INTRODUCTION
Erosion, caused by water drops and wind under the influence of gravity, results in the transfer of soil and significantly impacts land stability (Ellision, 1945) Vietnam has approximately 25 million hectares of steep land with a high erosion potential of about 10 tons per hectare annually (Vinh and Minh, 2009) Systematic monitoring since 1960 indicates that 10-20% of the area is affected by moderate to severe erosion, leading to substantial soil loss in mountainous regions Erosion damages the surface soil layer, diminishes soil fertility, and causes soil exhaustion, threatening sustainable land use It also transports suspended solids that accumulate in low-lying areas, negatively affecting water quality and sedimentation Recently, erosion has intensified, particularly impacting vital water sources like the Bui River, which supplies water for local communities Therefore, assessing erosion potential is crucial for sustainable resource management and environmental protection in Vietnam.
Historically, estimating soil erosion involved building reservoirs to monitor soil loss, a method that was costly and time-consuming Today, researchers favor process-oriented modeling approaches that describe erosion dynamics, with popular models based on the Universal Soil Loss Equation (USLE), such as MUSLE (William, 1975), ANSWERS (Beasley et al., 1980), SLEMSA (Elwell, 1981), SOILOSS (Rosewell, 1993), and RUSLE (Renard, 1997), each with its own advantages and limitations The USLE is an empirical model widely used globally to estimate soil loss caused by raindrop impact and surface runoff In Vietnam, studies by Tu (2011) and Ha (2009) successfully applied the USLE model to assess soil erosion levels in various regions.
Research in various areas has identified effective solutions to mitigate erosion, including ground cover, ladder field, and wetland methods, which have been successfully implemented worldwide These studies are highly regarded as dependable references due to their scientific rigor and relevance for land use planning This thesis aims to apply the USLE model to estimate soil erosion in the Bui River watershed, located in Lam Son commune, Luong Son, Hoa Binh, an area where over 70% of the terrain is mountainous with high erosion potential Currently, there is no existing research on soil erosion in the Bui River watershed, making this study on USLE application crucial for understanding and managing erosion risks in the region.
OBJECTIVES
General objective
This study provides scientific basic to propose possible solutions for soil erosion management in Bui river watershed at Lam Son commune, Luong Son district, HoaBinh city.
Specific objectives
Forming maps of rainfall erosion index (R), soil erodibility index (K), slope index to form potential and present condition map
Giving estimation about eroding rate as well as proposing the best solution for limiting soil erosion at Bui basin
STUDY AREA AND METHODS
Study area
The study area is carried out in Lam Son commune- belongs to Luong Son district, Hoa Binh province to the west
The study area has border:
- To the West: DanHoa, DanHa of KySon, HoaBinh
- To the North: TienXuan, DongXuan commune
- To the East: LuongSon district
- To the South: TanVinh, TruongSon commune of LuongSon, HoaBinh
Lam Son lies about 10km along the 6 highway, it is about 45km far from HaNoi city
The study area features numerous rivers, streams, ponds, and lakes, which have been supplied by 1,796.3 hectares of forest, including 1,692.2 hectares of planted forest, 22.4 hectares of bamboo forest, and 91.7 hectares of mixed forest, resulting in a forest cover of 56.1% Land designated for domestic use covers 55.1 hectares, while other land uses occupy 562.3 hectares and vacant land totals 557.9 hectares (Forest Inventory and Planning Institute of VFU) The region experiences a rainy season accounting for over 70% of total annual rainfall, often leading to flooding in the headwater catchment of the Bui River, while dry seasons frequently cause water shortages affecting agriculture and daily life Lam Son commune is inhabited mainly by Kinh and Muong ethnic groups, with the local economy heavily reliant on agriculture, forestry, and service industries such as golf and crafts The local population actively cultivates rice, maize, fruit trees, and woody plants, as well as engaging in cattle grazing and poultry farming Key weather data indicative of the regional climate are summarized in the accompanying table.
