Soil Loss Practical: The Relationship between Vegetative Ground Cover and Soil Loss - Assignment Example

Soil Loss Practical: The Relationship between vegetative ground cover and soil loss Introduction Soil is taken as being the most basic resource that provides the medium for plant growth and water retention. Erosion and landslides is a concern that land managers cannot turn a blind on. Reduction of soil erosion and conservation of the capacity of land to be productive is an important first step of keeping farmlands, timberlands, and fisheries productive. Soil erosion For many years soil conservation has been at the centre stage of land management. Surface erosion encampass processes like rilling, sweetwash, gullying, rain splash and dry ravel. Through undertaking of extensive experiments by researchers in the 1950s and 1960s the equation that calculates agricultural surface erosion was produced (Wischmeier and Smith, 1978). The equation puts into consideration hillslope gradient, slope length,the type of soil, the intensity of rain and its duration, the management and vegetation cover (Reid, 1993). The equation which is abbreviated as USLE (Universal Soil Loss Equation) was modified so as to make a better prediction of surface erosion on forest lands and the vegetation cover by incorporation of C-Factor function and thus was expanded is of reflect the complexity and importance (Dissmeyer and Foster, 1984). Role of Vegetation Vegetation cover has effect on both the surface and mass stability of the slopes in several ways. The stabilizing or protective benefits derived from vegetation is dependant on the type of vegetation and slope degradation process type. Where mass stability is concerned, the woody vegetation protective benefits include mechanical reinforcement and the ability of the stems and roots discouraging modification of slope hydrology which could is brought about by extraction of soil moisture through evapotrapiration (Gray and Sotir, 1996).When slope vegetation is removed the end result may be an increase in erosion rate are it is likely to bring about an increase in slope failure. The cause effect relationship has been successfully been demonstrated by numerous laboratory and field studies (Gray and Sotir, 1996). Vegetation is highly beneficial when it comes to surficial erosion prevention. There are protocols that have been established that are used in the description of the factors that play important role effectiveness of vegetation in controlling surface erosion. The three major sub-factors that have been identified by Wischmeier (1975) are canopy, surface cover and below surface effects. There was modification by Dissmeyer and Foster (1984) with additions being made the original work to factor in fore conditions. The primary forest sub-factors utilized in application of the modified USLE are canopy, ground cover, soil reconsolidation, fine roots, organic content, residual binding effect and on-site storage of water. The summary of the primary effects of herbaceous and to smaller extent woody vegetation in minimization of erosion of surficial soils as given by Gray and Leiser (1082) in: 1. Interception- foliage and plant residues are able absorb rain fall energy and thus preventing soil compaction. 2. Restraint – root systems have the ability to physically bind or restrain soil particles while above-ground residues filter sediment out of run-off. 3. Retardation-above-ground residues have a tendency of increasing surface roughness and slowing down run-off velocity. 4. Infiltration-roots and plant residues help maintain soil porosity and permeability. 5. Transpiration-depletion of soil moisture by plants results to delay of the onset of saturation and consequently run-off. Greenway (1987) was in agreement with the work above and notes that removal of vegetation on a watershed, there will be an increase water yield and water table levels rise in response to logging. These occurrences would tend to increase soil saturation and runoff. Methods Raw data from a runoff and soil loss experiment conducted at Scone Research Station for 1988 is used in this experiment. The data include rainfall (mm), rainfall intensity (mm/hr), run off (mm), soil loss (kg/ha), and plot ground cover (%). The soil loss plots were 30 m long x 2.4 m wide. There were different percentages of vegetative ground cover (plot 1 - 60%, plot 2 - 20%, plot 3 - 40%, plot 4 - 60% plot 5 - 80%, plot 6 - 0%, plot 7 - 80%, plot 8 - 40%, plot 9 - 100%). There was replication of some % vegetative ground cover treatments. Vegetative ground cover was maintained by herbicides, weeding, cutting and limited burning. There was a rain gauge located at the plots as well as a pluviograph to measure rainfall intensity. Results Descriptive statics The descriptive statistics for the two important variables are as shown in table 1. From the table it can be seen that the mean vegetation cover is 57.23 and the maximum is 100.00. The minimum soil loss is zero, mean soil loss is 928.3 and maximum soil loss is 29106.00. The distribution of the vegetation cover variable is represented by figure 1 while figure 2 gives stem and leaf plots for the variable. Table 