“SAWA” Spatial plan and aquaculture carrying capacity in Lake Victoria
The Lake Victoria spatial plan
The Sustainable Activities in Water Areas (SAWA) project is an initiative focused on sustainable management and spatial planning for the Kenyan portion of Lake Victoria. Funded by Gatsby Africa and implemented by the Kenya Marine and Fisheries Research Institute (KMFRI), the project aims to balance multiple lake uses such as fishing, aquaculture, navigation, and transport, toward building a sustainable blue economy that supports local communities.
About the SAWA Platform
The SAWA platform is a web-based spatial planning resource that overlays diverse datasets (spatial maps) representing key lake uses and environmental considerations, including:
- Aquaculture suitability
- Navigation routes
- Capture fisheries zones
- Tourism areas
- Conservation and fish breeding grounds
- Water hyacinth and other invasive macrophytes hotspots
Other catchment based drivers like the drainage network and nutrient dynamics are also considered in the overall ecological analysis for mapping and spatial planning.
Through spatial planning, the project maps suitable areas for activities such as fish cage farming while protecting sensitive zones like fish breeding grounds and navigation corridors. This approach promotes ecosystem-friendly governance and helps decision-makers minimize conflicts between different lake uses.
Supporting a Thriving Blue Economy
By integrating fisheries, aquaculture, tourism, and conservation data, SAWA supports an ecosystem-based approach to resource management. This ensures that ecological health is maintained alongside economic and social development, contributing to long-term prosperity for communities around Lake Victoria.
Access the Platform
The SAWA Lake Victoria Spatial Plan is freely accessible online at:
👉 https://sawa.blue/
Users can explore the platform interactively—toggling between different data layers and visualizing spatial maps, including aquaculture suitability maps, to support informed planning and decision-making.
Prepared by: Collins Ongore
Research Scientist