Storm Surge Risk Research Articles

Storm Surge Risk Assessment in Coastal Communities in the Rio Grande Valley: An Application of GIS-Based Spatial Multicriteria Decision Analysis with Analytical Hierarchy Process

Kyne, D., 2023. Storm surge risk assessment in coastal communities in the Rio Grande Valley: An application of GIS-based spatial multicriteria decision analysis with analytical hierarchy process. Journal of Coastal Research, 39(3), 471–483. Charlotte (North Carolina), ISSN 0749-0208. Cameron County, which is located in the Rio Grande Valley, maintains records of storm surges associated with noticeable property damage, fatalities, and injuries. This study investigates storm surge inundation risk in Cameron County using storm surge hazard datasets from the National Oceanic and Atmospheric Administration, along with American Community Survey 2019 block group datasets. Using a GIS-based spatial multicriteria decision analysis with an analytical hierarchy process method, the study estimates that storm surge water levels could be above 6.1 m (20 ft) in category 4 and 5 hurricane events, whereas about 37% of the county's population (159,659 people) could be exposed to floodwater in the event of a category 5 hurricane. The inundation risk map shows that in the event of a category 4 or 5 hurricane, about 28 and 42%, respectively, of county's area could be exposed to a very high level of inundation risk. Because of the destructive power of such storms and their potential consequences, the findings suggest that storm surge risk should not be underestimated. All stakeholders should proactively prepare for potential storm surge events.

Impact of Storm Surge on the Yellow River Delta: Simulation and Analysis

Storm surges can lead to serious natural hazards and pose great threats to coastal areas, especially developed deltas. Assessing the risk of storm surges on coastal infrastructures is crucial for regional economic development and disaster mitigation. Combining in situ observations, remote sensing retrievals, and numerical simulation, storm surge floods in the Yellow River Delta (YRD) were calculated in different scenarios. The results showed that NE wind can cause the largest flooding area of 630 km2, although the overall storm surge risk in the delta is at lower levels under various conditions. The coastal oilfields are principally at an increasing storm surge risk level. E and NE winds would result in storm surges of 0.9–1.4 m, increasing the risk of flooding in the coastal oilfields. Nearshore seabed erosion in storm events resulted in a decrease in inundation depths and inundation areas. To prevent and control storm surge disasters, we should adapt to local conditions. Different measures should be taken to prevent the disaster of storm surges on different seashores, such as planting saltmarsh vegetation to protect seawalls, while the key point is to construct and maintain seawalls on high-risk shorelines.

The utilization of physically based models and GIS techniques for comprehensive risk assessment of storm surge: A case study of Huizhou

Quantitative analyses of storm surge risk, which are mostly focused on physical vulnerability, have been widely used to help coastal communities mitigate impacts and damage. Such assessments, however, overlook the social aspect of vulnerability in storm surge risk. By considering both the community’s social vulnerability and buildings’ physical vulnerability, this study proposed a methodology that incorporates social vulnerability into the framework for making quantitative risk assessments of storm surge using a coupled hydrodynamic and wave model, Geographical Information System (GIS) techniques, and the Principal Component Analysis (PCA) method. The coastal area of Huizhou was chosen as the case study due to its high concentration of oil and gas infrastructure in China’s southern Guangdong Province. By combining hazard, exposure, physical vulnerability, and social vulnerability, it was possible to explore the effect of social vulnerability on the physical vulnerability-based risk assessment of storm surge and determine the overall risk level. First, the Gumbel distribution was utilized to establish five representative and plausible hypothetical typhoon events with different return periods (10, 20, 50, 100, and 1000 years) for the study area. Then, using the well-validated fully-coupled model, the Simulating Waves Nearshore (SWAN) model and the ADvanced CIRCulation (ADCIRC) model, storm surge simulations for defined return periods were run, and the geographical distribution of the maximum surge elevations displayed on a GIS platform was used to assess hazard levels. In terms of the physical aspect, the depth-damage functions for buildings were established to estimate direct economic losses and assign risk levels accordingly. For the social vulnerability of a community, a composite score was computed using the PCA method by combining and aggregating indicators representing various characteristics of the social group. The results show that the overall risk level, taking into account both social vulnerability and physical vulnerability, has decreased on average. It suggests that social vulnerability-based risk assessment may account for a significant portion of the overall risk assessment, which is frequently overlooked in traditional storm surge risk assessment. Additionally, the comprehensive and precise risk maps can assist local policymakers in identifying areas at different risk levels and developing evacuation plans, thereby minimizing potential losses, especially in high-risk areas.