Table1.1 Basis criteria datum of weather in the study area Weather criteria
(Source: Bioclimatology software-Institute of ecological forest resources and environment- Vietnam National University of Forestry)
Lam Son has tropical monsoon climate with two seasons:
-Rainy season with more vapors and last from April to October
-In dry season, humidity is low, dry and last from October to March in the next year
Temperature regime: Average temperature per year is 23.1 o C, July is the hottest month on average and the coldest month is in January
The region experiences an average annual precipitation of 1,913mm, with the rainy season primarily occurring during summer months, specifically July, August, and September December records the lowest rainfall, marking the driest period of the year The annual average humidity is around 84%, with October exhibiting the lowest humidity levels, while August has the highest humidity at 86%, reflecting seasonal variations in moisture content.
The wind regime in the study area is primarily characterized by two main wind directions: the Southeast wind, which predominates during the rainy season from April to October, bringing hot air and moisture, and the Northeast wind, active from November to April, which is dry and southwest Additionally, the region is influenced by hot, dry westerly winds and cold North winds, contributing to the area's complex wind climate.
The region's hydrology is characterized by numerous streams, ponds, and gullies resulting from its fragmented topography With over 70% of precipitation occurring in the area, it frequently experiences flash floods, particularly upstream of the Bui River Despite the high rainfall, the area often faces water shortages that impact both agricultural production and domestic use.
Generalizations about soil erosion
Erosion is a natural process driven by the energy of water, wind, and gravity, which causes the detachment, transport, and deposition of soil particles Soil detachment happens when external forces such as raindrop impact, moving water, or wind exceed the forces holding soil particles in place Understanding erosion mechanisms is essential for soil conservation and preventing land degradation (Joy et al 2002; Rose 1960).
3.2.2 Summary about history of soil erosion research
Historical studies on soil erosion date back to 1877 when German scientists conducted early research on the topic (Huson, 1995) In 1907, the U.S Department of Agriculture implemented policies aimed at protecting soil resources through dedicated research efforts Laws (1941) provided the first detailed analysis of the mechanics of raindrop impact on soil and the erosion process, advancing understanding of how soil is displaced Zingg (1940) developed a mathematical equation to assess the influence of slope gradient and length on erosion rates, contributing significantly to soil erosion modeling.
In 1947, Musgrave et al developed the empirical Musgrave equation, which was widely used until it was replaced by the Universal Soil Loss Equation (USLE) in 1958 From the mid-1980s to the early 1990s, various erosion models based on USLE emerged worldwide, including the Soil Loss Equation Model for South America (SLEMSA) developed by Elwell in 1981, Australia's SOILOSS model introduced by Rosewell in 1993, and the ANSWERS model, expanded in the late 1970s to assess river basin aggradation levels (Beasley et al., 1980).
In Vietnam, erosion occurs gradually because the country has mountainous topography so, researches about this problem have been carried out early Tung and Moorman
(1958) had some basic researches about soil erosion After completing the study, they
Terraced farming is an effective method for reducing soil erosion, as concluded by recent studies Since 1960, research has emphasized the significant influence of slope on soil erosion, leading to the development of soil protection criteria for steep terrains Chu Dinh Hoang's studies in 1962 and 1963 explored the impact of rainfall on soil erosion and demonstrated how specific farming methods could prevent erosion, highlighting the importance of adopting suitable agricultural practices to preserve soil health.
Since the 1980s, researchers have utilized the Universal Soil Loss Equation (USLE) developed by Wischmeier and Smith (1978) to assess soil erosion potential Dung (1991) applied the USLE to predict soil erosion risks in the Tay Nguyen region and proposed preventive measures, while Xiem and Phien (1996) conducted studies focused on mountainous lands in Vietnam to evaluate erosion threats and suggest sustainable soil conservation practices.
The Universal Soil Loss Equation (USLE) is a groundbreaking tool in soil and water conservation, developed in the 20th century to estimate soil erosion caused by raindrop impact and surface runoff As a highly influential empirical model, USLE has been widely applied worldwide to assess erosion risks and implement effective conservation practices Its development resulted from decades of extensive research and experimentation by university faculty and federal scientists across the United States, making it a cornerstone in sustainable land management.
The USLE (Universal Soil Loss Equation) was developed at the USDA National Runoff and Soil Loss Data Center at Purdue University, led by Walter H Wischmeier and Dwight D Smith, as part of a nationwide effort Based on extensive erosion data collected across the United States, the USLE provides a quick and reliable method for estimating long-term average annual soil loss (A) This equation incorporates six key factors that influence soil erosion, making it a valuable tool for soil conservation planning and land management.
