scholarly journals Comparison of the Applicability of Different Soil Erosion Models to Predict Soil Erodibility Factor and Event Soil Losses on Loess Slopes in Hungary

Water ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 3517
Author(s):  
Boglárka Keller ◽  
Csaba Centeri ◽  
Judit Alexandra Szabó ◽  
Zoltán Szalai ◽  
Gergely Jakab
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Coefficient Of Determination ◽  
Soil Erodibility ◽  
The European Union ◽  
Extreme Precipitation Events ◽  
Erosion Models ◽  
Physically Based ◽  
Physically Based Models ◽  
Soil Losses

Climate change induces more extreme precipitation events, which increase the amount of soil loss. There are continuous requests from the decision-makers in the European Union to provide data on soil loss; the question is, which ones should we use? The paper presents the results of USLE (Universal Soil Loss Equation), RUSLE (Revised USLE), USLE-M (USLE-Modified) and EPIC (Erosion-Productivity Impact Calculator) modelling, based on rainfall simulations performed in the Koppány Valley, Hungary. Soil losses were measured during low-, moderate- and high-intensity rainfalls on cultivated soils formed on loess. The soil erodibility values were calculated by the equations of the applied soil erosion models and ranged from 0.0028 to 0.0087 t ha h ha−1 MJ−1 mm−1 for the USLE-related models. EPIC produced larger values. The coefficient of determination resulted in an acceptable correlation between the measured and calculated values only in the case of USLE-M. Based on other statistical indicators (e.g., NSEI, RMSE, PBIAS and relative error), RUSLE, USLE and USLE-M resulted in the best performance. Overall, regardless of being non-physically based models, USLE-type models seem to produce accurate soil erodibility values, thus modelling outputs.

Application of a physically based soil erosion model, GUEST, in the absence of data on runoff rates I. Theory and methodology

Soil Research ◽  
1999 ◽  
Vol 37 (1) ◽  
pp. 1 ◽  
Author(s):  
B. Yu ◽  
C. W. Rose
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Soil Erodibility ◽  
Erosion Model ◽  
Erosion Models ◽  
Loss Data ◽  
Physically Based ◽  
Set Up ◽  
Data Requirements

When physically based erosion models such as GUEST are used to determine soil erodibility parameters or to predict the rate of soil loss, data on runoff rates, as distinct from event runoff amount, are often needed. Data on runoff rates, however, are not widely available. This paper describes methods that can be used to overcome this lack of data on runoff rates. These methods require only rainfall rates and runoff amounts, which are usually available for sites set up primarily to test and validate the USLE technology. In addition, the paper summarises the data requirements for the erosion model GUEST and application procedures. In the accompanying paper, these methods are applied to 4 experimental sites in the ASIALAND Network.

Modelling of impacts of erosion processes on agricultural landscapes due to intensive rainfall events

2020 ◽  
Author(s):  
Silvia Kohnová ◽  
Zuzana Németová
Keyword(s):  
Soil Erosion ◽  
Soil Degradation ◽  
Agricultural Land ◽  
Assessment Methods ◽  
Rainfall Events ◽  
Degradation Processes ◽  
Erosion Processes ◽  
Erosion Models ◽  
Physically Based ◽  
Physically Based Models

<p>At present, the occurrence of extreme precipitation events is becoming more and more frequent and therefore it is important to quantify their impact on the landscape and soil degradation processes. Until now a wide range of soil erosion models have been developed and many significant studies performed to evaluate soil erosion processes at local and regional level, but there are still many modeling principles that suffer from a range of problems. The general problem in soil erosion modelling lies in the validation and verification of the methodologies used. The validation of erosion models is a very complicated and complex process due to lack of suitable sites, financial demands and due to the high temporal and spatial variability. The paper points to validate the physically and event-based Erosion-3D model predominantly developed to calculate the amounts of soil loss, surface runoff, and depositions resulting from natural and design rainfall events. In the study two different erosion assessment methods were chosen in order to compare diverse evaluation approaches. Both water erosion assessment methods used have certain advantages and disadvantages, but nowadays the use of physically-based models, which are a younger generation of models, are regarded to be a more innovative and effective technique for the evaluation of complex runoff-erosion processes, deposition and transport processes. The significant contribution of physically-based models is seen in their more precise representation of the erosion and deposition processes, a more proper calculation of the erosion, deposition and sediment yields and the application of more complicated characteristics, including fluctuating soil conditions and surface properties in comparison with empirical models. The validation of the models was performed based on the continuous rainfall events for the period selected (2015, 2016 and 2017). The extreme rainfall events occurring during the period were chosen and their serious impact on the agricultural land was modeled. The modelled sediment data were compared with the measured sediment deposition data obtained by a bathymetry survey of the Svacenicky Creek polder. The polder is situated in the middle of the Myjava hill lands in the western part of Slovakia and the bathymetry measurement were conducted using a hydrographical survey using the EcoMapper Autonomous Underwater Vehicle (AUV) device. The results of the study include a comparison between the modelled and measured data and an assessment of the impact of the intensive rainfall events on the investigated territory.</p><p>Key words: intensive rainfall events, agricultural land, soil degradation processes, hydrological extremes, physically-based model</p>

