Low-lying Coastal Areas Research Articles

Sea Level Rise in Europe: Summary for Policymakers

Abstract. Sea level rise (SLR) is a global concern for low-lying coastal areas, including many European coasts. The European Knowledge Hub on Sea Level Rise (KH-SLR), a collaborative effort by the Joint Programming Initiatives for “Connecting Climate Knowledge for Europe” (JPI Climate) and for “Healthy and Productive Seas and Oceans” (JPI Oceans), has developed the 1st Assessment Report (SLRE1) to address the challenges posed by SLR in Europe. The report's target audience includes national and subnational bodies focused on research and policy advice for coastal management and climate adaptation, as well as European experts who contribute to shaping policy frameworks and collecting information at a pan-European scale. This report, preceded by a series of targeted surveys and workshops with researchers and stakeholders (e.g. coastal decision-makers), has synthesized the current scientific knowledge on SLR drivers, impacts, and policies at local, national, and European basin scales. It provides in-depth and basin-specific analyses on local sea level changes, compared with relevant global assessments of the Intergovernmental Panel on Climate Change (IPCC). In addition, it identified critical knowledge gaps needed to support the development of actionable information. The Summary for Policymakers (SPM) distils the key findings of the SLRE1, presenting information specific to the six European basins: Mediterranean Sea, Black Sea, North Sea, Baltic Sea, Atlantic, and Arctic. The SPM highlights basin-specific trends, vulnerabilities, and potential impacts, while also orienting future requirements.​​​​​​​

Assessment of coastal flood risk scenarios on infrastructure in the Keta municipality in Ghana using a GIS approach

Coastal flooding and erosion, caused by climate change-induced sea level rise, pose significant threats to low-lying coastal areas worldwide. The African continent, including Ghana, has experienced severe impacts from these hazards, affecting the socio-economic development of coastal communities. This research focuses on the Keta municipality in Ghana. The Keta municipality is highly vulnerable to coastal flooding and erosion due to its low elevation and the construction of the Akosombo hydroelectric dam. This research aims to predict the impact of coastal flooding on infrastructure in the Keta municipality using different flood scenarios. It also fills the existing knowledge gap in understanding how future flood risk can impact on critical infrastructure and consequently on other vital socio-economic sectors in the coastal community of Keta. The study utilizes a Geographic Information System (GIS)-based approach, combining various datasets, including topographic data, administrative shapefiles, field survey points, and infrastructure data. Two flood scenarios were considered to assess areas at risk: a 2.5-m sea level flood scenario representing potential climate change events and a worst-case 5-m sea level flood scenario. The findings reveal that 3.3 km2 (9 %) of coastal land area, 3.9 km of roads, and 69 structures are at risk under a 2.5m sea level rise scenario, increasing to 7.1 km2 (19.4 %), 13.6 km of roads, and 667 structures under a 5m scenario. The study highlights the urgency of addressing these risks to protect coastal communities' socio-economic development and livelihoods. Recommendations include implementing appropriate coastal management strategies, improving infrastructure resilience, and promoting sustainable land-use practices. By understanding and addressing the future impact of coastal flooding, decision-makers can mitigate climate change's adverse effects on coastal areas and ensure the region's long-term sustainability.

The role of Nature-Based Solutions for the water flow management in a Mediterranean urban area

