A Review of Cost Estimates for Flood Adaptation

Site selection for nature-based solutions for stormwater management in urban areas: An approach combining GIS and multi-criteria analysis

In recent years, particularly following the definition of the UN Sustainable Development Goals (SDGs) for 2030, Nature-Based Solutions (NBS) have gained considerable attention, capturing the interest of both the scientific community and policymakers committed to addressing urban environmental issues. However, the need for studies to guide decision-makers in identifying suitable locations for NBS implementation within urban stormwater management is evident. To address this gap, the present study employs a methodological approach grounded in multi-criteria analysis integrated with Geographic Information Systems (GIS) to identify areas with potential for NBS implementation. In this process, ten NBS were proposed and tested in the drainage area of a shallow tropical urban lake in Londrina, southern Brazil. Additionally, the study investigates areas hosting lower-income populations, a relevant aspect for public managers given the diverse economic subsidies required to implement NBS. Furthermore, the study incorporates a preliminary analysis that evaluates the potential ecosystem benefits to determine the most suitable NBS for a specific site. The result shows that all the ten analyzed NBS were deemed suitable for the study area. Rain barrels had the highest percentage coverage in the study area (37.1%), followed by tree pits (27.9%), and rain gardens (25.4%). Despite having the highest distribution in the basin area, rain barrels exhibited only moderate ecosystem benefits, prompting the prioritization of other NBS with more significant ecological advantages in the final integrated map. In summary, the methodology proposed showed to be a robust approach to selecting optimal solutions in densely populated urban areas.

Modeling saltwater intrusion risk in the presence of uncertainty

The Mekong Delta is one of the most productive rice-producing regions in the world, exporting approximately one-fifth of the global rice traded annually. Previous studies note that saltwater intrusion is a serious concern, and the intensity of saltwater intrusion is primarily driven by sea level rise, land subsidence, anthropogenic sediment starvation, and upstream hydro-infrastructure developments. However, these studies often rely on scenario-based approaches instead of an integrated approach to assess the possible impacts of saltwater intrusion. Using an integrated hydrodynamic-statistical-economic model, we investigate how and the extent to which these drivers may impact the saltwater intrusion. We also examine the costs and returns of two popular saltwater intrusion control policies, i.e., hard-engineering structural and soft-land use planning. When comparing the baseline scenarios, the findings indicate that anthropogenic forces lead to a four times greater saltwater intrusion intensity than the climate change-induced sea level rise. The results further reveal a 50 % or less chance that annual saltwater-affected areas would exceed 1.93 million ha for the baseline, but the likelihood is highly likely to be 100 % with a sea level rising of 22 cm. Under the combined effects of sea-level rise, land subsidence, and riverbed incision, our model shows that the probability of annual saltwater-affected areas staying above 2.30 million ha is almost equal to one. This finding implies that a large share of the current rice-planted areas of the Delta could be wiped out of production for at least one season a year. The findings show that a combination of hard and soft policies would be a more sustainable and cost-effective strategy to lower the intensity and risks of saltwater intrusion. Therefore, there is an urgent need for better coordination of governance and investments among regions within the Delta and counties in the whole Mekong River Basin.

Flood insurance is a driver of population growth in European floodplains

Future flood risk assessments typically focus on changing hazard conditions as a result of climate change, where flood exposure is assumed to remain static or develop according to exogenous scenarios. However, this study presents a method to project future riverine flood risk in Europe by simulating population growth in floodplains, where households' settlement location decisions endogenously depend on environmental and institutional factors, including amenities associated with river proximity, riverine flood risk, and insurance against this risk. Our results show that population growth in European floodplains and, consequently, rising riverine flood risk are considerably higher when the dis-amenity caused by flood risk is offset by insurance. This outcome is particularly evident in countries where flood risk is covered collectively and notably less where premiums reflect the risk of individual households.

Non-structural flood mitigation optimization at community scale: Middle Cedar Case Study

Flooding is the leading natural hazard in Iowa and has resulted in billions of dollars of damage to properties and critical infrastructure over the past couple of decades. Land alterations, urbanization, and changing precipitation regimes increase the magnitude and frequency of flood events. Considering the increasing risk, flood mitigation efforts are significant to reduce future losses. In this study, we present a comprehensive flood mitigation assessment for the cities of Cedar Falls, Cedar Rapids, and Waterloo in Iowa, utilizing various datasets such as property information, flood inundation maps, mitigation costs, and depth-damage functions. The research revealed that flooding has a minimal impact on Waterloo below the 200-year return period flood scenario, but Cedar Falls and Cedar Rapids are significantly vulnerable, requiring more mitigation investments and planning. The study conducted a benefit-cost analysis, indicating that dry floodproofing is the most feasible option to reduce flood impacts in all studied communities. Moreover, the research conducted a climate data-driven analysis, which found that elevating structures significantly increases the number of feasible mitigation options, regardless of various long-term climate projections. The study also analyzed predetermined mitigation budgets, revealing potential avoided losses and benefit-cost ratios for properties with the highest BCRs and prioritizing them to maximize the total benefit to the communities. The study findings offer crucial insights and recommendations to guide decision-makers in the community on prioritizing cost-effective flood mitigation strategies and minimizing flood impact in the studied regions.

