INTRODUCTION
Soil erosion occurs when the removal of soil by wind and water exceeds its natural formation, leading to land degradation (National Department of Agriculture) Causes include natural factors, climate change, overgrazing, overcultivation, forest clearing, mechanized farming, and infrastructure development, all contributing to soil decline The effects of soil erosion are severe, impacting agriculture, forestry, and human livelihoods by reducing land fertility, causing desertification, and increasing the risk of devastating floods Erosion diminishes soil productivity by impairing nutrient efficiency, damaging seedlings, lowering rooting depth, decreasing water-holding capacity, and increasing surface runoff and infiltration issues (Zuazo et al., 2011) Additionally, soil erosion leads to water pollution through increased turbidity, heavy metal concentrations, and complex non-point source pollution, complicating assessment and quantification efforts According to the Food and Agriculture Organization (FAO), global land loss due to erosion is estimated at 5-7 million hectares annually, highlighting the urgency of addressing soil degradation worldwide.
Each year, between 5 to 12 million hectares of land—about 0.3% to 0.8% of the world's arable land—becomes unsuitable for agriculture due to soil degradation According to Oldeman et al (1991), human-induced soil degradation has affected nearly 2 billion hectares, or approximately 15% of the Earth's land area, since the mid-20th century Globally, water erosion has impacted around 1,094 million hectares, while wind erosion has affected approximately 548 million hectares, highlighting the significant extent of soil loss Zuazo et al (2011) estimate that current soil loss from farmlands exceeds 6 tons per hectare annually, underscoring the urgent need for sustainable soil management practices.
Overland flow is a critical hydrological process that occurs when rainfall intensity exceeds soil infiltration rates (Hortonian overland flow) or when saturated soil and depression storage capacity are surpassed (Dung, 2001) Raindrops impact the soil surface, breaking down soil structures and dispersing aggregate particles, which are then easily transported by surface runoff Fine materials such as silt, clay, and organic matter are more readily removed by rain splash and surface runoff, while larger sand and gravel particles require greater rainfall intensity or surface runoff to be mobilized.
Surface runoff and soil erosion are most pronounced during short-duration, high-intensity thunderstorms, whereas long-lasting, less intense storms result in less noticeable soil loss Excess water on slopes that cannot be absorbed into the soil causes surface runoff, which increases when factors like decreased infiltration due to plant cover, soil compaction, roughness, and topography impede water absorption Romkens (2001) found that initial smooth surfaces produce less total sediment yield compared to medium-rough and rough surfaces, with similar sediment yields observed between medium and rough conditions under the same slope steepness and rainfall intensity Additionally, sediment yield is higher in initially smooth surfaces on 8% and 17% slopes during decreasing rainstorm intensities compared to increasing ones During prolonged rainfall on dry soil surfaces, sediment concentration in surface runoff spikes rapidly and then gradually declines.
Topography's slope length and steepness are critical factors influencing soil erosion and surface runoff Steeper slopes contribute significantly to increased sediment yields by accelerating surface runoff velocities As both slope length and steepness rise, soil erosion intensifies due to higher volume and speed of runoff Accurate assessment of slope steepness is essential for measuring and managing soil erosion effectively.
Soil texture significantly impacts surface runoff and soil erosion, with soil erodability indicating a soil’s resistance based on physical characteristics Soils with higher infiltration rates, greater organic matter, and improved structure typically resist erosion better Sandy, loamy, and sandy loam soils are generally less erodible than silt, very fine sand, and certain clay soils According to Zuazo et al (2011), silty soils are more erosive, whereas soils with higher clay content tend to be less prone to erosion Even soils with similar sand, silt, and clay ratios can exhibit vastly different erodability due to differences in soil structure, which influences water infiltration and surface runoff—better structure promotes more infiltration and reduces erosion.