Due to climate change and rapid urban sprawl, central Mediterranean regions are subjected to short but intensive storm events resulting in a significant increase of flow rates and runoff volumes in low-lying coastal urban areas. Within the framework of green urban infrastructures (GUIs), a suitable combination of Nature-Based Solutions (NBS) with traditional grey infrastructures should be adopted to mitigate flood risk effects in urban and sub-urban areas contributing at the same time to achieve multiple benefits for both the environment and the community. The aim of this study is (i) to evaluate flood hazard maps for identifying the areas within a Sicilian hydrological river basin (Toscano catchment) with a high risk of flooding by implementing the HEC-RAS model at catchment scale; (ii) to quantify the peak flow and floodplain area reduction; (iii) to assess the effectiveness of small-scale NBS (green roofs, porous pavements, rain gardens and rain barrel), in terms of peak flow and runoff volume reductions, at urban block scale by using the EPA SWMM model Model simulations are performed integrating the hydraulic (HEC-RAS) and hydrological (EPA SWMM) models for return periods of 10, 50 and 200 years. The results showed that the estimated peak flow (m3 s−1) obtained from the simulations performed at catchment scale for each T in the current scenario (without NBS) using HEC-RAS and EPA SWMM models are very close to each other (R2 = 0.99). In addition, the utopian scenario simulation showed the HEC-RAS model sensitivity to CN calibration achieving a peak flow reduction up to about 60% with the floodplain area decreasing up to about 17%. Finally, the model EPA SWMM shows its sensitivity to NBS implementation at urban block scale with a peak flow reduction up to about 16% and a runoff volume (mm) reduction up to about 24%. These reductions decrease as T increases with a higher NBS mitigation effects for the lowest T. The results highlighted that the integration of NBS in urban areas could have hydrological and hydraulic positive effects, particularly in terms of peak flow and runoff volume reduction. Furthermore, the results suggest that small-scale NBS have a potential to be effective to smaller rainfall events, but a combination with large-scale NBS is necessary to cope with extreme events.

The future of the Portuguese (SW Europe) most vulnerable coastal areas under climate change – Part II: Future extreme coastal flooding from downscaled bias corrected wave climate projections

Episodic extreme coastal flooding is considered one of the most serious threats to the global coastlines, endangering infrastructure, ecosystems, and communities. The synchronized effects of extreme wave events, storm surges and astronomical tides are particularly worrying in the context of sea level rise (SLR), and a comprehensive understanding of their future dynamics remains challenging. In this study, an innovative approach for a vulnerability assessment of sandy low-lying coastal areas, based on dynamic ensemble projections is proposed. In the current Part II study, the combined effects of future projected SLR, tides, storm surges and wave action are investigated at five key-locations along the Portuguese coastline, considering projected digital terrain models, built upon the shoreline projections obtained in Part I. Future extreme total water levels are obtained through a probabilistic approach, and extreme wave events are defined considering high wave energy thresholds in a changing climate. Overall, extreme coastal flooding is projected across several urbanized sections along the Portuguese coastline, especially in areas without artificial protection infrastructures. Dune erosion is expected along the sandy stretches, reducing the natural protection against extreme coastal events up to 13.3%, and promoting widespread overtopping, leaving populations more exposed. Future projections reveal the episodic flooding of up to 1.47 km2 of land along the 14 km of analyzed coastline, threatening households and commercial hubs, besides services and communication routes. As physical and human losses may increase substantially in the future, our results call for the implementation of adequate coastal management and adaptation plans, strategically defined to withstand changes until 2100 and beyond.

Public support for flood adaptation policy in Tokyo lowland areas

ABSTRACT Sea level rise induced flooding is projected to cause significant damage to the low-lying coastal areas of many countries around the planet. Many households located in vulnerable areas have already started to adapt to flooding, although some empirical studies indicate that informal adaptation is reaching its limit and that more formal countermeasures by governments will be necessary to cope with the increased flood risks. In such cases, public support for flood adaptation policy is crucial to ensure a successful and timely adaptation, as these strategies can directly affect coastal residents. However, there is limited understanding on the mechanisms and factors that determine public support for flood adaptation policy. Thus, this study proposes a new model – the Foundation of Adaptation Policy Support (FAPS) – which integrates the Protection Motivation Theory and the Risk Information Seeking and Processing models. FAPS was tested using structural equation modelling with latent variables and data that was collected from a household questionnaire survey conducted in the Tokyo lowland areas (n = 388), with the super levee representing a policy that could be applied to sea level rise adaptation. The proposed FAPS model showed a good fit with the collected data, indicating that the strongest predictors of policy support include the perceived effectiveness of the policy and the importance of the issue of flooding to individuals. Other important predictors of policy support include knowledge about flooding, the opinions of surrounding people (i.e. family and friends), and the systematic processing by respondents of information related to floods. The FAPS model sets the foundation for understanding the mechanisms of public support for adaptation policy and provides new insights into designing and planning such policies in practice. Key policy insights Perceived policy effectiveness and the importance of addressing floods are the strongest predictors of public support for adaptation policy. Increasing people’s knowledge about flooding is essential to communicate the importance of adaptation policy. Investigating people’s knowledge and the perceived importance of the issue of flooding prior to designing policies can predict public preferences for certain countermeasures.

