The measurement, estimation and monitoring of soil erosion by runoff at the field scale: Challenges and possibilities with particular reference to Britain

2019 ◽  
Vol 44 (1) ◽  
pp. 31-49 ◽  
Author(s):  
John Boardman ◽  
Robert Evans
Keyword(s):  
Soil Erosion ◽  
Arable Land ◽  
Small Scale ◽  
Detailed Data ◽  
Field Scale ◽  
Volumetric Measurement ◽  
Alternative Strategies ◽  
Erosion Risk ◽  
Erosion Rates ◽  
Scale Challenges

Soil erosion is widely acknowledged as a global problem but attempts to measure and estimate its significance are frustrated by our inability to develop reliable, cheap and easy methods of assessment. The limitations of qualitative methods such as GLASOD, errors and inaccuracies inherent in modelling based on small-scale plot experiments, and problems with 137Cs approaches, mean that alternative strategies are required. For runoff-related erosion on arable land we propose the use of a well-tried estimation technique: volumetric measurement of rills, gullies and fans. Amounts of wash and interrill erosion can also be estimated. This approach allows for the estimation of erosion rates at the field scale, rather than relying on extrapolations from plot-based data. Measurements are based on sampling the population of rills and gullies and can be adapted to the aims of the project for ‘broad-brush’ or detailed data. Monitoring of large areas to produce regional assessments of erosion risk is frequently required and volumetric estimates provide these data. Thus predictions of the extent, frequency and amounts of erosion can be made and the vulnerability of particular crops becomes clear.

Erosion and sediment transport models with reference to the needs of small scale

2021 ◽  
Author(s):  
Ahsan Raza ◽  
Thomas Gaiser ◽  
Muhammad Habib-Ur-Rahman ◽  
Hella Ahrends
Keyword(s):  
Soil Erosion ◽  
Overland Flow ◽  
Model Development ◽  
Agroforestry Systems ◽  
Specific Model ◽  
Small Scale ◽  
Field Scale ◽  
Erosion Prediction ◽  
Dynamic Components ◽  
Output Information

<p>Information on field scale soil erosion and related sedimentation process is very important for natural resource management and sustainable farming. Plenty of models are available for study of these processes but only a few are suitable for dynamic small scale soil erosion assessments. The available models vary greatly in terms of their input requirements, analysis capabilities, process [t1] complexities, spatial and temporal scale of their intended use, practicality, the manner they represent the processes, and the type of output information they provide. The study aims in examining, theoretically, 51 models classified as physical, conceptual, and empirical based on their representation of the processes of soil erosion. The literature review shows that there is no specific model available for soil erosion prediction under agroforestry systems.   It is further suggested that models like EPIC, PERFECT, GUEST, EPM, TCRP, SLEMSA, APSIM, RillGrow, and CREAMS can be potentially used for soil erosion assessment at plot/field scale at daily time steps. Most of these models are capable to simulate the soil erosion process at small scale; further model development is needed regarding their limitations with respect to components interaction i.e., rainfall intensity, overland flow, crop cover, and their difficulties in upscaling. The research suggested that SIMPLACE network can provide modules with LintulBiomass, HillFlow, Runoff to develop new dynamic components to simulate overland flow and soil erosion incorporating improved upscaling capabilities</p>

scholarly journals Spatiotemporal Analysis of Potential Impact of Soil Erosion on Maize and Groundnuts Yield in Northern Ghana

2021 ◽  
Vol 5 (2) ◽  
pp. 486-493
Author(s):  
Wilson Agyei Agyare ◽  
Eliasu Salifu
Keyword(s):  
Soil Erosion ◽  
Water Conservation ◽  
Arable Land ◽  
Current Trend ◽  
Spatiotemporal Analysis ◽  
Crop Productivity ◽  
Potential Effect ◽  
Northern Ghana ◽  
Erosion Rates ◽  
North East

Abstract Soil erosion is a threat to the viability of arable land, which has a relationship with crop productivity. This study was carried out in the Northern, North-East and Savannah Regions of Ghana, which have a high agricultural potential. The study examined erosion-yield relationship by comparing estimated erosion rates with maize and groundnut yields in a GIS environment. The study also projected soil erosion and determined its potential effect on the yield of maize and groundnuts. The soil erosion rates were found to be 4.2 t ha-1y-1, 5.1 t ha-1y-1 and 7.1 t ha-1y-1 for the Northern, North-East and Savannah Regions respectively. Projections for the next 10 years showed that, soil erosion will averagely increase by about 12 %, which could reduce the yield of maize and groundnut by 21 % and 16 % respectively by the year 2031, should the current trend continue. The study also found out that crop (maize and groundnut) yield per land area is relatively lower in areas severely affected by soil erosion. Farmers in the study area and areas of similar ecology must be encouraged to adopt Soil and Water Conservation (SWC) strategies to enhance and sustain productivity.

