41 km2, respectively. In conclusion, this study demonstrated that expected coastal flooding scenarios will lead up to serious impacts on LULC classes and coastal features in the study area.

The role of nature-based infrastructure (NBI) in coastal resiliency planning: A literature review.

The use of nature-based infrastructure (NBI) has attracted increasing attention in the context of protection against coastal flooding. This review is focused on NBI approaches to improve coastal resilience in the face of extreme storm events, including hurricanes. We not only consider the role of NBI as a measure to protect people and property but also in the context of other ecological goods and services provided by tidal wetlands including production of fish and shellfish. Although the results of many studies suggest that populated areas protected by coastal marshes were less likely to experience damage when exposed to the full force of storm surge, it was absolutely critical to place the role of coastal wetlands into perspective by noting that while tidal marshes can reduce wave energy from low-to-moderate-energy storms, their capacity to substantially reduce storm surge remains poorly quantified. Moreover, although tidal marshes can reduce storm surge from fast moving storms, very large expanses of habitat are needed to be most effective, and for most urban settings, there is insufficient space to rely on nature-based risk reduction strategies alone. The success of a given NBI method is also context dependent on local conditions, with potentially confounding influences from substrate characteristics, topography, near shore bathymetry, distance from the shore and other physical factors and human drivers such as development patterns. Furthermore, it is important to better understand the strengths and weaknesses of newly developed NBI projects through rigorous evaluations and characterize the local specificities of the particular built and natural environments surrounding these coastal areas. In order for the relevant science to better inform policy, and assist in land-use challenges, scientists must clearly state the likelihood of success in a particular circumstance and set of conditions. We conclude that "caution is advised" before selecting a particular NBI method as there is no "one size fits all" solution to address site-specific conditions.

Flow-tub model: A modified bathtub flood model with hydraulic connectivity and path-based attenuation.

Global climate change and sea level rise are increasing the risks of flooding for coastal communities. Probabilistic coastal flood risk analysis at regional or global scales requires flood models with relatively low data requirements and low computational costs. Bathtub inundation models, which compute flood depth as the difference between water level and ground elevation, are well-suited for large-scale flood risk analysis. However, these models may overestimate floods because they do not capture some of the relevant underlying hydrodynamic processes that govern flood propagation on land. We present Flow-Tub, a modified bathtub inundation model that integrates two hydrodynamic processes to improve the accuracy of the bathtub inundation model while retaining computational efficiency: hydraulic connectivity and path-based attenuation.1.Hydraulic connectivity ensures that inundation is restricted to areas connected to the water source.2.Path-based attenuation ensures that the modeled flood water depths are reduced along the flow paths to represent the effects of surface friction and the temporary nature of storm surges. We validate the Flow-tub model against a hydrodynamic model. We also compare results of the bathtub model and the Flow-Tub model, highlighting the improved accuracy in the estimation of flood depths in the latter.

Comparison of wave overtopping estimation models for urban beaches. Towards an early warning system on the Basque coast.

This study compares the performance of different wave overtopping estimation models at urban beaches. The models selected for comparison are the Mase et al. (2013) and EurOtop parametric models and the XBeach process-based model in surfbeat and non-hydrostatic mode. Seven energetic storms are selected between 2015 and 2022 with offshore significant wave height ranging between 3 m and 8 m and peak period between 12 s and 20 s to perform the model comparison. The information required to run and validate the models (beach slope, shoreface shape, absence/presence of overtopping) was collected for each storm from coastal videometry. To account for the uncertainties derived from the incident waves randomness and the bathymetry shape when using the process-based model, a series of simulations with random seed boundary conditions were run over two different realistic profile shapes for each storm. The present study is a pilot study on the beach of Zarautz; however, it can be extended to other beaches of the Basque coast. Results indicate that while Mase et al. (2013) and EurOtop tend to reasonably predict the absence or presence of overtopping events, they tend to underestimate the hazard level at the beach of Zarautz. Additionally, the beach underwater profile shape can affect the process-based model performance at intermediate intensity storms and to a lesser extend during moderate storms. Finally, the hazard level at the beach of Zarautz varies significantly alongshore due to the configuration of the seawall, highlighting the need for local adaptation measures. Considering that there is no model that systematically performs better than others, it might be reasonable to use model assemble techniques to draw conclusions from a probabilistic perspective.