Storm surge hazard over Bengal delta: a probabilistic–deterministic modelling approach

Abstract. Storm-surge-induced coastal inundation constitutes a substantial threat to lives and properties along the vast coastline of the Bengal delta. Some of the deadliest cyclones in history made landfall in the Bengal delta region claiming more than half a million lives over the last five decades. Complex hydrodynamics and observational constraints have hindered the understanding of the risk of storm surge flooding of this low-lying (less than 5 m above mean sea level), densely populated (> 150 million) mega-delta. Here, we generated and analysed a storm surge database derived from a large ensemble of 3600 statistically and physically consistent synthetic storm events and a high-resolution storm surge modelling system. The storm surge modelling system is developed based on a custom high-accuracy regional bathymetry enabling us to estimate the surges with high confidence. From the storm surge dataset, we performed a robust probabilistic estimate of the storm surge extremes. Our ensemble estimate shows that there is a diverse range of water level extremes along the coast and the estuaries of the Bengal delta, with well-defined regional patterns. We confirm that the risk of inland storm surge flooding at a given return period is firmly controlled by the presence of coastal embankments and their height. We also conclude that about 10 % of the coastal population is living under the exposure of a 50-year return period inundation under current climate scenarios. In the face of ongoing climate change, which is likely to worsen the future storm surge hazard, we expect our flood maps to provide relevant information for coastal infrastructure engineering, risk zoning, resource allocation, and future research planning.

On the Geographic Balance of Risk and Amenity: Changes in Evacuation Zones and Their Ripples in Housing Prices in Pinellas County, FL

This study considers the balance of amenities and coastal hazards on housing prices between 2000 and 2015. We test whether risk communication via hurricane evacuation zone (a proxy for storm-surge risk and coastal flooding) affects sales price while controlling for relevant property characteristics, beach frontage, flood zones, and proximity to the coast. Additionally, we employ a difference-in-difference technique to test whether two highly publicized updates to evacuation zone maps, which changed the status of many homes in the county, led to price penalties for homes. We focus our study on areas of the new evacuation zone maps that reclassified parcels into zones associated with higher coastal surge exposure. This approach allows us to isolate the effects of risk communication about a property independent of changes to its insurance premiums or actual hazard exposure. We find that amenities are associated with significant bonuses and hazard variables correlated with price penalties, and homes in areas reclassified “up” in hazard zone classification have lost value. Our findings shed light on how information changes about hazards may affect coastal real estate markets as concerns about coastal hazards and exposure to storm-related surges increase along with climate change.

Benchmarking household storm surge risk perceptions to scientific models in the Philippines

Household perceptions of hazards play an important role in mobilizing efforts for disaster risk reduction. This research aimed to examine perceptions of storm surge in the Philippines through a case study of the Municipality of Carigara located in the province of Leyte. Surveys from 1,093 households were collected asking about perceived storm surge exposure. Building vulnerability indicators were combined with storm surge inundation models and household perceptions to compare differences in storm surge risk. More than half of households in modelled inundation zones either did not know their exposure or believed they were not exposed to 2-m surge heights and above. While there was alignment between modelled and perceived risk of low-level storm surge events, our results show a significant disconnect between household perceptions and probabilistic models for larger storm surge inundation events, pointing to continued gaps in storm surge knowledge in the Philippines.

Improving Tropical Cyclone Forecast Communication by Understanding NWS Partners’ Decision Timelines and Forecast Information Needs