Enhancing flood susceptibility modeling using multi-temporal SAR images, CHIRPS data, and hybrid machine learning algorithms

Flood susceptibility maps are useful tool for planners and emergency management professionals in the early warning and mitigation stages of floods. In this study, Sentinel-1 dB radar images, which provide Synthetic-Aperture Radar (SAR) data were used to delineate flooded and non-flooded locations. 12 input parameters, including elevation, lithology, drainage density, rainfall, Normalized Difference Vegetation Index (NDVI), curvature, ground slope, Stream Power Index (SPI), Topographic Wetness Index (TWI), soil, Land Use Land Cover (LULC), and distance from the river, were selected for model development. The importance of each input parameter on flood occurrences was assessed via the Mutual Information (MI) technique. Several machine learning models, including Radial Basis Function (RBF), and three hybrid models of Bagging (BA-RBF), Random Committee (RC-RBF), and Random Subspace (RSS-RBF), were developed to delineate flood susceptibility areas at Goorganrood watershed, Iran. The performance of each model was evaluated using several error indicators, including correlation coefficient (r), Nash Sutcliffe Efficiency (NSE), Mean Absolute Error (MSE), Root Mean Square Error (RMSE), and the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC). The results showed that the hybrid techniques enhanced the modeling performance of the standalone model, and generally, all hybrid models are more accurate than the standalone model. Although all developed models have performed well, RC-RBF outperforms all of them (AUC = 0.997), followed by BA-RBF (AUC = 0.996), RSS-RBF (AUC = 0.992), and RBF (AUC = 0.975). Generally, about 12 % of the study area has high and very high susceptibility to future flood occurrences.

Urban flood risk differentiation under land use scenario simulation

The frequent urban floods have seriously affected the regional sustainable development in recent years. It is significant to understand the characteristics of urban flood risk and reasonably predict urban flood risk under different land use scenarios. This study used the random forest and multi-criteria decision analysis models to assess the spatiotemporal characteristics of flood risk in Zhengzhou City, China, from 2005 to 2020, and proposed a robust method coupling Bayesian network and patch-generating land use simulation models to predict future flood risk probability. We found that the flood risk in Zhengzhou City presented an upward trend from 2005 to 2020, and its spatial pattern was "high in the middle and low in the surrounding areas". In addition, land use patterns under the sustainable development scenario would be more conducive to reducing flood risk. Our results can provide theoretical support for scientifically optimizing land use to improve urban flood risk management.

Biophysical and biochemical features' feedback associated with a flood episode in a tropical river basin model

Global climate change scenarios such as frequent and extreme floods disturb the river basins by destructing the vegetation resulting in rehabilitation procedures being more costly. Thus, understanding the recovery and regeneration of vegetation followed by extreme flood events is critical for a successful rehabilitation process. Spatial and temporal variation of biochemical and biophysical features derived from remote sensing technology in vegetation can be incorporated to understand the recovery and regeneration of vegetation. The present study explores the flood impact on vegetation caused by major river basins in Sri Lanka (a model tropical river basin) by comparing pre-flood and post-flood cases. The study utilized enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), the fraction of photosynthetically active radiation (FPAR), and gross primary productivity (GPP) of the Moderate Resolution Imaging Spectroradiometer (MODIS) platform. A remarkable decline in EVI, LAI, FPAR, GPP, and vegetation condition index was observed in the post-flood case. Notably, coupled GPP-EVI and GPP-LAI portrayed dependency of features and showed a significant impact triggered by the flood episode by narrowing the feature in post-flood events. EVI depicted the highest regeneration (0.333) while GPP presented the lowest regeneration (0.093) after the flood event. Further, it was revealed that 1.18 years have been on the regeneration. The regeneration of GPP and LAI remained low comparatively justifying the magnitude and impact of the flood event. The study revealed successful implications of vegetation indices on flood basin management of small to large tropical river basins.