Assessment and Monitoring of Soil Erosion Risk and Land Degradation in Arable Land Combining Remote Sensing Methodologies and RUSLE Factors

2021 ◽  
pp. 704-716
Author(s):  
Biagio Tucci ◽  
Gabriele Nolè ◽  
Antonio Lanorte ◽  
Valentina Santarsiero ◽  
Giuseppe Cillis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Land Degradation ◽  
Arable Land ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
Assessment And Monitoring

scholarly journals Spatial distribution of water erosion risk in a watershed with eucalyptus and Atlantic Forest

2013 ◽  
Vol 37 (5) ◽  
pp. 427-434 ◽  
Author(s):  
Junior Cesar Avanzi ◽  
Marx Leandro Naves Silva ◽  
Nilton Curi ◽  
Lloyd Darrell Norton ◽  
Samuel Beskow ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Atlantic Forest ◽  
Soil Loss ◽  
Management Practices ◽  
Water Erosion ◽  
Native Forest ◽  
Erosion Risk ◽  
Erosion Rates ◽  
Soil Loss Tolerance ◽  
Loss Tolerance

The process of water erosion occurs in watersheds throughout the world and it is strongly affected by anthropogenic influences. Thus, the knowledge of these processes is extremely necessary for planning of conservation efforts. This study was performed in an experimental forested watershed in order to predict the average potential annual soil loss by water erosion using the Universal Soil Loss Equation (USLE) and a Geographic Information System (GIS), and then compared with soil loss tolerance. All the USLE factors were generated in a distributed approach employing a GIS tool. The layers were multiplied in the GIS framework in order to predict soil erosion rates. Results showed that the average soil loss was 6.2 Mg ha-1 yr-1. Relative to soil loss tolerance, 83% of the area had an erosion rate lesser than the tolerable value. According to soil loss classes, 49% of the watershed had erosion less than 2.5 Mg ha-1 yr-1. However, about 8.7% of the watershed had erosion rates greater than 15 Mg ha-1 yr-1, being mainly related to Plinthosol soil class and roads, thus requiring special attention for the improvement of sustainable management practices for such areas. Eucalyptus cultivation was found to have soil loss greater than Atlantic Forest. Thus, an effort should be made to bring the erosion rates closer to the native forest. Implementation of the USLE model in a GIS framework was found to be a simple and useful tool for predicting the spatial variation of soil erosion risk and identifying critical areas for conservation efforts.

scholarly journals Mapping Spatio-Temporal Soil Erosion Patterns in the Candelaro River Basin, Italy, Using the G2 Model with Sentinel2 Imagery

Geosciences ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 89 ◽  
Author(s):  
Christos Karydas ◽  
Ouiza Bouarour ◽  
Pandi Zdruli
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Arable Land ◽  
European Space Agency ◽  
Retention Factor ◽  
Mitigation Measures ◽  
Erosion Rates ◽  
Apulia Region ◽  
Space Agency ◽  
Spatio Temporal

This study aims at mapping soil erosion caused by water in the Candelaro river basin, Apulia region, Italy, using the G2 erosion model. The G2 model can provide erosion maps and statistical figures at month-time intervals, by applying non data-demanding alternatives for the estimation of all the erosion factors. In the current research, G2 is taking a step further with the introduction of Sentinel2 satellite images for mapping vegetation retention factor on a fine scale; Sentinel2 is a ready-to-use, image product of high quality, freely available by the European Space Agency. Although only three recent cloud-free Sentinel2 images covering Candelaro were found in the archive, new solutions were elaborated to overcome time-gaps. The study in Candelaro resulted in a mean annual erosion rate of 0.87 t ha−1 y−1, while the autumn months were indicated to be the most erosive ones, with average erosion rates reaching a maximum of 0.12 t ha−1 in September. The mixed agricultural-natural patterns revealed to be the riskiest surfaces for most months of the year, while arable land was the most extensive erosive land cover category. The erosion maps will allow competent authorities to support relevant mitigation measures. Furthermore, the study in Candelaro can play the role of a pilot study for the whole Apulia region, where erosion studies are rather limited.