Exploring sustainable watershed flood risks management: An innovative TFAHP-TOPSIS methodology in the Georges River Basin, Australia

Floods occur frequently in low-lying coastal and riverine areas, making it crucial to effectively identify the distribution of flood risks in flood-prone areas. Traditional risk assessment models based on Multiple-Criteria Decision-Making (MCDM) method have limitations in both accuracy and effectiveness, particularly in identifying potential risks in watershed floodplains. To refine the flood measurement process, an optimized integrated MCDM model is proposed in this paper. Taking the Georges River Basin in Australia is chosen as an example, twelve risk indicators were identified, considering factors related to hazard, exposure, and vulnerability. To more accurately describe the characteristics of watershed floods, the flood hazard indicators were separated into sub-basins. The Triangular Fuzzy Analytic Hierarchy Process (TFAHP) is employed to optimize the weight calculation, and in combination with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the spatial distribution of flood risks was determined. The results indicate that high-risk areas are concentrated in the central-eastern part of Liverpool, the eastern part of Fairfield, and the central part of Bankstown-Canterbury. Medium to very-high potential risk areas identified by the integrated TFAHP-TOPSIS model are 17.3 % more than the single TFAHP method and 12.7 % more than the TOPSIS method, indicating that the integrated model performs better in identifying potential risks in floodplains. The results can provide decision support for disaster prevention strategies making in flood-prone areas.

Imprints of washover sediments by tropical storm Pabuk 2019 along the coast of the Gulf of Thailand; insight into coastal geomorphological response to storm surge

Tropical storm Pabuk (4th January 2019) struck southern Thailand, causing damage to the low-lying coastal area. The combination of waves, storm surge, and high tide resulted overwash and inundation of regions on the West coast of the Gulf of Thailand (GOT) side. After the event, we conducted a field survey from January 7–10 and 15–20, 2019 to investigate the effect of storm surges and the degree of damage from the site under the eye of storm affected area up to the north 500 km from the landfall sites. This paper investigates how variations in coastal geomorphological features respond to the storm surge generated by tropical storm Pabuk at a regional scale. Coastal damage was observed along the beach from the presence of the scour, beach scarp, knocked down trees, and destroyed buildings and infrastructure. The most damaged area was at Nakhon Si Thammarat (NST), where the tropical storm made landfall with maximum wind speeds of almost 100 km/h and a storm surge height of 5 m. At NST site, the washover deposits extended as far as 80 m from the coastline with a maximum inundation of 330 m. From this study, two types of washover deposits including perched fan and washover terrace were identified. The thickest washover sediment, 60 cm thick, was discovered in a relatively low-lying area adjacent to a small estuary. Mud rip-up clasts, planar stratification, cross stratification, foreset bedding, scouring at base, and sharp and erosional contact are characteristics of sedimentary structures found in storm sediments. Bedform surfaces, such as current ripples with indicated storm surge direction, were well-preserved at several sites. We suggest that the local geomorphological controlling factors, especially coastal elevation have played important roles in the difference of coastal geomorphological responses as well as the type of washover deposits.

Accuracy assessment of global DEMs for the mapping of coastal flooding on a low-lying sandy environment: Cassino Beach, Brazil

Projected sea level rise in the 21st century, driven by climate change, threatens low-lying coastal areas with the risk of persistent flooding. Accurately estimating flooding extent and depth is crucial to implementing effective coastal management, with digital elevation models (DEMs) playing a pivotal role. Intrinsic inaccuracies of DEMs might lead to uncertainty in the flooding projections due to SLR scenarios, which are problematic for decision-makers. This work assessed the accuracy of five global digital elevation models for coastal flooding mapping on a low-lying sandy coastal environment in the south of Brazil (Cassino Beach). Five global DEMs were assessed, namely ALOS-AW3D30, ALOS-PALSAR, ASTER, SRTM, and TanDEM-X, and a high-resolution digital elevation model (created using local aerial vehicle (UAV) imagery) was used as a benchmark. A morphometric comparison was conducted between the five global DEMs and the high-resolution local DEMs. Several statistical metrics were calculated, including the root mean squared error, correlation coefficient, and bias.Additionally, flood depths and extent were computed for different scenarios of sea level rise, and comparisons between the different DEMs were quantified. Results show that among the DEMs evaluated, TanDEM-X DEM achieved the highest correlation with the UAV DEM elevation in the beach and dune region, presenting R² equal to 0.56 and RMSE equal to 0.88 m. On the other hand, the ALOS-AW3D30, ALOS-PALSAR, ASTER, and SRTM DEMs presented low correlation and RMSE values above 2.49 m. The analysis of coastal flooding extension and depths confirms that the TanDEM-X DEM exhibited the highest similarity with the UAV DEM across various sea level scenarios, and it was the only global DEM analyzed capable of capturing dune depressions and roads, which serve as primary pathways for flooding in the type of coastal region under consideration.

