scholarly journals Modelisation Du Risque D’érosion Hydrique Par L’équation Universelle Des Pertes En Terre Dans Le Rif Occidental: Cas Du Bassin Versant De Moulay Bouchta (Maroc)

2018 ◽  
Vol 14 (3) ◽  
pp. 524 ◽  
Author(s):  
Anis Zouagui ◽  
Mohamed Sabir ◽  
Mustapha Naimi ◽  
Mohamed Chikhaoui ◽  
Moncef Benmansour
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Land Development ◽  
Principal Component ◽  
Slope Length ◽  
Increased Risk ◽  
Effect Of Support ◽  
Soil Losses

Soil erosion causes many environmental and socio-economic problems: loss of biodiversity, decrease in the productivity of agricultural land, siltation of dams and increased risk of flooding. It is therefore essential to establish a detailed evaluation of this process before any spatial planning. To evaluate the effects of soil erosion spatially and quantitatively in order to face this phenomenon, and propose the best conservation and land development strategies, the Universal Soil Loss Equation (USLE) coupled with a geographic information system (GIS) is applied. This model is a multiplication of the five erosion factors: the erosivity of the rain, the erodibility of the soil, the inclination and the slope length, the vegetation cover and the anti-erosion practices. The study area is the Moulay Bouchta watershed (7 889 ha), which is located in the western part of the Rif Mountains, is characterized by a complex and contrasting landscape. The resulting soil loss map shows an average erosion rate of 39.5 (t/ha/yr), 87% of the basin has an erosion rate above the tolerance threshold for soil loss (7 (t/ha/yr)). Soil losses per subbasin range from 16.2 to 81.4 (t/ha/yr). The amount of eroded soil is estimated at 311,591 (t/yr), corresponding to a specific degradation of 12.1 (t/ha/yr). In the absence of any erosion control, 25% of the soil losses would reach the new dam located a little upstream of the basin outlet, reducing its water mobilization capacity to 59,625 (m3/yr). The application of Principal Component Analysis (PCA) to soil erosion factors shows a significant influence of topographic factor (LS) on soil erosion process, followed by the effect of support practices (P), then by soil erodibility (K).

scholarly journals Sediment Yield and Soil Loss Estimation Using GIS Based Soil Erosion Model: A Case Study in the MAN Catchment, Madhya Pradesh, India

2021 ◽  
Vol 8 (1) ◽  
pp. 26
Author(s):  
Manti Patil ◽  
Radheshyam Patel ◽  
Arnab Saha
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Crop Production ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Reservoir Sedimentation ◽  
Reservoir Water ◽  
Slope Length ◽  
Soil Erosion Rate

Soil erosion is one of the most critical environmental hazards of recent times. It broadly affects to agricultural land and reservoir sedimentation and its consequences are very harmful. In agricultural land, soil erosion affects the fertility of soil and its composition, crop production, soil quality and land quality, yield and crop quality, infiltration rate and water holding capacity, organic matter and plant nutrient and groundwater regimes. In reservoir sedimentation process the consequences of soil erosion process are reduction of the reservoir capacity, life of reservoir, water supply, power generation etc. Based on these two aspects, an attempt has been made to the present study utilizing Revised Universal Soil Loss Equation (RUSLE) has been used in integration with remote sensing and GIS techniques to assess the spatial pattern of annual rate of soil erosion, average annual soil erosion rate and erosion prone areas in the MAN catchment. The RUSLE considers several factors such as rainfall, soil erodibility, slope length and steepness, land use and land cover and erosion control practice for soil erosion prediction. In the present study, it is found that average annual soil erosion rate for the MAN catchment is 13.01-tons/ha/year, which is higher than that of adopted and recommended values for the project. It has been found that 53% area of the MAN catchment has negligible soil erosion rate (less than 2-tons/ha/year). Its spatial distribution found on flat land of upper MAN catchment. It has been detected that 26% area of MAN catchment has moderate to extremely severe soil erosion rate (greater than 10-tons/ha/year). Its spatial distribution has been found on undulated topography of the middle MAN catchment. It is proposed to treat this area by catchment area treatment activity.

