Heterogeneity of values for coastal flood risk management with nature-based solutions

Investigating socio-ecological vulnerability to climate change via remote sensing and a data-driven ranking algorithm

The necessity for extensive historical data, variables, and weight determination still presents challenges and complexity, notwithstanding the growth in research on socio-ecological vulnerability to climate change. In order to fill in these gaps, this study used China's Fujian Province as a case study to propose a unique strategic approach for studying socio-ecological vulnerability to climate change from 2000 to 2020 by utilizing remote sensing and the framework of the Intergovernmental Panel on Climate Change. In a GIS scenario, this method employs a comprehensive framework with a wide variety of indicators and a data-driven ranking algorithm. The findings of this study revealed a moderate degree of socio-ecological vulnerability throughout the coast, with significant regional heterogeneity in its spatial distribution. Furthermore, throughout the course of the two-decade, the highly vulnerable zones expanded by 6.04%, outpacing the low-risk areas by 1116 km2 (61.41%) and 2066 km2 (123.39%), respectively, with the majority of the increase taking place in Fuzhou and Ningde. These changes in vulnerability were shown to be principally influenced by changes in vegetation, precipitation, GDP, and land use (LULC). The major influence of precipitation was highlighted further in the spatial autocorrelation analysis, which demonstrated a close correlation between growing socio-ecological vulnerability and increased precipitation. To conclude, this study's methodology differs from other socio-ecological vulnerability studies in that it is flexible and self-sufficient, offering users a choice of weight application. It also gives a more useful, accurate, and suggestive model to enable decision-makers or stakeholders build strategies or ideas for constructing more resilient coastal systems.

Top ten priorities for global saltmarsh restoration, conservation and ecosystem service research

Coastal saltmarshes provide globally important ecosystem services including 'blue carbon' sequestration, flood protection, pollutant remediation, habitat provision and cultural value. Large portions of marshes have been lost or fragmented as a result of land reclamation, embankment construction, and pollution. Sea level rise threatens marsh survival by blocking landward migration where coastlines have been developed. Research-informed saltmarsh conservation and restoration efforts are helping to prevent further loss, yet significant knowledge gaps remain. Using a mixed methods approach, this paper identifies ten research priorities through an online questionnaire and a residential workshop attended by an international, multi-disciplinary network of 35 saltmarsh experts spanning natural, physical and social sciences across research, policy, and practitioner sectors. Priorities have been grouped under four thematic areas of research: Saltmarsh Area Extent, Change and Restoration Potential (including past, present, global variation), Spatio-social contexts of Ecosystem Service delivery (e.g. influences of environmental context, climate change, and stakeholder groups on service provisioning), Patterns and Processes in saltmarsh functioning (global drivers of saltmarsh ecosystem structure/function) and Management and Policy Needs (how management varies contextually; challenges/opportunities for management). Although not intended to be exhaustive, the challenges, opportunities, and strategies for addressing each research priority examined here, providing a blueprint of the work that needs to be done to protect saltmarshes for future generations.

Adaptation strategies for future coastal flooding: Performance evaluation of green and grey infrastructure in South Korea

Climate change is contributing to an increasing frequency and intensity of floods in Korea. This study predicts areas with a high probability of flooding in coastal areas of South Korea owing to future climate change, which is likely to cause extreme rainfall and sea-level rise, using a spatiotemporal downscaled future climate change scenario with random forest, artificial neural network, and k-nearest neighbor techniques. In addition, the change in coastal flooding risk probability according to the application of different adaptation strategies (green spaces and seawalls) was identified. The results showed a clear difference in the risk probability distribution in the absence and presence of either adaptation strategy. Their effectiveness in moderating future flooding risks is subject to change owing to strategy type, geographic region, and urbanization intensity and the results show that green spaces are slightly more effective than seawalls when forecasting for 2050. This demonstrates the importance of a nature-based strategy. Moreover, this study highlights the need to prepare adaptation measures according to regional characteristics to mitigate the impact of climate change. Korea is surrounded by seas on three sides that have independent geophysical and climate characteristics. The south coast has a higher risk of coastal flooding than the east and west coasts. In addition, a higher urbanization rate is associated with a higher risk probability. This implies that climate change response strategies for coastal cities are necessary as the population and socioeconomic activities of coastal urban areas are likely to increase in the future.

Assessment of Air Quality and Meteorological Changes Induced by Future Vegetation in Madrid

Nature-based solutions and green urban infrastructures are becoming common measures in local air quality and climate strategies. However, there is a lack of analytical frameworks to anticipate the effect of such interventions on urban meteorology and air quality at a city scale. We present a modelling methodology that relies on the weather research and forecasting model (WRF) with the building effect parameterization (BEP) and the community multiscale air quality (CMAQ) model and apply it to assess envisaged plans involving vegetation in the Madrid (Spain) region. The study, developed within the VEGGAP Life project, includes the development of two detailed vegetation scenarios making use of Madrid’s municipality tree inventory (current situation) and future vegetation-related interventions. An annual simulation was performed for both scenarios (considering constant anthropogenic emissions) to identify (i) variations in surface temperature and the reasons for such changes, and (ii) implications on air-quality standards according to EU legislation for the main pollutants (PM10, PM2.5, NO2 and O3). Our results suggest that vegetation may have significant effects on urban meteorology due to changes induced in relevant surface properties such as albedo, roughness length or emissivity. We found a net-heating effect of around +0.18 °C when trees are introduced in dry, scarcely vegetated surfaces in the city outskirts. In turn, this enhances the planetary boundary layer height (PBLH), which brings about reductions in ambient concentrations of relevant pollutants such as NO2 (in the range of 0.5–0.8 µg m−3 for the annual mean, and 2–4 µg m−3 for the 19th highest 1 h value). Conversely, planting new trees in consolidated urban areas causes a cooling effect (up to −0.15 °C as an annual mean) that may slightly increase concentration levels due to less-effective vertical mixing and wind-speed reduction caused by increased roughness. This highlights the need to combine nature-based solutions with emission-reduction measures in Madrid.