Abstract As tropical cyclone threats evolve, broadcast meteorologists and emergency managers rely on timely forecast information to help them communicate risk with the public and protect public safety. This study aims to improve the usability and applicability of National Weather Service (NWS) forecast information in the context of these NWS core partners’ decisions during tropical cyclone threats. The research collected and analyzed data from in-depth interviews with broadcast meteorologists and emergency managers in three coastal U.S. states. These data were used to analyze broadcast meteorologists’ and emergency managers’ tropical cyclone decision and action timelines, their use of tropical cyclone information during different phases of threats, and gaps in forecast information for decision-making. Based on these findings, several opportunities for improving tropical cyclone risk communication were identified. Recommendations to address gaps in the NWS tropical cyclone product suite include designing improved ways to communicate storm-specific storm surge risk at greater than 48 h of lead time, expanding the use of concise highlights that help people quickly extract and understand key information, and improving product understandability and usability by more comprehensively integrating users’ perspectives into product research and development. Broader strategic recommendations include developing new approaches for informing broadcast meteorologists about major forecast updates, presenting forecast information in ways that enable locally relevant interpretation, and supporting human forecasters’ contributions to the effectiveness of NWS products and services. These findings and recommendations can help NOAA prioritize ways to modernize the current NWS tropical cyclone product suite as well as motivate research to enable longer-term high-priority improvements. Significance Statement Tropical cyclones pose significant risks to coastal and inland U.S. populations. This project aims to improve creation, communication, and use of tropical cyclone forecast and warning information by studying broadcast meteorologists’ and emergency managers’ information needs for decision-making during different phases of tropical cyclone threats. We identify several priority areas for improvement, including advancing longer-lead-time storm surge forecast communication, enhancing dissemination of forecast updates, and increasing use of concise text highlights. Additional findings include the importance of locally interpretable forecast information, the value of human forecasters in weather risk communication, and the need for iterative, user-informed forecast product development. These findings can help NOAA and the research community improve forecast communication and invest in research that facilitates continued improvements.

Evaluation of the Risk of Simultaneous Storm Surge and Food in the Kochi Plain Bised on 5km Dynamical Downscaling Dataset

Evaluation of the Risk of Simultaneous Storm Surge and Food in the Kochi Plain Bised on 5km Dynamical Downscaling Dataset

Assessing Risk of Storm Surge for Coastal Provinces in Viet Nam

Viet Nam is seriously affected by natural disasters including storms and storm surges. Assessing disaster risks, particularly storm surges for coastal provinces, thus, provides not only scientific evidence but also supports policymaking in natural disaster prevention and control. Given this importance, this study assesses the risks of storm surges in Vietnamese coastal provinces. The results show that the coastal areas of Quang Ninh, Thanh Hoa, Nghe An, Ha Tinh, Quang Tri and Hue face the highest risk of storm surges. On the contrary, other provinces including Da Nang, Quang Nam, Binh Dinh, Phu Yen, and Ba Ria- Vung Tau face the lowest risk of storm surges. The results provide useful information for better natural disaster preparedness in Viet Nam, namely planning and zoning of future development as well as supporting early warning efforts.

Development of an adaptation model by applying non-linear programming to compute adaptation deficiency in climatic hotspots

For the policy makers, risk-based planning to minimize future climatic risk needs decision on investment priority. This is particularly important where there are resource constraints, and in cases where the decisions depend on socio-political reality of the region. For the policy makers, it is also extremely important to know how a system will behave if investment is made on any specific adaptation in any specific location to minimize climatic risk in the region. To answer these questions, an Adaptation Model is developed in this study to compute adaptation deficiency for a location that will minimize climatic risk in that location. In this methodology, a system approach is followed by applying non-linear programming. The non-linear programming system is formulated by defining future climatic risk as the objective function where the risk is a non-linear function of hazard, exposure, vulnerability, where vulnerability is a linear combination of sensitivity and adaptive capacity. The system is restricted by seven constraints composed of different combinations of hazard, exposure, sensitivity and adaptive capacity. The model can be applied in any part of the world, for any climatic hazard, and for any time domain. In this study, the model is applied in Bangladesh coastal zone to compute adaptation deficiency required to be filled to minimize mid-century storm surge risk in the identified hotspots. The results show that out of 20 identified storm surge risk hotspots in Bangladesh coastal zone, cyclone shelter has the maximum adaptation deficiency in 10 hotspots followed by plantation in 8 hotspots. The output from the model can be used by the policy makers to decide on the most appropriate investment options for risk-based planning that will minimize future risks in the identified hotspots. The model shows the risk limit below which risk cannot be reduced. Any investment attempt on adaptation to reduce the risk beyond this limit will disrupt the system equilibrium and will make this investment a surplus.