scholarly journals Prioritization of Watershed Using Remote Sensing and Geographic Information System

2021 ◽  
Vol 13 (16) ◽  
pp. 9456
Author(s):  
Devendra Kumar ◽  
Arvind Dhaloiya ◽  
Ajeet Singh Nain ◽  
Mahendra Paal Sharma ◽  
Amandeep Singh
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Soil Erosion ◽  
Natural Resources ◽  
Best Management Practices ◽  
Soil Loss ◽  
Management Practices ◽  
Agricultural Land ◽  
Geographical Information ◽  
Slope Length

Soil erosion is becoming a major concern at the watershed scale for the environment, natural resources, and sustainable resource management. Therefore, the estimation of soil loss through this phenomenon and the identification of critical soil erosion-prone areas are considered to be key tasks in the soil conservation programme for the design and implementation of best management practices for specific regions or areas. In the present study, revised universal soil loss equation (RUSLE) modelling is combined with remote sensing (RS) and geographical information system (GIS) techniques and used to predict soil erosion and the prioritization of watersheds in Nainital district Uttarakhand, India. For the estimation of soil loss, different factors, namely, rainfall-runoff erosivity (R) factor, soil erodability (K) factor, slope length steepness (LS) factor, cover management (C) factor, and the erosion control practices (P) factor were computed. The data on various other aspects such as land use/land cover (LU/LC), the digital elevation model (DEM), slope, contours, drainage network, soil texture, organic matter, and rainfall were integrated to prepare a database for the RUSLE equation by employing ENVI & QGIS software. The results showed that a major portion (70.26%) of Nainital district is covered with forest, followed by area under fallow and agricultural land. Annual average soil loss ranged between 20 to 80 t ha−1 yr−1 in the study area. Out of 50 watersheds in the study area, 7 watersheds were given top priority for conserving natural resources, while 11 watersheds, mostly in the east-central part of Nainital, were kept under the next priority category. Only 4 watersheds of the total were given lowest priority. Moreover, it was concluded that major portions of Nainital district were in a severely prone category of soil erosion, and therefore required immediate action plans to check soil erosion and evade the possibility of landslides.

scholarly journals Soil Erosion Estimation Using RUSLE Modeling and Geospatial Tool: Case Study of Kathmandu District, Nepal

2020 ◽  
Vol 17 ◽  
pp. 118-134
Author(s):  
Roshan Dahal
Keyword(s):  
Soil Erosion ◽  
Spatial Data ◽  
Soil Loss ◽  
Erosion Rate ◽  
Slope Length ◽  
Erosion Rates ◽  
High Erosion Rate ◽  
Time Savings ◽  
Data Screening

Revised Universal Soil Loss Equation (RUSLE) model is applied in this study to evaluate the risk of erosion in Kathmandu district. The calculation of erosion requires certain data from various sources available in different formats and scales. Geographic Information System (GIS) was used which allowed considerable time savings in the processing of spatial data, screening the effects of each factor affecting soil erosion. Among various erosion factors, topography, rainfall, soil properties, and soil conservation practices were used for the study. Average soil loss was calculated by multiplying these factors. Final results of soil erosion rates were separated into six classes based on erosion severity, in which 2.18% of land (> 80Mg ha-1yr-1), followed by 2.85% of land (40-80 Mg ha-1yr-1), 5.56% of land (20-40 Mg ha-1yr-1), 8.73% of land (10-20 Mg ha-1yr-1), 10.53% of land (5-10 Mg ha-1yr-1) and 70.14% of land (0-5 Mg ha-1yr-1), falls under very severe, severe, very high, moderate and low severity zone respectively. Area having high slope length (LS) factor has high erosion rate. In Dakshinkali, Nagarjun and Budanilkantha area, there is high erosion rate. From the result, spatial distribution of soil erosion across Kathmandu district, can be applied for management and controlling the erosion.

scholarly journals Estimation of Soil Erosion in Nepal Using a RUSLE Modeling and Geospatial Tool