Vegetation cover is the most critical factor influencing soil erosion, as plants and litter protect the soil surface, slow water flow, and enhance water infiltration Roots stabilize the soil and prevent it from washing away, while plant structures diffuse raindrop impact, reducing erosion (National Department of Agriculture) Studies highlight that ground vegetation significantly controls overland flow and inter-rill erosion by minimizing soil particle detachment caused by raindrop impact (Miyata et al., 2009) Research shows that increasing vegetative cover from 0% to 47% can reduce soil erosion from 30-35 t ha-1 to as low as 0.5 t ha-1, with greater-than-expected reductions at lower coverage levels (Zuazo et al., 2011).
The combination of root systems and canopy cover significantly reduces soil erosion by promoting infiltration and intercepting rainfall Tree roots increase macro-pore formation, enhancing water infiltration and decreasing surface runoff, while canopy cover acts as a protective roof over the land surface In forested areas, the presence of trees drastically reduces surface runoff and soil erosion, with leaf litter providing additional soil protection (Descroix et al., 2001) The surface runoff coefficient is notably lower with trees (0.028%) compared to without trees (0.23%), and remains further reduced with litter alone (0.085%) Similarly, sediment quantities are significantly decreased with tree presence—133 g at sites without trees, 30 g with litter but no trees, and only 1.1 g where trees are present—highlighting the effectiveness of forest cover in erosion control.
Vietnam's landscape is predominantly hilly with steep slopes, contributing to significant surface runoff during the rainy season, which lasts 4-5 months and accounts for 80% of annual rainfall (1800-2000 mm/year) The heavy rainfall causes substantial surface runoff flows with high intensity, especially during peak months Forest cover in Vietnam is approximately 39%, mainly consisting of degraded forests due to deforestation and soil cultivation, leading to increased soil erosion Recent years have seen farmland expansion driven by the loss of grass and shrub areas caused by herbicides, further exacerbating soil degradation In the Northwest, soil loss has risen from 119.2 tons/ha in 1962 to 134.0 tons/ha in 1963, with annual river sediment transport reaching 200 million tons to the oceans The Red River basin in northern Vietnam produces about 1000 grams of water per liter (Phuong et al., 2012) Deforestation between 1983 and 1994, totaling approximately 1.3 million hectares for timber and cultivation, has dramatically increased soil erosion, resulting in rapid soil degradation—particularly in northern Red River, where about 700,000 hectares have been affected.
Vietnam's soil loss is estimated at 1-2% annually, with around 80,000 tons of soil being lost each year, resulting in damages of approximately 15 billion VND (nearly $7,000) Over 50% of natural land is projected to become degraded, and soil erosion and degradation pose increasing threats to Vietnam’s economic development (Phuong et al., 2012).
Soil erosion causes significant environmental damage, with vegetation cover being a key factor in preventing surface runoff and erosion Despite its importance, research on the role of shrubs and grasses in soil protection remains limited In Vietnam, the focus on cultivating medicinal herbs and cattle feed has led to overgrazing in grasslands, exacerbating erosion issues While many studies highlight the benefits of forests for air quality and scenery, their role in soil conservation is often overlooked Understanding the differences in soil erosion among Cinnamomum parthenoxylon forests, grasslands, and shrub areas is essential for developing effective erosion control strategies based on vegetation cover types.
Determining the most effective cover type for managing soil erosion is essential for protecting and developing vulnerable land areas Cinnamomum parthenoxylon, widely planted across Vietnam, offers high canopy cover and significant economic benefits, making it a valuable vegetation option Given that much of Vietnam’s land surface is covered by grass and shrubs, researching the roles of these three vegetation types—trees, grass, and shrubs—in preserving soil stability is critically important for sustainable land management and erosion control.
