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1
Keller, Boglárka, Csaba Centeri, Judit Alexandra Szabó, Zoltán Szalai, and Gergely Jakab. "Comparison of the Applicability of Different Soil Erosion Models to Predict Soil Erodibility Factor and Event Soil Losses on Loess Slopes in Hungary." Water 13, no. 24 (December 9, 2021): 3517. http://dx.doi.org/10.3390/w13243517.
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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.
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Todisco, Francesca, Lorenzo Vergni, Sofia Ortenzi, and Lucio Di Matteo. "Soil Loss Estimation Coupling a Modified USLE Model with a Runoff Correction Factor Based on Rainfall and Satellite Soil Moisture Data." Water 14, no. 13 (June 29, 2022): 2081. http://dx.doi.org/10.3390/w14132081.
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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.
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Kinnell, P. I. A. "Event erosivity factor and errors in erosion predictions by some empirical models." Soil Research 41, no. 5 (2003): 991. http://dx.doi.org/10.1071/sr02123.
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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.
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Freebairn, DM, DM Silburn, and RJ Loch. "Evaluation of three soil erosion models for clay soils." Soil Research 27, no. 1 (1989): 199. http://dx.doi.org/10.1071/sr9890199.
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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.
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Oshunsanya, Suarau Odutola, and Nkem Joseph Nwosu. "Suitability of Universal Soil Loss Erodibility, Inter-rill and Rill Erodibility Models for Selected Tropical Soils." Agricultura Tropica et Subtropica 50, no. 4 (December 1, 2017): 191–98. http://dx.doi.org/10.1515/ats-2017-0020.
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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.
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Schürz, Christoph, Bano Mehdi, Jens Kiesel, Karsten Schulz, and Mathew Herrnegger. "A systematic assessment of uncertainties in large-scale soil loss estimation from different representations of USLE input factors – a case study for Kenya and Uganda." Hydrology and Earth System Sciences 24, no. 9 (September 15, 2020): 4463–89. http://dx.doi.org/10.5194/hess-24-4463-2020.
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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.
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Fiener, Peter, Tomáš Dostál, Josef Krása, Elmar Schmaltz, Peter Strauss, and Florian Wilken. "Operational USLE-Based Modelling of Soil Erosion in Czech Republic, Austria, and Bavaria—Differences in Model Adaptation, Parametrization, and Data Availability." Applied Sciences 10, no. 10 (May 25, 2020): 3647. http://dx.doi.org/10.3390/app10103647.
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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.
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László, Péter, and Kálmán Rajkai. "A talajerózió modellezése." Agrokémia és Talajtan 52, no. 3-4 (November 1, 2003): 427–42. http://dx.doi.org/10.1556/agrokem.52.2003.3-4.13.
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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.
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SOUZA, Alessandra Ribeiro de, Francisco Antonio DUPAS, Isabela Neves DRUMMOND, and Carlos Wilmer COSTA. "ZONEAMENTOS DA VULNERABILIDADE AMBIENTAL E EXPECTATIVA DE PERDA DE SOLO: É POSSÍVEL USAR A USLE NA DETERMINAÇÃO DE VULNERABILIDADE AMBIENTAL?" Geosciences = Geociências 38, no. 4 (April 7, 2020): 1105–19. http://dx.doi.org/10.5016/geociencias.v38i4.14083.
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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.
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JONG, E. DE, C. WANG, and H. W. REES. "SOIL REDISTRIBUTION ON THREE CULTIVATED NEW BRUNSWICK HILLSLOPES CALCULATED FROM 137Cs MEASUREMENTS, SOLUM DATA AND THE USLE." Canadian Journal of Soil Science 66, no. 4 (November 1, 1986): 721–30. http://dx.doi.org/10.4141/cjss86-071.
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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
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Manaouch, Mohamed, Anis Zouagui, and Imad Fenjiro. "A review of soil erosion modeling by R/USLE in Morocco: Achievements and limits." E3S Web of Conferences 234 (2021): 00067. http://dx.doi.org/10.1051/e3sconf/202123400067.
