Spring discharge variation and groundwater distribution in the Kulfo River basin, Southern Ethiopia

Spring discharge is an important indicator of groundwater occurrence, movement, and distribution, particularly in structurally complex volcanic terrains where borehole information is limited. This study evaluates the influence of spatial variation in spring discharge on groundwater occurrence and distribution in the Kulfo River basin, Southern Ethiopia. A total of 92 perennial springs were investigated in relation to lithology, faults, physiography, drainage, and groundwater-flow conditions. Spring discharge varies considerably across the basin, with numerous low-yield springs in the upper catchment and fewer but highly productive springs in the lower rift-floor area, particularly around the Arba Minch spring system. Spatial analysis revealed a clustered distribution of springs (Nearest Neighbor Ratio = 0.526), indicating that groundwater emergence is controlled by localized hydrogeological conditions rather than random processes. Moran’s I analysis showed weak but statistically significant positive spatial autocorrelation of spring yield, while hotspot analysis identified high-discharge zones mainly associated with fault-controlled and structurally connected areas. Ordinary Least Squares regression indicated that fault density was the most influential significant predictor among the evaluated environmental variables, confirming the important role of structural connectivity in controlling spring discharge. However, the model’s low explanatory power (R² = 0.134) indicates that spring discharge variability in fractured volcanic aquifers is also influenced by subsurface factors, including fracture connectivity, fault aperture, aquifer storage, and preferential flow pathways that are not fully represented by basin-scale datasets. The fractured rift-floor basalt, fractured trap-series basalt, and Quaternary alluvial deposits represent the major groundwater-bearing units in the basin. The study demonstrates that integrating spring inventory, geological interpretation, hotspot analysis, spatial statistics, and regression modelling provides a process-based framework for understanding groundwater controls in data-limited volcanic regions. The findings support prioritization of groundwater exploration zones, spring conservation strategies, and sustainable water-resource management. The study contributes to SDG 6 by improving understanding of groundwater potential and supports SDG 13 by providing hydrogeological information for climate-resilient water-resource planning.