OBJECTIVES
Objectives
The specific objectives of this research are:
1 To determine the characteristic of precipitation on Luot mountain
2 To examine effects of different cover types: Cinnamomum parthenoxylon plantation, grass and shrubs on overland flow generation
3 To evaluate soil erosion characteristics: amount of sediment and soil erosion rate in
Cinnamomum parthenoxylon plantation, grass and shrubs
4 To evaluate the relationship between surface runoff and sedimentation in Cinnamomum parthenoxylon plantation, grass and shrub
5 To examine the effect of rainfall on total surface runoff and sediment.
STUDY SITE AND METHODS
Study site
Figure 1 (a) Location and topography of study site (b) detail of study site and sample plots (c) plot 1 (d) plot 2 (e) plot 3
The research was conducted on Luot Mountain which is a part of Vietnam Forestry University campus This has large area of Cinnamomum parthenoxylon plantation, grass,
Luot Mountain features moderate mountainous terrain with two small peaks, measuring 133 meters and 99 meters above sea level The region experiences a tropical monsoon climate, with an average temperature of around 23.9°C, ranging from a low of 17.1°C in January to a high of 28.5°C in June and July The area's average relative humidity is 81.5%, peaking at 85.5% in March and dropping to 78% The slope of the terrain varies between 15 and 20 degrees, making it suitable for diverse flora, including grass, trees, and shrubs.
% in December Annual precipitation is 1647 mm/year The highest monthly precipitation is in July and August with more than 300 mm and the lowest is 22 mm in December.
Methods
Using GPS to measure the distance between 3 points that will be established sample plots
Overland flow and soil erosion were monitored across three types of vegetation cover—Cinnamomum parthenoxylon plantation, shrub, and grass—using designated plots measuring 1 meter wide with a 2-meter slope length Each vegetation type had one dedicated monitoring plot, with a total plot size of 2 square meters, labeled as Plot 1 for the plantation, and similarly designated for shrub and grass areas These measurements aimed to evaluate the impact of different vegetation covers on soil erosion and runoff under controlled conditions.
The Cinnamomum parthenoxylon plantation consisted of Plot 1, with a canopy cover of 90%, and ground surface coverage of 80% by small trees and litterfall Plot 2 was predominantly covered by shrubs and litterfall, reaching up to 90% ground cover, while Plot 3 had 40-80% surface coverage with grass Photographs of each plot were taken and analyzed using Photoshop to accurately calculate canopy cover percentages.
The plot boundaries were constructed using plastic materials buried at least 8 cm deep to ensure stability during heavy rain, with a border height of 25 cm to prevent rain splash Each plot was aligned perpendicular to the contour line, and at the downhill end, a plastic sheet was inserted beneath the O-horizon to channel overland flow and sediment into a collection gutter, enabling efficient sediment and runoff collection after storm events The gutter, made from a large plastic pipe, was designed to accommodate intense surface runoff and sediment transfer during heavy storms, and was covered with nylon to prevent external rain splash After establishing the plots, rain gauges were installed for each plot, positioned perpendicular and away from trees to avoid interception by the canopy, allowing accurate measurement of rainfall data.
In Plot 3, we first cleared all shrubs covering the grass and then removed all surrounding trees to prevent raindrop interference and ensure that only grass remained on the plot We documented the changes by taking photos of the site at different time periods, allowing us to analyze the variation in cover ratio over time.
Erosion factor, surface runoff and sediment measurement
Time of observation was from 17 July 2014 to 30 August 2014
Precipitation was measured using an American plastic rain gauge, recording both the total rainfall and the start and end times of each event A total of 10 storm events were documented, with an inter-storm period defined as the interval lasting at least a specified duration between rainfall events.
6 hr without rain Because the amount of overland flow decreased quickly after
Precipitation cessation was used to distinguish storm events, with a 6-hour period without rain indicating the end of a storm (Dzung et al., 2011) The second storm was unaffected by the first, as confirmed by rainfall data After each storm, rainfall was measured at multiple rain gauges and compared with data from Vietnam Forestry University's weather station to ensure accuracy Additionally, rainfall measurements across three plots helped determine the throughfall in Cinnamomum parthenoxylon forest, providing insights into storm impact and forest hydrology.
(b) Surface runoff: We collected the amount of surface runoff from the collecting cans
To accurately measure surface runoff, we used a 1000 ml vitro for volumes exceeding 100 ml and a 50 ml vitro for amounts less than 100 ml This approach ensures precise measurement across different runoff volumes, optimizing data accuracy for our analysis.
