scholarly journals Modelling soil erosion at European scale: towards harmonization and reproducibility

2015 ◽  
Vol 15 (2) ◽  
pp. 225-245 ◽  
Author(s):  
C. Bosco ◽  
D. de Rigo ◽  
O. Dewitte ◽  
J. Poesen ◽  
P. Panagos
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Regional Scale ◽  
Computational Modelling ◽  
Mitigation Strategies ◽  
Soil Parameters ◽  
Rainfall Erosivity ◽  
Nutrient Contents ◽  
Continental Scale ◽  
Country Level

Abstract. Soil erosion by water is one of the most widespread forms of soil degradation. The loss of soil as a result of erosion can lead to decline in organic matter and nutrient contents, breakdown of soil structure and reduction of the water-holding capacity. Measuring soil loss across the whole landscape is impractical and thus research is needed to improve methods of estimating soil erosion with computational modelling, upon which integrated assessment and mitigation strategies may be based. Despite the efforts, the prediction value of existing models is still limited, especially at regional and continental scale, because a systematic knowledge of local climatological and soil parameters is often unavailable. A new approach for modelling soil erosion at regional scale is here proposed. It is based on the joint use of low-data-demanding models and innovative techniques for better estimating model inputs. The proposed modelling architecture has at its basis the semantic array programming paradigm and a strong effort towards computational reproducibility. An extended version of the Revised Universal Soil Loss Equation (RUSLE) has been implemented merging different empirical rainfall-erosivity equations within a climatic ensemble model and adding a new factor for a better consideration of soil stoniness within the model. Pan-European soil erosion rates by water have been estimated through the use of publicly available data sets and locally reliable empirical relationships. The accuracy of the results is corroborated by a visual plausibility check (63% of a random sample of grid cells are accurate, 83% at least moderately accurate, bootstrap p ≤ 0.05). A comparison with country-level statistics of pre-existing European soil erosion maps is also provided.

scholarly journals Modelling soil erosion at European scale: towards harmonization and reproducibility

2014 ◽  
Vol 2 (4) ◽  
pp. 2639-2680 ◽  
Author(s):  
C. Bosco ◽  
D. de Rigo ◽  
O. Dewitte ◽  
J. Poesen ◽  
P. Panagos
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Computational Modelling ◽  
Mitigation Strategies ◽  
Rainfall Erosivity ◽  
Large Spatial Scale ◽  
Nutrient Contents ◽  
Continental Scale ◽  
Country Level ◽  
Soil Erosion By Water

Abstract. Soil erosion by water is one of the most widespread forms of soil degradation. The loss of soil as a result of erosion can lead to decline in organic matter and nutrient contents, breakdown of soil structure and reduction of the water holding capacity. Measuring soil loss across the whole landscape is impractical and thus research is needed to improve methods of estimating soil erosion with computational modelling, upon which integrated assessment and mitigation strategies may be based. Despite the efforts, the prediction value of existing models is still limited, especially at regional and continental scale. A new approach for modelling soil erosion at large spatial scale is here proposed. It is based on the joint use of low data demanding models and innovative techniques for better estimating model inputs. The proposed modelling architecture has at its basis the semantic array programming paradigm and a strong effort towards computational reproducibility. An extended version of the Revised Universal Soil Loss Equation (RUSLE) has been implemented merging different empirical rainfall-erosivity equations within a climatic ensemble model and adding a new factor for a better consideration of soil stoniness within the model. Pan-European soil erosion rates by water have been estimated through the use of publicly available datasets and locally reliable empirical relationships. The accuracy of the results is corroborated by a visual plausibility check (63% of a random sample of grid cells are accurate, 83% at least moderately accurate, bootstrap p ≤ 0.05). A comparison with country level statistics of pre-existing European maps of soil erosion by water is also provided.

