Sea Level Rise Vulnerability Assessment Research Articles

Urban Vulnerability Assessment of Sea Level Rise in Singapore through the World Avatar

This paper explores the application of The World Avatar (TWA) dynamic knowledge graph to connect isolated data and assess the impact of rising sea levels in Singapore. Current sea level rise vulnerability assessment tools are often regional, narrow in scope (e.g., economic or cultural aspects only), and are inadequate in representing complex non-geospatial data consistently. We apply TWA to conduct a multi-perspective impact assessment of sea level rise in Singapore, evaluating vulnerable buildings, road networks, land plots, cultural sites, and populations. We introduce OntoSeaLevel, an ontology to describe sea level rise scenarios, and its impact on broader elements defined in other ontologies such as buildings (OntoBuiltEnv ontology), road networks (OpenStreetMap ontology), and land plots (Ontoplot and Ontozoning ontology). We deploy computational agents to synthesise data from government, industry, and other publicly accessible sources, enriching buildings with metadata such as property usage, estimated construction cost, number of floors, and gross floor area. An agent is applied to identify and instantiate the impacted sites using OntoSeaLevel. These sites include vulnerable buildings, land plots, cultural sites, and populations at risk. We showcase these sea level rise vulnerable elements in a unified visualisation, demonstrating TWA’s potential as a planning tool against sea level rise through vulnerability assessment, resource allocation, and integrated spatial planning.

Sea level rise vulnerability assessment for State wildlife areas surrounding Humboldt Bay, northern California

Humboldt Bay has the highest rate of sea level rise (SLR) in California (47.2 cm/century). Due to compaction and tectonic subsidence, former tidelands and pastures behind dikes surrounding Humboldt Bay are lower in elevation than bay waters at high tide. Adaptation to future climate change and SLR requires that resource managers understand vulnerability and risk to each wildlife area at a local level, because adaptation to SLR is a risk-based management strategy against an uncertain future requiring site-specific solutions. We conducted a vulnerability assessment of the shoreline of three State wildlife areas surrounding Humboldt Bay: Elk River (ERWA), Fay Slough (FSWA), and Mad River Slough (MRSWA). Breaching of shorelines that border each refuge has the potential to flood a diversity of wetland communities, wildlife habitats, and critical infrastructure within the historic tidal inundation footprint. The total length of diked 1-m shoreline segments potentially impacted by SLR was 6.2 km. The relationship between vulnerability and elevation of diked shoreline segments was significantly correlated for all wildlife areas. Vulnerability of diked shoreline was significantly affected by the type of surface covering. MRSWA had the highest percentage of shoreline fortified with concrete and rock (62.2% [2,876 m]), followed by ERWA (0.3% [2,815 m]). ERWA and FSWA had the greatest percentage of shoreline anchored by vegetation (99.3% [2,834 m] and 91.5% [3,385 m], respectively); FSWA had the highest percentage of unvegetated (i.e., exposed) shoreline (7.4% [252 m]); and ERWA had the highest percentage (86.6% [436 m]) of diked shoreline followed by FSWA (69.2% [633 m]) and MRSWA (33.0% [276 m]). The highest overall ratings of shoreline vulnerability were at ERWA (91.7%), followed by FSSWA (72,4%), and MRSWA (34.4%). Issues related to retention of unique characteristics of each wildlife area, natural resources and species at risk, and adaptive planning for future SLR are discussed.