Geosciences ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 147 ◽  
Author(s):  
Pooja Koirala ◽  
Sudeep Thakuri ◽  
Subesh Joshi ◽  
Raju Chauhan
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Entire Area ◽  
Barren Land ◽  
Erosion Risk ◽  
Soil Erosion Rate ◽  
Severe Erosion ◽  
The Mean

Soil erosion is a major issue, causing the loss of topsoil and fertility in agricultural land in mountainous terrain. Estimation of soil erosion in Nepal is essential because of its agriculture-dependent economy (contributing 36% to national GDP) and for preparing erosion control plans. The present study, for the first time, attempts to estimate the soil loss of Nepal through the application of the Revised Universal Soil Loss Equation (RUSLE) model. In addition, it analyzes the effect of Land Use and Land Cover (LULC) and slope ( β ) exposition on soil erosion. Nation-wide mean annual soil loss of Nepal is estimated at 25 t ha−1 yr−1 with a total of 369 million tonnes (mT) of potential soil loss. Soil erosion based on the physiographic region of the country shows that the Middle Mountains, High Mountains, High Himal, Chure, and Terai have mean erosion rates of 38.0, 32.0, 28.0, 7.0, and 0.1 t ha−1 yr−1. The soil erosion rate by basins showed that the annual erosions of the Karnali, Gandaki, Koshi, and Mahakali River basins are 135, 96, 79, and 15 mT, respectively. The mean soil erosion rate was significantly high (34 t ha−1 yr−1) for steep slopes (β > 26.8%) and the low (3 t ha−1 yr−1) for gentle slopes (β < 5%). Based on LULC, the mean erosion rate for barren land was the highest (40 t ha−1 yr−1), followed by agricultural land (29 t ha−1 yr−1), shrubland (25 t ha−1 yr−1), grassland (23 t ha−1 yr−1), and forests (22 t ha−1 yr−1). The entire area had been categorized into 6 erosion classes based on the erosion severity, and 11% of the area was found to be under a very severe erosion risk (> 80 t ha−1 yr−1) that urgently required reducing the risk of erosion.

scholarly journals Soil loss estimation and severity mapping using RUSLE model and GIS: a case study in Megech Watershed, Ethiopia

2022 ◽  
Author(s):  
Legese Abebaw Getu ◽  
Attila Nagy ◽  
Hailu Kendie Addis
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Risk Category ◽  
Model Parameters ◽  
Main Concern ◽  
Slope Length ◽  
Rusle Model ◽  
Soil Erosion Rate ◽  
Very High

Abstract AbstractBackground: Soil erosion is the most serious problem that affects economic development, food security, and ecosystem services which is the main concern in Ethiopia. This study focused on quantifying soil erosion rate and severity mapping of the Megech watershed for effective planning and decision-making processes to implement protection measures. The RUSLE model integrated with ArcGIS software was used to conduct the present study. The six RUSLE model parameters: erosivity, erodibility, slope length and steepness, cover management, and erosion control practices were used as input parameters to predict the average annual soil loss and identify erosion hotspots in the watershed. Results: The RUSLE estimated 1,399,210 tons yr-1 total soil loss from the watershed with a mean annual soil loss of 32.84 tons ha-1yr-1. The soil erosion rate was varied from 0.08 to greater than 500 tons ha-1yr-1. A severity map with seven severity classes was created for 27 sub-watersheds: low (below 10), moderate (10-20), high (20-30), very high (30-35), severe (35-40), very severe (40-45) and extremely severe (above 45) in which the values are in tons ha-1yr-1. The area coverage was 6.5%, 11.1%, 8.7%, 22%, 30.9%, 13.4%, and 7.4% for low, moderate, high, very high, severe, very severe, and extremely severe erosion classes respectively. Conclusion: About 82 % of the watershed was found in more than the high-risk category which reflects the need for immediate land management action. This paper could be important for decision-makers to prioritize critical erosion hotspot areas for comprehensive and sustainable management of the watershed.

scholarly journals Soil erosion assessment and control in Northeast Wollega, Ethiopia

