[1] Spatial patterns of soil often do not reflect those of topographic controls. We attempted to identify possible causes of this by comparing observed and simulated soil horizon depths. Observed depths of E, Bt, BC, C1, and C2 horizons in loess-derived soils in Belgium showed a weak to absent relation to terrain attributes in a sloping area. We applied the soil genesis model SoilGen2.16 onto 108 1 × 1 m2 locations in a 1329 ha area to find possible causes. Two scenarios were simulated. Model 1 simulated soil development under undisturbed conditions, taking slope, aspect, and loess thickness as the only sources of variations. Model 2 additionally included a stochastic submodel to generate tree-uprooting events based on the exposure of trees to the wind. Outputs of both models were converted to depths of transitions between horizons, using an algorithm calibrated to horizon depths observed in the field. Model 1 showed strong correlations between terrain attributes and depths for all horizons, although surprisingly, regression kriging was not able to model all variations. Model 2 showed a weak to absent correlation for the upper horizons but still a strong correlation for the deeper horizons BC, C1, and C2. For the upper horizons the spatial variation strongly resembled that of the measurements. This is a strong indication that bioturbation in the course of soil formation due to treefalls influences spatial patterns of horizon depths.
Phytoremediation of hydrocarbon-contaminated soils is a challenging process. In an effort to enhance phytoremediation, soil was artificially contaminated with known concentration of light crude oil containing Total petroleum hydrocarbon (TPH) at a concentration of 75 gkg −1 soil. The contaminated soil was subjected to phytoremediation trial using four plant species ( Oryza longistaminata, Sorghum arundinaceum, Tithonia diversifolia , and Hyparrhenia rufa ) plus no plant used as control for natural attenuation. These phytoremediators were amended with concentrations (0, 5 and 10 gkg −1 soil) of organic manure (cow dung). Results at 120 days after planting, showed that application of manure at concentrations of 5 and 10 gkg −1 soil combined with an efficient phytoremediator can significantly enhance reduction of TPH compared to natural attenuation or use of either manure or a phytoremediator alone (p<0.05). The study also showed that a treatment combination of manure 5 gkg −1 soil, with a phytoremediator gives a similar mean percentage reduction of TPH as manure 10 gkg −1 soil (p>0.05). Therefore, the study concludes that use of phytoremediators and manure 5 gkg −1 soil could promote the restoration of TPH contaminated-soils in the Sudd region of South Sudan.
Abstract. Silicate mineral dissolution rates depend on the interaction of a number of factors categorized either as intrinsic (e.g. mineral surface area, mineral composition) or extrinsic (e.g. climate, hydrology, biological factors, physical weathering). Estimating the integrated effect of these factors on the silicate mineral dissolution rates therefore necessitates the use of fully mechanistic soil evolution models. This study applies a mechanistic soil evolution model (SoilGen) to explore the sensitivity of silicate mineral dissolution rates to the integrated effect of other soil-forming processes and factors. The SoilGen soil evolution model is a 1-D model developed to simulate the time-depth evolution of soil properties as a function of various soil-forming processes (e.g. water, heat and solute transport, chemical and physical weathering, clay migration, nutrient cycling, and bioturbation) driven by soil-forming factors (i.e., climate, organisms, relief, parent material). Results from this study show that although soil solution chemistry (pH) plays a dominant role in determining the silicate mineral dissolution rates, all processes that directly or indirectly influence the soil solution composition play an equally important role in driving silicate mineral dissolution rates. Model results demonstrated a decrease of silicate mineral dissolution rates with time, an obvious effect of texture and an indirect but substantial effect of physical weathering on silicate mineral dissolution rates. Results further indicated that clay migration and plant nutrient recycling processes influence the pH and thus the silicate mineral dissolution rates. Our silicate mineral dissolution rates results fall between field and laboratory rates but were rather high and more close to the laboratory rates possibly due to the assumption of far from equilibrium reaction used in our dissolution rate mechanism. There is therefore a need to include secondary mineral precipitation mechanism in our formulation. In addition, there is a need for a more detailed study that is specific to field sites with detailed measurements of silicate mineral dissolution rates, climate, hydrology, and mineralogy to enable the calibration and validation of the model. Nevertheless, this study is another important step to demonstrate the critical need to couple different soil-forming processes with chemical weathering in order to explain differences observed between laboratory and field measured silicate mineral dissolution rates.
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