Fire regimes and soil erosion in north Australian hilly savannas

2006 ◽  
Vol 15 (4) ◽  
pp. 551 ◽  
Author(s):  
Jeremy Russell-Smith ◽  
Cameron Yates ◽  
Brian Lynch
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Fire Regimes ◽  
Dry Season ◽  
Rainfall Erosivity ◽  
Storm Events ◽  
Wet Season ◽  
Continental Scale ◽  
Erosion Processes ◽  
Intense Storm

Soil erosion is recognised as a major landscape management issue in northern Australia, given highly erodible soils, and high rainfall erosivity associated with low soil surface cover and intense storm events at the commencement of the wet season. Although recent continental-scale erosion modelling addresses such conditions, it does not take account of contemporary fire regimes dominated by annual, late dry season wildfires, especially in extensive higher slope (≥5%) regions of monsoonal Australia. The present paper reports a simple erosion pin assessment at two sites, contrasting soil loss and movement on unburnt and late dry season-burnt hillslopes over one wet season. Although very significant erosion was observed on both unburnt and burnt treatments, overall there was roughly three times the net soil loss and two times more soil movement on late dry season-burnt plots. The landscape scale of late dry season fire regimes, and implications for increased impacts of soil erosion on soil organic matter, nutrients, and ecosystem health are discussed. Collectively, assembled data suggest that more attention needs to be given to understanding and managing the impacts of contemporary fire regimes on hillslope soil erosion processes in the seasonal Australian tropics.

scholarly journals Assessing Soil Loss by Water Erosion in a Typical Mediterranean Ecosystem of Northern Greece under Current and Future Rainfall Erosivity

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2002
Author(s):  
Stefanos Stefanidis ◽  
Vasileios Alexandridis ◽  
Chrysoula Chatzichristaki ◽  
Panagiotis Stefanidis
Keyword(s):  
Open Source ◽  
Soil Loss ◽  
Renewable Resource ◽  
Mitigation Strategies ◽  
Mitigation Measures ◽  
Mediterranean Ecosystem ◽  
Rainfall Erosivity ◽  
Negative Consequences ◽  
Northern Greece ◽  
Erosion Risk

Soil is a non-renewable resource essential for life existence. During the last decades it has been threatened by accelerating erosion with negative consequences for the environment and the economy. The aim of the current study was to assess soil loss changes in a typical Mediterranean ecosystem of Northern Greece, under climate change. To this end, freely available geospatial data was collected and processed using open-source software package. The widespread RUSLE empirical erosion model was applied to estimate soil loss. Current and future rainfall erosivity were derived from a national scale study considering average weather conditions and RCMs outputs for the medium Representative Concentration Pathway scenario (RCP4.5). Results showed that average rainfall erosivity (R-Factor) was 508.85 MJ mm ha h−1 y−1 while the K-factor ranged from 0.0008 to 0.05 t ha h ha−1 MJ−1 mm−1 and LS-factor reached 60.51. Respectively, C-factor ranged from 0.01 to 0.91 and P-factor ranged from 0.42 to 1. The estimated potential soil loss rates will remain stable for the near future period (2021–2050), while an increase of approximately 9% is expected by the end of the 21th century (2071–2100). The results suggest that appropriate erosion mitigation strategies should be applied to reduce erosion risk. Subsequently, appropriate mitigation measures per Land Use/Land Cover (LULC) categories are proposed. It is worth noting that the proposed methodology has a high degree of transferability as it is based on open-source data.

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 RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

2021 ◽  
Author(s):  
Habtamu Tamiru ◽  
Meseret Wagari
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Landsat 8 ◽  
Land Resources ◽  
Rusle Model ◽  
Factor C ◽  
Significant Factors

Abstract Background: The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. The annual dramatic increment of the depletion of very important soil nutrients exposes the residents of this catchment to high expenses of money to use artificial fertilizers to increase the yield. This paper was conducted in Fincha Catchment where the soil is highly vulnerable to erosion, however, where such studies are not undertaken. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss, where such studies are not undertaken, by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Results: Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations (2010-2019) and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. Conclusion: Finally, it was concluded that having information about the spatial variability of soil loss severity map generated in the RUSLE model has a paramount role to alert land resources managers and all stakeholders in controlling the effects via the implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.

scholarly journals Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)