Since 1990, GIS technology has been increasingly applied in soil erosion assessment in Vietnam The USLE model remains the primary tool for evaluating soil erosion, with studies by Dung (1991), Ha (2009), and Vinh and Minh (2009) utilizing its empirical approach based on data from 47 sites across 21 U.S states This model considers factors such as climate, topography, soil components, and human activities, quantified through six erosion coefficients: rainfall (R), slope length (L), slope steepness (S), cover and management (C), and support practices (P) Over time, the USLE model has been adapted and improved by researchers globally and locally, such as Ha (1996), to better suit specific regional conditions Recently, incorporating GIS and advanced technologies into the calculation of these coefficients has significantly increased the accuracy and reliability of soil erosion assessments.
According to researches of soil erosion process of Ellision 1994, Wishmeier and Smith 1978 etc, soil erosion factors include: rain, topography, ground cover, human
After doing many researches of soil erosion systematically, scientists found that the most factor of soil erosion is raindrop
The first person pointed out that raindrop caused erosion is Elision (Elision 19940 In
1985, Hudson N W concluded that raindrops have the dynamic of 256 times more than its surface flow
Rain impacts soil structure primarily through its kinetic energy, causing topsoil to break apart and detaching grains from the ground Additionally, rainfall facilitates surface runoff,Transporting detached grains to sediment areas and contributing to soil erosion.
Soil erodibility is the factor, which determines the level of erosion Raindrops cause two effects on soil erosion process:
- Energy of raindrops splash and break the combination of soil, it also impacts on chemical and biological property of soil and integrate soil particles
Maintaining proper soil structure and equilibrium is essential for preventing soil degradation, as well-structured soil resists breaking under external forces When soil lacks proper structure, particles do not bind effectively, making the soil highly susceptible to erosion, especially from raindrop impact Soil erodibility is influenced not only by its composition but also significantly by its structure, highlighting the importance of soil management for sustainable land use.
Slope directly influences soil erosion by affecting the velocity of surface runoff and the detachment of soil particles Steeper slopes increase surface flow speed, making soils more vulnerable to erosion through processes like splash, sheet, and gully erosion The shape of the slope also impacts erosion rates, with concave slopes experiencing higher soil loss compared to convex ones, while flat slopes tend to have more erosion on concave shapes Additionally, longer slopes can exacerbate erosion, as increased slope length allows for more runoff accumulation and soil displacement.
Under the impact of rain, bare lands with steep slope have high potential of erosion But when there are ground cover, vegetation layer will have two functions:
- Firstly, ground cover absorb the energy impact of raindrops, disintegrate the impact of rain, water move along the stem of tree will be reduced the impact on soil
- Secondly, leaves and branches when fall down will deposit and form a slime layer, which limit the surface runoff
Human activities significantly impact the environment, with both positive and negative effects that can directly and indirectly contribute to soil erosion Practices such as prolonged ploughing, deforestation, and livestock raising are primary human factors that accelerate soil degradation and loss of fertility Understanding these activities is essential to implementing sustainable land management strategies and mitigating soil erosion's adverse effects.
Soil erosion has made huge impact on agricultural activities, natural and ecosystem:
Soil erosion causes significant soil loss, undermining the essential resource for agricultural productivity This process depletes surface nutrients necessary for healthy tree growth and alters the soil's physicochemical properties Consequently, nutrient loss not only diminishes soil fertility but also negatively impacts crop yields and overall land sustainability.
- Plant productivity: the productivity of plant is reduced due to nutrient loss Seriously, some area lost all crop because of erosion
Nutrient runoff during soil erosion can harm the environment and aquatic ecosystems by carrying soil particles, including phosphorus, nitrates, and pesticides, into water bodies When algae die due to nutrient overload, their decomposition by microorganisms reduces oxygen levels in the water, threatening fish and other aquatic life Additionally, soil erosion contributes to water pollution, impacting water quality and posing health risks to humans through contaminated water sources, ultimately disrupting the balance of aquatic ecosystems.
Methodology
To create a soil erosion map of the study site using USLE and GIS, it is essential to generate individual maps for the R (rainfall erosivity), K (soil erodibility), LS (slope length and steepness), and C (cover management) factors These maps are combined to produce a potential erosion map, highlighting areas susceptible to erosion based on natural factors Subsequently, integrating the C factor map with the potential erosion map allows for the development of a current soil erosion map, reflecting the present condition of soil stability at the site.
