scholarly journals A New European Slope Length and Steepness Factor (LS-Factor) for Modeling Soil Erosion by Water

Geosciences ◽  
2015 ◽  
Vol 5 (2) ◽  
pp. 117-126 ◽  
Author(s):  
Panos Panagos ◽  
Pasquale Borrelli ◽  
Katrin Meusburger
Keyword(s):  
Soil Erosion ◽  
Slope Length ◽  
Soil Erosion By Water ◽  
Steepness Factor

MODELS TO PREDICT SLOPE LENGTH FROM OTHER WATERSHED ATTRIBUTES

2020 ◽  
Vol 51 (4) ◽  
pp. 1025-1037
Author(s):  
Mohammed & Karim
Keyword(s):  
Soil Erosion ◽  
Drainage Density ◽  
Slope Gradient ◽  
Bifurcation Ratio ◽  
Slope Length ◽  
Objective Standard ◽  
Slope Length Factor ◽  
Watershed Slope ◽  
Soil Erosion By Water ◽  
Least Squares Techniques

Soil erosion by water is an extensive and increasing problem worldwide. Albeit, this problem has been recognized as a significant hazard in Iraq, yet the number of studies on this topic is very limited. Most of the models used for estimating soil erosion contain parameters for slope length factor (LS). A major constraint is the difficulty in extracting the LS factor. Accordingly, the current study was initiated with the main objective of deriving models to predict the slope length from relatively easy to measure basin characteristics with a reasonable accuracy. To achieve the above objective, standard methodologies were employed to describe 30 main basins with the upper part of Iraq in terms linear, areal and relief morphometric parameters. The majority of the delineated watersheds were characterized by having high slope lengths indicating lower drainage density and higher erosion rate. Linear and non-linear least squares techniques were applied to predict the slope length from other basin characteristics. Different indicators were used to test the performance of the proposed models and the approach was validated using K-fold procedure at independent basins. The results indicated that the 4-parameter regression model outperformed the remaining models of watershed slope length. The regressors of this model are bifurcation ratio, perimeter, and basin length and slope gradient.

scholarly journals Computing slope length (USLE): return to original definitions.

2021 ◽  
Author(s):  
Antonio Saa-Requejo ◽  
Pablo Sevilla ◽  
Ana María Tarquis ◽  
Anne Gobin
Keyword(s):  
Soil Erosion ◽  
Horizontal Resolution ◽  
Department Of Agriculture ◽  
Slope Length ◽  
Erosion Risk ◽  
Slope Length Factor ◽  
Erosion Models ◽  
Original Field ◽  
Field Perspective ◽  
Soil Erosion By Water

<p>Soil erosion is an important process of consideration in different erosion risk models and in planning soil conservation. Common erosion models, such as the USLE and its derivatives are widely used. In this context, the slope length is the variable with the most difficulties due to the different scales and procedures available that lead to very different results. Furthermore, many of the calculation procedures are based on a hydrological network definition that poses many problems in areas with a complex topography.</p><p>We propose an algorithm implemented in GIS, returning to the original field perspective form defined by the USLE and RUSLE, which is detached from the hydrological network definition. The calculation procedure is based on 5 m DEM and defines overland water flow at the field scale.</p><p>This method has been applied in three areas with different climate and geomorphology. The results are similar to those derived from aerial photograph observation.</p><p><strong>References</strong></p><p>Honghu Liu, Jens Kiesel, Georg Hörmann, Nicola Fohrer. (2011). Effects of DEM horizontal resolution and methods on calculating the slope length factor in gently rolling landscapes. Catena, 87, 368–375</p><p>Renard, K.G., Foster, G.R., Weesies, G.A., Mc. Cool, D.K y Yoder, D.C. (1997). Predicting Soil Erosion by Water: A Guide To Conservation Planning With The Revised Universal Soil Los Equation. Agricultural Handbook 703. USA: US Department of Agriculture.</p><p><strong>Acknowledgements</strong></p><p>Authors are grateful to Authors are grateful to Agroseguro funding this research.</p>

scholarly journals Modelling Effects of Rainfall Patterns on Runoff Generation and Soil Erosion Processes on Slopes

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2221
Author(s):  
Qihua Ran ◽  
Feng Wang ◽  
Jihui Gao
Keyword(s):  
Soil Erosion ◽  
Rainfall Intensity ◽  
Temporal Patterns ◽  
Runoff Generation ◽  
Slope Length ◽  
Erosion Processes ◽  
Total Runoff ◽  
Wide Range ◽  
Critical Slope ◽  
Rainfall Patterns

Rainfall patterns and landform characteristics are controlling factors in runoff and soil erosion processes. At a hillslope scale, there is still a lack of understanding of how rainfall temporal patterns affect these processes, especially on slopes with a wide range of gradients and length scales. Using a physically-based distributed hydrological model (InHM), these processes under different rainfall temporal patterns were simulated to illustrate this issue. Five rainfall patterns (constant, increasing, decreasing, rising-falling and falling-rising) were applied to slopes, whose gradients range from 5° to 40° and projective slope lengths range from 25 m to 200 m. The rising-falling rainfall generally had the largest total runoff and soil erosion amount; while the constant rainfall had the lowest ones when the projective slope length was less than 100 m. The critical slope of total runoff was 15°, which was independent of rainfall pattern and slope length. However, the critical slope of soil erosion amount decreased from 35° to 25° with increasing projective slope length. The increasing rainfall had the highest peak discharge and erosion rate just at the end of the peak rainfall intensity. The peak value discharges and erosion rates of decreasing and rising-falling rainfalls were several minutes later than the peak rainfall intensity.