2009 ◽  
Vol 13 (10) ◽  
pp. 1907-1920 ◽  
Author(s):  
M. Angulo-Martínez ◽  
M. López-Vicente ◽  
S. M. Vicente-Serrano ◽  
S. Beguería
Keyword(s):  
Soil Erosion ◽  
Prediction Models ◽  
Regional Scale ◽  
Geostatistical Simulation ◽  
High Temporal Resolution ◽  
Rainfall Erosivity ◽  
Ebro Basin ◽  
Spatial Coverage ◽  
Interpolation Techniques ◽  
Ne Spain

Abstract. Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) was used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods. To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme, as well as the uncertainty of the predictions, modeled by Gaussian geostatistical simulation. All methods were able to capture the general spatial pattern of both erosivity indices. The semivariogram analysis revealed that spatial autocorrelation only affected at distances of ~15 km around the observatories. Therefore, local interpolation techniques tended to be better overall considering the validation statistics. All models showed high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of having long data series with a dense spatial coverage.

GIS estimation of annual average soil loss rate from Hangar River watershed using RUSLE

2019 ◽  
Vol 11 (2) ◽  
pp. 529-539 ◽  
Author(s):  
Mahmud Mustefa ◽  
Fekadu Fufa ◽  
Wakjira Takala
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Study Finding ◽  
Mitigation Measures ◽  
Rainfall Erosivity ◽  
Vegetative Cover ◽  
Annual Average ◽  
Slope Length ◽  
Soil Loss Rate

Abstract Currently, soil erosion is the major environmental problem in the Blue Nile, Hangar watershed in particular. This study aimed to estimate the spatially distributed mean annual soil erosion and map the most vulnerable areas in Hangar watershed using the revised universal soil loss equation. In this model, rainfall erosivity (R-factor), soil erodibility (K-factor), slope steepness and slope length (LS-factor), vegetative cover (C-factor), and conservation practice (P-factor) were considered as the influencing factors. Maps of these factors were generated and integrated in ArcGIS and then the annual average soil erosion rate was determined. The result of the analysis showed that the amount of soil loss from the study area ranges from 1 to 500 tha−1 yr−1 with an average annual soil loss rate of 32 tha−1 yr−1. Considering contour ploughing with terracing as a fully developed watershed management, the resulting soil loss rate was reduced from 32 to 19.2 tha−1 yr−1. Hence, applying contour ploughing with terracing effectively reduces the vulnerability of the watershed by 40%. Based on the spatial vulnerability of the watershed, most critical soil erosion areas were situated in the steepest part of the watershed. The result of the study finding is helpful for stakeholders to take appropriate mitigation measures.

scholarly journals Effects of Climate and Land-Cover Changes on Soil Erosion in Brazilian Pantanal

2019 ◽  
Vol 11 (24) ◽  
pp. 7053 ◽  
Author(s):  
Carina Colman ◽  
Paulo Oliveira ◽  
André Almagro ◽  
Britaldo Soares-Filho ◽  
Dulce Rodrigues
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Ecosystem Service ◽  
Soil Loss ◽  
Land Cover Changes ◽  
Rainfall Erosivity ◽  
Comprehensive Planning ◽  
Brazilian Pantanal

The Pantanal biome integrates the lowlands of the Upper Paraguay Basin (UPB), which is hydrologically connected to the biomes of the Cerrado and Amazon (the highlands of the UPB). The effects of recent land-cover and land-use (LCLU) changes in the highlands, combined with climate change, are still poorly understood in this region. Here, we investigate the effects of soil erosion in the Brazilian Pantanal under climate and LCLU changes by combining different scenarios of projected rainfall erosivity and land-cover management. We compute the average annual soil erosion for the baseline (2012) and projected scenarios for 2020, 2035, and 2050. For the worst scenario, we noted an increase in soil loss of up to 100% from 2012 to 2050, associated with cropland expansion in some parts of the highlands. Furthermore, for the same period, our results indicated an increase of 20 to 40% in soil loss in parts of the Pantanal biome, which was associated with farmland increase (mainly for livestock) in the lowlands. Therefore, to ensure water, food, energy, and ecosystem service security over the next decades in the whole UPB, robust and comprehensive planning measures need to be developed, especially for the most impacted areas found in our study.