The R factor represents rainfall and runoff erosivity, serving as a key parameter in evaluating the potential for rain erosion and surface runoff It is not simply a measure of precipitation; rather, it is calculated based on the total amount of rainfall combined with rainfall intensity Understanding the R factor is essential for accurately assessing soil erosion risk and managing sustainable land use practices.
After many researches, with 8.250 experimental indice of 35 stations, Wishmeier
(1985) found the product between kinetic energy of rain and maximum rainfall intensity in 30 minutes singned EI30 This value reflect the relationship between ammount of soil loss and rain mode
Wishmeier proposed equation to calculate R fsctor based on EI30 as follow:
In which: R: Rainfall and runoff erosivity index
I 30: Maximum rainfall in 30 minutes (mm/h)
Table 3.1 Some equations to calculate R factor
Roose (1975)- Erosion index calculated by annual precipitation (P)
Morgan (1974)- Erosion index calculated by annual precipitation (P)
Foster et al (1981) - Erosion index calculated by annual precipitation (P) and I30
El-Swaify and others (1985) - Erosion index calculated by annual precipitation (P)
Wanapiryarat et al (1986)- Erosion index calculated by daily precipitation (X)
Ha Nguyen Trong equation (Water resources
University)- Erosion index calculated by annual precipitation (P)
The R factor equation varies based on the location of research areas due to differences in rainfall patterns, distribution, and characteristics Higher rainfall intensity and longer rainy periods increase erosion potential, making the R factor a critical component in erosion assessment Since the R factor fluctuates annually, obtaining accurate values requires multi-year precipitation and rain mode data When calculating the R factor, selecting the most appropriate equation tailored to the specific research area's conditions is essential for precise results.
The R factor map illustrates the distribution of rainfall and flow within the Bui River watershed To calculate the R factor, an equation incorporating annual precipitation and 30-minute rainfall intensity (I30) from Wishmeier (1985) is typically used However, due to limited data on 30-minute rainfall intensity, the R factor in the Bui River watershed will be estimated based on average annual precipitation values and the application of Ha’s (1996) equation.
In which: R is erosion coefficients of rain and flow
Based on an overview of relevant documents, this equation has been specifically studied under Vietnam's climate conditions, making it more accurate for calculating the R factor compared to other equations The precipitation data from Lam Son weather station (Table 1.1) indicates that Lam Son commune experiences a high average annual precipitation Using this average precipitation data, an interpolation algorithm was applied to generate a detailed map illustrating the spatial distribution of precipitation within Lam Son commune.
The result was carried out by Arcgis 10.1 software The process is as follow:
Spatial Analys Interpolate to Raster Inverse Distance Weighted…
After interpolation, we conducted to overlay the class area of rain on the boundary map and digitize them to form the map of average precipitation
Figure 3.3 Process of forming R factor map in Arcgis 10.1
The K factor indicates soil erodibility, with higher values signifying greater potential for erosion It depends on soil properties and the stability of soil structure and components Various methods exist for calculating the K factor, enabling accurate assessment of soil susceptibility to erosion.
In which: M is defined as: (%) M = (%limon + %fine sand)(100% - %clay) a: percent organic matter b: classes for structure c: permeability
For more easily in calculating K factor, Wischmeier and Smith proposed nomogram based on equation of Wischmeier and Smith (1987) to look up for K factor
Figures 3.4 Nomogram for calculatin K factor of Wischmeier and Smith (1978)
In this thesis, K factor is referenced from multiple sources
To create the K index map in ArcGIS 10.0, I utilized an algorithm to query all soil types in the soil map and assign K index values according to Table 4.2 After determining the K index, I converted the vector data to raster format using the Feature to Raster tool, based on the K index field.
LS factor represents for the effect of slope steepness factor (S) and length (L) to the process of erosion
S is the slope steepness, soil loss much when the slope is steeper
L represents the distance from the start of water runoff on the land to the point where sediment is deposited or the runoff enters a well-defined channel The slope length factor evaluates how the length of the slope influences erosion rates For slope lengths exceeding 1000 feet, this interactive calculator is not recommended, as the accuracy of the erosion calculations may become unreliable.