A NEW FRAMEWORK FOR ACCURACY ASSESSMENT OF LIDAR-DERIVED DIGITAL ELEVATION MODELS

Abstract. Existing approaches to accuracy assessment of LiDAR-derived DEM are typically based on statistical methodology and focus on vertical accuracy. This paper presents a new framework which calls for assessment of not only a DEM’s vertical accuracy, but also its ability to preserve a point’s elevation rank in the bare earth topographic surface. New methods to assess each aspect are presented. For DEM’s vertical accuracy, approximation theory from numerical analysis is used to quantify the total error at each DEM point as well as its three error components – sensor error, ground error, and interpolation error. For DEM’s elevation order which is critical to model terrain structure, the concept of isomorphism in set theory is drawn as the mathematical rationale and Kendall’s rank correlation efficient is used to quantify the accuracy. The new framework is illustrated using a DEM derived from LiDAR for sea-level rise vulnerability assessment of a tidal salt marsh. Compared to conventional methods based on statistics, the new framework and methods produce detailed mapping of error distribution thus enable the identification of the main sources of error and where improvement is needed most. Results call for re-evaluation of the current practice of assessing filtering accuracy in LiDAR data processing and further research on relative elevation and isomorphism.

Elevations of mangrove forests of Pohnpei, Micronesia

Mangrove surface elevation is the crux of mangrove vulnerability to sea level rise. Local topography influences critical periods of tidal inundation that govern distributions of mangrove species and dictates future distributions. This study surveyed ground surface elevations of the extensive mangroves of Pohnpei, Federated States of Micronesia, integrating four survey technologies to solve issues of canopy blocking satellite reception, dense aerial roots limiting line-of-sight, and remoteness from surveyed datums. The island-wide average elevation of the mangrove seaward edge was −0.57 ± 0.13 m relative to MSL, while the landward average elevation was 0.33 ± 0.12 m relative to MSL. The overall mangrove elevation range was thus estimated to be 0.90 m. Mangrove species Bruguiera gymnorrhiza, Rhizophora apiculata and Sonneratia alba had large, overlapping elevation ranges, while Rhizophora stylosa occurred low in the tide frame. These species are likely to be less vulnerable to rising sea level given their greater range of elevation occurrence and presumably flooding tolerance, and hence have the highest adaptive capacity to rising sea level. Some landward edge species had very narrow elevation ranges, increasing their vulnerability to sea-level rise, with adjacent potential upland migration areas limited due to steep topography and human development. Pohnpei mangroves occupied 74% of the mean tidal range, similar to surveys elsewhere in the Pacific. This study demonstrates how more extensive understanding of the elevation distributions of intertidal species can contribute to sea-level rise vulnerability assessments, to allow prioritised climate change adaptation. However, more work is needed in standardizing approaches for global comparisons.

Evaluating sea-level rise vulnerability assessments in the USA

Many coastal communities around the world are increasingly faced with pressure from sea level rise (SLR). Adapting to the impacts of SLR is now considered inevitable. Many coastal communities in the USA have started to invest in vulnerability assessments that seek to identify the degree of future risk induced by SLR and key vulnerable sectors as well as to provide a sound factual basis for designing and implementing adaptations. However, no study has systematically analyzed the content of these emerging assessments and their quality. This study aims to address this gap by evaluating 64 SLR vulnerability assessments in the USA using an established multi-criteria evaluation framework and by identifying governance factors that affect assessment quality. This study is the first baseline study to understand how the vulnerability of SLR has been assessed by US governments and, more importantly, shed light on pathways for their future improvement. Our analysis finds that the content and quality of the existing assessments vary widely. One-sided assessments that only consider physical exposure are common, and most assessments do not include plans for adaptations. The wealth of the area, amount of funding, mainstreaming efforts, and public awareness are all positively correlated with the assessment quality. We also find that assessments primarily authored by planning staff are lower in quality than those conducted through collaboration. Our findings offer comparative, empirical knowledge for urban planners and coastal managers to improve future vulnerability assessments and adaptation planning for SLR.