Planning for wastewater infrastructure adaptation under deep uncertainty

Infrastructure in low-lying coastal areas faces challenges from climate change, sea level rise, and the impact of compound hazards. Dynamic adaptive pathways planning (DAPP) is increasingly being applied as a way of planning under deep uncertainty. Stress testing for robustness is an integral part of DAPP which provides decision-makers with confidence. We outline a seven-step approach—combining scoping workshops, systems mapping, DAPP, exploratory modelling, robust decision-making, real options analysis and validation workshops—to support decision-making for infrastructure in low-lying coastal areas. We apply the seven steps to two wastewater treatment plant (WWTP) case studies in New Zealand to quantify indicators, signals, triggers and adaptation thresholds within DAPP plans and to identify adaptation pathways that are robust against future uncertainty. Case study one focuses on the implementation of an existing DAPP at Helensville WWTP. Our modelling enabled the challenge of quantifying indicators for adaptation thresholds and triggers to be overcome. We show that an adaptation threshold occurs at 31 cm of RSLR, the trigger point is sufficient lead time to enable relocation, and the indicator is the rate of observed RSLR. Case study one demonstrates in a quantitative way how an existing DAPP can be functionally implemented by a water management agency. Modelling for case study two, the Seaview WWTP, showed that 26 cm and 56 cm of RSLR are key thresholds. Nuisance flooding may occur after 26 cm of RSLR, which could happen as early as 2040 under a high emissions scenario. Inundation of plant assets may occur after 56 cm of RSLR, which could occur as early as 2060. Modelling showed that implementing changes to plant layout would allow the plant to remain on site for its design life (until 2080). Five adaptation archetypes were developed—sequences of adaptive actions that achieve the performance objective of continuing levels of service and avoid inundation of WWTPs. The seven-step approach is a way to stress-test a DAPP, to quantify signals, triggers and adaptation thresholds and to simulate implementation of a DAPP under a range of scenarios. This can facilitate more robust decision-making for wastewater infrastructure assets under future uncertainty.

DeltaDTM: A global coastal digital terrain model

Coastal elevation data are essential for a wide variety of applications, such as coastal management, flood modelling, and adaptation planning. Low-lying coastal areas (found below 10 m +Mean Sea Level (MSL)) are at risk of future extreme water levels, subsidence and changing extreme weather patterns. However, current freely available elevation datasets are not sufficiently accurate to model these risks. We present DeltaDTM, a global coastal Digital Terrain Model (DTM) available in the public domain, with a horizontal spatial resolution of 1 arcsecond (∼30 m) and a vertical mean absolute error (MAE) of 0.45 m overall. DeltaDTM corrects CopernicusDEM with spaceborne lidar from the ICESat-2 and GEDI missions. Specifically, we correct the elevation bias in CopernicusDEM, apply filters to remove non-terrain cells, and fill the gaps using interpolation. Notably, our classification approach produces more accurate results than regression methods recently used by others to correct DEMs, that achieve an overall MAE of 0.72 m at best. We conclude that DeltaDTM will be a valuable resource for coastal flood impact modelling and other applications.