L and Sare two factors to be considered when calculating erosion
Wischmeier and Smith (1978) proposed formula o calculate LS factor as follow:
In which: x: the length of the slope (m)
19 s: percent of slope n: actual parameter n = 0.5 when S > 5%; n = 0.4 when 3.5 < S< 4.5% n = 0.3 when 1% < S < 3.5%; n = 0.3 when S < 1%
Figure 3.5 Process of forming LS factor in Arcgis 10.1
The C factor, as defined by Wischmeier and Smith (1978), quantifies the relationship between erosion on bare soil and erosion under cropping systems by incorporating plant cover, production levels, and cropping techniques It ranges from 1 on bare soil to as low as 1/1000 in forested areas, 1/100 in grasslands and cover crops, and between 1 and 9/10 in root and tuber crop systems This parameter is essential for assessing soil erosion risk and implementing effective land management practices.
To define C factor for the study area, it is necessary to have long-time observations There are two methods to calculate C factor o Surveying method Wischmeier and Smith (1978)
20 o Using current land use status map or satellite figures to forming plant cover, after that collecting C factor of each status from other documents
This study considers C as the cover of surface vegetation, where a thicker cover layer corresponds to a larger cover area and reduced erosion A C index map can be generated using the described methodology, but due to limited satellite data, the C index is categorized based on land use maps and additional sources Land use classifications are utilized to assign C values across the study area, aligning with government categories as detailed in Table 3.2, thereby ensuring accurate representation of surface cover for erosion assessment.
Table 3.2 C index of Bui river basin
Soil Type C index Total area(km 2 )
In the USLE equation, the P factor evaluates the effectiveness of farming practices in preventing soil erosion It reflects the impact of management methods on conserving soil and reducing erosion rates In RUSLE, the P factor is composed of three sub-factors that further detail how specific practices influence soil conservation efforts.
P st: Contour plant sub-factor
P ter : sub-factor of embankment to prevent erosion
Due to the limit of the thesis, P factor is considered equal to 1
The potential erosion map illustrates the impact of natural factors on soil erosion, providing valuable insights for land management Using the USLE model, this map is generated by integrating the R (rainfall erosivity), K (soil erodibility), and LS (slope length and steepness) factor maps Geographic Information System (GIS) software plays a crucial role in combining these datasets accurately, resulting in a comprehensive assessment of erosion risks across the landscape.
Aside from natural factors, socio-economic influences like land use and farming methods significantly impact current erosion rates To assess soil loss at a specific time, we combine the C factor map with the potential erosion map, creating a comprehensive current erosion map.
RESULTS AND DISCUSSION
Mapping factors
Figure 4.1 Annual Precipitation Interpolation map of Lam Son commune
After apply the equation (3.1) for map of annual interpolated precipitation map of Bui river watershed in Lam Son commune, we get the R factor in the whole commune from
Table 4.1 R factor of Lam Son commune
R factor in the study area is medium and decreases from the North to the South Calculating R factor did not reflect the effect of rain and flow to on erosion
Figure 4.2 R factor map in Lam Son commune
Table 4.2 K index of some types of soil in Lam Son Commune
Symbol K index Total area (km 2 )
In Lam Son commune, the K coefficient value ranges from 0.2 to 0.3, indicating similar soil characteristics across the area The consistent K coefficient values among different soil types suggest that soil erosion resistance coefficients are relatively uniform throughout the study region.
Figure 4.3 K factor map of Lam Son commune
Figure 4.4 Steep map in Bui river watershed Table 4.3 Slope analysis in Bui river watershed Steep ( 0 ) Total area (km 2 ) Percentage of steep (%)
Slope in the study area is almost from 8 0 – 25 0 so I choose n = 0.5
Table 4.4 LS coefficient table in Lam Son commune
Figure 4.5 LS factor map in Lam Son commune
This study considers the cover of surface vegetation—referred to as C—as a key factor influencing erosion, where thicker vegetation coverage results in a larger cover area and reduced erosion risk The C index map can be generated using the methodology outlined previously; however, due to limited satellite data, the C index is classified based on land use maps and supplementary resources Land use data is utilized to categorize surface cover types across the study area, assigning corresponding C index values as detailed in Table 3.2, which reflects the relationship between land use types and vegetation cover characteristics.