Socioeconomic impacts from coastal flooding in the 21st century China's coastal zone: A coupling analysis between coastal flood risk and socioeconomic development.

Coastal flooding due to sea level rise significantly affects socioeconomic development. The dynamic nature of coastal flood risk (CFR) and socioeconomic development level (SDL) leads to uncertainties in understanding their future interplay. This ambiguity challenges coastal nations in devising effective flood adaptation and coastal management strategies. This study quantitatively examines the expected GDP affected (EGA) and population affected (EPA) by coastal flooding in China's coastal zone (CCZ) from 2030 to 2100 under various climate scenarios (RCP2.6-SSP1, RCP4.5-SSP2, and RCP8.5-SSP5). The future SDL in CCZ is assessed using a method combining the analytic hierarchy process with entropy weight. The future CFR-SDL dynamic relationship is analyzed using the coupling coordination degree (CCD) model. The results reveal that in CCZ under the RCP2.6-SSP1, RCP4.5-SSP2, and RCP8.5-SSP5 scenarios: by 2100, the EGA and EPA will reach $814.90 billion & 6.17 million people, $828.16 billion & 7.63 million people, and $1568.83 billion & 8.05 million people, respectively, where the coastal cities in Jiangsu and Guangdong provinces will face more obvious risks of socioeconomic losses; The total area in the CCZ at "Very high" and "High" level of socioeconomic development by 2100 is projected to reach 11.33 × 103 km2, 12.86 × 103 km2, and 15.82 × 103 km2, respectively, with the Pearl River Delta, Yangtze River Delta, and Tianjin-Hebei remaining pivotal for CCZ's socioeconomic growth. Cities such as Lianyungang, Jiaxing, Shenzhen, Dongguan, and Foshan show notable CCD characteristics, and addressing the trade-off between SDL and CFR is crucial in achieving sustainable development. This study highlights the potential socioeconomic impacts of coastal flooding and emphasizes the importance of considering the interrelationship between CFR and SDL when developing coastal flood adaptation policies.

Wind and rain compound with tides to cause frequent and unexpected coastal floods.

With sea-level rise, flooding in coastal communities is now common during the highest high tides. Floods also occur at normal tidal levels when rainfall overcomes stormwater infrastructure that is partially submerged by tides. Data describing this type of compound flooding is scarce and, therefore, it is unclear how often these floods occur and the extent to which non-tidal factors contribute to flooding. We combine measurements of flooding on roads and within storm drains with a numerical model to examine processes that contribute to flooding in Carolina Beach, NC, USA - a community that chronically floods outside of extreme storms despite flood mitigation infrastructure to combat tidal flooding. Of the 43 non-storm floods we measured during a year-long study period, one-third were unexpected based on the tidal threshold used by the community for flood monitoring. We introduce a novel model coupling between an ocean-scale hydrodynamic model (ADCIRC) and a community-scale surface water and pipe flow model (3Di) to quantify contributions from multiple flood drivers. Accounting for the compounding effects of tides, wind, and rain increases flood water levels by up to 0.4 m compared to simulations that include only tides. Setup from sustained (non-storm) regional winds causes deeper, longer, more extensive flooding during the highest high tides and can cause floods on days when flooding would not have occurred due to tides alone. Rainfall also contributes to unexpected floods; because tides submerge stormwater outfalls on a daily basis, even minor rainstorms lead to flooding as runoff has nowhere to drain. As a particularly low-lying coastal community, Carolina Beach provides a glimpse into future challenges that coastal communities worldwide will face in predicting, preparing for, and adapting to increasingly frequent flooding from compounding tidal and non-tidal drivers atop sea-level rise.

Ecosystem services at risk in Italy from coastal inundation under extreme sea level scenarios up to 2050: A spatially resolved approach supporting climate change adaptation.

