Effect of vegetation cover on sediment yield an empirical study through plots experiment

Journal of Environment and Earth Science www.iiste.org
ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online)
Vol 2, No.5, 2012

Effect of Vegetation Cover on Sediment Yield: An Empirical
Study through Plots Experiment

Pravat Kumar Shit1*, Gouri Sankar Bhunia2 and Ramkrishna Maiti1
1. Department of Geography & Environment Management, Vidyasagar University, Medinipur.721102,
West Bengal, India.
2. Senior Research Fellow (ICMR), Rajendra Memorial Research Institutes of Medical Sciences
(ICMR),Agamkuan, Patna-800007, Bihar, India
* E-mail of the corresponding author: pravatgeo2007@gmail.com

Abstract
Rill and gully erosion is a critical environmental problem in India, where vegetal cover plays vital role in the
runoff and soil loss reduction and stabilization of disturbed systems. Here, the impact of vegetal cover on runoff
and soil erosion in lateritic environment was assessed through experimental observation on five plots (<5 m2
area), containing varied vegetal cover at successive time period. Runoff and rate of soil loss were measured in
each plot under seven natural rain storm conditions and compared them. The observed data showed bare plots
experienced larger sediment yield than they are with vegetal cover. The simulation results corroborated
significant relationship between the soil detachment and explanatory variables, e.g. runoff volume and vegetal
cover (R2= 0.95; P<0.001). A very significant relationship was found between vegetal cover and sediment
concentration (Adjusted R2= 0.91, P<0.001). This plot-scale study has the advantage of allowing for detailed
process monitoring at micro scale, providing a basic description of the most relevant aspect of vegetal cover on
sediment yield.

Keywords: Rill-gully erosion; lateritic environment; sediment yield; vegetation cover

1. Introduction

Rill-gully erosion plays a crucial role in soil erosion process; inflicts multiple and serious damages in managed
ecosystems such as crops, pastures, or forests as well as in natural ecosystems (Zuazo et al. 2006; Zuazo and
Pleguezuelo 2008). In India, approximately 3.97 million hectare area is affected by rills and gullies. In West
Bengal, about 14% of the area is affected by water erosion, of which Puruliya is affected to the extent of 328
thousand ha, followed by West Medinipur (218 thousand ha), Bankura (199 thousand ha), Koch Bihar (174
thousand ha) and Jalpaiguri (132 thousand ha) (Pandey et al. 2011).
Runoff and soil loss by water erosion can be successfully controlled by protecting the soil with a soil surface
cover which may aid to reduce runoff and soil loss under different environmental conditions (Poesen and Lavee
1991; Gyssels et al. 2005; Smets et al. 2007). In general, there are differences in soil properties between
vegetation patches and open areas that may exert an important influence on soil and water fluxes. It is widely
accepted that vegetation strongly reduces soil erosion rates via intercepting raindrops, enhancing infiltration,
transpiring soil water and trapping some of the eroded sediment (Styczen and Morgan 1995; Bochet et al. 2000;
Rey et al. 2007). These differences commonly result in lower runoff and sediment yields, and higher soil
moisture contents in vegetation patches than in open areas (Bhark and Small 2003; Bochet et al. 2006).
Vegetation patterns with high patch density can be expected to involve important obstructions to the surface flow
and therefore increased opportunities for re-infiltration.
Plot-scale experimental studies are designed to understand interrelationship between the process involving
hydrological, ecological and geomorphological factors (Wainwright et al. 2000). Plot-scale studies have the
advantage of allowing for detailed process monitoring at large scale, providing a basic description of the most
relevant aspects (Michaelides et al. 2009). This study is also useful in providing experimental data involving
rainfall, surface runoff and soil erosion. Some researchers have highlighted the role of experimental studies at
different scales, in light of the need to increase levels of complexity and connectivity in the study of processes
(Bergkamp 1998; Cammeraat 2002).

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To understand the effectiveness of vegetation in protecting the soil surface against erosion is not only scientific
and environmental interest, but can be of great practical value in land management and agriculture in semi-arid
lateritic environments. In the present study, we specially focused on the impact of vegetal cover in reducing
runoff and soil loss and to analyze the interrelationship between vegetal cover, surface runoff and sediment
concentration on lateritic land.

