Exploring the Relationship between Cover Crop Adoption and Soil Erosion Severity: A Case Study from the Simcoe Watershed, Ontario, Canada

Runoff from agricultural fields during the nongrowing season is a significant factor leading to phosphorous loading and diminishing water quality in Lake Simcoe, Ontario. Cover crops offer the potential to alleviate phosphorous loss during the nongrowing season by minimizing soil erosional processes and uptaking excess phosphorous; however, recent research suggests that its adoption remains relatively low. More concern lies with the lack of cover crop adoption on areas that are sensitive to soil erosion. This study intends to investigate the likelihood of agricultural productions located on erosive soils to adopt cover crops. Using satellite imagery in corroboration with the Universal Soil Loss Equation (USLE), this study reveals the frequency of cover crop production and associates soil loss sensitivity at a 30 m resolution from 2013 to 2018. Consistent with recent literature, this study reveals that a small portion (18%) of agricultural operations in the south Simcoe Watershed have incorporated cover crops over the past six years. Cover crops tend to be adopted at a low frequency in areas that have a low sensitivity to soil erosion. This study reveals that areas with higher soil erosion sensitivity are consistent with low-frequency adoption, indicating that these areas are less likely to adopt cover crops regularly. Promoting farm-scale benefits associated with cover crops should target areas in the south Simcoe Watershed that are prone to soil erosion to mitigate total phosphorus (TP) loading into Lake Simcoe.

Assessment of Land Use and Land Cover Changes on Soil Erosion Using Remote Sensing, GIS and RUSLE Model: A Case Study of Battambang Province, Cambodia

Soil erosion causes land degradation which negatively impacts not only natural resources but also livelihoods of people due to low agricultural productivity. Cambodia is prone to soil erosion due to poor agricultural practices. In this research we use Battambang province as a case study to quantify impact of land use and land cover change (LULC) on soil erosion. This study assessed the impact from LULC changes to soil erosion. LULC change maps were analyzed based on Landsat satellite imagery of 1998, 2008, and 2018, computed in QGIS 6.2.9, while the soil erosion loss was estimated by the integration of remote sensing, GIS tools, and Revised Universal Soil Loss Equation (RUSLE) model. The results showed that the area of agricultural land of Battambang province significantly increased from 44.50% in 1998 to 61.11% in 2008 and 68.40% in 2018. The forest cover significantly decreased from 29.82% in 1998 to 6.18% in 2018. Various soil erosion factors were estimated using LULC and slope. Based on that, the mean soil loss was 2.92 t/ha.yr in 1998, 4.20 t/ha.yr in 2008, and 4.98 t/ha.yr in 2018. Whereas the total annual soil loss was 3.49 million tons in 1998, 5.03 million tons in 2008, and 5.93 million tons in 2018. The annual soil loss at the agricultural land dramatically increased from 190,9347.9 tons (54%) in 1998 to 3,543,659 tons (70.43%) in 2008 and to 4,267,439 tons (71.91%) in 2018 due to agricultural land expansion and agricultural practices. These losses were directly correlated with LULC, especially agricultural land expansion and forest cover decline. Our results highlight the need to develop appropriate land use and crop management practices to decrease land degradation and soil erosion. These data are useful to bring about public awareness of land degradation and alert local citizens, researchers, policy makers, and actors towards land rehabilitation to bring the area of land back to a state which is safe for increasing biodiversity and agricultural productivity. Measures to reduce or prevent soil erosion and the use of conservation agriculture practices, along with water and soil conservation, management, agroforestry practices, vegetation cover restoration, the creation of slope terraces, and the use of direct sowing mulch-based cropping systems should be considered.

Modeling and Assessing Potential Soil Erosion Hazards Using USLE and Wind Erosion Models in Integration with GIS Techniques: Dakhla Oasis, Egypt

Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. The current study proposed a spatial-based model that integrated geographic information systems (GIS) techniques with both the universal soil loss equation (USLE) model and the Index of Land Susceptibility to Wind Erosion (ILSWE). The proposed Spatial Soil Loss Model (SSLM) was designed to generate the potential soil erosion maps based on water erosion and wind erosion by integrating factors of the USLE and ILSWE models into the GIS environment. Hence, the main objective of this study is to predict, quantify, and assess the soil erosion hazards using the SSLM in the Dakhla Oasis as a case study. The water soil loss values were computed by overlaying the values of five factors: the rainfall factor (R-Factor), soil erodibility (K-Factor), topography (LS-Factor), crop types (C-Factor), and conservation practice (P-Factor). The severity of wind-driven soil loss was calculated by overlaying the values of five factors: climatic erosivity (CE-Factor), soil erodibility (E-Factor), soil crust (SC-Factor), vegetation cover (VC-Factor), and surface roughness (SR-Factor). The proposed model was statistically validated by comparing its outputs to the results of USLE and ILSWE models. Soil loss values based on USLE and SSLM varied from 0.26 to 3.51 t ha−1 yr−1 with an average of 1.30 t ha−1 yr−1 and from 0.26 to 3.09 t ha−1 yr−1 with a mean of 1.33 t ha−1 yr−1, respectively. As a result, and according to the assessment of both the USLE and the SSLM, one soil erosion class, the very low class (<6.7 t ha−1 yr−1), has been reported to be the prevalent erosion class in the study area. These findings indicate that the Dakhla Oasis is slightly eroded and more tolerable against water erosion factors under current management conditions. Furthermore, the study area was classified into four classes of wind erosion severity: very slight, slight, moderate, and high, representing 1.0%, 25.2%, 41.5%, and 32.3% of the total study area, respectively, based on the ILSWE model and 0.9%, 25.4%, 43.9%, and 29.9%, respectively, according to the SSLM. Consequently, the Dakhla Oasis is qualified as a promising area for sustainable agriculture when appropriate management is applied. The USLE and ILSWE model rates had a strong positive correlation (r = 0.97 and 0.98, respectively), with the SSLM rates, as well as a strong relationship based on the average linear regression (R2 = 0.94 and 0.97, respectively). The present study is an attempt to adopt a spatial-based model to compute and map the potential soil erosion. It also pointed out that designing soil erosion spatial models using available data sources and the integration of USLE and ILSWE with GIS techniques is a viable option for calculating soil loss rates. Therefore, the proposed soil erosion spatial model is fit for calculating and assessing soil loss rates under this study and is valid for use in other studies under arid regions with the same conditions.

Spatial Analysis of Erosion and Quantification of Soil Losses in Western Algeria

The objective of this study is to establish a soil loss map of a region located in western Algeria allowing the spatialization of erosion models, deposition, and quantification of soil loss. The model applied is Universal Soil Loss Equation (USLE), wich was developed by Wischmeier and Smith. The map of current soil losses derived from it shows five areas: very low, low, medium, strong, and very strong. The significant loss in soil areas is located in most of the south of the area, the upstream mountains part, and a portion to the northwest of the region. They cover an area of 16,805 ha (15.27%) of the study area. The remainder of area constituting unrigged flat terrain accounts for a loss in low soil. The latter receives all the solid contributions which are deposited there constituting an important deposit.

Estimation of Soil Erosion and Sediment Yield in the Lancang–Mekong River Using the Modified Revised Universal Soil Loss Equation and GIS Techniques

The Lancang–Mekong River basin, as an important transboundary river in Southeast Asia, is challenged by rapid socio-economic development, especially the construction of hydropower dams. Furthermore, substantial factors, such as terrain, rainfall, soil properties and agricultural activity, affect and are highly susceptible to soil erosion and sediment yield. This study aimed to estimate average annual soil erosion in terms of spatial distribution and sediment deposition by using the revised universal soil loss equation (RUSLE) and GIS techniques. This study also applied remote sensing and available data sources for soil erosion analysis. Annual soil erosion in most parts of the study area range from 700 to 10,000 t/km2/y with a mean value of 5350 t/km2/y. Approximately 45% of the total area undergoes moderate erosion. Moreover, the assessments of sediment deposition and erosion using the modified RUSLE and the GIS techniques indicate high sediment erosion along the flow direction of the mainstream, from the upper Mekong River to the Mekong Delta. The northern part of the upper Mekong River and the central and southern parts of the lower Mekong River are the most vulnerable to the increase in soil erosion rates, indicating sediment deposition.

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

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.

An assessment to prioritise the critical erosion-prone sub-watersheds for soil conservation in the Gumti basin of Tripura, North-East India

Erosion-induced land degradation problem has emerged as a serious environmental issue across the world. Assessment of this problem through modelling can generate valuable quantitative information for the planners to identify priority areas for proper soil conservation measures. The Gumti River basin of Tripura falls under humid tropical climate and experiences soil erosion for a prolonged period which has turned into a major environmental issue. Increased sediment supply through top soil erosion is one of the major reasons for reduced navigability of this river. Thus, the present study is an attempt to prioritize the sub-watersheds of the Gumti basin by estimating soil loss through the USLE (Universal Soil Loss Equation) model. For that purpose, five parameters of the USLE model were processed, computed and overlaid in a GIS environment. The result shows that potential mean annual soil loss of the Gumti basin ranges between 0.03 and 114.08 t ha^-1 year^-1. The resultant values of soil loss were classified into five categories considering the minimum and maximum values. It has been identified that low, moderate, high, very high and severe soil loss categories occupy 68.71, 8.94, 5.86, 5.02 and 11.47% of the basin respectively. Moreover, it has been recognised that sub-watersheds like SW7, SW8, SW12, SW21, SW24 and SW29 fall under very high priority class for which mitigation measures are essential. Therefore, the present study recommends mitigation measures through terrace cultivation, as an alternative of shifting cultivation in the hilly areas and through construction of check dams at the appropriate sites of the erosion prone sub-watersheds. Moreover, proper afforestation programmes that have been implemented successfully in other parts of Tripura through the Japan International Cooperation Agency, Joint Forest Management, and National Afforestation Programme should be initiated in the highly erosion-prone areas of the Gumti River basin.