Sediment measurement was conducted by collecting samples from cans after each storm event, ensuring sediment had accumulated at the bottom before carefully pouring the surface runoff into a container Labeled bottles were used to collect and transport the sediments to the laboratory for drying at 105ºC The sediment samples were weighed before and after drying to determine sediment accumulation accurately, providing essential data for sediment analysis in stormwater management.
Figure 3 (a) Weighing soil samples (b) Soil drying
(d) Soil properties: We identified soil characteristics by soil porosity and bulk density To measure soil porosity and bulk density we did some following steps:
- Step 1: We cut surface vegetation and cleaned ground surface
- Step 2: We used a wood to gentle hammer to the bulk density ring until its level with the soil surface
- Step 3: A shovel was used to dig around the ring after that we used a knife to cut the redundant soil
- Step 4: Soils were labeled in plastic bags
- Step 5: We brought the samples to Laboratory to weigh and dry the soil
Soil porosity and bulk density were calculated by following formulas:
Bulk Density (p) = Mass of oven dried soil / Total volume
Porosity: we calculated soil porosity when bulk density was known by below formula:
P = 1 - where: BD is bulk density and PD is particle density
Because we only knew bulk density, so we can assume particle density is equal to 2.65 g/ ( )
(e) Vegetation cover: After finished establishing the plots, we took photos of each plot and then using photoshop software to calculate the cover of each
(g) Slope: We used Compass to measure slope in each plot The slope gradient of Plot 1 was 20.5 º, Plot 2 was 18.5º and 17º was steepness of Plot 3
Surface runoff coefficient = (total amount of surface runoff/ total of precipitation)*100
- Using ANOVA - testing to test the difference of surface runoff and sediment from three different vegetation cover means
- Based on my collected data, the rainfall was divided to 2 levels: rainfall less than 25 mm and bigger than 25 mm to compare the effect of small storms with big storms.
RESULTS
Rainfall characteristics on Luot Mountain
Figure 4.1 Rainfall characteristic measured at the VFU Luot Mountain weather station
From January to October, Luot Mountain received a total rainfall of 1,517 mm, with an average of 152 mm per month The highest monthly precipitation occurred in August, reaching nearly 500 mm, while June experienced the lowest rainfall at just 1.2 mm.
Our monitoring time was in July and August that were two of three months having highest precipitation on the study site.
Surface runoff from Cinnamomum parthenoxylon plantation, grass and shrub
An ANOVA test was conducted to assess differences in surface runoff generation among various land covers The results indicated that there is no significant difference in the amount of surface runoff between Cinnamomum parthenoxylon plantations, grass covers, and shrub covers, as shown in Table 1.
Source: Weather station of VFU in 2/11/2014
Table 1 Results of surface runoff analysis between three vegetation cover means:
Cinnamomum parthenoxylon plantation, grass and shrub
Vegetation cover means n Sum (mm) Mean (mm) P- value
The P-value of 0.7 indicates that there is no significant difference in surface runoff among Cinnamomum parthenoxylon plantations, grasslands, and shrub areas since it exceeds the threshold of 0.05 Table 2 illustrates the surface runoff amounts across various vegetation covers over time, highlighting observed changes in runoff levels among different cover types.
Table 2 Surface runoff from Cinnamomum parthenoxylon plantation, grass and shrub
Cinnamomum parthenoxylon plantation Shrub Grass
Figure 4.2 illustrates the response of surface runoff in Cinnamomum parthenoxylon plantations, grass, and shrub covers to individual storm events The data highlights how precipitation (a) influences surface runoff, with higher rainfall leading to increased runoff in all cover types Surface runoff during each storm (b) varies significantly across different vegetation covers, indicating that plant type impacts runoff dynamics The surface runoff coefficient (c) demonstrates how efficiently rainfall converts to surface runoff, with shrub and grass covers showing lower coefficients compared to Cinnamomum parthenoxylon plantations These findings suggest that ground cover type plays a crucial role in managing surface runoff and enhancing watershed resilience during storm events.