2. Materials and Methods
2.1 Experimental site
An experimental plot-scale studies was carried out at Vidyasagar University Campus (22°25´ 48.8 ″ N and
87°17´ 55.1 ″E), in Paschim Medinipur, West Bengal, India (Figure 1). To conduct the study, five closed
experimental erosion plots (2 x 2.5 m) were developed on a lateritic upland area (inclination ≈ 12%), and each
experimental plot was 2.5 m in length and 2.0 m in width, and 0.1meter in depth. Each experimental plot
consisted of a synthetic nylon enclosure, drawer collector, and sediment and runoff tank. Experiment was carried
out at different gradient slope (9° - 14°). The surface conditions as well as the slope for each experimental plot
are different (Table 1). Soils are micro-aggraded sandy loam and the soil organic matter content ranges from 3.6
to 8.1%. Climatic factors such as rainfall and temperature regulate water availability and biological processes in
the region. The climate of the region is semi-arid (mean annual temperature ≈ 28.4°C), and with a high inter-
annual variability of rainfall (mean annual rainfall ≈ 1850mm). The vegetation cover is arranged in vegetated
patches of one or several grass species. The grass used in the experimental plots are Andropogon aciculate
(Poaceae), Eragrostis cynosuroides (Poaceae), Panicum maxima (Poaceae), and Saccharum munja (Poaceae);
the leaves of which are 10-15 cm higher and grow very well.
2.2 Measurement of vegetation and soil properties
Before experiments, the grasses were transplanted onto the experimental plots and the coverage degree is
calculated by the grass area occupied the surface area during experiment. The percentage of soil covered by
grass species was recorded at the beginning of monitoring period. The whole area has been divided into 5 cm2
grid cell. This percentage was determined by counting the number of grid intersections which intercepted
vegetation (Zuazo et al. 2006, 2008).

At the same time, three soil samples were taken from each plot using a cylindrical corer (Metal rings: 25 cm long
and 5cm diameter). The soil samples were stored at 5ºC temperature and analyzed within 15 days after
collection. One of the two soil cores was used to determine bulk density (grams per cubic centimeter) at a depth
of 0 - 20 cm by oven drying at 105ºC for 48 h. The collected soil samples were dried and 100g from each sample
were mechanically sieved in the laboratory to sort the sediment into different grain size groups. The average and
standard deviation of results after analysis in laboratory were recorded in table 1.
2.3. Measurements of rainfall, runoff rate and soil erosion
In the present study, rainfall in natural condition has been considered to carry out the experiment. Self recording
rain gauge is used for measuring the rainfall. In the experimental plots, rainfall is commonly represented in
millimeter per 24 hour period.
Runoff rate is directly measured by collecting overland flow samples at the lower end of the experimental plot
during a certain time period through a container. Soil loss rates are determined by collecting, oven-drying and
weighting sediment loaded runoff samples. Soil surface covered area was calculated to estimate soil and water
conservation in the experimental plot (Poesen and Lavee 1991). Runoff and soil detachment under varied
vegetation cover is compared with those in bare condition to get the value of relative runoff and relative soil
detachment.
2.4 Statistical analysis
We explored the relationships between the explanatory variables and the independent variable by computing
Pearson’s correlation coefficient. Student t-test was used to measure the significance. Because of correlations
and interactions between explanatory variables, correlation co-efficient may reveal only part of the relationship
between vegetation cover and explanatory variables. Therefore, we also applied linear and multivariate
regression analysis, to see how a variable varies in combination with the other variables. Furthermore it gives us

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an indication of the percentage of variability in vegetation cover explained by the chosen explanatory variables.
Results were considered to be significant if P<0.05.
3. Results and Discussion
As the global environment alters plot scale studies may provide information about runoff mechanisms, soil
erosion and vegetation dynamics process that result from these changes. The potential for retaining resources,
especially water, within the system is crucial to ecosystem functioning in semiarid and lateritic upland area.