Estimation of the non-exceedance probability of extreme storm surges in South Korea using tidal-gauge data

Abstract. Global warming, one of the most serious aspects of climate change, can be expected to cause rising sea levels. These have in turn been linked to unprecedentedly large typhoons that can cause flooding of low-lying land, coastal invasion, seawater flows into rivers and groundwater, rising river levels, and aberrant tides. To prevent typhoon-related loss of life and property damage, it is crucial to accurately estimate storm-surge risk. This study therefore develops a statistical model for estimating such surges' probability based on surge data pertaining to Typhoon Maemi, which struck South Korea in 2003. Specifically, estimation of non-exceedance probability models of the typhoon-related storm surge was achieved via clustered separated peaks-over-threshold simulation, while various distribution models were fitted to the empirical data for investigating the risk of storm surges reaching particular heights. To explore the non-exceedance probability of extreme storm surges caused by typhoons, a threshold algorithm with clustering methodology was applied. To enhance the accuracy of such non-exceedance probability, the surge data were separated into three different components: predicted water level, observed water level, and surge. Sea-level data from when Typhoon Maemi struck were collected from a tidal-gauge station in the city of Busan, which is vulnerable to typhoon-related disasters due to its geographical characteristics. Fréchet, gamma, log-normal, generalized Pareto, and Weibull distributions were fitted to the empirical surge data, and the researchers compared each one's performance at explaining the non-exceedance probability. This established that Weibull distribution was better than any of the other distributions for modelling Typhoon Maemi's peak total water level. Although this research was limited to one city on the Korean Peninsula and one extreme weather event, its approach could be used to reliably estimate non-exceedance probabilities in other regions where tidal-gauge data are available. In practical terms, the findings of this study and future ones adopting its methodology will provide a useful reference for designers of coastal infrastructure.

The lasting impacts of the Saffir-Simpson Hurricane Wind Scale on storm surge risk communication: The need for multidisciplinary research in addressing a multidisciplinary challenge

Historically, storm surge risk was indicated alongside the Saffir-Simpson Hurricane Wind Scale (SSHWS), and a lasting association remains among the general public. In recent years, the National Hurricane Center (NHC) has continually developed their advisories and products to explicitly communicate the storm surge hazard. In this study, we examine these developments to understand its impact on risk perception and discuss that though not explicitly, underlying associations to the SSHWS remain. We also find that despite the messaging produced through official storm surge guidance, the SSHWS continues to influence public perception and response. Our findings suggest that while improvements in storm surge messaging can improve risk communication and perception and ultimately save lives, it only addresses one component of the multidisciplinary system that defines storm surge risk. Truly effective resilience efforts will require comprehensive, multidisciplinary approaches.

Assessing and zoning of typhoon storm surge risk with a geographic information system (GIS) technique: a case study of the coastal area of Huizhou

Abstract. Storm surge is one of the most destructive marine disasters to life and property for Chinese coastal regions, especially for Guangdong Province. In Huizhou city, Guangdong Province, due to the high concentrations of chemical and petroleum industries and the high population density, the low-lying coastal area is susceptible to the storm surge. Therefore, a comprehensive risk assessment of storm surge over the coastal area of Huizhou can delimit zones that could be affected to reduce disaster losses. In this paper, typhoon intensity for the minimum central pressure of 880, 910, 920, 930, and 940 hPa (corresponding to a 1000-, 100-, 50-, 20-, and 10-year return period) scenarios was designed to cover possible situations. The Jelesnianski method and the Advanced Circulation (ADCIRC) model coupled with the Simulating Waves Nearshore (SWAN) model were utilized to simulate inundation extents and depths of storm surge over the computational domain under these representative scenarios. Subsequently, the output data from the coupled simulation model (ADCIRC–SWAN) were imported to the geographic information system (GIS) software to conduct the hazard assessment for each of the designed scenarios. Then, the vulnerability assessment was made based on the dataset of land cover types in the coastal region. Consequently, the potential storm surge risk maps for the designed scenarios were produced by combining hazard assessment and vulnerability assessment with the risk matrix approach. The risk maps indicate that due to the protection given by storm surge barriers, only a small proportion of the petrochemical industrial zone and the densely populated communities in the coastal areas were at risk of storm surge for the scenarios of 10- and 20-year return period typhoon intensity. Moreover, some parts of the exposed zone and densely populated communities were subject to high and very high risk when typhoon intensities were set to a 50- or a 100-year return period. Besides, the scenario with the most intense typhoon (1000-year return period) induced a very high risk to the coastal area of Huizhou. Accordingly, the risk maps can help decision-makers to develop risk response plans and evacuation strategies in coastal communities with a high population density to minimize civilian casualties. The risk analysis can also be utilized to identify the risk zones with the high concentration of chemical and petroleum industries to reduce economic losses and prevent environmental damage caused by the chemical pollutants and oil spills from petroleum facilities and infrastructures that could be affected by storm surge.

