Do the Adaptations of Venice and Miami to Sea Level Rise Offer Lessons for Other Vulnerable Coastal Cities?

Multi-model chain for climate change scenario analysis to support coastal erosion and water quality risk management for the Metropolitan city of Venice

Under the influence of anthropogenic climate change, hazardous climate and weather events are increasing in frequency and severity, with wide-ranging impacts across ecosystems and landscapes, especially fragile and dynamic coastal zones. The presented multi-model chain approach combines ocean hydrodynamics, wave fields, and shoreline extraction models to build a Bayesian Network-based coastal risk assessment model for the future analysis of shoreline evolution and seawater quality (i.e., suspended particulate matter, diffuse attenuation of light). In particular, the model was designed around a baseline scenario exploiting historical shoreline and oceanographic data within the 2015-2017 timeframe. Shoreline erosion and water quality changes along the coastal area of the Metropolitan city of Venice were evaluated for 2021-2050, under the RCP8.5 future scenario. The results showed a destabilizing trend in both shoreline evolution and seawater quality under the selected climate change scenario. Specifically, after a stable period (2021-2030), the shoreline will be affected by periods of erosion (2031-2040) and then accretion (2041-2050), with a simultaneous decrease in seawater quality in terms of higher turbidity. The decadal analysis and sensitivity evaluation of the input variables demonstrates a strong influence of oceanographic variables on the assessed endpoints, highlighting how the factors are strongly connected. The integration of regional and global climate models with Machine Learning and satellite imagery within the proposed multi-model chain represents an innovative update on state-of-the-art techniques. The validated outputs represent a good promise for better understanding the varying impacts due to future climate change conditions (e.g., wind, wave, tide, and sea-level). Moreover, the flexibility of the approach allows for the quick integration of climate and multi-risk data as it becomes available, and would represent a useful tool for forward-looking coastal risk management for decision-makers.

Exploring spatial feedbacks between adaptation policies and internal migration patterns due to sea-level rise

Climate change-induced sea-level rise will lead to an increase in internal migration, whose intensity and spatial patterns will depend on the amount of sea-level rise; future socioeconomic development; and adaptation strategies pursued to reduce exposure and vulnerability to sea-level rise. To explore spatial feedbacks between these drivers, we combine sea-level rise projections, socioeconomic projections, and assumptions on adaptation policies in a spatially-explicit model ('CONCLUDE'). Using the Mediterranean region as a case study, we find up to 20 million sea-level rise-related internal migrants by 2100 if no adaptation policies are implemented, with approximately three times higher migration in southern and eastern Mediterranean countries compared to northern Mediterranean countries. We show that adaptation policies can reduce the number of internal migrants by a factor of 1.4 to 9, depending on the type of strategies pursued; the implementation of hard protection measures may even lead to migration towards protected coastlines. Overall, spatial migration patterns are robust across all scenarios, with out-migration from a narrow coastal strip and in-migration widely spread across urban settings. However, the type of migration (e.g. proactive/reactive, managed/autonomous) depends on future socioeconomic developments that drive adaptive capacity, calling for decision-making that goes well beyond coastal issues.

Combining remote sensing analysis with machine learning to evaluate short-term coastal evolution trend in the shoreline of Venice