17-Jul 24-Jul 31-Jul 7-Aug 14-Aug 21-Aug 28-Aug
17-Jul 24-Jul 31-Jul 7-Aug 14-Aug 21-Aug 28-Aug
Surface runoff during each storm event (b)
17-Thg7 24-Thg7 31-Thg7 07-Thg8 14-Thg8 21-Thg8 28-Thg8
Surface runoff coefficient during each storm event
Figure 4.3 Surface runoff from Cinnamomum parthenoxylon plantation, grass and shrubs
Surface runoff was lowest in Cinnamomum parthenoxylon plantations at just 7 mm and highest in grass areas at 13 mm, indicating that vegetation cover significantly influences runoff levels Surface runoff began in shrub and grass plots at 3 mm of rainfall, while in Plot 1, covered by Cinnamomum parthenoxylon, runoff appeared only at 7 mm of rainfall The data shows a consistent trend where surface runoff increases with higher precipitation levels, highlighting the direct relationship between rainfall intensity and runoff volume Notably, surface runoff in grass was 1.8 times higher than in Cinnamomum parthenoxylon forests, with similar runoff patterns observed in shrub and grass covers, where shrub runoff was 1.7 times higher than in the forest These findings suggest that dense Cinnamomum parthenoxylon vegetation effectively reduces surface runoff compared to grass and shrub landscapes.
The results have shown that the relationship between overland flow and rainfall in three vegetation means is best represented by linear function with R² = 0.931
Cinnamomum forest, R² = 0.985 in shrub and R² = 0.977 in grass
Precipitation (mm) Surface runoff from vegetation cover types
Table 3 Percentage of surface runoff in Cinnamomum parthenoxylon, shrub and grass (%)
Surface runoff is lowest in Cinnamomum parthenoxylon forests and highest in grasslands, with variations influenced by rainfall intensity When rainfall was light at 3 mm, overland flow was 0% in Cinnamomum parthenoxylon plantations, 1% in shrublands, and 0.3% in grasslands At moderate rainfall of 7 mm, overland flow increased slightly to 0.1% in plantations, 0.3% in shrubs, and grass During heavy rainfall of 202 mm, surface runoff in shrubs slightly exceeded that in grass, reaching 3.6% compared to 3.5%, while Cinnamomum parthenoxylon plantations maintained the lowest rate at 2.5% The surface runoff percentages differ significantly among these vegetation types, with grasslands experiencing over two times higher runoff than Cinnamomum parthenoxylon forests, highlighting the influence of vegetation cover on water runoff under different rainfall conditions.
Cinnamomum parthenoxylon plantation and 1.2 times higher than in shrub (table 3).
Sediment from Cinnamomum parthenoxylon plantation, grass and shrub
The study found that the amount of eroded soil in Cinnamomum parthenoxylon plantations, grass, and shrub areas showed no significant difference, similar to surface runoff levels This was confirmed through ANOVA testing, as detailed in Table 4.
Table 4 Results of surface runoff analysis between three vegetation cover means:
Cinnamomum parthenoxylon plantation, grass and shrub
Vegetation cover means n Sum(g/m2) Mean (g/m2) P-value
P-value was 0.4 and greater than 0.05 so it had no great deal of difference in statistic Therefore we can first decide that grass and shrubs have an important role in protecting soil surface And it agrees with the previous study conducted in surface cover (Khiet,
Although the sediment differences among the three types of vegetation cover were minimal, the highest sediment deposition was observed in areas with grass coverage, indicating that grasslands contribute significantly to sediment accumulation.
The Cinnamomum parthenoxylon plantation exhibited a range of sediment accumulation, with the highest at 86 grams per square meter and the lowest near 36 grams per square meter Sediment visibly began to accumulate in shrub areas with just 3 mm of rainfall, while sediment appeared in grasslands at 4.5 mm of rainfall In contrast, sediment in the Cinnamomum parthenoxylon area started forming at 9 mm of rainfall, highlighting differences in sediment deposition thresholds across land types.