Tropical cyclone risk mapping for a coastal city using geospatial techniques

Tropical cyclone associated storm surges and their disastrous influences are becoming a major concern amongst the worldwide coastal community. The detailed risk modelling study seems an urgent need to support the storm surge mitigation actions. Using a Geographic Information System (GIS) based risk model, this study attempted to obtain both present and future storm surge wave heights in the Cox’s Bazar Sadar Upazilla in Bangladesh. Linear storm surge model setup was done for the different return periods includes 5, 10, 20, 50, and 100 years. Also, to assess climate change effects, a 0.34 m sea-level rise in 2050 was tested using the regional scale surge models. The simulated storm surge model provided a time series dataset for the risk model and obtained risk maps comprised of the relationship among risk zone and the return periods. With the present inundation depth trend, the acquired risk maps of 50 and 100 year return period showed that 10.13% and 36.4% of the study area belongs to very high-risk zone respectively. Conversely, for future inundation depth conditions 30.83% and 49.9% of the study area would be within a very high-risk zone in 50 and 100 year return period respectively. This is envisaged that a detailed historical inundation dataset could enrich the adopted approach considering both present and future storm surge risk modelling for the Decision Support System (DSS). Also, this approach might be adopted for other identical coastal environments to aid mitigation programs and strategies.

Risk assessment for typhoon-induced storm surges in Wenchang, Hainan Island of China

A risk assessment for storm surge disasters can provide scientific support for coastal management as well as marine disaster prevention and mitigation. By taking the Wenchang City of Hainan Province as a pilot area, a risk assessment approach for typhoon-induced storm surge disasters is introduced in detail in this article. First, a numerical simulation system for storm surge inundation is developed, which is applied for the simulation and calculation of the probable maximum storm surge in Wenchang, and the obtained inundation areas and depths are used to assess the storm surge hazard. Then, the data of land use and disaster-bearing bodies are used to classify and assess the vulnerability of Wenchang. Finally, by taking the community as unit, the risk assessment for typhoon-induced storm surge affecting Wenchang is performed by combining the assessment results of both hazard and vulnerability, thereby obtaining a level map of risk distribution. The results show that there are risks of typhoon-induced storm surge in most of the coastal areas of Wenchang, especially for its northeast and east coastal areas, where the risks reach Levels I–II. This approach can be conveniently applied to risk assessments of storm surge in other coastal areas. Note that this approach focuses on the current risk of typhoon-induced storm surge in coastal areas, and further studies will be conducted on the assessment methods for the potential risk.

UNCERTAINTY ASSESSMENT OF FUTURE CHANGE PROJECTION TO TYPHOON PROPERTIES AND MAXIMUM STORM SURGE HEIGHT DEPENDING OF FUTURE SEA SURFACE TEMPERATURE AND GREENHOUSE GAS EMISSION SCENARIOS

In order to evaluate the future storm surge risk at the national scale, it is necessary to evaluate typhoon characteristics for a country-specific in prior to conducting storm surge simulation using them. When projecting future changes of tropical cyclones (TC) by using the atmospheric general circulation model (AGCM), there are several uncertainties due to model resolution, model physics parameterization, given sea surface temperature (SST) under future climate condition, and global warming scenarios. The uncertainties stemming from physics and numerical modeling configuration can be reduced by improving the accuracy of AGCMs, while those from the global warming scenario and future SST condition are unable to be. This study assessed uncertainties in projecting future change to typhoon properties such as tracks, frequency and intensity and extreme storm surge height (SSH) depending of future SST and greenhouse gas emission scenarios.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/Wzp35k4tyhM

On the use of synthetic tropical cyclones and hypothetical events for storm surge assessment under climate change