Assessing the sea-level rise vulnerability in coastal communities: A case study in the Tampa Bay Region, US

Sea-level rise (SLR) has drawn unprecedented attention from coastal communities around the world. In fact, many are already being affected and, in response, SLR vulnerability assessments have increasingly emerged in the US as the local communities' first attempt on the adaptation planning agenda. However, to date, little is known about these early planning endeavors in terms of how vulnerability is conceptualized and operationalized. By reviewing the current local SLR vulnerability assessments in the US, we find that most are only focusing on their biophysical exposure to SLR overlooking other important vulnerability factors including sensitivity and adaptive capacity. The limited number of SLR scenarios and the lack of consideration for extreme events are also considered as the major deficiencies. To fill these gaps, we propose a conceptual vulnerability assessment framework to operationalize the full concept of vulnerability and test it through a case study in the Tampa Bay region, Florida. By comparing the vulnerability results of the common practice with our proposed framework, we find large variances in the resulting findings stressing the importance of selecting the proper assessment approach. This paper finally concludes with urban planning and governance implications and future research directions. Coastal planner and managers wanting to improve their understanding of the communities' vulnerability to SLR will benefit from this study.

Sea-Level Rise Vulnerability Assessment of Bicycle and Trail Networks

AbstractTransportation infrastructure continues to be at risk to climate change impacts including sea-level rise (SLR) inundation. Past studies have primarily focused on motorized facilities; howev...

Modeling multiple sea level rise stresses reveals up to twice the land at risk compared to strictly passive flooding methods

Planning community resilience to sea level rise (SLR) requires information about where, when, and how SLR hazards will impact the coastal zone. We augment passive flood mapping (the so-called “bathtub” approach) by simulating physical processes posing recurrent threats to coastal infrastructure, communities, and ecosystems in Hawai‘i (including tidally-forced direct marine and groundwater flooding, seasonal wave inundation, and chronic coastal erosion). We find that the “bathtub” approach, alone, ignores 35–54 percent of the total land area exposed to one or more of these hazards, depending on location and SLR scenario. We conclude that modeling dynamic processes, including waves and erosion, is essential to robust SLR vulnerability assessment. Results also indicate that as sea level rises, coastal lands are exposed to higher flood depths and water velocities. The prevalence of low-lying coastal plains leads to a rapid increase in land exposure to hazards when sea level exceeds a critical elevation of ~0.3 or 0.6 m, depending on location. At ~1 m of SLR, land that is roughly seven times the total modern beach area is exposed to one or more hazards. Projected increases in extent, magnitude, and rate of persistent SLR impacts suggest an urgency to engage in long-term planning immediately.

Satellite remote sensing to monitor mangrove forest resilience and resistance to sea level rise

Abstract Coastal ecosystems, such as mangroves, provide key ecosystem services for climate change mitigation and adaptation. However, combined anthropogenic activities and climatic change‐driven sea level rise (SLR) pose a severe threat to their global persistence, and to the continued delivery of these services. Mangrove vulnerability to SLR depends upon capacity for both resilience (landward migration) and resistance (maintained functioning with the existing distribution), which are in turn hindered by extractive activities and coastal infrastructure development. Limited landscape‐scale data availability means existing SLR vulnerability assessment frameworks lack rigorous quantification of these discrete processes. Here we develop and implement a novel multi‐product (multispectral, microwave, derived‐product) open‐access satellite remote sensing approach to assess both coastal ecosystem SLR resilience and resistance capacity in multiple mangrove sites across the world, and landscape‐level and anthropogenic factors driving these capacities. Our approach allows comparative ranking of resilience and resistance capacities across sites, based on relative observed ecosystem change (biomass, distribution) and in constraints to these two components of SLR vulnerability. We observe mostly low SLR resilience and resistance across our case study sites. Furthermore, we find that site‐specific resilience and resistance capacities and constraints can be highly incongruent, highlighting the importance of comprehensive SLR vulnerability monitoring for effective management. High within‐site variation was also detected in resilience and resistance capacities and their constraints. This underlines the importance of spatially explicit monitoring at extensive spatial scales to inform decision making. The methodology developed and repeat‐pass imagery employed adds to the remote monitoring and assessment toolkit for adaptive coastal ecosystem management under SLR, providing a new approach to inform conservation and management priority assessments in data‐deficient regions.

ELEVATION-BASED SEA-LEVEL RISE VULNERABILITY ASSESSMENT OF MINDANAO, PHILIPPINES: ARE FREELY-AVAILABLE 30-M DEMS GOOD ENOUGH?