Understanding the impact of climate-induced sea level rise on groundwater inundation in a low-lying coastal area: A numerical simulation in Southeast India

Global warming has led to rising sea levels, severely threatening coastal areas, particularly in low-elevation coastal zones. The groundwater in coastal aquifers of lower elevation is susceptible to groundwater inundation (GWI), an emerging hidden long-term hazard earlier to marine inundation. The inundation is mainly due to the hydraulic connection between sea level and shallow unconfined aquifers, resulting in groundwater upsurging towards the ground surface. To understand the potential impact of sea level rise (SLR) induced GWI on low-lying coasts, a transient state model was simulated and predicted in the Cuddalore regions of South India under 0.3 m, 0.6 m, and 1 m SLR scenarios. The simulation reveals that the aerial extent of groundwater rise (GWR) was 331.9 km2, 566.2 km2, and 650.8 km2 for 0.3 m, 0.6 m, and 1 m SLR scenarios, respectively. About 50% of the response was observed in the northern and central parts of the study area within a 5 km buffer, which is attributed to the deeper groundwater table. In contrast, the southern region exhibited a 10% decline in response due to shallow groundwater discharge to drainage, which dampened the shoaling effect. The present-day shallow groundwater tables in the southern region are more vulnerable to GWI from rising sea levels. Specifically, a 0.3 m SLR could inundate 14.9 km2. In comparison, a 1 m SLR could inundate 40.5 km2 of the area, including the Pichavaram mangrove forest, agricultural land, municipal structures, and the other regions that flooding could threaten. These inundations could have potential impacts, such as wetland loss, agricultural flooding, deteriorating water quality, and infrastructural damage. The present study provides valuable insights into the subsurface hydrodynamic and exposure impacts of sea rise-induced inundations. This can aid coastal engineers, policymakers, and decision-makers to plan appropriate mitigation measures.

The global long-term effects of storm surge flooding on human settlements in coastal areas

People in low-lying coastal areas live under the great threat of damage due to coastal flooding from tropical cyclones. Understanding how coastal population settlements react to such events is of high importance for society to consider future adaptation strategies. Here we generate a new global hydrodynamic data set on tropical cyclone-generated storm surge flooding for the period 1851–2020. By combining this data with spatial data on human populations, we analyze the influence of the depth of storm surge flooding on the rural, urban, and total populations in low elevation coastal zones from 1941–2010. We find that in response to a one standard deviation increase in storm surge flooding depth (0.43 m), the exposed population in a 10×10 km low elevation coastal zone decreases by around 970 individuals on average per decade. This reduction corresponds to 9% of the average population living in an exposed grid cell. Tropical cyclone generated wind speed and rainfall do not influence the relocation of coastal populations. The majority of the threatened population lives in Eastern, South–Eastern, and Southern Asia. We show that the exposed coastal population appears to have adapted over time by reducing its exposure in recent decades. This finding applies to all regions other than North America, Oceania, and Western Asia.

Compound Impact of Storm Surge and Flood Characteristics in Coastal Area Based on Copula

In low-lying coastal areas, the interplay of various factors including precipitation, river flow, and storm surge can lead to greater influence on floods when they occur simultaneously. The copula method was used in this study to investigate the bivariate flood risk of compounding storm surge and river discharge events in the Pearl River Delta (PRD). Our results indicate that while the correlation between storm surge and flood peak (S-Q) was weak, there was a strong dependence between the pairs of storm surge–flood volume (S-V) and storm surge–flood duration (S-D). For these three pairs, the Clayton copula was the optimal function for S-Q, while the Frank copula was the optimal function for S-V and S-D, respectively. When the flood volume exceeds 2.0 × 104 m3/s and the flood duration is more than 10 days, the bivariate hydrologic risk for S-V and S-D is observed to decrease rapidly. Furthermore, the failure probability (FP) would be underestimated when the combined impact of river flow and storm surge is ignored in coastal flood risk assessment. Such bivariate hydrologic risk analysis implies that when determining design values in coastal flood risk assessment, the combined impact of river flow and storm surge should be taken into account.