3.1 Rainfall, runoff and sediment concentration
On the experimental plot area, the natural rainfall was recorded through rain gauge and considered to determine
its role on runoff and sediment yield. The total amount of rainfall during the experiment is given in figure 2.
During the two months study period, highest rainfall amount was recorded (60 mm) in 6th -14th August, 2011. At
the experimental plot, runoff events were relatively frequent. Both runoff and sediments produced by individual
rainfall events showed a highly skewed distribution e.g., 0.84 and 0.45 respectively. On an event basis, plot
runoff was positively correlated with the rainfall amount (r = 0.51, P<0.003). However, total runoff and
sediment concentration varied greatly between the experimental plots (Table 2), ranging from 202.55 liter to
1473.72 liter (581.68 ± 63.88), and from 0.072 kg to 0.85 kg (0.36 ± 0.04), respectively. No any significant
relationship was found between the total runoff and sediment concentration (r = 0.27, p<0.020) on the
experimental plot, and it may be due to the effect of vegetation coverage on plots. However, earlier studies have
shown that vegetation pattern also plays an important role in functioning of semiarid ecosystems (Bautista et al.
2007; Kéfi et al. 2007).

3.2 Vegetation covers versus relative soil detachment and runoff
One of the most important factors in predicting soil detachment is the effect of vegetation cover. Vegetation
cover (grass surface) during the first period did not affect measurable runoff or sediment yield prior to onset of
monsoon. As the rain stabilized, vegetative cover became more dominant. However, vegetation cover and its
functional diversity showed significant correlations with the hydrologic response variables (Table 3). To
determine the independent effect of vegetal cover on runoff and relative soil detachment, we used partial
correlation analysis, controlling for the effects of the variables correlated with vegetal cover (percent of surface
cover). We found a negative independent effect of vegetal cover on relative soil detachment (r = -0.95, p=
<0.002) and on relative runoff volume (r = -0.94, p = 0.001). However, an explanatory analysis of these data
derived from experimental plots suggested a very significant linear relationship between soil detachment and
explanatory variables (relative runoff volume and vegetal cover) (Adjusted R2 = 0.95, df = 2, p = <0.001).
Previously, this result is also proved and established by other researchers (Dillaha et al. 1988; Xiong et al. 1996;
Zhang and Liang 1996; Van Dijk et al. 1996). Hence, in the hillslope–gully side erosion system, the grass
coverage degree must be increased in order to reduce soil loss.
Vegetation cover is considered a good explanatory variable for runoff and sediment yields (Elwel and Stocking
1976; Thornes 1990). The analysis of our result showed a significant interaction between sediment concentration
on percent of vegetation cover and surface runoff (Adjusted R2=0.95, p<0.008). The regression coefficients and
the significance levels are given in table 4. The results also indicate that soil detachment increases with
decreasing the percent of vegetal cover and increasing with the surface runoff (Figure 3). As the rainy period
continued, vegetation and biological activity interacted with soil, increasing porosity and enhancing soil storage
capacity.

3.3. Vegetation covers versus sediment concentration
Another important observation from this study was the sediment concentration in the experimental plot. During
the study period, 35 precipitation-runoff-sediment yield events were recorded and their physical properties were
evaluated. It was observed that as the rainy period progressed, the vegetation density increased, along with the
increase infiltration capacity and soil water storage, and consequently sediment concentration dropped to below
0.072. Thus vegetal cover was negatively correlated to sediment concentration (figure 3), because vegetal cover
in the plots most dense at the end of the rainy season. A very significant relationship was found between vegetal
cover and sediment concentration (Adjusted R2= 0.91, p=<0.001). Initially, the concentration of sediment was

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very high (Figure 3); it may be due to less the vegetal cover, however, the concentration of sediment decreases
by increasing vegetal cover on the surface in the experimental plot. Rogers & Schumm, (1991) demonstrated that
sediment yield increases rapidly as vegetative cover decreases from 43% to 15%, but with less than 15%
vegetative cover the rate of increase of sediment yield diminishes markedly.
4. Conclusion
Our results present empirical evidence for the relationship between the hydrologic response of lateritic lands and
functional diversity of vegetation. The effect of spatial distribution of grass cover on the sediment yield is
obvious. The present study suggests that an increasing in vegetation cover has a negative effect on sediment
yield. In general, plant’s structural attributes are better explanatory variables for runoff and erosion than soil
surface attributes. The present study is based on only five plots each monitored for seven storms. A furthers
detailed and continued study may yield considerable value of data, that may enable to draw concrete inference.