1 Statistics Soil loss cover N Valid 243 243 Missing 0 0 Mean 928.3004 57.23 Median .0000 60.00 Std. Deviation 3095.19557 28.53 Variance 9580235.591 814.01 Minimum .00 5.00 Maximum 29106.00 100.00 Relationship between vegetation cover and soil loss Figure 1 gives the relationship between vegetation cover and soil loss. This graph has been generated from data from a single date in the seven plots where the rain was constant for all the plots. From the plot it can be seen that there is a strong relationship between vegetation cover and soil loss. The correlation test result in table 2 also supports the results in diagram 1 where it can be observed that there is a statistically negative correlation between soil loss variable and vegetation cover with Pearson correlation value of -0.4 (p=000). The table also show that the time duration of rain is positively correlated to rainfall amount (Pearson value=0.694 p=0.000) and time is negatively correlated with intensity (Pearson value= -0.428 p=0.000) while the other variables show no significant correlation with time duration of the rain. There is also a positive significant correlation between rain intensity and soil loss (Pearson value= -0.27 p=0.000) and indication high intensity rainfall is a condition of the rainfall that significantly contribute to high soil loss. Figure 1 Table 2 Correlations cover soiloss rain time intensity cover Pearson Correlation 1 -.400** .016 .030 -.013 Sig. (2-tailed) .000 .801 .639 .843 N 243 243 243 243 243 soiloss Pearson Correlation -.400** 1 .068 -.067 .270** Sig. (2-tailed) .000 .293 .300 .000 N 243 243 243 243 243 rain Pearson Correlation .016 .068 1 .694** .056 Sig. (2-tailed) .801 .293 .000 .381 N 243 243 243 243 243 time Pearson Correlation .030 -.067 .694** 1 -.428** Sig. (2-tailed) .639 .300 .000 .000 N 243 243 243 243 243 intensity Pearson Correlation -.013 .270** .056 -.428** 1 Sig. (2-tailed) .843 .000 .381 .000 N 243 243 243 243 243 **. Correlation is significant at the 0.01 level (2-tailed). Relationship between cover, soil loss and runoff From table 2 it can be seen that there is a statistically significant negative correlation between runoff and cover (Pearson value=-0.475 p=0.000). The table also shows that there is a strong, positive statistically significant correlation between runoff and soil loss (Pearson value=0.686 p=0.000) Table 2 Correlations cover runoff Soil loss cover Pearson Correlation 1 -.475** -.415** Sig. (2-tailed) .000 .002 N 54 54 54 runoff Pearson Correlation -.475** 1 .686** Sig. (2-tailed) .000 .000 N 54 54 54 Soil loss Pearson Correlation -.415** .686** 1 Sig. (2-tailed) .002 .000 N 54 54 54 **. Correlation is significant at the 0.01 level (2-tailed). Relationship between rainfall and soil loss Figure 2 gives the pattern exhibited between rainfall and soil loss. From the figure it can be seen that there is seen that there are some points where rainfall is high but there is no proportional high level soil loss. Figure 2 Discussion The amount of runoff is directly responsive for the level of soil loss as manifested by the strong correlation between the two variables. From the results it has been seen that vegetation cover reduces soil loss. There was no correlation between rainfall amount and soil loss and this was seen from figure 2 where the value of amount of rainfall appeared to have no bearing on the amount of soil loss. The amount of rainfall has a bearing on soil loss depending on its intensity. The runoff is dependant on the rainfall intensity which is associated with rain events of shorter durations. The amount of runoff is positively correlated to rainfall intensity but vegetation cover is able to reduce the runoff caused by high intensity rainfall. The rainfall intensity is beyond human control and this means that soil loss can be controlled by addressing the vegetation cover of land where soil loss is to be avoided. Human activities using land as grazing field affect vegetation cover. Overstocking reduces grass considerably living the land exposed to soil erosion as the land does not enjoy the protection of vegetation coverage observed by Wischmeier (1975). This therefore calls for ensuring that the stocking level is optimal to avoid overgrazing. Also when investigation he level of soil loss that is likely to occur it is important to put into consideration the slope of the land. References Dissmeyer, G.E., and G.R. (1984).A Guide for Predicting Sheet and Rill Erosion on Forest Land. U.S.DA. Forest Service, Southern Region, Atlanta, Georgia. Gray, D. H., and R. B. Sotir (1996). Biotechnical and Soil Bioengineering Slope Stabilization: A practical Guide for Erosion Control. John Wiley and Sons. Greensway, D.R. (1987). Vegetation and Slope Stability. In Slope Stability, edited by M. F. Anderson and K.S. Richards. Wiley and Sons, New York. Reid, L. M. (1993). Research and Cumulative Watershed Effects. G.T.R. PSW-GTE-141. P.S.W. Research Statio, U.S.D.A. Forest Service, Albany, California. WischmeierW.H., and D.D. Smith (1978). Predicting Rainfall Erosion Losses-A guide to Conservation Planning. Agriculture Handbook. No. 537. U.S. Department of Agriculture, Washington. D.C. Read More