Abstract. We assessed the vertical accuracies and uncertainties of three freely-available global DEMs as inputs to elevation-based sea-level rise vulnerability assessment of Mindanao, Philippines – an area where above average SLR of 14.7 mm/year was recently found. These DEMs are the Shuttle Radar Topography Mission (SRTM) DEM, ASTER Global DEM (GDEM Version 2), and ALOS World 3D-30 (AW3D30). Using 2,076 ground control points, we computed each DEM’s vertical accuracies and uncertainties, and from these we determined the smallest increment of sea-level rise (SLRImin) that should be considered when using the DEMs for SLR impact assessment, as well as the Minimum Planning Timeline (TLmin) for an elevation-based SLR assessment. Results of vertical accuracy assessment revealed Root Mean Square Errors of 9.80 m for ASTER GDEM V2, 5.16 m for SRTM DEM, and 4.32 m for AW3D30. Vertical uncertainties in terms of the Linear Error at 95 % Confidence (LE95) were found to be as follows: 19.21 m for ASTER GDEM V2, 10.12 m for SRTM DEM, and 8.47 m for AW3D30. From these, we found that ASTER GDEM2 is suitable to model SLR increments of at least 38.41 m and it will take 2,613 years for the cumulative water level increase of 14.7 mm/year to reach the minimum SLR increment afforded by this DEM. For the SRTM DEM, SLRImin and TLmin were computed as 20.24 m and 1,377 years, respectively. For the AW3D30, SLRImin and TLmin were computed as 16.92 m and 1,151 years, respectively. These results suggest that the readily available global DEMs' suitability for mapping coastal inundations due to SLR in our study area is limited by their low vertical accuracies and high uncertainties. All the three DEMs do not have the necessary accuracy and minimum uncertainties that will make them suitable for mapping inundations of Mindanao at smaller increments of SLR (e.g., SLR ≤ 5 m). Hence, users who apply any of these DEMs for SLR impact assessment at SLRIs lower than the DEM’s SLRImin must be cautious in reporting the areas of SLR vulnerable zones. Reporting the inundated areas as a range instead of a singular value for a given SLR scenario can highlight the inherent accuracy and uncertainty of the DEM used in the assessment.

Incorporating uncertainty of future sea-level rise estimates into vulnerability assessment: A case study in Kahului, Maui

Accurate sea-level rise (SLR) vulnerability assessments are essential in developing effective management strategies for coastal systems at risk. In this study, we evaluate the effect of combining vertical uncertainties in Light Detection and Ranging (LiDAR) elevation data, datum transformation and future SLR estimates on estimating potential land area and land cover loss, and whether including uncertainty in future SLR estimates has implications for adaptation decisions in Kahului, Maui. Monte Carlo simulation is used to propagate probability distributions through our inundation model, and the output probability surfaces are generalized as areas of high and low probability of inundation. Our results show that considering uncertainty in just LiDAR and transformation overestimates vulnerable land area by about 3 % for the high probability threshold, resulting in conservative adaptation decisions, and underestimates vulnerable land area by about 14 % for the low probability threshold, resulting in less reliable adaptation decisions for Kahului. Not considering uncertainty in future SLR estimates in addition to LiDAR and transformation has variable effect on SLR adaptation decisions depending on the land cover category and how the high and low probability thresholds are defined. Monte Carlo simulation is a valuable approach to SLR vulnerability assessments because errors are not required to follow a Gaussian distribution.

Consideration of Vertical Uncertainty in Elevation-Based Sea-Level Rise Assessments: Mobile Bay, Alabama Case Study

