Author
Listed:
- J. Shanthini
(SRM Institute of Science & Technology, Department of Data Science and Business Systems, School of Computing, College of Engineering and Technology)
- J. Dhanalakshmi
(SRM Institute of Science & Technology, Department of Data Science and Business Systems, School of Computing, College of Engineering and Technology)
- R. Rajeswari
(SRM Institute of Science & Technology, Department of Data Science and Business Systems, School of Computing, College of Engineering and Technology)
- C. S. Madhumathi
(Department of Computer Science and Engineering, Dr. N.G.P Institute of Technology)
Abstract
Coastal systems are ever changing as the rate of climate change accelerates on the planet. Increased sea levels, common hazards of extreme weather, and the rapid changes of the shoreline are a threat to the ecological balance and human settlement as well as economic infrastructure. The coastal areas are very prone due to a high population density, unplanned urbanization as well as the weak natural buffers present there. Climate models show the sea level rising significantly over the course of the twenty-first century with disastrous effects on storm surge risks, coastal floods, and erosion. In this chapter, a discussion will focus on the physical forces, spatial, and socio-environmental impacts of coastal hazards in the future climate forecasts. The analysis uses IMF Climate Data and IPCC AR6 report pathways to assess the trends in sea-level rise in several different scenarios, focusing on the medium- and high-emission paths. The forecasting based on ARIMA assist in the comparative evaluation of future sea-level behavior and risk exposure development. The indices of coastal vulnerability are discussed to measure the level of hazards and the possible loss of infrastructure, agriculture, ecosystem, and human livelihood. The discussion focuses on regional effects and the differences between the developing and developed economies. Nations that have low levels of adaptation are more exposed to displacement risk, economic unstable conditions, and more expensive to manage the occurrence of disasters. The results highlight the need to use integrated coastal zone planning, resilient engineering structures, early warning systems based on data and policy-backed mitigation measures. The chapter helps understand the concept of climate-induced coastal change better and offers evidence-based information to facilitate the decision-making process. The development of more sophisticated prediction methods and scenario-level impact evaluation is supposed to support a long-term sustainability planning in dangerous coastal areas.
Suggested Citation
J. Shanthini & J. Dhanalakshmi & R. Rajeswari & C. S. Madhumathi, 2026.
"AI-Enhanced Optimization of Water Management Under Climate Uncertainty,"
Springer Optimization and Its Applications,,
Springer.
Handle:
RePEc:spr:spochp:978-3-032-19012-3_7
DOI: 10.1007/978-3-032-19012-3_7
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