scholarly journals Assessment of Soil Erosion at Multiple Spatial Scales Following Land Use Changes in 1980-2017 in the Black Soil Region, (NE) China

2020 ◽  
Author(s):  
Haiyan Fang ◽  
Zemeng Fan
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Spatial Scales ◽  
Land Use Changes ◽  
Arable Land ◽  
Rainfall Erosivity ◽  
Erosion Rates ◽  
Soil Erosion Rate

Impact of land use and land cover (LULC) change on soil erosion is still imperfectly understood, especially in northeastern China (NEC). Based on the Revised Universal Loss Equation (RUSLE), the variability of soil erosion at different spatial scales following land use changes in1980, 1990, 2000, 2010, and 2017 was analyzed. The regionally spatial patterns of soil loss coincided with the topography, rainfall erosivity, soil erodibility, and use patterns, and around 45% soil loss came from arable land. Regionally, soil erosion rates increased from 1980 to 2010 and decreased from 2010 to 2017, ranging from 3.91 to 4.45 t ha-1 yr-1 with an average of 4.22 t ha-1 yr-1 in 1980-2017. The rates of soil erosion less than 1.41 t ha-1 yr-1 decreased from 1980 to 2010, and increased from 2010 to 2017, and opposite changing patterns occurred in higher erosion classes (i.e., above 5 t ha-1 yr-1). At a provincial scale, Liaoning Province experienced the highest soil erosion rate of 9.43 t ha-1 yr-1, followed by Jilin Province, the east Inner Mongolia, and Heilongjing Province. Arable land continuously increased at the expense of forest in the high-elevation and steep-slope areas from 1980 to 2010, and decreased from 2010 to 2017, resulting in increased areas with erosion rates higher than 7.05 t ha-1 yr-1. At a county scale, around 75% of the countries had soil erosion rate higher than its tolerance level. The county numbers with higher erosion rate increased in 1980-2010 and decreased in 2010- 2017, resulting from the sprawl and withdrawal of arable land. The results indicate that appropriate policies can control soil loss through limiting arable land sprawl in areas of unfavorable regions in the NEC.

scholarly journals Estimation of Soil Loss Using Remote Sensing And GIS-Based Universal Soil Loss Equation In Northern Catchment of Lake Tana Sub-Basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Author(s):  
Veera Narayana Balabathina ◽  
Raju RP ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Lake Tana ◽  
Erosion Risk ◽  
Priority Areas ◽  
Erosion Rates ◽  
The Mean ◽  
Soil Loss Equation

Abstract Background: Soil erosion, one of the major environmental challenges, is influenced by topography, climate, soil characteristics, and human activities and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. The present study attempts to estimate soil erosion risk in the Northern catchment of Lake Tana basin, situated in northwest part of Ethiopia, with available data through the application of the Universal Soil Loss Equation model integrated with Geographic Information System and remote sensing technologies to identify priority areas for controlling soil erosion. In addition, it analyzes the effect of land use and land cover, topography, erodibility, and drainage density on soil erosion potential of the catchment, and the possible relationships among them. Results: The results show that the mean annual soil loss of catchment is estimated at 37.89 ± 59.2 t ha−1yr−1 with a total annual soil loss of 1,705,370 tons. The topography (LS-factor), followed by the support practice (P-factor) and the soil erodibility (K-factor) were the most sensitive factors affecting soil erosion in the catchment. To identify high priority areas for management, the study area was subdivided into five major sub-basins and further categorized into five erosion classes based on erosion severity. The mean soil erosion rates of the Derma, Megech, Gumara, Garno, and Gabi Kura River sub-basins are 46.8, 40.98, 30.95, 30.04, and 29.66 t ha−1yr−1, respectively. About 58.9% of the area was found in very low erosion risk which extends from 0-1 t ha−1yr−1 and accounted only 1.1% of total soil loss, while 12.4% of the area was found to be under high and extreme erosion risk with erosion rates of 10 t ha−1yr−1 or more that contributes about 82.1% of total soil loss warrant high priority for reducing the risk of soil erosion. Conclusions: This study permits the understanding of the soil erosion process and the various factors that lead to the spatial variability of the risk in the catchment, and thus enhances the effectiveness of proposed conservation strategies for sustainable land management.