Bayesian Network Analysis for Shoreline Dynamics, Coastal Water Quality, and Their Related Risks in the Venice Littoral Zone, Italy

The coastal environment is vulnerable to natural hazards and human-induced stressors. The assessment and management of coastal risks have become a challenging task, due to many environmental and socio-economic risk factors together with the complex interactions that might arise through natural and human-induced pressures. This work evaluates the combined effect of climate-related stressors on low-lying coastal areas by applying a multi-risk scenario analysis through a Bayesian Network (BN) approach for the Venice coast. Based on the available open-source and remote sensing data for detecting shoreline changes, the developed BN model was trained and validated with oceanographic variables for the 2015–2019 timeframe, allowing us to understand the dynamics of local-scale shoreline erosion and related water quality parameters. Three “what-if” scenarios were carried out to analyze the relationships between oceanographic boundary conditions, shoreline evolution, and water quality parameters. The results demonstrate that changes in sea surface height and significant wave height may significantly increase the probability of high-erosion and high-accretion states. Moreover, by altering the wave direction, the water quality variables show significant changes in the higher-risk class. The outcome of this study allowed us to identify current and future coastal risk scenarios, supporting local authorities in developing adaptation plans.

Combined storm surge and wave overtopping inundation based on fully coupled storm surge-wave-tide model

Inundations in low-lying coastal areas are commonly caused by compound flooding due to the combination of surge overflow and wave overtopping. The increasing frequency of strong tropical cyclones accompanied by high waves is exacerbating flooding risks. In recent studies, wave-induced flooding (i.e., wave run-up and overtopping) has been reported as a critical component of coastal inundations. However, no clear standard has been established for estimating compound flooding caused by the nonlinear interactions of each component. The present study developed a fully coupled model of surge, wave, tide, and wave overtopping to propose a framework for assessing compound coastal inundations. A series of numerical experiments were conducted in an idealized coastal area to analyze flooding risk comprehensively. The experimental results revealed that the conventional decoupled calculation processes for wave overtopping/run-up tend to overestimate the inundation. The advanced approaches provided stable estimations of offshore wave characteristics that change dynamically under extreme wave conditions, resulting in a reliable wave overtopping calculation. Furthermore, a considerable amount of inundation can occur even when typhoons make landfall during low tidal conditions due to the prolonged occurrence of wave overtopping. The proposed framework can be considered an optimal method for practical flooding risk assessments in coastal areas by estimating compound inundations and including transition processes of surge overflow and wave overtopping/run-up.

Alaska’s climate sensitive Yukon–Kuskokwim Delta supports seven million Arctic-breeding shorebirds, including the majority of six North American populations

Abstract Baseline information about declining North American shorebird populations is essential to determine the effects of global warming at low-lying coastal areas of the Arctic and subarctic, where numerous taxa breed, and to assess population recovery throughout their range. We estimated population sizes on the Yukon–Kuskokwim Delta (YKD) in western Alaska on the eastern edge of the Bering Sea. We conducted ground-based surveys during 2015 and 2016 at 589 randomly selected plots from an area of 35,769 km2. We used stratified random sampling in 8 physiographic strata and corrected population estimates using detection ratios derived from double sampling on a subset of plots. We detected 11,110 breeding individuals of 21 taxa. Western Sandpiper (Calidris mauri), Red-necked Phalarope (Phalaropus lobatus), Dunlin (subspecies C. alpina pacifica), and Wilson’s Snipe (Gallinago delicata) were the most abundant taxa. We estimated that ~7 million individual shorebirds were breeding on the entire YKD in 2015 and 2016. Our surveys of this region provided robust population estimates (coefficient of variations ≤ 0.35) for 14 species. Our results indicate that the YKD supports a large proportion of North America’s breeding populations of the Pacific Golden-Plover (Pluvialis fulva), the western population of a Whimbrel subspecies (Numenius phaeopus hudsonicus), a Bar-tailed Godwit subspecies (Limosa lapponica baueri), Black Turnstone (Arenaria melanocephala), a Dunlin subspecies (C. alpina pacifica), and Western Sandpiper. Our study highlights the importance of breeding shorebirds of this relatively pristine but climatically sensitive deltaic system. Estuaries and deltaic systems worldwide are rapidly being degraded by anthropogenic activities. Our population estimates can be used to refine prior North American population estimates, determine the effects of global warming, and evaluate conservation success by measuring population change over time.