With increasing storminess and incessant sea-level rise, coastal erosion is becoming a primary issue along many littorals in the world. To cope with present and future climate change scenarios, it is important to map the shoreline position over years and assess the coastal erosion trends to select the best risk management solutions and guarantee a sustainable management of communities, structures, and ecosystems. However, this objective is particularly challenging on gentle-sloping sandy coasts, where also small sea-level changes trigger significant morphological evolutions. This study presents a multidisciplinary study combining satellite images with Machine Learning and GIS-based spatial tools to analyze short-term shoreline evolution trends and detect erosion hot-spots on the Venice coast over the period 2015-2019. Firstly, advanced image preprocessing, which is not frequently adopted in coastal erosion studies, was performed on satellite images downloaded within the same tidal range. Secondly, different Machine Learning classification methods were tested to accurately define shoreline position by recognizing the land-sea interface in each image. Finally, the application of the Digital Shoreline Analysis System tool was performed to evaluate and visualize coastal changes over the years. Overall, the case study littoral reveals to be stable or mainly subjected to accretion. This is probably due to the high presence of coastal protection structures that stabilize the beaches, enhancing deposition processes. In detail, with respect to the total length of the considered shoreline (about 83 km), 5 % of the coast is eroding, 36 % is stable, 52 % is accreting and 7 % is not evaluable. Despite a significant coastal erosion risk was not recognized within this region, well-delimited erosion hot-spots were mapped in correspondence of Caorle, Jesolo and Cavallino-Treporti municipalities. These areas deserve higher attention for territorial planning and prioritization of adaptation measures, facing climate change scenarios and sea-level rise emergencies in the context of Integrated Coastal Zone Management.

Where are People Dying in Disasters, and Where is it Being Studied? A Mapping Review of Scientific Articles on Tropical Cyclone Mortality in English and Chinese

Background:

Tropical cyclones are a recurrent, lethal hazard. Climate change, demographic, and development trends contribute to increasing hazards and vulnerability. This mapping review of articles on tropical cyclone mortality assesses geographic publication patterns, research gaps, and priorities for investigation to inform evidence-based risk reduction.

Methods:

A mapping review of published scientific articles on tropical cyclone-related mortality indexed in PubMed and EMBASE (English) and SINOMED and CNKI (Chinese), focusing on research approach, location, and storm information, was conducted. Results were compared with data on historical tropical cyclone disasters.

Findings:

A total of 150 articles were included, 116 in English and 34 in Chinese. Nine cyclones accounted for 61% of specific event analyses. The United States (US) reported 0.76% of fatalities but was studied in 51% of articles, 96% in English and four percent in Chinese. Asian nations reported 90.4% of fatalities but were studied in 39% of articles, 50% in English and 50% in Chinese. Within the US, New York, New Jersey, and Pennsylvania experienced 4.59% of US tropical cyclones but were studied in 24% of US articles. Of the 12 articles where data were collected beyond six months from impact, 11 focused on storms in the US. Climate change was mentioned in eight percent of article abstracts.

Interpretation:

Regions that have historically experienced high mortality from tropical cyclones have not been studied as extensively as some regions with lower mortality impacts. Long-term mortality and the implications of climate change have not been extensively studied nor discussed in most settings. Research in highly impacted settings should be prioritized.

An Analysis of Resilience Planning at the Nexus of Food, Energy, Water, and Transportation in Coastal US Cities

Climate change poses increased risks to coastal communities and the interconnected infrastructure they rely on, including food, energy, water, and transportation (FEWT) systems. Most coastal communities in the US are ill-prepared to address these risks, and resilience planning is inconsistently prioritized and not federally mandated. This study examined the resilience plans of 11 coastal US cities to understand 1. How FEWT systems were considered within resilience plans and, 2. How nexus principles or elements critical to a nexus approach were incorporated within resilience plans. A “Nexus Index” was created to examine the incorporation of nexus principles, which included partnerships and collaborations, reference to other plans or reports, discussion of co-benefits, cascading impacts, and inclusion of interdisciplinary or cross-silo principles. These principles were used to score each action within the resilience plans. Results showed that only eight actions (1% of all actions across the 11 plans) focused on the connections among FEWT systems within the resilience plans. The transportation system was associated with the most actions, followed by the energy system, water system, and the food system. While FEWT systems were not consistently included, there was evidence from the Nexus Index that the plans included elements critical to a nexus approach, such as the inclusion of partnerships and reference to co-benefits with the actions they designed to build resilience. The heterogeneity among the systems that each plan emphasized reflects the heterogeneity among the challenges that each city faces. While context-specific differences in resilience plans across cities are expected, some consistency in addressing certain infrastructural needs and their nexus interactions may greatly benefit and improve the implementation of resilience planning.