Jinal Jain

and 1 more

Number: 1424249 Marginalized vulnerable coastal communities living along the urban coasts are continuously under the dual threat of natural hazards and the adverse impact of infrastructure development, which results in the increase of cumulative risk for these communities. Further, the irreversible impacts of climate change have also exacerbated the risks associated with aging infrastructure and vulnerable coastal communities. Therefore, strengthening the climate resilience of such communities stands as a duly acknowledged priority for developing nations. One of the possible solutions to strengthen climate resilience is through the development and implementation of sustainable hybrid infrastructure alternatives. In this work, we characterized the data-driven Coastal Infrastructure Resilience Index (CIRI) to assess the performance of existing coastal infrastructure along the coast of Mumbai City in India. This study thoroughly utilized the potential of high-resolution remote-sensing imagery and socio-economic parameters from SEDAC data to derive CIRI. The robustness of the CIRI is improved with integrated value function and expert knowledge. As both grey infrastructure, such as seawalls, levees, and bulkheads and green infrastructure, such as salt marshes, mangroves, beaches, dunes, oysters and coral reefs have limited resilience in a multi-hazard environment, we identified the major hotspots of concerns through CIRI to propose the plausible hybrid (green-grey) infrastructure alternatives (green-grey) using Adaptive Gradient Framework for Mumbai’s coastal context. Adapting Hybrid infrastructure alternatives empowers coastal communities with heightened climate benefits and co-benefits. The major findings of this study contribute as a science-policy instrument to localize the Sustainable Development Goals 11(11.5, 11. b), 13, and 14.2 of the United Nations.Keyword- Integrated Coastal Management, Adaptation, risk-informed, Urban coastal areas, decision-analysis

Ravinder Dhiman

and 2 more

Environmental spatial planning of urban coastal regions is critical for sustainable development and designing of coastal resilience in developing countries. The process of environmental spatial planning in coastal regions involves classification of areas into different categories by retaining the synergy between environmental conservation and urban development. Existing coastal regulations for classification of coastal regions in India are based on the subjective approaches. In this study, a quantitative approach is developed by coupling geospatial science and multicriteria decision making in which we prioritized the different physical coastal features quantitatively based on the environmental sensitivity of particular physical coastal feature for the integrated natural coastal ecosystem. Afterwards, these quantitative ranking values of coastal features are combined with linear weighting schemes to derive distinct categories of urban coastal regions spatially, where each category embodies the unique environmental sensitivity. A final map indicating the environmental sensitivity of different coastal regions is prepared. Uncertainty analysis for different weighting schemes was performed to assess the robustness of the developed approach. Finally, we carried out a comparative assessment of the prevailing method of coastal area classification being used by planning authorities and the application of this quantitative approach along the coast of Mumbai, India. Results of comparison clearly demonstrate the effectiveness of the quantitative approach for environmental spatial planning in urban coastal regions. Essentially, the method is found useful for highlighting the locations which need special consideration by planning authorities for the application of inclusive coastal management measures. Furthermore, this approach is modular and scalable, which will facilitate the environmental spatial planning of urban coastal regions based on scientific principles in different coastal cities in developing countries.