Application of a RUSLE-based soil erosion modelling on Mauritius Island

Soil Research ◽  
2012 ◽  
Vol 50 (8) ◽  
pp. 645 ◽  
Author(s):  
Rody Nigel ◽  
Soonil D. D. V. Rughooputh
Keyword(s):  
Soil Erosion ◽  
Water Conservation ◽  
Soil Loss ◽  
Regional Scale ◽  
Soil And Water Conservation ◽  
Geographical Information ◽  
Environmental Damage ◽  
Total Soil ◽  
Mauritius Island ◽  
Soil And Water

Soil erosion by water is one of the most important natural resources management problems in the world. The damages it causes on-site are soil loss, breakdown of soil structure, and decline in organic matter content, nutrient content, fertility, and infiltration rate. Lands with the highest erosion risk on Mauritius Island are crop cultivations (sugarcane, tea, vegetables) on erosion-susceptible terrain (slopes >20% coupled with highly erodible soils). The locations of such lands on Mauritius were mapped during previous, qualitatively based regional-scale erosion studies. In order to propose soil conservation strategies, there is a need to apply a more quantitative approach to supplement the previous, qualitatively based studies. This paper reports an application of the Revised Universal Soil Loss Equation (RUSLE) within a geographical information system in order to estimate soil loss on the island, and particularly for the high-erosion areas. Results show that total soil loss on the island is estimated at 298 259 t year–1, with soil loss from high-erosion areas summing 84 780 t year–1 (28% of total soil loss). If all of the high-erosion areas were afforested, their soil loss would be reduced to 10 264 t year–1, i.e. a reduction of 88% for the high-erosion areas and a reduction of 25% for the island. This study thus calls for soil and water conservation programs directed to these erosion-prone areas before the land degradation and environmental damage they are causing become irreversible. The methodological approach used in this work to quantitatively estimate soil loss from erosion-prone areas can be adopted in other countries as the basis for a nationwide erosion assessment in order to better inform environmental policy needs for soil and water conservation.

scholarly journals Geospatial Analysis of Soil Erosion Susceptibility and Causative Factors in Anambra State, South East, Nigeria

2021 ◽  
pp. 5-32
Author(s):  
Romanus Udegbunam Ayadiuno ◽  
Dominic Chukwuka Ndulue ◽  
Chinemelu Cosmas Ndichie ◽  
Arinze Tagbo Mozie ◽  
Philip O. Phil-Eze ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Soil Loss ◽  
Vegetation Index ◽  
Anthropogenic Activities ◽  
Rainfall Erosivity ◽  
Anambra State ◽  
Causative Factors

Land degradation is a function of soil erosion leading to soil loss and reduction in crop productivity as well as other socio-economic activities. The menace of soil erosion is challenging due to diverse factors including advertent and inadvertent anthropogenic activities. This study looks at soil erosion susceptibility and causative factors in Anambra State, both static and dynamic with the intent of identifying them, investigating spatial variability of soil loss, relate erodibility to soil properties and causative factors to soil erosion. Eight (8) prominent causative factors (CFs), were identified. These causative factors (CFs) were analyzed using ArcGIS 10.2. Sixty (60) soil samples were extracted randomly, analyzed, and tested. The study identified CFs such as Drainage Density, Erosion Density, Lineament Density, Slope Length, Land Surface Temperature, and Rainfall Erosivity, which contribute to Soil Erodibility (K - Factor). Land Surface Temperature, Soil Moisture Index, Rainfall Erosivity, and Normalized Difference Vegetation Index contributed to the loss of 8.97 ton/ha/yr, 9.1288 ton/ha/yr, 1,1134.7 ton/ha/yr, and 0.245 ton/ha/yr respectively to erosion in Anambra State. Conclusively, the dynamic causative factors influence soil susceptibility and trigger erosion in the State.

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