Grid Impact of Wastewater Resource Recovery Facilities-Based Community Microgrids

The overarching goal of this paper is to explore innovative ways to adapt existing urban infrastructure to achieve a greener and more resilient city, specifically on synergies between the power grid, the wastewater treatment system, and community development in low-lying coastal areas. This study addresses the technical feasibility, benefits, and barriers of using wastewater resource recovery facilities (WRRFs) as community-scale microgrids. These microgrids will act as central resilience and community development hubs, enabling the adoption of renewable energy and the provision of ongoing services under emergency conditions. Load flow modeling and analysis were carried out using real network data for a case study in New York City (NYC). The results validate the hypothesis that distributed energy resources (DERs) at WRRFs can play a role in improving grid operation and resiliency.

Dairy farming exposure and impacts from coastal flooding and sea level rise in Aotearoa-New Zealand

Globally, episodic coastal flooding is expected to have increasingly severe impacts on agriculture in low-lying coastal areas, as climate change continues to cause relative sea level rise (RSLR). This study analyses dairy farm exposure and impacts from extreme sea levels (ESL) and RSLR in Aotearoa-New Zealand (A-NZ). Spatio-temporal modelling is undertaken using: 1) a dairy production land layer; 2) a static coastal inundation model from 10, 100, 200 and 500-year annual recurrence interval (ARI) ESL events at 0–2 m RSLR (0.5 m increments); and 3) an Impact State (IS) scheme relating percentage of farmland inundated and depth of flooding at milking shed locations to categorise the severity of damage. Through this analysis we highlight the increasing exposure of the dairy industry to coastal flooding, with 472 farms potentially impacted (at or greater than IS 1) by a 10-year ARI event and 1276 farms exposed to a 500-year ARI event at current sea levels, rising to 1276 (10-year ARI) and 1344 farms (500-year ARI) with 2 m RSLR. RSLR is identified as the factor driving this increase in exposure and severity of impacts to dairying, with the increase in the number of farms impacted in a 500-year compared to 10-year event only 5 % greater when considered with 1 m of RSLR, compared to 37 % greater at 0 m RSLR. This has significant implications for A-NZ where the dairy industry is of high economic and social importance, demonstrating the need for industry targeted climate change adaptation and disaster risk reduction measures.

Opportunity mapping for nature-based solutions: Mitigating storm surge and land erosion in the Caribbean

The islands of the Caribbean are particularly susceptible to the effects of climate change due to their low-lying coastal areas and location within the Atlantic basin's hurricane belt. The UK Overseas Territory of Anguilla is one such island. The predicted increase in the severity of hurricanes and sea-level rise is highly likely to increase the flood risk of already vulnerable island communities. In this study, flood risk and erosion models are used to prioritise opportunity areas for nature-based restoration and to identify those that would have the greatest impact on coastal and in-land flood risk reduction. Two study sites in Anguilla were selected to highlight this ecologically-based modelling approach; Cove Bay and Pond, a degraded sand dune system and brackish pond, and the East End Pond, an Important Bird and Biodiversity Area that floods following heavy rainfall events. At the coastal site, the restoration of mangroves, sand dunes and coral reefs have the potential to provide flood risk reduction up to 500 m inland and protect homes, infrastructure and tourism developments. For the in-land East End Pond, areas of high erosion risk were predominately identified as bare or disturbed land within 1 km of the pond's basin. Habitat restoration of these areas was identified as having the greatest impact on reducing flood risk. The creation of flood risk, opportunity and impact models are invaluable tools that can be used to inform, advocate and justify the implementation of nature-based solutions to a range of stakeholders from policy-makers to local communties.

COMPOUND URBAN COASTAL FLOOD MODELING: INTEGRATING TIDE, WAVES, PRECIPITATION AND HYDRAULIC INFRASTRUCTURE

Compound coastal flooding considers the joint impacts of marine and hydrologic interactions and has recently been identified as an international research priority. Along the US West Coast, winter storms often bring high marine water levels along with energetic waves and precipitation. Hydrodynamic models have been widely used to estimate flood impacts, including extreme estuarine water levels in compound events (e.g., riverine discharge-tide-storm surge interactions), and produced satisfactory results. However, few studies further consider overland flow routing and high-resolution flood mapping in highly urbanized, low-lying coastal areas. Here, an integrated Delft3D-FM based numerical modeling framework is used to explicitly resolve multi-pathway flood processes (i.e., high marine water levels, waves overtopping, precipitation) and infrastructure (e.g., seawalls, storm drains, artificial dunes).