This study presents a new approach to assess storm surge risk from tropical cyclones under climate change by direct calculation of the local flood levels using a limited number of events with an associated probability. The approach is based on the near-worst-case flood scenario, associated with a known tropical cyclone wind intensity probability (return period). We applied the method for the locality of Manzanillo, Colima, Mexico, using synthetic tropical cyclones derived from six different general circulation models for the present and future climates under the Representative Concentration Pathway 8.5. The synthetic events allowed the characterization of the wind intensity for the present and future climates for a given return period, as well as to determine the key tropical cyclones parameters related to storm surge. For Hurricane Patricia (2015), the strongest tropical cyclone to impact the region, we determined that its 95 m/s winds have a return period above 4000 years for the present climate and 198 years in a future climate scenario. Using Hurricane Patricia’s peak wind intensity, we created hypothetical events representing all possible approaches of tropical cyclones (211 events) to Manzanillo. We forced a hydrodynamic model with the hypothetical events over a mesh created with LiDAR-derived topography and then calculated the storm surge to create the near-worst-case flood scenario based on the maximum envelopes of water (MEOWs) and the maximum of MEOWs. Using those results, we created flood risk maps at city block level based on the combination of flood hazard and socioeconomic vulnerability maps. The presented method provides a tool for tropical cyclones storm surge hazard and risk assessment by generating near-worst-case flood maps under projected climates using a limited set of hypothetical events.

Super typhoons Hato and Mangkhut, part II: challenges in forecasting and early warnings

This is the second paper of a two‐part series about Super Typhoons Hato (1713) and Mangkhut (1822), which hit Hong Kong successively in 2017 and 2018, respectively, and necessitated the issuance of the highest tropical cyclone warning signal. While their maximum intensity and wind structure are analysed in Part I, this paper covers the challenges in forecasting and early warning of the storms. The actual and predicted tropical cyclone track, intensity and storm surge in Hong Kong and their associated storm surge risk are reviewed. Experience in early warning and disaster risk reduction is also shared in this paper.

Using a WRF-ADCIRC Ensemble and Track Clustering to Investigate Storm Surge Hazards and Inundation Scenarios Associated with Hurricane Irma

AbstractThis article investigates combining a WRF-ADCIRC ensemble with track clustering to evaluate how uncertainties in tropical cyclone–induced storm tide (surge + tide) predictions vary in space and time and to explore whether this method can help elucidate inundation hazard scenarios. The method is demonstrated for simulations of Hurricane Irma (2017) initialized at 1200 UTC 5 September, approximately 5 days before Irma’s Florida landfalls, and 1200 UTC 8 September. Mixture models are used to partition the WRF ensemble tracks from 5 and 8 September into six and five clusters, respectively. Inundation is evaluated in two affected regions: southwest (south and west Florida) and northeast (northeast Florida through South Carolina). For the 5 September simulations, inundation in the southwest region varies significantly across the ensemble, indicating low forecast confidence. However, clustering highlights the areas of inundation risk in south and west Florida associated with different storm tracks. In the northeast region, every cluster has high inundation probabilities along a similar coastal stretch, indicating high confidence at a ~5-day lead time that this area will experience inundation. For the 8 September simulations, track and inundation in both regions vary less across the ensemble, but clustering remains useful for distinguishing among flooding scenarios. These results demonstrate the potential of dynamical TC–surge ensembles to illuminate important aspects of storm surge risk, including highlighting regions of high forecast confidence where preparations can reliably be initiated early. The analysis also shows how clustering can augment probabilistic hazard forecasts by elucidating inundation scenarios and variability across a surge ensemble.

Growth Machine Up-links and the Manufacture of Flood Risk in Mid-twentieth Century New Orleans

Environmentally destructive megaprojects, which substantially shift the topography and hydrology of the ecosystems in which they are embedded in ways that potentially exacerbate preexisting disaster risks, are created through a combination of lobbying by municipal growth machines and applications of higher level state authority, resources, and control. New Orleans’ manufactured hurricane storm surge risk provides a crucial case study of this dynamic. After Hurricane Katrina, forensic engineers found that the proximate cause of the New Orleans flood was the levee and floodwall failures along the city’s shipping and drainage canals, but this disaster cannot be fully understood without an examination of the city’s mid-twentieth century political economy, particular regarding the power of the local shipping industry and its up-links to entities in the federal government. During this time period, local New Orleans elites were able to take advantage of the two world wars and postwar economic expansion to dramatically enlarge the city’s shipping canal system with massive funding and expertise from the Maritime Commission and the Corps of Engineers, massively amplifying the city’s flood risk in ways that ultimately led to the Katrina catastrophe.