Gesch, D.B., 2013. Consideration of vertical uncertainty in elevation-based sea-level rise assessments: Mobile Bay, Alabama case study, In: Brock, J.C.; Barras, J. A., and Williams, S.J. (eds.), Understanding and Predicting Change in the Coastal Ecosystems of the Northern Gulf of Mexico, Journal of Coastal Research, Special Issue No. 63, pp. 197–210, Coconut Creek (Florida), ISSN 0749-0208.The accuracy with which coastal topography has been mapped directly affects the reliability and usefulness of elevationbased sea-level rise vulnerability assessments. Recent research has shown that the qualities of the elevation data must be well understood to properly model potential impacts. The cumulative vertical uncertainty has contributions from elevation data error, water level data uncertainties, and vertical datum and transformation uncertainties. The concepts of minimum sealevel rise increment and minimum planning timeline, important parameters for an elevation-based sea-level rise assessment, are used in recognition of the inherent vertical uncertainty of the underlying data. These concepts were applied to conduct a sea-level rise vulnerability assessment of the Mobile Bay, Alabama, region based on high-quality lidar-derived elevation data. The results that detail the area and associated resources (land cover, population, and infrastructure) vulnerable to a 1.18-m sea-level rise by the year 2100 are reported as a range of values (at the 95% confidence level) to account for the vertical uncertainty in the base data. Examination of the tabulated statistics about land cover, population, and infrastructure in the minimum and maximum vulnerable areas shows that these resources are not uniformly distributed throughout the overall vulnerable zone. The methods demonstrated in the Mobile Bay analysis provide an example of how to consider and properly account for vertical uncertainty in elevation-based sea-level rise vulnerability assessments, and the advantages of doing so.

Using enhanced dasymetric mapping techniques to improve the spatial accuracy of sea level rise vulnerability assessments

This article reports on the application of dasymetric mapping techniques to interpolate and disaggregate block group population counts to smaller areal units (i.e., tax parcels) and derive surface population models with more realistic representations of population distributions in our residential study area in Miami-Dade, Florida. Three methods of dasymetric interpolation were tested: (i) binary, (ii) three-class, and (iii) limiting variable. Our enhanced limiting variable approach introduced an adjustment factor for parcel vacancy rates in the dasymetric calculations, and applied dasymetric mapping techniques to disaggregate future population projections to the tax lot level of analysis. The limiting variable interpolation generated the lowest coefficient of variation (0.188), followed by the three-class interpolation (0.645). We also found that population densities vary substantially within land use classes of single family, medium density and high density classes, and these variations also highlighted the importance of incorporating vacancy rates when interpolating population counts to categorical land use data. Overall, the enhanced dasymetric mapping technique is particularly useful for examining the impact of sea-level rise as its derivatives are compatible with high resolution LiDAR and orthoimagery data. Coastal counties can also benefit from such high resolution surface population models to enhance the accuracy of hazard-related vulnerability assessments and to guide the development of relevant shore zone conservation and adaptation strategies.

Sea level rise vulnerability assessment in coastal areas in Rio de Janeiro state, Brazil

This article was submitted without an abstract, please refer to the full-text PDF file.

Sea level rise vulnerability assessment in coastal areas in Rio de Janeiro state, Brazil

Sea level rise vulnerability assessment in coastal areas in Rio de Janeiro state, Brazil

Towards Successful Adaptation to Sea-Level Rise along Europe's Coasts

Adaptation is defined as the planned or unplanned, reactive or anticipatory, successful or unsuccessful response of a system to a change in its environment. This paper examines the current status of adaptation to sea-level rise and climate change in the context of European coasts. Adaptation can greatly reduce the impact of sea-level rise (and other coastal changes), although it requires adjustment of coastal management policies to changing circumstances. Consequently, adaptation is a social, political, and economic process, rather than just a technical exercise, as it is often conceived. The Synthesis and Upscaling of sea-level Rise Vulnerability Assessment Studies project has shown that adaptation to sea-level rise is widely divergent among European countries. Crudely, four groups of countries were identified: 1. Those that do not worry about accelerated sea-level rise and should not as their coasts are not susceptible 2. Those that do not worry as they have more urgent problems 3. Those that do not worry but probably should 4. Those that do worry and have started to adapt At the European Union level, while coastal management is a focus, this effort is mainly targeted at today's problems. Hence, this paper suggests the need for a concerted effort to address adaptation in coastal zones across Europe. Sharing of experience among countries would facilitate this process.