The soil loss by water erosion at the European part of Russia

2020 ◽  
Author(s):  
Kirill Maltsev ◽  
Oleg Yermolaev
Keyword(s):  
Comparative Analysis ◽  
Soil Erosion ◽  
Soil Loss ◽  
Arable Land ◽  
Water Erosion ◽  
European Part ◽  
The European Union ◽  
Taiga Forest ◽  
European Part Of Russia ◽  
Soil Losses

<p>A quantitative assessment of the potential soil erosion on arable land in the European part of Russia (EPR) was carried out. The total area of arable land of the EPR is about 650,000 km<sup>2</sup>. The majority of the population of Russia lives here - about 95 million people. The level of generalization of work is regional and corresponds to a scale of 1: 500,000.</p><p>As a research method, mathematical modeling based on modified for Russia’s natural conditions USLE equation for calculating potential soil loss from erosion. Another leading method for assessing soil erosion and presenting results is GIS. A raster model of data presentation was used in the calculations, including a model of slope angles, slope lengths, soil erodibility, erosive rainfall potential, water reserves in snow, intra-annual redistribution of rainfall, and land use types.</p><p>New data have been obtained on the value of soil erosion losses during melt and storm runoff periods and total annual losses. An electronic map of soil erosion losses on arable lands of the European part of Russia has been compiled, which allows determining spatial features of soil erosion rates.</p><p>The average soil erosion losses, taking into account the soil-protective coefficients of agricultural crops for the study area, are 4.04 t / ha per year. In annual soil losses due to erosion, storm 3.78 prevails, soil loss from melt water is almost an order of magnitude less - t / ha 0.26. About half of the territory is located in conditions under which the soil loss does not exceed 0.5 t / ha per year.</p><p>The rate of potential soil erosion on arable land in the European part of Russia naturally decreases in the direction from the taiga-forest to the steppe landscape zone. The band of maximum potential soil erosion of the west-east sub-latitudinal strike is clearly distinguished, confined to the subzone of mixed and broad-leaved forests with very high plowing. A comparative analysis of our data and data obtained in the mid-1980s showed a reduction in soil loss from water erosion in all landscape zones. In addition, a comparative analysis of the data obtained by us and the data for the European Union was carried out, which showed that the soil losses on the EPR are slightly higher.</p>

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 Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees

2008 ◽  
Vol 12 (2) ◽  
pp. 523-535 ◽  
Author(s):  
M. López-Vicente ◽  
A. Navas ◽  
J. Machín
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Loss ◽  
Rainfall Intensity ◽  
Soil Moisture Content ◽  
Rainfall Erosivity ◽  
Soil Erodibility ◽  
Maximum Rainfall ◽  
Freeze Thaw ◽  
Soil Losses

