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Introduction

India’s updated Nationally Determined Contributions (NDCs) emphasise integrating climate adaptation into development planning. However, persistent mitigation bias in finance and institutions constrains effective grassroots outcomes, necessitating a shift towards locally driven and adequately funded adaptation frameworks.

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Policy–Practice Gap in India’s NDCs (Adaptation vs Mitigation Bias)

• Mitigation Bias: Climate finance and policy priorities remain skewed towards mitigation over adaptation.
  Eg: India’s NDCs (2031–35) stress adaptation, yet global commitments highlight “tripling adaptation finance by 2035,” indicating existing underfunding.
• Output Focus: Policies emphasise targets (renewables, emissions) rather than resilience outcomes.
  Eg: Adaptation areas like heat mitigation and coastal resilience lack measurable outcome indicators.
• Weak Metrics: Absence of clear frameworks to quantify adaptation benefits limits accountability.
  Eg: Unlike emission reductions tracked via carbon inventories, National Adaptation Fund for Climate Change (NAFCC) lacks uniform indicators to measure resilience gains across projects.
• Centralised Planning: Top-down policy design limits contextual adaptation at local levels.
  Eg: NDC strategies lack district-level adaptation frameworks.
• Implementation Gap: Mainstreaming intent not fully translated into sectoral execution.
  Eg: Despite inclusion of disaster preparedness in NDCs, recurrent extreme events (430 events, 1995–2024) show gaps in local resilience.

Structural and Institutional Constraints to Adaptation

• Financing Deficit: Inadequate and unpredictable funding for adaptation initiatives.
• Institutional Fragmentation: Multiple agencies operate without effective coordination.
  Eg: Adaptation sectors (biodiversity, infrastructure, livelihoods) handled by different ministries with limited convergence.
• Capacity Gaps: Local bodies lack technical expertise for climate adaptation planning.
  Eg: Panchayats often lack climate data and planning tools for resilience building.
• Data Limitations: Insufficient localised climate risk data hampers targeted interventions.
  Eg: While national vulnerability is identified (9th globally), micro-level risk mapping remains weak.
• Monitoring Issues: Weak evaluation mechanisms reduce policy effectiveness.

Scaling Locally Led Adaptation (LLA): Way Forward

• Decentralised Planning: Empower local institutions for context-specific adaptation strategies.
  Eg: Integrating adaptation into Gram Panchayat Development Plans (GPDPs) under the Ministry of Panchayati Raj.
• Dedicated Finance: Ensure predictable and targeted adaptation funding streams.
  Eg: Expanding National Adaptation Fund for Climate Change (NAFCC) with higher allocations.
• Community Participation: Promote grassroots involvement in planning and implementation.
  Eg: Self Help Groups under DAY-NRLM engaged in climate-resilient livelihoods like drought-resistant farming.
• Data Systems: Develop localised climate data and early warning systems.
  Eg: IMD’s district-level weather forecasting supports heat action and disaster preparedness.
• Outcome Metrics: Institutionalise measurable adaptation indicators for accountability.
  Eg: Adoption of Belem Adaptation Indicators framework to track resilience outcomes.

Conclusion 

Bridging India’s adaptation gap requires rebalancing finance and institutions towards resilience, strengthening local capacities, and embedding measurable outcomes, ensuring that climate action evolves from policy intent to effective grassroots transformation through genuinely locally led adaptation approaches.

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