"What if satellite data could help protect the livelihoods of millions who depend on Africa's largest lake?"
Our team JONAM had the privilege of participating in the Kijani Space Hackathon, where we proudly secured 3rd place while tackling Challenge 2: Sustainable Fisheries & Blue Economy.
Rather than building another dashboard, we wanted to solve a real problem affecting millions of people around Lake Victoria: declining fish stocks caused by worsening water quality.
Lake Victoria supports millions of people through fishing, transportation, agriculture, and tourism. However, over the years the lake has experienced:
- Increasing water pollution
- Poor water quality
- Frequent algal blooms
- Reduced fish breeding habitats
- Declining fish populations
For fishing communities, these are not just environmental issues—they directly affect livelihoods, food security, and local economies.
Our question became:
Can Earth observation data help communities understand where water conditions are becoming unsuitable for fish before the problem becomes critical?
Our Solution: JONAM
JONAM is an AI-powered web application that combines satellite-derived environmental data with machine learning to monitor water quality and provide insights into conditions that may contribute to declining fish stocks.
Instead of relying solely on manual sampling—which is expensive and only covers small areas—our platform continuously analyses satellite observations covering the entire lake.
Why Copernicus?
To build JONAM, we integrated the KijaniBox API, which provides access to environmental datasets from the Copernicus Programme.
Copernicus is the European Union's Earth observation programme. It uses a constellation of Sentinel satellites together with in-situ observations to monitor Earth's atmosphere, land, and oceans.
For our project, we focused specifically on live water telemetry variables available through the KijaniBox platform.
- Water Temperature
Satellites measure the thermal radiation emitted from the water surface to estimate temperature.
Temperature influences:
- Fish metabolism
- Oxygen availability
- Fish breeding conditions
Abnormally warm water can reduce dissolved oxygen and stress aquatic ecosystems.
- Turbidity
Turbidity measures how cloudy the water is.
Using reflected sunlight captured by optical sensors, satellites estimate suspended sediments and particles within the water.
High turbidity often indicates:
- Soil erosion
- Runoff after rainfall
- Pollution entering rivers and lakes
Excessive turbidity limits sunlight penetration and disrupts aquatic life.
- Chlorophyll-a
Chlorophyll-a is estimated from the colour of the water observed by satellite sensors.
It acts as an indicator of phytoplankton concentration.
Moderate levels indicate healthy productivity.
Very high concentrations may indicate harmful algal blooms, which:
- Reduce oxygen
- Produce toxins
- Kill fish
- Signal nutrient pollution
- Precipitation
Rainfall estimates are generated by combining satellite observations with weather models.
Heavy rainfall often transports:
- Agricultural fertilisers
- Industrial waste
- Urban runoff
- Sediments
into Lake Victoria, increasing pollution and nutrient loading.
- Wind Speed
Wind speed is estimated using atmospheric observations and numerical weather prediction models.
Wind affects:
- Water mixing
- Oxygen distribution
- Surface circulation
- Dispersion of pollutants
Strong winds can either improve oxygenation or spread polluted water to previously unaffected areas.
From Data to Action
JONAM analyses these environmental variables together instead of looking at each independently.
By learning relationships between:
- Temperature
- Turbidity
- Chlorophyll-a
- Precipitation
- Wind speed
our AI model identifies environmental conditions associated with deteriorating water quality and declining fish habitats.
The platform presents these insights through an intuitive dashboard, enabling users to monitor changing conditions across Lake Victoria.
Why This Matters
Traditional water quality monitoring often depends on field teams collecting samples from a handful of locations.
Satellite observations provide:
- Consistent coverage
- Frequent updates
- Large-scale monitoring
- Lower operational costs
- Historical trends for comparison
This makes environmental intelligence more accessible to researchers, governments, conservation organisations, and eventually fishing communities themselves.
The Hackathon Experience
The Kijani Space Hackathon challenged us to think beyond technology and focus on measurable environmental impact.
Throughout the event, we transformed Earth observation data into practical insights that could contribute toward healthier aquatic ecosystems and more sustainable fisheries.
We're incredibly proud that JONAM earned 3rd place in Challenge 2, but the experience reinforced something even more valuable:
Satellite data becomes truly powerful when transformed into decisions that improve people's lives.
Our vision for JONAM extends beyond the hackathon.
Hackathons often end when prizes are awarded.
For us, this is just the beginning.
Lake Victoria's challenges require continuous innovation, and by combining Earth observation, AI, and accessible environmental data through the KijaniBox API, we hope JONAM can become one small step toward more sustainable fisheries and cleaner waters.
If you're interested in Earth observation, environmental AI, or geospatial technologies, we'd love to connect and continue building solutions that make a real-world impact.
The future of conservation isn't just in collecting more data—it's in turning that data into timely, actionable intelligence.
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