Table 5 Sediment from Cinnamomum parthenoxylon plantation, grass and shrub by each storm event
Figure 4.4 The response of sediment in Cinnamomum parthenoxylon plantation, grass and shrub cover to each storm (a) precipitation, (b) sediment in each storm
Figure 4.5 Sediment from Cinnamomum parthenoxylon plantation, grass and shrub
17-Jul 24-Jul 31-Jul 7-Aug 14-Aug 21-Aug 28-Aug
17-Jul 24-Jul 31-Jul 7-Aug 14-Aug 21-Aug 28-Aug
Sediment erosion during each storm event (b)
Precipitation(mm) Sediment from vegetation cover types
Sediment accumulation increases with higher rainfall intensity, highlighting the impact of storm size on erosion During small storm events, shrubs tend to retain more sediment compared to grasses, indicating their relative effectiveness in sediment capture under low rainfall conditions However, in larger storms exceeding 25 mm, grasses exhibit higher sediment levels than shrubs, suggesting that storm magnitude influences sediment retention differently across vegetation types (Figure 4.4 and 4.5).
The amount of sediment in shrub was 2.1 times higher than in Cinnamomum parthenoxylon forest The amount of sediment in grass was 2.4 times higher than in
Cinnamomum parthenoxylon forest and 1.1 times higher than in shrub (table 5)
The best function representing for the relation between eroded soil and rainfall is linear function with the coefficient of determination R² = 0.916 in Cinnamomum parthenoxylon forest, R² = 0.788 in shrub and R² = 0.587 in grass.
Relationship between sediment and surface runoff
Figure 4.6 The relationship between sediment and surface runoff in different vegetation
Sediment and runoff in Cinnamomum parthenoxylon forest
Sediment and runoff in shrub
Surface runoff (mm) Sediment and runoff in grass
Figure 4.6 illustrates the relationship between sediment and surface runoff across three different vegetation cover types, showing similar patterns As surface runoff increases, the amount of eroded soil also rises, indicating a positive correlation The best-fit model for this relationship is a linear function, with coefficient of determination values of 0.870 in Cinnamomum forest, 0.798 in shrub areas, and 0.682 in grassland This suggests that surface runoff significantly influences sediment yield across various vegetation types, with the strongest correlation observed in Cinnamomum forests.
A single large storm event can significantly increase differences in sediment erosion between plots with different vegetation covers, especially under high precipitation conditions The limited data from only 10 storm events restricts our ability to identify consistent sediment erosion trends across the study area Notably, erosion differences between plots are more pronounced during the largest storm, suggesting that vegetation type may play a critical role in erosion during extreme weather events Conducting long-term studies with more comprehensive data can enhance understanding of how large storms influence erosion across various vegetation types.
Amount of surface runoff and sediment from big storms compared to small storms 21 V DISSCUSION
Storms are categorized into two types: those with rainfall exceeding 25 mm and those with less than 25 mm The surface runoff coefficients and sediment yields vary significantly between these two storm types, as illustrated in Figure 4.7 and Table 6 Understanding this distinction helps in predicting runoff and sediment transport more accurately for different storm intensities.
Figure 4.7 Amount of sediment, surface runoff, surface runoff coefficient from small storms and big storms: (a) sediment, (b) surface runoff, (c) surface runoff coefficient
Amount of sediment from small storms and big storms
Surface runoff from small storms and big storms (mm) cinamomum shrub grass
Runoff coefficient from small storms and big storms (%) cinamomum shrub grass
Table 6 Amount of surface runoff and sediment in different storm sizes
Small storm events and large storm events show significant differences in surface runoff and sedimentation, as indicated by the data in Table 6 The P-value is less than 0.05, demonstrating that rainfall intensity has a substantial impact on both sediment transport and surface runoff These findings highlight the crucial role of storm event magnitude in influencing erosion and hydrological responses.
Surface runoff, surface runoff coefficient, and sediment in storms exceeding 25 mm were significantly higher than in storms smaller than 25 mm Specifically, the total surface runoff amount during >25 mm storms was 105 times greater, with surface runoff percentage being 6.1 times higher and sediment levels 16.5 times greater compared to