Figure 4.6 Land use map in Lam son commune
In ArcGIS 10.1, creating a C factor map involves the same steps as generating a K factor map, ensuring consistency in the process The C coefficient maps for different plants are relatively similar, with a C coefficient of approximately 0.01 in Lam Son commune, indicating a low risk of erosion This low C value helps effectively reduce soil erosion within the study area, supporting sustainable land management.
It required long time and money to survey to calculate P factor Due to the limit of the research, P factor in the thesis is considered equal to 1
Erosion map
4.2.1 Potential erosion map based on R, K LS factor
As I mentioned in chapter 3, potential erosion map is formed by gathering R, K, LS map together After calculating and using Arcgis 10.1 to integrated maps of factor by Raster Calculator tool The result is shown as follow:
Figure 4.8 Potential erosion map based on R,K, LS factor
Table 4.5 Classifying potential erosion in Bui river watershed
The amount of soil loss (tons/ha/year)
Percentage of potential erosion area (%)
Based on the potential erosion map and classification according to Vietnam standard TCVN 5299-1995, the potential erosion classification for the Bui River watershed indicates significant erosion issues The map reveals that most areas are experiencing severe erosion, highlighting critical environmental concerns Three primary types of potential erosion are identified in the watershed, emphasizing the need for targeted erosion control and conservation strategies.
Level 2: 1-5 tons/year: In the research area, the potential erosion area count for 9.6% of the whole region, erosion area concentrate mainly from the North to the Northwest This area has low rate of erosion thanks to the low of slope, main type of soil is valley land by slope (D)
Level 3 (5-10 tons/year): Count for km2 (0.05%), this area has low potential of erosion due to the not steep of slope and high density of ground cover
Level 5 (>50 tons/year) Count for 90.33%, in general, almost the region is eroded seriously Lam son is a small commune with main soil type is yellow-red soil on clay with K index = 0.31, high of average precipitation per year and steep of slope, so the potential erosion is very high
The current erosion map of the Bui River watershed illustrates the extent of soil erosion by integrating the C factor map and potential erosion map Utilizing ArcGIS 10.1 with the Raster Calculator tool, we processed the data to generate an accurate representation of soil erosion levels The final map provides a clear visualization of erosion severity across the watershed, aiding in targeted soil conservation efforts.
According to regulation of classifying current erosion follow Vietnamese standard
(TCVN 5299-1995) in the study area, we can divide into level of erosion:
Figure 4.10 Distribution of erosion area
30.40% level 1 level 2 level 3 level 4 level 5
Ground cover significantly reduces soil erosion, as evidenced by statistical data showing its effectiveness The potential and current erosion values are adaptable based on various conditions In Lam Son, analysis of Table 4.7 and the erosion map reveal three primary levels of current erosion—levels 1, 2, and 3—highlighting the varying severity across the area.
Level 1(30tons/ha): This area distributed from the North to the South with total area of 10,602 km 2 Almost this area belongs to abandoned hill or still waiting for plan
Forest land plays a crucial role in preventing erosion, as it generally exhibits the least erosion compared to other land types The presence of trees and vegetation helps protect steep slopes and reduces soil loss, highlighting the environmental importance of forests beyond their economic value Without adequate forest cover, especially on steep terrain, the risk of severe erosion increases significantly An assessment of the Bui River watershed in Lam Son commune underscores the need for forest conservation to maintain soil stability and prevent erosion.
- Current erosion of the research area is uneven between levels of erosion Total area suffered from erosion is up to 80%
Erosion levels 4 and 5 can reach up to 60%, primarily due to sparse population density and mountainous terrain, resulting in high annual erosion rates The eroded soil often flows into rivers and reservoirs, causing sedimentation that negatively impacts water quality and disrupts aquatic ecosystems This ongoing erosion poses significant environmental challenges, emphasizing the need for effective soil conservation and land management strategies.
