Academic literature on the topic 'USLE'

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.

Satellite observations (Copernicus Sentinell-1) can supply antecedent soil moisture data, which helps to predict thresholds triggering runoff and runoff volume. In the paper, we developed a runoff correction factor to the USLE, using rainfall and satellite antecedent soil moisture data, following the approach of the modified USLE models such as the USLE-M and USLE-MM. The runoff and soil loss estimations accuracy are validated by plot-scale measurements (2008–2020 period) provided by SERLAB (Soil Erosion Laboratory) of the University of Perugia. The results show that the event rainfall depth added to the antecedent soil moisture is a fairly suitable predictor of the runoff. Using the simulated runoff in a USLE-MM model, the capability to predict event soil losses is enhanced with an RMSE = 0.57 Mg/ha lower than the RMSE ≈ 3.1 Mg/ha obtained by the USLE model. Using a modified USLE model, albeit with remote estimated runoff data, is still more advantageous at the event scale than the USLE model, which does not consider the runoff. These results are particularly significant for the estimation of runoff and soil losses. Satellite data shows the potential of applying the modified USLE models for large-scale monitoring and quantification of event soil erosion and runoff.

Analyses undertaken in this paper show that the Universal Soil Loss Equation (USLE) tends to overestimate low values of soil loss when the soil surface has a high capacity to infiltrate rainfall, but the degree of overestimation falls as the capacity of the soil to produce runoff increases. The USLE-M, a version of the USLE that uses the product of the runoff ratio and the EI30 as the event erosivity index, is more efficient in estimating soil loss because runoff is considered explicitly in the event erosivity index, whereas it is not in the USLE. The results show clearly that the problem of the USLE and the RUSLE overpredicting observed erosion losses, when erosion losses are low, is related to a large degree to model formula. In addition, the removal of restrictions to what constitutes a valid EI30 value increases the capacity of the RUSLE to overpredict low soil losses. As the USLE is an empirical model, values of USLE K, C, and P can only be used when the event erosivity parameter is EI30. Models like EPIC ignore this fact.

The Universal Soil Loss Equation (USLE) and two modified USLE models were assessed for their ability to predict soil erosion on contour bay catchments on the Darling Downs, Queensland. The models were applied using USLE handbook values as well as optimized values determined by fitting the models to the experimental data. All three models explained greater than 80% of the variance in measured soil loss with no single model being consistently superior to the others. Cover reduced erosion more than that predicted by the USLE.

AbstractThe universal soil loss equation (USLE) and water erosion prediction project (WEPP) (inter-rill and rill) erodibility factors are important indicators for land degradation assessment all over the world, which were primarily developed for the United States of America (USA). However, information on suitability of USLE and WEPP for tropical environment is scarce. Therefore, studies were carried out to investigate the suitability of USLE and WEPP for selected tropical soils of Southwestern Nigeria. Four pedons classified based on USDA soil taxonomy as Plinthic Petraquept (Adio series), Kanhaplic Haplaustalf (Oyo series), Typic Plinthustalf (Temidire series) and Typic Haplaustalf (Owutu series) were used for the study. Soil erodibility factor was determined using USLE and WEPP models. Origin-Pro. 8.1 software was employed to compare USLE and WEPP models for conformity and suitability. The results showed perfect agreement (R2= 1.0;P< 0.001) between the two WEPP (inter-rill and rill) erodibility models in all the four soil types investigated. In addition, WEPP models (inter-rill and rill erodibility) significantly (R2= 0.82;P< 0.001) related to USLE (El-Swaify and Dangler, 1977) erodibility model. There was a poor relationship (R2= 0.46;P< 0.06) between USLE (Wischmeier and Mannering, 1968) and the WEPP erodibility factors. The WEPP erodibility models with a perfect relationship with soil properties of the four soil types are more suitable than USLE models for predicting soil erodibility of the identified soil types in tropical environments.

Abstract. The Universal Soil Loss Equation (USLE) is the most commonly used model to assess soil erosion by water. The model equation quantifies long-term average annual soil loss as a product of the rainfall erosivity R, soil erodibility K, slope length and steepness LS, soil cover C, and support measures P. A large variety of methods exist to derive these model inputs from readily available data. However, the estimated values of a respective model input can strongly differ when employing different methods and can eventually introduce large uncertainties in the estimated soil loss. The potential to evaluate soil loss estimates at a large scale is very limited due to scarce in-field observations and their comparability to long-term soil estimates. In this work we addressed (i) the uncertainties in the soil loss estimates that can potentially be introduced by different representations of the USLE input factors and (ii) challenges that can arise in the evaluation of uncertain soil loss estimates with observed data. In a systematic analysis we developed different representations of USLE inputs for the study domain of Kenya and Uganda. All combinations of the generated USLE inputs resulted in 972 USLE model setups. We assessed the resulting distributions in soil loss, both spatially distributed and on the administrative level for Kenya and Uganda. In a sensitivity analysis we analyzed the contributions of the USLE model inputs to the ranges in soil loss and analyzed their spatial patterns. We compared the calculated USLE ensemble soil estimates to available in-field data and other study results and addressed possibilities and limitations of the USLE model evaluation. The USLE model ensemble resulted in wide ranges of estimated soil loss, exceeding the mean soil loss by over an order of magnitude, particularly in hilly topographies. The study implies that a soil loss assessment with the USLE is highly uncertain and strongly depends on the realizations of the model input factors. The employed sensitivity analysis enabled us to identify spatial patterns in the importance of the USLE input factors. The C and K factors showed large-scale patterns of importance in the densely vegetated part of Uganda and the dry north of Kenya, respectively, while LS was relevant in small-scale heterogeneous patterns. Major challenges for the evaluation of the estimated soil losses with in-field data were due to spatial and temporal limitations of the observation data but also due to measured soil losses describing processes that are different to the ones that are represented by the USLE.