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.

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.

Selecting suitable climate models for examining future changes in soil erosion

2021 ◽  
Author(s):  
Neil Brannigan ◽  
Donal Mullan ◽  
Karel Vandaele ◽  
Conor Graham ◽  
Jennifer McKinley ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Model Selection ◽  
Climate Models ◽  
Climate Model ◽  
Study Region ◽  
Extreme Precipitation Events ◽  
Suitable Climate ◽  
Erosion Models ◽  
Soil Erosion By Water ◽  
The Impact

&lt;p&gt;Climate models consistently project large increases in the frequency and magnitude of extreme precipitation events in the 21st century, revealing the potential for widespread impacts on various aspects of society. While the impacts on flooding receive particular attention, there is also considerable damage and associated cost for other precipitation driven phenomena, including soil erosion and muddy flooding. Multiple studies have shown that climate change will worsen the impacts of soil erosion and muddy flooding in various regions. These studies typically drive erosion models with a single model or a few models with little justification. A blind approach to climate model selection increases the risk of simulating a narrower range of possible scenarios, limiting vital information for mitigation planning and adaptation. This study provides a comprehensive methodology to efficiently select suitable climate models for simulating soil erosion and muddy flooding. For a case study region in eastern Belgium using the WEPP soil erosion model, we compare the performance of our novel methodology against other model selection methods for a future period (2081 &amp;#8211; 2100). The main findings reveal that our novel methodology is successful in generating the widest range of future scenarios from a small number of models, when compared with other ways of selecting climate models. This approach has not previously been achieved for modelling soil erosion by water. Other precipitation-driven impact sectors may also wish to consider applying this method to assess the impact of future climatic changes, so that the worst- and best-case scenarios can be adequately prepared for.&lt;/p&gt;

Modelling Soil Erosion by Water: Some Conclusions

1998 ◽  
pp. 515-517 ◽  
Author(s):  
John Boardman ◽  
David Favis-Mortlock
Keyword(s):  
Soil Erosion ◽  
Soil Erosion By Water

REVISITING THE METHODOLOGICAL DEVELOPMENT IN SOIL EROSION RESEARCH

Ensemble ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 145-165
Author(s):  
Tanmoy Sarkar ◽  
◽  
Tapas Pal ◽  
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Geographic Information ◽  
Methodological Development ◽  
Advantages And Disadvantages ◽  
The Future ◽  
Soil Erosion By Water

Soil erosion (by water) is a major land degradation process that may threat the Sustainable Development Goals (SDG) by its negative impact on environment and human well-being. Soil erosion research demands scientific methods, tools and techniques to assess soil erosion with more accuracy and reliability. Soil erosion research has had experienced crude field-based techniques in early twentieth century to model-based approaches since the 1970s and very recent machine learning and artificial intelligence models to predict soil erosion susceptibility and risk. The paper aims to review the trend in methodological development in soil erosion by water through time. The brief background of different approaches, their relative advantages and disadvantages are reviewed. Depending on the time of establishment and wide application the approaches are classified and represented as erosion plot/runoff approach, erosion pin technique followed by environmental tracer method and model approach in combination with Remote Sensing (RS) and Geographic Information System (GIS). Recent advancement in artificial intelligence and application of statistical techniques have a great potential to contribute in soil erosion research by identifying various degrees of susceptibility in large scale and also to quantify the erosion rate with high accuracy. The Remote sensing (RS) and Geographic Information System (GIS) contribute to develop regional scale data base with exploration of real time data and spatial analysis. The combination of RS & GIS and process-based models must be more effective than the traditional soil erosion model in the context of prediction with greater reliability and validity. The future research on soil erosion is better to focus on the theoretical analysis and development of erosion prediction model with more quantitative refinement and to model the future.

Advances in techniques to assess soil erodibility

2021 ◽  
pp. 175-214
Author(s):  
R. J. Rickson ◽  
◽  
E. Dowdeswell Downey ◽  
G. Alegbeleye ◽  
S. E. Cooper ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Test Procedure ◽  
Aggregate Stability ◽  
Analytical Techniques ◽  
Soil Biology ◽  
Soil Erodibility ◽  
Erosion Rates ◽  
Erosion Processes ◽  
Assessment Techniques ◽  
Soil Erosion By Water

Soil erodibility is the susceptibility of soil to the erosive forces of rainsplash, runoff and wind. It is a significant factor in determining present and future soil erosion rates. Focusing on soil erosion by water, this chapter shows that erodibility is determined by static and dynamic soil properties that control a range of sub-processes affecting soil erosion, but there is no standardised test procedure, making comparison of erodibility assessment techniques and their results challenging. Most researchers agree that aggregate stability is the best indicator of soil erodibility. Selection of techniques to measure aggregate stability need to consider the type of disruptive forces and breakdown processes to which field aggregates are subjected. New indices must incorporate spatial and temporal variabilities in erodibility; the different erosion processes operating; the impact of climate change; and the role of soil biology. New analytical techniques such as computer aided tomography show promise in considering soil erodibility as a dynamic continuum operating over 3 dimensions.

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