Water Efficiency Powers Saudi Arabia's Sustainable Future
Durra.ai — Using AI to conserve Saudi Arabia’s precious groundwater by raising irrigation efficiency from a dismal 50% to a world-leading 90%.
Saudi Arabia’s Water Challenge
Agriculture is vital to Saudi Arabia’s food security, yet it consumes over 80 % of the Kingdom’s freshwater—most of it drawn from non-renewable aquifers and desalination plants, according to the Ministry of Environment, Water and Agriculture (MEWA). This dependence on fossil groundwater and energy-intensive desalination increases costs, depletes reserves, and threatens long-term sustainability. Current irrigation and monitoring technologies remain fragmented and hardware-driven, offering no unified national view of water use or efficiency.
Our Solution
AI-Powered Smart Irrigation & National Water Twin
Durra.ai combines satellite imagery, IoT sensors, weather forecasts, and farmer input to provide actionable irrigation advice.
Phase 1 – Smart Irrigation
- Delivers crop-specific recommendations to farmers.
- Reduces over-watering and energy use.
- Improves yields by 20–30% while saving 20–40% of water.
- Generates Saudi-specific datasets to strengthen AI models.
Phase 2 – National Digital Twin of Water
- Integrates aquifers, desalination, wastewater reuse, and urban demand.
- Provides predictive analytics and “what-if” simulations for policymakers.
- Enables system-wide planning, reduces reliance on costly desalination, and creates a national intelligence layer.
Scientific Foundation of Durra.ai
Durra.ai applies AI and open IoT to transform irrigation from a habit to a science, ensuring every crop receives the right amount of water at the right time. The platform brings scientific precision to irrigation by analysing weather, soil, and crop data to determine the exact irrigation depth and timing for each field. It can automate existing pumps and valves through hardware-independent, open-protocol controllers.
The platform is grounded in the FAO-56 crop-water model, which defines irrigation need as:
where ETo (reference evapotranspiration) is derived from local weather using the Penman–Monteith equation, and Kc adjusts dynamically according to crop type and growth stage.
These calculations are continuously refined using satellite imagery (NDVI, NDMI) and on-farm IoT sensor data, ensuring every irrigation event delivers the right amount of water at the right time, protecting yields, lowering inputs, and conserving groundwater.
Impact & Benefits
Water Savings
Reduce irrigation volumes by 20–40% using AI-driven, crop-specific recommendations.
Yield Gains
Increase crop productivity by 20–30% through optimized irrigation and stress reduction.
Cost Efficiency & ROI
Lower pumping and fertilizer expenses; software-only solution keeps adoption affordable.
Energy & Environmental Benefits
Cut electricity/fuel usage, reduce greenhouse gas emissions, and limit runoff and soil degradation.
National Data Asset
Build a Saudi-specific dataset with each irrigation cycle to support long-term water and food security planning.
AI-Driven Gains
Durra.ai’s AI-powered irrigation improves both efficiency and profitability across the farm system.
Yield Consistency
Gain of 5–10%
AI forecasts crop-water demand and automatically adjusts irrigation timing. This keeps plants healthier and ensures more reliable harvests season after season.
Water Efficiency
Increase of up to 40%
Using the FAO-56 model combined with real-time IoT data, the system optimises every irrigation event so more water reaches the root zone and less is wasted.
Energy Use
Reduction of 25–35%
Smart scheduling shortens pump cycles and prevents over-operation. The result is lower energy consumption, reduced fuel cost, and a smaller carbon footprint.
Fertiliser Retention
Improvement of 15–25%
AI maintains ideal soil-moisture balance, preventing nutrient leaching and protecting soil health for stronger, long-term yields.
Compound Outcome
Profitability Improved by 20–25%
Together, these gains reduce resource waste and environmental impact while increasing overall farm efficiency and financial returns.
Technology & Differentiation
How the AI Works
Durra.ai’s intelligence engine merges process-based irrigation science with machine-learning algorithms to predict, optimise, and continuously improve irrigation performance at both farm and national scale.
Predictive Modelling
Integrates the FAO-56 evapotranspiration framework with machine-learning models such as gradient-boosted regression and temporal convolutional networks to forecast crop-water demand several days ahead.
Data Fusion
Uses Kalman filtering and Bayesian optimisation to merge satellite indices (NDVI, NDMI) with IoT data on soil moisture, pressure, and flow, correcting for bias and sensor drift.
Reinforcement Learning
Refines irrigation scheduling through season-over-season learning, guided by performance metrics like yield response and water-use efficiency (WUE).
All connected farms contribute to a National Digital Twin of Water, a real-time, spatio-temporal model integrating on-farm hydrological data with regional weather and groundwater information to support informed decision-making by MEWA and other agencies.
Why Durra.ai is Different
Plant-Level Precision
Provides real-time irrigation recommendations tailored to the needs of each plant.
Integrated Data Sources
Combines satellite, IoT, weather, and farmer input for superior accuracy.
Advanced AI Models
LSTM forecasting, XGBoost optimisation, and deep learning for actionable insights.
Intuitive User Interface
Arabic-first, voice-enabled, designed for rapid adoption by local farmers.
Durra.ai Advantage
Software-led, scalable, partner-friendly, and able to integrate across the full water cycle.
Key Differentiators
Expertise Backed by Years of Industry Projects
Durra.ai builds on years of expertise in agri-tech consulting and digital transformation. Our team has contributed to projects across the region.
Market Opportunity & Adoption
Saudi Arabia
The serviceable market covers around 500,000 hectares of high-value crops, representing a near-term value of $200M.
MENA & GCC Expansion
Over 5 million hectares of farmland could benefit within five years, with potential market value exceeding $1B.
Adoption Strategy
- Farmer-first Onboarding: Easy-to-use interface and dedicated Farmer Success Team.
- Agribusiness Pilots: Partner with large-scale producers to validate technology at scale.
- Agency Partnerships: Integrate with national bodies to enable a full intelligence layer.
Our Roadmap
Year 1 (2025)
Controlled pilot trials on selected farms; achieve water savings of 20–40% and yield gains of 20–30%.
Years 2–3 (2026–2027)
Rollout to 20+ farms; establish recurring revenue and expand the dataset across regions and crops.
Years 3–4 (2027–2028)
Expansion into MENA; integrate with Saudi agencies and connect farm data to national water systems.
Year 5 (2029)
Launch full National Digital Twin of Water; position Saudi Arabia as a global leader in AI-driven water governance.
Partners & Vision 2030 Alignment
Actively forging strategic partnerships with leading institutions. Durra.ai aligns with Vision 2030, enhancing water efficiency, strengthening food security, and improving economic resilience.
Research Collaboration
The DESAL Research Group at KAUST, led by Prof. Noreddine Ghaffour, is collaborating with Durra.ai to explore how desalination and water-reuse innovations can complement AI-based irrigation systems. The partnership focuses on data exchange and pilot validation to enhance water-use efficiency and sustainability in agriculture, bridging scientific research and field implementation across Saudi farms.
Be Part of the First National Water Twin
Join Durra.ai to pioneer AI-driven water-smart agriculture in Saudi Arabia.