In the European Union, soil erosion is identified as one of the main environmental threats, addressed with a variety of rules and regulations for soil and water conservation. The by far most often officially used tool to determine soil erosion is the Universal Soil Loss Equation (USLE) and its regional adaptions. The aim of this study is to use three different regional USLE-based approaches in three different test catchments in the Czech Republic, Germany, and Austria to determine differences in model results and compare these with the revised USLE-base European soil erosion map. The different regional model adaptations and implementation techniques result in substantial differences in test catchment specific mean erosion (up to 75% difference). Much more pronounced differences were modelled for individual fields. The comparison of the region-specific USLE approaches with the revised USLE-base European erosion map underlines the problems and limitations of harmonization procedures. The EU map limits the range of modelled erosion and overall shows a substantially lower mean erosion compared to all region-specific approaches. In general, the results indicate that even if many EU countries use USLE technology as basis for soil conservation planning, a truly consistent method does not exist, and more efforts are needed to homogenize the different methods without losing the USLE-specific knowledge developed in the different regions over the last decades.

A talajerózió becslésére világszerte leginkább elterjedt egyetemes talajvesztési egyenletről (USLE) több irodalmi forrás is megállapítja, hogy az USA-n kívüli területeken csak érvényesítés után használható sikeresen. Az USLE az erózió összetett folyamatát egyszerű képletben összegzi, amelyben a szorzótényezők függetlenek és az erózió éves összegként jelenik meg. Az USLE módosítására és helyettesítésére több kísérlet történt. A fejlesztések során a vízgyűjtők területén lezajló egyszeri csapadékeseményre bekövetkező felszíni lefolyás és talajlehordás térbeli és időbeli előrejelzésére tettek kísérletet. Az empirikus USLE mellett a folyamat fizikai jellegét figyelembe vevő mechanisztikus modellek is megjelentek. A számítástechnika és a GIS rohamos fejlődésével lehetőség nyílt a talajerózió lejtő- vagy táblaszintű, illetve vízgyűjtő léptékű becslésére. Hazánkban a talajerózió előrejelzésére - a klímaváltozás várható jellegzetességei miatt - az empirikus, táblaszintű, éves talajveszteséget becslő USLE modell helyett a fizikai törvényekre épített, csapadékeseményhez kötött modellek felhasználása ajánlható. Tekintettel arra, hogy a modellek érvényessége lokális a felhasználás előtt minden egyes modellt a helyi viszonyokra érvényesíteni szükséges. Összefoglalásképpen megállapítható, hogy a mezőgazdasági termelés fenntarthatósága érdekében a talajerózió előrejelzésére új hazai rendszer kiépítése és érvényesítése szükséges.

Para garantir a sustentabilidade das práticas de uso do solo, os métodos de zoneamento da vulnerabilidade ambiental (ZVA) são essenciais na ocupação de áreas em bacias hidrográficas. Nesse sentido, utilizando como área de estudo a bacia hidrográfica do Ribeirão do Feijão (BHRF), São Carlos-SP (Brasil), os ZVA obtidos pelo método da Análise Empírica da Fragilidade dos Ambientes Naturais e Antropizados (AEFANA), apoiado em índices de dissecação do relevo e classes de declividades, foram comparados com a expectativa de perda de solo (EPS) resultante da Equação Universal de Perda de Solo (USLE). Esta comparação visa identificar a possibilidade de usar a USLE como mais um método para determinação do ZVA em bacias. Os dados foram processados em Sistema de Informações Geográficas e comparados por meio de acertos por matriz de confusão em classes de estabilidade. Os resultados demonstram uma baixa coincidência entre os modelos AEFANA e USLE, porém, a maior influência da topografia em conjunto com as atividades antrópicas permitiu à USLE a determinação de fragilidades não indiciadas pelo ZVA da AEFANA, especialmente nas cabeceiras dos rios. A predição de erosão hídrica pela USLE como modelo para ZVA poderá auxiliar o planejamento territorial da BHRF quando integrada a AEFANA.

137Cs, solum data and the USLE were used to estimate soil erosion on three medium-textured soils in New Brunswick that had been in nearly continuous potato monoculture over the past 15 yr. Sampling transects were located on slopes ranging from 425 to 1040 m long, and from 4.8 to 6.0% slope. Ten equally spaced sites were sampled on each transect. The 137Cs data were used to divide the sampling sites into four groups: deposition, little erosion or deposition, moderately eroded and severely eroded areas. The four groups generally agreed well with soil profile properties. Solum, A horizon thickness and organic carbon content of the A horizon all decreased going from depositional sites to sites with severe erosion. Variations in A horizon thickness and organic carbon content explained about 65% of the variation in 137Cs. Soil losses predicted by the USLE were better correlated with soil losses calculated from 137Cs when the 137Cs data were used to delineate slope segments that were subject to erosion than when 137Cs and USLE soil losses were calculated on a field basis. The USLE overestimated soil losses at high erosion rates. Key words: Erosion, deposition, 137Cs, USLE, soil profile