Spatial variability soils

Delhi soils by studying its speciation in the soil profile and to assess if there was any spatial variability. Soils representing the Aravali Ridge and the alluvial floodplains of river Yamuna were collected as a single, undisturbed core up to a depth of lm and the profile differentiated into four layers- 0-17 cm, 17-37 cm, 37-57 cm, and 57-86 cm. Pseudo total Aluminum and Iron in the soils were speciated into the operationally defined species (weakly exchangeable, organic matter complexes, amorphous oxides and hydroxides, and crystalline or free oxides) by widely recommended selective extraction procedures. Both A1 and Fe in these soils are bound predominantly as Fe oxides and silicates and have only very low percentages in the easily mobilizable pools. 

Marinussen MPJC, Van derZee SEATM. 1996. Conceptual approach to estimating the effects of home-range size on the exposure of organisms to spatially variable soil contamination. Ecol Model 87 83-89. 

Meuller-Harvey, L, Juo, A. S. R., and Wild, A. (1985). Soil organic C, N, S and P after forest clearance in Nigeria mineralisation rates and spatial variability./. Soil Sci. 36,586-591. 

G. P. Robertson, J. R. Crum, and B. G. Ellis, The spatial variability of soil resources following long term disturbance. Oecologia 96 451 (1993). 

Gustafson, D.I. and Holden, L.R. (1990) Nonlinear pesticide dissipation in soil a new model based on spatial variability, Environ. Sci. Technol., 24(7) 1032-1038. 

Because of the irregular rainfall distribution, mean precipitation values have little meaning in the (semi)-arid zone, if not also the range of variation is indicated. This variability refers to both temporal and spatial variability. Temporal variability affects not only the onset and duration of the rains in the year, but plays also a role in year-by-year differences. The variability is highest in the hyper-arid zone, where the mean precipitation value is composed of a few intensive rainstorms. When these fall on a heated barren surface - as is often the case in the arid zone - a part of it is immediately evaporated and lost for soil processes. High rainfall intensity results on the other hand in a rapid saturation of the surface layers and creates lateral runoff and erosion, in particular on sloping land. Many arid and semi-arid soils show therefore features of gully and sheet erosion. 

As noted in Table I, average surface radium concentrations appear to vary by about a factor of 20. This can also be seen from the distributions from the NARR data. Soil permeabilities, on the other hand, have much larger variations, and thus, in principle, may have a greater influence on the spatial variations in average indoor radon concentrations that have been observed. As with the case of surface radium concentrations, the spatial variability of air permeabilities of soils is an important element in developing a predictive capability. 

Nematode population Various extraction techniques Indicates soil food web functioning, species richness, and abundance spatially variable time-consuming Blair et al. (1996)... 

Although there exists a good understanding of the chemistry of phosphorus in soil-water systems, the hydrologic pathways linking spatially variable phosphorus sources, sinks, temporary storages, and transport processes in landscapes are less... 

To examine the vertical distribution of the different Aluminum species in the soil profile and determine any spatial variability in the Al species between the ridge and the floodplain soils,... 

Bunzl, K., Schimmack, W., Belli, M., and Riccardi, M., 1997, Sequential extraction of fallout radiocesium from the soil Small scale and large-scale spatial variability. J. Radioanal. Nucl. Ghent. 226 47-53. 

The composition of the aeolian particles is temporally and spatially variable. These particles are typically fragments of weathered rocks, soil, or biogenic detritus, such as terrestrial plant fragments. Other biogenic particles include bacteria, phytoplankton, mold, fungal spores, seeds, and even insects. 

Fig. 10.2 Pattern of contaminant advance (water containing dye) in a partially saturated soil. Note the high degree of spatial variability in the pattern, both laterally and with depth. Reprinted from Ghodrati M, Jury WA (1992) A field study of the effects of soil structure and irrigation method on preferential flow of pesticides in unsaturated soil. J Contam Hydrol 11 101-125 Copyright 1992 with permission of Elsevier...

