Geospatial modeling of water quality for emerging irrigation challenges in Ethiopia’s Awash Basin

Recent data on the water quality and suitability dynamics of the Awash River, Ethiopia's most heavily used river for irrigated agriculture, with water that spatiotemporally varies in the transport pathways, is scarce. Increasing anthropogenic activities and the effects of climate change are exacerbating concerns about salinity and water quality degradation, presenting significant challenges for the sustainable management of the Awash River This study addresses these issues by using big data analytics and Geo-spatial Sci-tech to assess water quality in a robust framework, enabling precise, timely insights essential for sustainable irrigation management. The vast volume, high velocity, and complex variety of big data including pH, EC, and ion concentrations align well with these demands. Leveraging geospatial analysis, this research valorized extensive data from ten water quality monitoring stations over a period of twenty years for tracking and visualizing water quality trends across time and space. A slightly to moderately alkaline pH, between 7.4 and 8.4, was observed in the results., while EC ranged from 0.209 to 1.161dS/m between 2004 and 2019. Ion concentrations generally followed the northward sequence of Ca²? > Na? > Mg²? > K?, HCO?? > Cl? > SO?²?, and Na? > Ca²? > Mg²? > K?. Spatial trend analysis demonstrated a positive progression of ECw, SAR, RSC, and other ionic constituents, with temporal variations indicating a progressive decline in water quality, largely due to human activities. The findings also indicated slight to moderate sodicity hazards across samples. These spatio--temporal variations underscore the importance of using updated water quality evaluations and spatiotemporal analysis to inform water management strategies.