Impact of climate change scenario on sea level rise and future coastal flooding in major coastal cities of India
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View abstract on PubMed
Summary
This summary is machine-generated.Projected sea level rise (SLR) significantly increases coastal flooding risks for Indian cities like Mumbai and Kolkata, especially under high emission scenarios. Machine learning models assessed these climate change impacts to guide adaptation strategies.
Area Of Science
- Environmental Science
- Climate Change Adaptation
- Urban Planning
Background
- Coastal cities in India face increasing threats from sea level rise (SLR).
- Accurate flood risk assessment is crucial for developing effective adaptation strategies.
Purpose Of The Study
- To evaluate the impacts of projected sea level rise on coastal flooding in eight major Indian cities.
- To assess flood risks under various Shared Socioeconomic Pathways (SSP) emission scenarios using advanced machine learning models.
Main Methods
- Utilized Long Short-Term Memory (LSTM), Random Forest (RF), and Gradient Boosting (GB) machine learning models.
- Integrated SLR projections with digital elevation models (DEMs) to identify flood-prone areas.
- Validated model performance using residual analysis and Receiver Operating Characteristic (ROC) curves.
Main Results
- Mumbai and Kolkata exhibit the highest flood risks, particularly under high emission scenarios (SSP 370 and SSP 585).
- Kochi and Mangaluru show moderate exposure to coastal flooding.
- Machine learning models demonstrated reliable predictive accuracy for flood risk assessment.
Conclusions
- Projected sea level rise poses significant threats to India's major coastal cities.
- Findings provide critical data for urban planners and policymakers to prioritize climate adaptation.
- Targeted strategies are needed for high-risk cities like Mumbai and Kolkata to mitigate future flood impacts.
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