scholarly journals Assessment of Soil Erosion at Multiple Spatial Scales Following Land Use Changes in 1980–2017 in the Black Soil Region, (NE) China

2020 ◽  
Vol 17 (20) ◽  
pp. 7378
Author(s):  
Haiyan Fang ◽  
Zemeng Fan
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Erosion Rate ◽  
Spatial Scales ◽  
Land Use Changes ◽  
Arable Land ◽  
Black Soil ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Black Soil Region

Impact of land use and land cover change on soil erosion is still imperfectly understood, especially in northeastern China where severe soil erosion has occurred since the 1950s. It is important to identify temporal changes of soil erosion for the black soil region at different spatial scales. In the present study, potential soil erosion in northeastern China was estimated based on the Revised Universal Loss Equation by integrating satellite images, and the variability of soil erosion at different spatial scales following land use changes in 1980, 1990, 2000, 2010, and 2017 was analyzed. The regionally spatial patterns of soil loss coincided with the topography, rainfall erosivity, soil erodibility, and use patterns, and around 45% of soil loss came from arable land. Regionally, soil erosion rates increased from 1980 to 2010 and decreased from 2010 to 2017, ranging from 3.91 to 4.45 Mg ha−1 yr−1 with an average of 4.22 Mg ha−1 yr−1 in 1980–2017. Areas with a rate of soil erosion less than 1.41 Mg ha−1 yr−1 decreased from 1980 to 2010 and increased from 2010 to 2017, and the opposite changing patterns occurred in higher erosion classes. Arable land continuously increased at the expense of forest in the high-elevation and steep-slope areas from 1980 to 2010, and decreased from 2010 to 2017, resulting in increased areas with erosion rates higher than 7.05 Mg ha−1 yr−1. At a provincial scale, Liaoning Province experienced the highest soil erosion rate of 9.43 Mg ha−1 yr−1, followed by Jilin Province, the eastern Inner Mongolia Autonomous Region, and Heilongjiang Province. At a county scale, around 75% of the counties had a soil erosion rate higher than the tolerance level. The county numbers with higher erosion rate increased in 1980–2010 and decreased in 2010–2017, resulting from the sprawl and withdrawal of arable land.

scholarly journals Evaluation of soil erosion rates in the southern half of the Russian Plain: methodology and initial results

2017 ◽  
Vol 375 ◽  
pp. 23-27 ◽  
Author(s):  
Valentin Golosov ◽  
Artem Gusarov ◽  
Leonid Litvin ◽  
Oleg Yermolaev ◽  
Nelly Chizhikova ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Erosion ◽  
Arable Land ◽  
Russian Plain ◽  
Model Calculations ◽  
Erosion Rates ◽  
Soil Erosion Rates ◽  
Land Use Transformation ◽  
Southern Half

Abstract. The Russian Plain (RP) is divided into two principally different parts. The northern half of the RP is a predominantly forested area with a low proportion of arable fields. In contrast, the southern half of the RP has a very high proportion of arable land. During the last 30 years, this agricultural region of the RP has experienced considerable land use transformation and changes in precipitation due to climate change have altered soil erosion rates. This paper describes the use of erosion model calculations and GIS spatial analytical methods for the evaluation of trends in erosion rates in the RP. Climate change (RIHMI World Data Center, 2016), land use transformation and crop rotation modification (Rosstat, 2016; R Core Team, 2016) are the main factors governing erosion rates in the region during recent decades. It was determined that mean annual erosion rates have decreased from 7.3 to 4.1 t ha−1 yr−1 in the forest zone mostly because of the serious reduction in the surface runoff coefficient for periods of snowmelt. At the same time, the erosion rates have increased from 3.9 to 4.6 t ha−1 yr−1 in the steppe zone due to the increasing frequency of heavy rain-storms.

Sign in / Sign up

Export Citation Format

Share Document