An agent-based model for evaluating reforms of the National Flood Insurance Program: A benchmarked model applied to Jamaica Bay, NYC

Coastal flood risk is expected to increase as a result of climate change effects, such as sea level rise, and socioeconomic growth. To support policymakers in making adaptation decisions, accurate flood risk assessments that account for the influence of complex adaptation processes on the developments of risks are essential. In this study, we integrate the dynamic adaptive behavior of homeowners within a flood risk modeling framework. Focusing on building-level adaptation and flood insurance, the agent-based model (DYNAMO) is benchmarked with empirical data for New York City, USA. The model simulates the National Flood Insurance Program (NFIP) and frequently proposed reforms to evaluate their effectiveness. The model is applied to a case study of Jamaica Bay, NY. Our results indicate that risk-based premiums can improve insurance penetration rates and the affordability of insurance compared to the baseline NFIP market structure. While a premium discount for disaster risk reduction incentivizes more homeowners to invest in dry-floodproofing measures, it does not significantly improve affordability. A low interest rate loan for financing risk-mitigation investments improves the uptake and affordability of dry-floodproofing measures. The benchmark and sensitivity analyses demonstrate how the behavioral component of our model matches empirical data and provides insights into the underlying theories and choices that autonomous agents make.

Supply-Demand Evaluation of Green Stormwater Infrastructure (GSI) Based on the Model of Coupling Coordination

The rational spatial allocation of Green Stormwater Infrastructure (GSI), which is an alternative land development approach for managing stormwater close to the source, exerts a crucial effect on coordinating urban development and hydrological sustainability. The balance between the supply and demand of urban facilities has been an influential standard for determining the rationality of this allocation. However, at this stage, research on evaluating planning from the perspective of supply-demand in GSI is still limited. This study proposed an evaluation method for assessing supply-demand levels in GSIs in Guangzhou, China, using the coupling coordination model consisting of Coupling Degree (CD) and Coupling Coordination Degree (CCD). Furthermore, the spatial distributions of supply-demand balance and resource mismatch were identified. The results indicated that the supply and demand levels of GSI exhibited significant spatial differences in distribution, with most streets being in short supply. The GSI exhibited a high CD value of 0.575 and a poor CCD value of 0.328, implying a significant imbalance in facility allocation. A lot of newly planned facilities failed to effectively cover the streets in need of improvement, so it became essential to adjust the planning scheme. The findings of this study can facilitate the decision-makers in assessing the supply-demand levels in GSI and provide a reference of facility allocation for the sustainable construction of Sponge City.

Full-Scale Interface Friction Testing of Geotextile-Based Flood Defence Structures

Open-topped woven polypropylene cellular containers filled with dense granular ballasts are often used as emergency flood defence structures. The effectiveness of these systems is highly dependent on the interaction with their bedding surface. The characteristics of the foundation will often govern the system’s overall resistance to applied loading imposed by retained floodwater. However, the frictional relationship between polypropylene bulk bag flood defences and common bedding surfaces has not been extensively investigated. This study aims to reduce the reliance on arbitrary static friction coefficients by measuring and presenting actual data obtained through quantitative testing. This study presents the results of full-scale field testing to quantify the frictional resistance generated between filled polypropylene bulk bags and seven common bedding surfaces. Findings resulting from testing each interface scenario are expressed as coefficients of static friction. Test interfaces affording high frictional resistance comprised an unmade gravel road (µ = 0.74) and grass (µ = 0.64). Contrastingly, interfaces generating significantly lower frictional resistance were steel floated concrete (µ = 0.40) and polypropylene plastic (µ = 0.40). Test interfaces involving asphalt (µ = 0.54) and tamped concrete (µ = 0.56–0.58) were also investigated. This study recommends new friction coefficients necessary to characterise the structural stability analysis of bulk bag flood defences with greater accuracy. Practical advice based on experimental observation and field design experience is also given.

Moving from adaptation capacities to implementing adaptation to extreme heat events in urban areas of the European Union: Introducing the U-ADAPT! research approach

Extreme Heat Events (EHE) are a major concern for many urban areas worldwide and are considered as one of the deadliest natural hazards globally. Climate change and socioeconomic trends (exposure and susceptibility) are expected to exacerbate the risk of urban heat stress. Several urban areas have recently declared a climate emergency and initiated the adaptation process, but progress is still patchy, uncoordinated, and of varied quality. The main constraint is the lack of mechanisms for monitoring and reporting adaptation strategies, not allowing the supervision and evaluation of the adaptation process. The EU-funded project U-ADAPT! (Urban-Adaptation) focuses on the concrete expression of adaptation to evaluate the current implementation and effectiveness of adaptation measures and strategies to reduce Heat Disaster Risk (HDR), moving the emphasis from the study of vulnerability, resilience, and potential adaptation (adaptation capacity) of communities to the actual depth and pace of the past and current adaptation process. In this article, we discuss the theoretical support and design of the project and set the base for next project stages, which ultimately aims to create a unique interdisciplinary framework and a replicable multidimensional indicator on adaptation to EHE that empower European Union citizens to demand a safe and sustainable environment and hold institutions accountable for the adaptation process to current and upcoming risks.