2015 ◽  
Vol 7 (4) ◽  
pp. 3511-3540 ◽  
Author(s):  
A. Adugna ◽  
A. Abegaz ◽  
A. Cerdà
Keyword(s):  
Soil Erosion ◽  
Land Tenure ◽  
Water Conservation ◽  
Soil Loss ◽  
Erosion Control ◽  
Temporal Variations ◽  
Farm Income ◽  
Slope Length ◽  
Soil Erosion Control ◽  
Soil Losses

Abstract. Soil erosion is the main driver of land degradation in Ethiopia, and in the whole region of East Africa. This study was conducted at the Northeast Wollega in West Ethiopia to estimate the soil losses by means of the Revised Universal Soil Loss Equation (RUSLE). The purpose of this paper is to identify erosion spot areas and target locations for appropriate development of soil and water conservation measures. Fieldwork and household survey were conducted to identify major determinants of soil erosion control. Six principal factors were used to calculate soil loss per year, such as rainfallerosivity, soil erodiblity, slope length, slope steepness, crop management and erosion-control practices. The soil losses have shown spatio-temporal variations that range from 4.5 Mg ha-1 yr-1 in forest to 65.9 Mg ha-1 yr-1 in cropland. Results from the analysis of stepwise multiple linear regression show that sustainable soil erosion control are determined byknowledge of farmers about soil conservation, land tenure security and off-farm income at community level. Thus, policy aim at keeping land productivity will need to focus on terracing, inter-cropping and improved agro-forestry practices.

scholarly journals Analysis of Ownership Data from Consolidated Land Threatened by Water Erosion in the Vlára Basin, Slovakia

2020 ◽  
Vol 13 (1) ◽  
pp. 51
Author(s):  
Alexandra Pagáč Mokrá ◽  
Jakub Pagáč ◽  
Zlatica Muchová ◽  
František Petrovič
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Agricultural Land ◽  
Water Erosion ◽  
Land Consolidation ◽  
Land Fragmentation ◽  
Erosion Risk ◽  
Definition Of ◽  
The Relationship ◽  
Soil Loss Equation

Water erosion is a phenomenon that significantly damages agricultural land. The current land fragmentation in Slovakia and the complete ambiguity of who owns it leads to a lack of responsibility to care for the land in its current condition, which could affect its sustainability in the future. The reason so much soil has eroded is obvious when looking at current land management, with large fields, a lack of windbreaks between them, and no barriers to prevent soil runoff. Land consolidation might be the solution. This paper seeks to evaluate redistributed land and, based on modeling by the Universal Soil Loss Equation (USLE) method, to assess the degree of soil erosion risk. Ownership data provided information on how many owners and what amount of area to consider, while taking into account new conditions regarding water erosion. The results indicate that 2488 plots of 1607 owners which represent 12% of the model area are still endangered by water erosion, even after the completion of the land consolidation project. The results also presented a way of evaluating the territory and aims to trigger a discussion regarding an unambiguous definition of responsibility in the relationship between owner and user.

scholarly journals Soil Erosion Estimates in Arid Region: A Case Study of the Koutine Catchment, Southeastern Tunisia

2021 ◽  
Vol 11 (15) ◽  
pp. 6763
Author(s):  
Mongi Ben Zaied ◽  
Seifeddine Jomaa ◽  
Mohamed Ouessar
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Scientific Evidence ◽  
Field Measurements ◽  
Spatiotemporal Variability ◽  
Soil Conditions ◽  
Storm Events ◽  
Erosion Processes ◽  
Study Results ◽  
Soil Losses