When water flows over a contaminated land surface, pollutants released from higher elevations are transported, as dissolved solute or adsorbed on suspended particles, and accumulate at lower elevations. This behavior is reflected in the spatial variability of contaminant concentration, which affects contaminant redistribution with depth following leaching. If a sorbed contaminant is not of uniform concentration across all soil-size ranges but is higher in the fine sediment fraction, the deposition of this soil fraction controls contaminant redistribution in the subsurface. 

Tables 12.2 and 12.3. The effect of vertical variability is shown in Table 12.2, while the lateral spatial variability is shown in Table 12.3. The vertical and lateral spatial variabilities were defined on the basis of either the measured adsorption coefficient K), as generated from adsorption isotherms on soil profiles, or on adsorption coefficients on soil organic matter calculated as adsorption on organic carbon per unit weight of soil. We see that both vertical (Table 12.2) and lateral (Table 12.3) variability of soil affect the adsorption coefficients. A comparison between the bromide (conservative) and the two nonconservative herbicides distributions with depth after about 900mm of leaching is shown in Fig. 12.3. We see that, in the case of bromide, there is a continuous displacement of the center of mass with cumulative infiltration. In contrast, the bulk of the herbicide contaminant mass remains in the upper soil layer, with very little displacement.

Figure 12.4 shows the spatial distribution of terbuthylazine and bromacil concentrations in a vertical cross section, after leaching by successive irrigations. Differences between the concentrations of the two herbicides may be explained in terms of the chemical properties and the soil spatial variability. The bnUc of the terbnthylazine remained close to the surface, being strongly affected by adsorption. In contrast, bromacil has a higher solubility in water and is leached downward under the inflnence of the spatial variability in hydranUc conductivity. 

With regard to the last point, [62] rightly point out that the storage capacity of the soil and subsoil is not exhausted everywhere, even in the case of extreme precipitation It is therefore important to determine the limit beyond which a catchment is virtually incapable of storing any more water. However, steep mountainous catchments are only capable of storing low volumes of water and generally react rapidly. The authors [62] then use case studies to demonstrate that in many alpine catchments the response can also be slower, which ultimately results in major spatial variability in the flood characteristics of alpine catchments. 

Husson, O., Verburg, P.H., Phung, M.T. and Van Mensvoort, M.E.F. (2000) Spatial variability of acid sulphate soils in the Plain of Reeds, Mekong delta, Vietnam. Geoderma, 97(1-2), 1-19. 

Research has previously shown that bacteria are not uniformly distributed in soil, reflecting soil structure and available nutrients (Richaume et al., 1993). The distribution of microorganisms throughout the soil can also be considered from the applied ecological perspective of patch dynamics, where patch formation is a reflection of intrinsic and extrinsic forces (Rao et al., 1986). The same authors also showed spatial variability in the degradation of pesticides applied to a soil system. 

Within the . alterniflora fringe, spatial variability in both the magnitude and speciation of biogenic sulfur emissions was found to reflect the inhomogeneity of vegetation coverage. This is vividly demonstrated in the data shown in Table I, a summary of measurements made within the Spartina fringe. DMS and H2S measurements were made from the same chambers, and all sites were within S meters of each other. The variations can be explained by the relative contributions to the total emission from soil bacteria versus plant... 

Even in the simplest cases, comprehensive emission measurements are necessary if a meaningful flux calculation is to be made. This can only be achieved by integrating the measurements over the relevant cycle, i.e. tidal (in the case of H2S from coastal environments), diel (in the case of DMS, CS2 and DMDS from all locations and H2S from non-tidal locations), and seasonal (temperature effects and water coverage effects). In addition, the effect of spatial variability, i.e. the effects of changing vegetation coverage and/or soil inundation need also be considered within some ecosystems. For these reasons, we do not attempt to attempt to average our emissions data, and for the purpose of flux extrapolation, use only the sites that have sufficient emissions data (8,2). 

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