Acknowledgement
We would like to thanks to Vidyasagar University, Department of Geography for providing laboratory facility to
carry out the research work. We are also very much thankful to Nityananda and Rabindra for their assistance
during the data collection.

References

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Figure 1. Location map and Experimental plot

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Figure 2. Amount of rainfall during the experiment, collected from the experimental plots using rain gauge.

Figure 3. Line graph, showing the relationship between vegetal cover and sediment concentration at different

experimental plots during the study period.

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Table 1. Particle size distribution of the surface soil (0-20 cm depth) on the experimental plots (P1-P5)

Slope Sand (>0.06 Silt loam Clay Bulk density
Micro-aggraded
gradient in mm) (0.002-0.06mm) (<0.002mm) (g/cm3)
Sandy loam soil
degree (in %) (in %) (in %)

P1 12 48.33±5.68 33.00±2.64 18.66±6.11 1.16±0.47

P2 13 45.00±3.00 36.33±3.51 18.66±5.77 1.23±0.15

P3 9 46.00±3.46 37.00±2.64 17.00±6.08 1.40±0.40

P4 14 41.33±2.88 32.00±2.64 26.66±0.57 1.43±0.15

P5 10 45.66±0.57 38.66±2.08 15.66±2.51 1.46±0.25

Mean values ± SD

Table 2. vegetation cover, runoff and sediment concentration during the study period

Period Vegetation cover (%) Relative soil Relative runoff

Detachment volume

Period1 (6 to 14 August , 2011) 8.4±7.70 0.938±0.06 0.926±0.93

Period2 (16 to 17 August , 2011) 25±3.61 0.766±0.09 0.744±0.06

Period3 (25 to 29 August , 2011)
34.8±1.92 0.546±0.09 0.658±0.12

Period4 (31 August to 01 Sept, 2011)
46±3.94 0.432±0.10 0.462±0.11

Period5 (3 to 4 Sept, 2011)
54.4±7.19 0.216±0.02 0.248±0.04

62.6±9.93 0.202±0.04 0.182±0.04

77.4±6.91 0.116±0.02 0.15±0.03

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Table 3. Relationship between the explanatory variables (runoff and soil detachment) and independent variable

(vegetation cover) in the experimental plot during the study period.

Period Relative soil Detachment Relative runoff volume Significance level

Period1 (6 to 14 August , -0.91 (-3.91) -0.89 (0.3.36) <0.05

2011)

Period2 (16 to 17 August , -0.81 (-2.41) -0.76 (-2.05) <0.05

2011)

Period3 (25 to 29 August , -0.37 (-0.68) 0.49 (0.99) >0.05
2011)

Period4 (31 August to 01 Sept, -0.87 (-3.13) -0.86 (-2.95) <0.05

2011)

Period5 (3 to 4 Sept, 2011) -0.38 (-0.71) -0.95 (-5.23) <0.05

Period6 (7 to 8 Sept, 2011) -0.77 (-2.11) -0.70 (-1.72) <0.05

Period7 (13 to 15 Sept, 2011) -0.93 (-4.30) -0.98 (-7.95) <0.05

*Correlation (Student t-test)

Table 4. Multivariate Regression result considering % vegetation coverage as independent and soil detachment

and runoff rate.

Variables Coefficient Standard error T-stat P-value

Intercept 0.36 (0.10-0.63) 0.13 2.78 0.008

% vegetation cover -0.005 (-0.008- -0.001) 0.002 -2.93 0.006

Relative runoff volume (liter) 0.64 (0.38-0.88) 0.12 5.09 <0.000

Adjusted R2=0.95, n=35

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