Flood mitigation data analytics and decision support framework: Iowa Middle Cedar Watershed case study

Flooding is one of the most frequent natural disasters, causing billions of dollars in damage and threatening vulnerable communities worldwide. Although the impact of flooding can never be diminished, minimizing future losses is possible by taking structural or non-structural mitigation actions. Mitigation applications are often costly practices. However, they can be more feasible for long-term planning and protection. On the other hand, selecting a feasible option requires a comprehensive analysis of potential risk and damages and comparing the costs and benefits of different mitigation types. This paper presents a web-based decision support framework called Mitigation and Damage Assessment System (MiDAS) that analyzes flood risk impacts and mitigation strategies at the community and property-level with the goal of informing communities on the consequences of flooding and mitigation alternatives and encouraging them to participate in the community rating system. The framework utilizes regulatory flood inundation maps, damage functions, property information, scenario-based climate projections, and mitigation inputs and guidelines from the Federal Emergency Management Agency (FEMA) and the United States Army Corps of Engineers (USACE). It will help users select the appropriate flood mitigation measures based on various characteristics (e.g., foundation type, occupancy, square footage) and provide cost estimates for implementing measures. The system also provides a decision tree algorithm for analyzing and representing the mitigation decision by reviewing existing guidelines (e.g., FEMA, USACE). We analyzed the community-level mitigation for three major cities in Eastern Iowa (Cedar Falls, Cedar Rapids, and Waterloo) and found certain measures (e.g., wet/dry floodproofing) are cost-effective for community-level mitigation. Implementation of mitigation measures can reduce the property's vulnerability and improve the response to a flooding event.

Climate change, riverine flood risk and adaptation for the conterminous United States

Riverine floods are among the most costly natural disasters in the United States, and floods are generally projected to increase in frequency and magnitude with climate change. Faced with these increasing risks, improved information is needed to direct limited resources toward the most cost-effective adaptation actions available. Here we leverage a newly available flood risk dataset for residential properties in the conterminous United States to calculate expected annual damages to residential structures from inland/riverine flooding at a property-level; the cost of property-level adaptations to protect against future flood risk; and the benefits of those adaptation investments assuming both static and changing climate conditions. Our modeling projects that in the absence of adaptation, nationwide damages from riverine flooding will increase by 20-30% under high levels of warming. Floodproofing, elevation and property acquisition can each be cost-effective adaptations in certain situations, depending on the desired return on investment (i.e., benefit cost ratio), the discount rate, and the assumed rate of climate change. Incorporation of climate change into the benefit-cost calculation increases the number of properties meeting any specified benefit-cost threshold, as today's investments protect against an increasing frequency of future floods. However, because future expected damages are discounted relative to present-day, the adaptation decisions made based on a static climate assumption are very similar to the decisions made when climate change is considered. If the goal is to optimize adaptation decision making, a focus on quantifying present-day flood risk is therefore at least as important as understanding how those risks might change under a warming climate.

Flood Risk Assessment under Land Use and Climate Change in Wuhan City of the Yangtze River Basin, China

Frequently occurring flood disasters caused by extreme climate and urbanization processes have become the most common natural hazard and pose a great threat to human society. Therefore, urban flood risk assessment is of great significance for disaster mitigation and prevention. In this paper, the analytic hierarchy process (AHP) was applied to quantify the spatiotemporal variations in flood risk in Wuhan during 2000–2018. A comprehensive flood risk assessment index system was constructed from the hazard, sensitivity, and vulnerability components with seven indices. The results showed that the central urban area, especially the area in the west bank of the Yangtze river, had high risk due to its high flood sensitivity that was determined by land use type and high vulnerability with dense population and per unit GDP. Specifically, the Jianghan, Qiaokou, Jiangan, and Wuchang districts had the highest flood risk, more than 60% of whose area was in medium or above-medium risk regions. During 2000–2018, the flood risk overall showed an increasing trend, with Hongshan district increasing the most, and the year of 2010 was identified as a turning point for rapid risk increase. In addition, the comparison between the risk maps and actual historical inundation point records showed good agreement, indicating that the assessment framework and method proposed in this study can be useful to assist flood mitigation and management, and relevant policy recommendations were proposed based on the assessment results.

