AutoGIS-driven solar pond site selection for water treatment in Africa aligned with the NEXUS framework

Access to clean and safe water remains a critical challenge across many regions in Africa. This study investigates the potential of solar ponds as wastewater treatment facilities by employing AutoGIS processing and DBSCAN clustering to identify suitable development sites across the African continent and its five regions: North, East, West, Central, and Southern Africa. By integrating environmental data such as solar radiation, wind speed, temperature, clear sky, cloud cover, and precipitation, this research highlights the effectiveness of geospatial tools in addressing clean water access issues. The findings reveal distinct suitability patterns for solar pond development at both continental and regional levels. Key environmental factors, notably direct normal radiation (DNR), temperature, and wind speed, consistently expanded the areas identified as suitable, while cloud cover demonstrated a positive effect. Precipitation showed minimal variation, particularly in Central Africa. Importantly, the study underscores the capability of DBSCAN clustering in handling large datasets, filtering noise, and capturing nuanced regional differences, which varied significantly from continent-wide trends. By streamlining the site selection process, this research offers practical insights into leveraging geospatial technologies to address water access challenges in Africa. The integration of AutoGIS and DBSCAN provides a scalable approach for analyzing complex environmental datasets, paving the way for more informed and sustainable development of wastewater treatment solutions across diverse regions.