The research team, led by hydrogeologists working across the region, focused on lateritic soils, the deeply weathered, iron-rich mantles that form under intense tropical rainfall. Laterites in western Uganda can extend tens of meters below the surface, often capped by hardened ferricrete layers, and they sit atop a basement complex of Archean gneisses, Proterozoic granites and quartzites of the Buganda-Toro mobile belt, and Miocene volcanic deposits. Because these rock types differ sharply in mineralogy and texture, the soils derived from them inherit distinctly different grain sizes, packing arrangements, and drainage behavior, all of which matter enormously when intense storms strike and water must either soak in or run off.

To quantify those differences, the researchers sampled five soil profiles, labeled S1 through S5, that had been freshly exposed by road construction and gully erosion. Each profile was cleaned in the field and sampled layer by layer, producing twenty-four specimens that spanned depths from about 0.2 to nearly 8 meters. Back in the laboratory, the samples were oven-dried at 105 degrees Celsius, weighed on a precision balance, and passed through nested sieves for particles coarser than 0.063 millimeters, while the finer fraction was analyzed by hydrometer sedimentation, following German DIN 4022 and DIN ISO 11277 standards. Stokes’ Law was then applied to convert settling velocities into particle sizes, yielding continuous grain size distribution curves for every sample.

From those curves, computed with the GGU-SIEVE software, the team derived two classic gradation indices: the uniformity coefficient, Cu, which compares the grain diameters at which 60 and 10 percent of the sample is finer, and the coefficient of curvature, Cc, which flags gap-graded material. They also estimated hydraulic conductivity using the century-old Hazen formula, which scales conductivity to the square of the effective grain diameter D10. The spread of results was striking. Uniformity coefficients ranged from 15 to 439, and estimated hydraulic conductivities spanned nearly four orders of magnitude, from 5.8 times ten to the minus eight to 1.3 times ten to the minus four meters per second, the difference between a slowly draining clayey horizon and a freely infiltrating sandy one.

Each lithology told its own story. The two gneiss-derived profiles, S1 and S5, produced moderately to well-graded soils with the highest conductivities, particularly near the surface, where the hilltop profile S5 reached the study’s maximum value of 1.3 times ten to the minus four meters per second. Conductivity then dropped off sharply with depth, a pattern the authors attribute to increasing fines, compaction, and illuvial clay accumulation. Notably, the two gneiss profiles also illustrated a classic toposequence: the hilltop soil was red and orange, indicating good drainage and oxidized iron minerals, while the downslope S1 profile was grey and brown, reflecting wetter, poorly drained conditions that change both soil chemistry and hydrology.

The quartzite- and granite-derived soils behaved almost in reverse. Although their uniformity coefficients were extreme, exceeding 200 in the deepest quartzite horizon at 439 and reaching 344 in the granite profile, their conductivities were uniformly low, in the range of ten to the minus eight to ten to the minus seven meters per second. The explanation lies in packing: these broadly graded soils contain enough fine matrix to fill the voids between coarser grains, producing dense, poorly connected pore networks that resist water flow. The gneiss-volcanic profile S2, influenced by mixed metamorphic and volcanic parentage, fell in between, with moderate conductivity that actually increased with depth as clay-rich upper horizons gave way to coarser material below.

The statistical analysis added an important layer of rigor. Pairwise correlations showed that the uniformity coefficient increased significantly with depth, with a correlation coefficient of 0.55, while hydraulic conductivity correlated negatively with Cu and with the fraction of fines. Conductivity declined systematically with depth across several lithologies, most dramatically in the gneiss. The team then compared ordinary least squares regression with mixed-effects models that treated profile identity as a random effect and lithology as a fixed factor, evaluating them with the Akaike and Bayesian information criteria and residual diagnostics. Perhaps counterintuitively, the simpler models won: with only fifteen usable parameter sets, the dataset was too small for hierarchical models to justify their extra complexity, and diagnostic plots showed the simpler formulations produced cleaner, more homoscedastic residuals.

The authors are careful about the limits of their measurements. Hazen’s formula is strictly valid only for clean, uniformly graded sands with minimal fines, and seven of the twenty-four samples contained fine fractions well outside that envelope. All conductivity values are therefore treated as index values rather than absolute measurements, interpreted qualitatively rather than taken at face value. That honesty does not blunt the central finding, however: parent lithology, grain-size heterogeneity, and depth structure jointly control the hydraulic behavior of these basement-derived soils, with the uniformity coefficient emerging as the single most consistent predictor of conductivity among the tested variables.

Why does this matter beyond the hillsides of western Uganda? Because the balance between infiltration and runoff set by these soils is a first-order control on sediment delivery to rivers, and ultimately to the estuaries where those rivers meet lakes and the sea. Coarser, more permeable quartzitic soils allow storm water to soak in, reducing sediment export, whereas finer gneiss- and granite-derived soils with low conductivity promote saturated-excess runoff, sheet and rill erosion, and gullying during high-intensity rainfall. In catchments where deforestation and agricultural expansion are stripping protective vegetation, the difference between a soil that absorbs a storm and one that sheds it can translate directly into turbid waterways, silted reservoirs, and degraded downstream ecosystems.

The practical applications reach well into geotechnical and water-management territory. The framework the authors describe, combining gradation indices with index conductivity values, can inform soil conservation planning, slope stability assessment, foundation design, and groundwater recharge modeling across basement-complex terrains in tropical Africa. The team proposes coupling their sieve- and hydrometer-derived parameters with in-situ infiltration tests and mineralogical characterization, and ultimately building geostatistical maps of conductivity across lithological boundaries. Long-term monitoring under changing land use and climate, they argue, would reveal how these ancient-rock-inherited soil properties evolve in real time. In the meantime, the study delivers a reminder that is easy to overlook: the plumbing of a landscape was installed hundreds of millions of years ago, in the chemistry of its bedrock, and any serious plan to protect rivers and estuaries must start by reading the rocks beneath our feet.

Subject of Research: The influence of basement rock lithology on hydraulic conductivity and grain size distribution in lateritic soils of western Uganda

Article Title: Influence of basement rock lithology on soil hydraulic conductivity and grain size distribution in lateritic soils of western Uganda: Implications for estuarine management

Article References: Hailu, H. (2025). Influence of basement rock lithology on soil hydraulic conductivity and grain size distribution in lateritic soils of western Uganda: Implications for estuarine management. Estuarine Management and Technologies, 2, 101-118. https://doi.org/10.3897/emt.2.175774

Image Credits: AI Generated

DOI: 10.3897/emt.2.175774

Keywords: lateritic soils, hydraulic conductivity, basement lithology, western Uganda, grain size distribution, uniformity coefficient, Hazen method, erosion, estuarine management, geotechnics, gneiss, quartzite