Abstract. The Mediterranean environment is characterized by strong temporal variations in rainfall volume and intensity, soil moisture and vegetation cover along the year. These factors play a key role on soil erosion. The aim of this work is to identify different erosive periods in function of the temporal changes in rainfall and runoff characteristics (erosivity, maximum intensity and number of erosive events), soil properties (soil erodibility in relation to freeze-thaw processes and soil moisture content) and current tillage practices in a set of agricultural fields in a mountainous area of the Central Pyrenees in NE Spain. To this purpose the rainfall and runoff erosivity (R), the soil erodibility (K) and the cover-management (C) factors of the empirical RUSLE soil loss model were used. The R, K and C factors were calculated at monthly scale. The first erosive period extends from July to October and presents the highest values of erosivity (87.8 MJ mm ha−1 h−1), maximum rainfall intensity (22.3 mm h−1) and monthly soil erosion (0.25 Mg ha−1 month−1) with the minimum values of duration of erosive storms, freeze-thaw cycles, soil moisture content and soil erodibility (0.007 Mg h MJ−1 mm−1). This period includes the harvesting and the plowing tillage practices. The second erosive period has a duration of two months, from May to June, and presents the lowest total and monthly soil losses (0.10 Mg ha−1 month−1) that correspond to the maximum protection of the soil by the crop-cover ($C$ factor = 0.05) due to the maximum stage of the growing season and intermediate values of rainfall and runoff erosivity, maximum rainfall intensity and soil erodibility. The third erosive period extends from November to April and has the minimum values of rainfall erosivity (17.5 MJ mm ha−1 h−1) and maximum rainfall intensity (6.0 mm h−1) with the highest number of freeze-thaw cycles, soil moisture content and soil erodibility (0.021 Mg h MJ−1 mm−1) that explain the high value of monthly soil loss (0.24 Mg ha−1 month−1). The interactions between the rainfall erosivity, soil erodibility, and cover-management factors explain the similar predicted soil losses for the first and the third erosive periods in spite of the strong temporal differences in the values of the three RUSLE factors. The estimated value of annual soil loss with the RUSLE model (3.34 Mg ha−1 yr−1) was lower than the measured value with 137Cs (5.38 Mg ha−1 yr−1) due to the low values of precipitation recorded during the studied period. To optimize agricultural practices and to promote sustainable strategies for the preservation of fragile Mediterranean agrosystems it is necessary to delay plowing till October, especially in dryland agriculture regions. Thus, the protective role of the crop residues will extend until September when the greatest rainfall occurs together with the highest runoff erosivity and soil losses.

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 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Soil Erodibility ◽  
Lake Tana ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Soil Loss Equation

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.

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

<p>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 – 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.</p>

Assessment of soil erosion models for predicting soil loss in cracked vegetated compacted surface layer

2021 ◽  
Author(s):  
Manash Jyoti Bora ◽  
Sanandam Bordoloi ◽  
Sreeja Pekkat ◽  
Ankit Garg ◽  
Sreedeep Sekharan ◽  
...  
Keyword(s):  
Surface Layer ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Models

scholarly journals A Soil Erosion Indicator for Supporting Agricultural, Environmental and Climate Policies in the European Union

2020 ◽  
Vol 12 (9) ◽  
pp. 1365 ◽  
Author(s):  
Panos Panagos ◽  
Cristiano Ballabio ◽  
Jean Poesen ◽  
Emanuele Lugato ◽  
Simone Scarpa ◽  
...  
Keyword(s):  
European Union ◽  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
National Level ◽  
Water Erosion ◽  
Soil Protection ◽  
Conservation Practices ◽  
The European Union ◽  
The Eu

Soil erosion is one of the eight threats in the Soil Thematic Strategy, the main policy instrument dedicated to soil protection in the European Union (EU). During the last decade, soil erosion indicators have been included in monitoring the performance of the Common Agricultural Policy (CAP) and the progress towards the Sustainable Development Goals (SDGs). This study comes five years after the assessment of soil loss by water erosion in the EU [Environmental science & policy 54, 438–447 (2015)], where a soil erosion modelling baseline for 2010 was developed. Here, we present an update of the EU assessment of soil loss by water erosion for the year 2016. The estimated long-term average erosion rate decreased by 0.4% between 2010 and 2016. This small decrease of soil loss was due to a limited increase of applied soil conservation practices and land cover change observed at the EU level. The modelling results suggest that, currently, ca. 25% of the EU land has erosion rates higher than the recommended sustainable threshold (2 t ha−1 yr−1) and more than 6% of agricultural lands suffer from severe erosion (11 t ha−1 yr−1). The results suggest that a more incisive set of measures of soil conservation is needed to mitigate soil erosion across the EU. However, targeted measures are recommendable at regional and national level as soil erosion trends are diverse between countries which show heterogeneous application of conservation practices.

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