SukhaRakshak AI

An AI-driven drought risk monitoring and advisory system designed to support proactive drought management and agricultural decision-making by translating climate and environmental data into location-specific advisories

Note: Focus on operational drought risk management

Link To DSS: https://dms.iwmi.org/home

Developer: IWMI

Stage Of Maturity: Pilot to early operational

Coverage: National (India)

Climate Timescales Covered: Extended Range (Sub-seasonal), Historical / Baseline, Real-time / Near Real-time Monitoring, Seasonal, Short-range (Weather: 0–10 days)

Strengths

Strong last-mile focus with farmer-oriented advisories
Uses AI to enhance predictive capability and localization
Integrates multiple datasets for holistic drought risk assessment
Supports actionable decision-making (not just data provision)
Aligns with impact-based and anticipatory approaches
Bridges gap between climate data and agricultural practices

Weaknesses

Geographic coverage currently limited (primarily India)
Dependent on quality and availability of local data inputs
AI models may require continuous validation and calibration
May face challenges in scaling across diverse agro-climatic zones
Integration with NMHS systems may be limited or evolving

Synergies

Can integrate forecasts from Climate Services Toolkit for improved advisory generation
Can use long-term projections from CORDEX South Asia for scenario planning
Can complement monitoring tools like PRISM Platform for drought indicators
Can incorporate datasets from ICIMOD Regional Database System for regional analysis
Can link with risk platforms (e.g., UN ESCAP Risk and Resilience Portal) for broader resilience planning

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SukhaRakshak AI

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