AquaIntel

The Problem & The Vision

Traditional agricultural water distribution relies on the generic requests of farmers rather than actual data.

Our mission is to ensure that water distribution is equitable and fully optimized based on real, satellite-detected needs, especially in case of water crisis and drought.

Product & Target Market

We will develop a B2B software solution designed specifically for land reclamation consortia, provinces, and municipalities.

Our platform provides these entities with a powerful system to significantly increase the efficiency of their water distribution.

The Technology & Data Sources

Our algorithm calculates a comprehensive water balance and generates trend forecasts based on meteorological predictions for humidity, temperature, and precipitation.

To achieve this, we ingest and combine critical climate, pedological, and crop data.

Key data inputs include Evapotranspiration (ET) indices, Sentinel-2 Normalized Difference Water Index (NDWI), precipitation data, Copernicus SAR soil moisture, and LiDAR slope data.

The system utilizes satellite technology to accurately recognize specific crop typologies.

This automated crop recognition allows the algorithm to estimate precise water requirements and calculate a positive or negative water balance.

The Output & Value Proposition

The algorithm generates a high-resolution raster map (e.g., 1-hectare grids) that processes the average data of each examined pixel.

Based on this raster, the software creates a dynamic "ranking" system that classifies farms or plots according to their actual crop water necessity.

This allows management consortia to prioritize and deliver water exactly where it is most needed, eliminating waste and maximizing agricultural yield.

Here are the exact data points used for the project:

• Evapotranspiration Index (ET)
• Normalized Difference Water Index (NDWI) 
• Precipitation and weather forecasts
• Soil moisture
• Slopes
• Crop type