Why People (Do Not) Adopt the Private Precautionary and Mitigation Measures: A Review of the Issue from the Perspective of Recent Flood Risk Research

Based on the literature review, this paper synthesizes recent state of knowledge on flood risk perception and related human behaviors. The main attention is paid to private precautionary and mitigation measures, and the reasons why these are (not) adopted by agents such as individual households. Results of a wide range of relevant studies are presented and critically examined. The findings are presented within an interpretive framework established during the review process; six key themes (responsibility, risk perception, people and social environment, geography of risk, emotions, theories and conceptual models) and several sub-themes closely related to them were identified by the content/thematic analysis. These were then utilized to overview and discuss particular factors and issues involved, as well as various relevant theoretical underpinnings and conceptual models. The review identifies, illustrates, and addresses not only the consensual views and contradictory findings of flood risk research, but also several related and essential ambiguities, uncertainties, and knowledge gaps. Based on these findings, suggestions for future research are discussed, including the terminological, semantic, methodological, theoretical, and ethical aspects. The paper thus serves two main tasks: (a) It is a useful reference/departure point for those with research interests in topics and issues such as flood risk perception, flood risk protective and mitigation behaviors and measures, or flood risk management in general; and (b) it provides suggestions and incentives for future flood risk research agenda.

The Affordability of Flood Risk Property-Level Adaptation Measures

The affordability of property-level adaptation measures against flooding is crucial due to the movement toward integrated flood risk management, which requires the individuals threatened by flooding to actively manage flooding. It is surprising to find that affordability is not often discussed, given the important roles that affordability and social justice play regarding flood risk management. This article provides a starting point for investigating the potential rate of unaffordability of flood risk property-level adaptation measures across Europe using two definitions of affordability, which are combined with two different affordability thresholds from within flood risk research. It uses concepts of investment and payment affordability, with affordability thresholds based on residual income and expenditure definitions of unaffordability. These concepts, in turn, are linked with social justice through fairness concerns, in that, all should have equal capability to act, of which affordability is one avenue. In doing so, it was found that, for a large proportion of Europe, property owners generally cannot afford to make one-time payment of the cost of protective measures. These can be made affordable with installment payment mechanisms or similar mechanisms that spread costs over time. Therefore, the movement toward greater obligations for flood-prone residents to actively adapt to flooding should be accompanied by socially accessible financing mechanisms.

The growth mode of built-up land in floodplains and its impacts on flood vulnerability

Built-up land in floodplains (BLF) is a vital indicator of the socio-hydrological system, and its dynamics are key to understanding and managing flood risk. However, previous studies have neglected the impacts of BLF growth modes (e.g., patch sizes and expansion types) on flood vulnerability. This paper fills this gap by assessing the BLF's growth modes and revealing their divergent impacts on flood vulnerability using a case study in the Yangtze River Economic Belt (YREB), China. The results show that the BLF has nearly doubled in the YREB during 1990-2014. A considerable proportion (35.43%) of the BLF growth is scattered in small patches (≤1 km²), which have a much stronger correlation with flood occurrence than that of the other patch sizes. In terms of expansion types, the edge-expansion type dominates 57.52% of the BLF growth, followed by the leapfrogging and infilling expansions. Both the leapfrogging and the edge-expanding BLFs are significantly associated with flood occurrence, while the infilling type is not. The patch size and expansion type can thus influence the vulnerability of BLF patches, which is also supported by real-world cases. These findings enrich a general understanding of BLF growth and its impacts on flood vulnerability. The scientific community and policymakers should pay attention to not only the quantity of BLF growth, but also its spatial arrangement.

An economic evaluation of adaptation pathways in coastal mega cities: An illustration for Los Angeles

Sea level rise and uncertainty in its projections pose a major challenge to flood risk management and adaptation investments in coastal mega cities. This study presents a comparative economic evaluation method for flood adaptation measures, which couples a cost-benefit analysis with the concept of adaptation pathways. Our approach accounts for uncertainty in sea level rise projections by allowing for flexibility of adaptation strategies over time. Our method is illustrated for Los Angeles County which is vulnerable to flooding and sea level rise. Results for different sea level rise scenarios show that applying adaptation pathways can result in higher economic efficiency (up to 10%) than individual adaptation strategies, despite the loss of efficiency at the initial strategy. However, we identified 'investment tipping points', after which a transition could decrease the economic efficiencies of a pathway significantly. Overall, we recommend that studies evaluating adaptation strategies should integrate cost-benefit analysis frameworks with adaptation pathways since this allows for better informing decision makers about the robustness and economic desirability of their investment choices.