Soil erosion remains one of the principal environmental problems in arid regions. This study aims to assess and quantify the variability of soil erosion in the Koutine catchment using the RUSLE (Revised Universal Soil Loss Equation) model. The Koutine catchment is located in an arid area in southeastern Tunisia and is characterized by an annual mean precipitation of less than 200 mm. The model was used to examine the influence of topography, extreme rainstorm intensity and soil texture on soil loss. The data used for model validation were obtained from field measurements by monitoring deposited sediment in settlement basins of 25 cisterns (a traditional water harvesting and storage technique) over 4 years, from 2015 to 2018. Results showed that slope is the most controlling factor of soil loss. The average annual soil loss in monitoring sites varies between 0.01 and 12.5 t/ha/y. The storm events inducing the largest soil losses occurred in the upstream part of the Koutine catchment with a maximum value of 7.3 t/ha per event. Soil erosion is highly affected by initial and preceding soil conditions. The RUSLE model reasonably reproduced (R2 = 0.81) the spatiotemporal variability of measured soil losses in the study catchment during the observation period. This study revealed the importance of using the cisterns in the data-scarce dry areas as a substitute for the classic soil erosion monitoring fields. Besides, combining modeling of outputs and field measurements could improve our physical understanding of soil erosion processes and their controlling factors in an arid catchment. The study results are beneficial for decision-makers to evaluate the existing soil conservation and water management plans, which can be further adjusted using appropriate soil erosion mitigation options based on scientific evidence.

scholarly journals Assessment of land cover on soil erosion in Lam Phra Phloeng watershed by USLE model

2018 ◽  
Vol 192 ◽  
pp. 02017 ◽  
Author(s):  
Jatuwat Wattanasetpong ◽  
Uma Seeboonruang ◽  
Uba Sirikaew ◽  
Walter Chen
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Soil Loss ◽  
Land Development ◽  
Developed Countries ◽  
Surface Erosion ◽  
Agricultural Field ◽  
Land Cover Data

Soil loss due to surface erosion has been a global problem not just for developing countries but also for developed countries. One of the factors that have greatest impact on soil erosion is land cover. The purpose of this study is to estimate the long-term average annual soil erosion in the Lam Phra Phloeng watershed, Nakhon Ratchasima, Thailand with different source of land cover by using the Universal Soil Loss Equation (USLE) and GIS (30 m grid cells) to calculate the six erosion factors (R, K, L, S, C, and P) of USLE. Land use data are from Land Development Department (LDD) and ESA Climate Change Initiative (ESA/CCI) in 2015. The result of this study show that mean soil erosion by using land cover from ESA/CCI is less than LDD (29.16 and 64.29 ton/ha/year respectively) because soil erosion mostly occurred in the agricultural field and LDD is a local department that survey land use in Thailand thus land cover data from this department have more details than ESA/CCI.

scholarly journals Estimation of annual soil erosion dynamics (2005 - 2015) in Pakistan using Revised Universal Soil Loss Equation (RUSLE)

2021 ◽  
Author(s):  
Hammad Gilani ◽  
Adeel Ahmad ◽  
Isma Younes ◽  
Sawaid Abbas
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Management Practices ◽  
Climatic Factors ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Conservation Practice ◽  
Administrative Units ◽  
Soil Loss Equation

Abrupt changes in climatic factors, exploitation of natural resources, and land degradation contribute to soil erosion. This study provides the first comprehensive analysis of annual soil erosion dynamics in Pakistan for 2005 and 2015 using publically available climatic, topographic, soil type, and land cover geospatial datasets at 1 km spatial resolution. A well-accepted and widely applied Revised Universal Soil Loss Equation (RUSLE) was implemented for the annual soil erosion estimations and mapping by incorporating six factors; rainfall erosivity (R), soil erodibility (K), slope-length (L), slope-steepness (S), cover management (C) and conservation practice (P). We used a cross tabular or change matrix method to assess the annual soil erosion (ton/ha/year) changes (2005-2015) in terms of areas and spatial distriburtions in four soil erosion classes; i.e. Low (<1), Medium (1–5], High (5-20], and Very high (>20). Major findings of this paper indicated that, at the national scale, an estimated annual soil erosion of 1.79 ± 11.52 ton/ha/year (mean ± standard deviation) was observed in 2005, which increased to 2.47 ±18.14 ton/ha/year in 2015. Among seven administrative units of Pakistan, in Azad Jammu & Kashmir, the average soil erosion doubled from 14.44 ± 35.70 ton/ha/year in 2005 to 28.03 ± 68.24 ton/ha/year in 2015. Spatially explicit and temporal annual analysis of soil erosion provided in this study is essential for various purposes, including the soil conservation and management practices, environmental impact assessment studies, among others.

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