Figure 4.11 Comparison between potential erosion and current erosion
Figure 4.12 Location in Doan Ket village (Level IV in the map)
Figure 4.13 Location behind Phoenix golf resort (Level V in the map)
Figure 4.14 Location in Kem village (Level V in the map)
Figure 4.15 Location near Phoenix golf resort (Level V in the map)
The soil erosion map was validated through direct observation, confirming that erosion levels 4 and 5 are most prominent near Phoenix Golf Resort, Kem Village, and Doan Ket Village These areas primarily suffer from soil degradation due to unplanned land use and improper tree planting practices To analyze this issue further, I examined seven specific sites displaying significant erosion according to the updated map and measured their affected areas Comparing these measurements allowed me to identify patterns and variations in soil erosion severity across the studied locations, providing valuable insights for sustainable land management.
Table 4.7 Comparison of current erosion in map and by observation
The discrepancies between the erosion areas in Level IV and V are primarily due to the land use map being compiled in 2015, while the thesis was conducted in August 2016, meaning the C factor map reflects 2015 conditions rather than 2016 This timing difference accounts for variations in erosion area measurements Additionally, the comparison indicates an increase in ground cover from 2015 to 2016, which explains why observed erosion areas are smaller than those projected by the map.
After observation, I moved to estimate the amount of soil erosion for observed locations follow:
Figure 4.16 Observed locations Table 4.8 Soil Erosion estimation at observed locations
Location Level of erosion Total area (ha) Amount erosion estimated (tons)
Solutions
Implementing strategies to increase canopy cover, such as utilizing crop residue to enhance ground cover and planting trees, shrubs, or grass to establish a protective cover layer, is essential for soil conservation Protecting watershed forests and top hill areas is particularly effective in reducing soil erosion, as these measures shield soil from raindrop impact and help preserve soil fertility.
In addition, to increase the ability of erosion resistance we can also improve the fertility of soil by liming, fertilizing to increase the quality of soil
Areas with high ground cover and strong community protection experience minimal erosion, highlighting the importance of maintaining existing vegetation To preserve this stability, it is essential to implement suitable planting and tree exploitation strategies, along with appropriate cropping practices Keeping the current ground cover intact is crucial for preventing further erosion and ensuring the area's environmental resilience.
Erosion primarily affects bare land and forested steep slopes that have recently been clear-cut or replanted, increasing the risk of soil degradation To combat this, it is essential to replant these areas with fast-growing, soil-improving species such as Acacia and bamboo Choosing appropriate vegetation helps stabilize the soil, prevent further erosion, and minimize environmental damage, ensuring sustainable land management and restoration.
CONCLUSION AND RECOMMENDATION
Conclusion
Soil erosion is a natural process; however, human activities—particularly harmful practices—have significantly exacerbated the issue, turning it into a serious environmental and societal problem This deterioration threatens land productivity, ecosystems, and biodiversity, making effective management and prevention essential Understanding the causes and consequences of soil erosion is crucial for developing sustainable solutions to protect our environment.
- By using USLE model and GIS technology, the thesis formed some maps of R, K,
LS, C factor of the research area, then made the potential erosion map and current erosion map for Bui river watershed
- R factor in the study area is medium fluctuating from 950 – 1050mmand decrease from the North to the South
- Main soil type in the research area is yellow-red soil on sand (Fs) with K coefficient = 0.27
Approximately 65% of the area is covered by vegetation, which is a crucial factor in determining erosion potential Implementing a well-designed forest exploitation and planting plan is essential to effectively control and prevent soil erosion.
The thesis findings are reliable, as they were verified within the research area, ensuring their accuracy and relevance These results can serve as a valuable document for land use planning in the designated research region, supporting informed decision-making and sustainable development.
- The thesis proposed some solutions for each level of erosion Due to the limitation of time and budget, some solutions may not enough
- The research area has total potential erosion (level 5) up to 89% and current erosion is 89%divided equally for 3 levels (level 1, level 4 and level 5)
- The area of erosion tends to decrease due to good farming method and conscious of local people
Recommendation 41 REFERENCES
Soil erosion is a long-term process influenced significantly by rainfall intensity, making comprehensive data collection and surveys essential Research highlights the critical role of canopy cover in reducing erosion, emphasizing the importance of scheduling crops to maximize canopy during rainy seasons Effective erosion control must be stable and sustainable, utilizing natural factors and human resources to modify environmental conditions while maintaining these core requirements Expanding research using GIS technology at district or national levels is vital for better analysis, assessment, and solution selection in soil erosion management For future studies, integrating GIS with real-time erosion measurement techniques can enhance the practical application and accuracy of soil erosion research.