According to the latest projections of the Intergovernmental Panel on Climate Change, at the end of the century, coastal zones and low-lying ecosystems will be increasingly threatened by rising global mean sea levels. In order to support integrated coastal zone management and advance the basic "source-pathway-receptor-consequence" approach focused on traditional receptors (e.g., population, infrastructure, and economy), a novel risk framework is proposed able to evaluate potential risks of loss or degradation of ecosystem services (ESs) due to projected extreme sea level scenarios in the Italian coast. Three risk scenarios for the reference period (1969-2010) and future time frame up to 2050 under RCP4.5 and RCP8.5 are developed by integrating extreme water-level projections related to changing climate conditions, with vulnerability information about the topography, distance from coastlines, and presence of artificial protections. A risk assessment is then performed considering the potential effects of the spatial-temporal variability of inundations and land use on the supply level and spatial distribution of ESs. The results of the analysis are summarized into a spatially explicit risk index, useful to rank coastal areas more prone to ESs losses or degradation due to coastal inundation at the national scale. Overall, the Northern Adriatic coast is scored at high risk of ESs loss or degradation in the future scenario. Other small coastal strips with medium risk scores are the Eastern Puglia coast, Western Sardinia, and Tuscany's coast. The ESs Coastal Risk Index provides an easy-to-understand screening assessment that could support the prioritization of areas for coastal adaptation at the national scale. Moreover, this index allows the direct evaluation of the public value of ecosystems and supports more effective territorial planning and environmental management decisions. In particular, it could support the mainstreaming of ecosystem-based approaches (e.g., ecological engineering and green infrastructures) to mitigate the risks of climate change and extreme events while protecting ecosystems and biodiversity. Integr Environ Assess Manag 2022;18:1564-1577. © 2021 SETAC.

Integrating urban traffic models with coastal flood maps to quantify the resilience of traffic systems to episodic coastal flooding.

Sea level rise and coastal floods are disrupting coastal communities across the world. The impacts of coastal floods are magnified by the disruption of critical urban systems such as transportation. The flood-related closure of low-lying coastal roads and highways can increase travel time delays and accident risk. However, quantifying the flood-related disruption of the urban traffic system presents challenges. Traffic systems are complex and highly dynamic, where congestion resulting from road closures may propagate rapidly from one area to another. Prior studies identify flood-related road closures by spatially overlaying coastal flood maps onto road network models, but simplifications within the representation of the road network with respect to the coastline or creeks may lead to an incorrect identification of flooded roads. We identify three corrections to reduce potential biases in the identification of flooded roads: 1. We correct for the geometry of highways; 2. We correct for the elevation of bridges and highway overpasses; and 3. We identify and account for road-creek crossings. Accounting for these three corrections, we develop a methodology for accurately identifying flooded roads, improving our ability to quantify flood impacts on urban traffic systems and accident rates.

Uncertainty and Bias in Global to Regional Scale Assessments of Current and Future Coastal Flood Risk.

This study provides a literature-based comparative assessment of uncertainties and biases in global to world-regional scale assessments of current and future coastal flood risks, considering mean and extreme sea-level hazards, the propagation of these into the floodplain, people and coastal assets exposed, and their vulnerability. Globally, by far the largest bias is introduced by not considering human adaptation, which can lead to an overestimation of coastal flood risk in 2100 by up to factor 1300. But even when considering adaptation, uncertainties in how coastal societies will adapt to sea-level rise dominate with a factor of up to 27 all other uncertainties. Other large uncertainties that have been quantified globally are associated with socio-economic development (factors 2.3-5.8), digital elevation data (factors 1.2-3.8), ice sheet models (factor 1.6-3.8) and greenhouse gas emissions (factors 1.6-2.1). Local uncertainties that stand out but have not been quantified globally, relate to depth-damage functions, defense failure mechanisms, surge and wave heights in areas affected by tropical cyclones (in particular for large return periods), as well as nearshore interactions between mean sea-levels, storm surges, tides and waves. Advancing the state-of-the-art requires analyzing and reporting more comprehensively on underlying uncertainties, including those in data, methods and adaptation scenarios. Epistemic uncertainties in digital elevation, coastal protection levels and depth-damage functions would be best reduced through open community-based efforts, in which many scholars work together in collecting and validating these data.