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Soil erosion is a major cause of land degradation. It can be estimated with several models, such as empirical, conceptual and physical based. One of the empirical models used worldwide nowadays for soil erosion assessment is the Universal Soil Loss Equation (USLE) and its updated form, the Revised Universal Soil Loss Equation (RUSLE). In Morocco, this model is being used to assess and quantify soil loss by water erosion. In spite of this, it was noted that limited studies employed correctly this important tool. The goal of this review paper was to identify potential usage of R/USLE models in Morocco. This was done by evaluating the conducted studies concerning these models and main gaps and challenges were determined accordingly. Improvement options and future requirements for using R/USLE models were recommended. In order to assess the statues of the R/USLE models applications, the 56 published documents related to R/USLE models conducted in Morocco during the first use till 2020 were collected and reviewed. These publications covered five main areas. The main benefits as well as gaps of the conducted studies were discussed for each area. Current concerns, need of future studies as well as related recommendations and suggestions were also presented.
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Hrabalíková, M., and M. Janeček. "Comparison of different approaches to LS factor calculations based on a measured soil loss under simulated rainfall." Soil and Water Research 12, No. 2 (April 10, 2017): 69–77. http://dx.doi.org/10.17221/222/2015-swr.
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Geographic Information Systems (GIS) in combination with soil loss models can enhance evaluation of soil erosion estimation. SAGA and ARC/INFO geographic information systems were used to estimate the topographic (LS) factor of the Universal Soil Loss Equation (USLE) that in turn was used to calculate the soil erosion on a long-term experimental plot near Prague in the Czech Republic. To determine the influence of a chosen algorithm on the soil erosion estimates a digital elevation model with high accuracy (1 × 1 m) and a measured soil loss under simulated rainfall were used. These then provided input for five GIS-based and two manual procedures of computing the combined slope length and steepness factor in the (R)USLE. The results of GIS-based (R)USLE erosion estimates from the seven procedures were compared to the measured soil loss from the 11 m long experimental plot and from 38 rainfall simulations performed here during 15 years. The results indicate that the GIS-based (R)USLE soil loss estimates from five different approaches to calculation of LS factor are lower than the measured average annual soil loss. The two remaining approaches over-predicted the measured soil loss. The best method for LS factor estimation on field scale is the original manual method of the USLE, which predicted the average soil loss with 6% difference from the measured soil loss. The second method is the GIS-based method that concluded a difference of 8%. The results of this study show the need for further work in the area of soil erosion estimation (with particular focus on the rill/interrill ratio) using the GIS and USLE. The study also revealed the need for an application of the same approach to catchment area as it might bring different outcomes.
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Faisol, Arif, and Mashudi Mashudi. "Estimation of Erosion Potentials through Utilization of Remote Sensing Data and The Universal Soil Loss Equation Model." Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) 12, no. 1 (March 20, 2023): 223. http://dx.doi.org/10.23960/jtep-l.v12i1.223-235.
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Remote sensing data and USLE models have been used widely for erosion analysis. In Indonesia, the USLE model is a reference in erosion analysis to assess land suitability for agricultural crop development. Erosion analysis using remote sensing data provides various advantages, including good accuracy, lower costs, and can analyze erosion rates quickly compared to direct measurement methods. The aim of this study was to analyze the potential erosion in the Arui watershed - Manokwari Regency – West Papua Province using remote sensing data and USLE models. The research was conducted from April to July 2022, with three main stages i.e data inventory, data analysis, and erosion rate estimation. The research shows that the potential erosion rate in the Arui watershed is 15 tons/ha/year or 3.480 tons/year, thus exceeding the tolerable soil loss (TSL) erosion rate threshold of 9.6 tons/ha/year. Therefore, a conservation and restoration program is needed to control the erosion rate in the Arui watershed. Keywords: Erosion rate, Remote sensing, Tolerable soil loss, USLE, Watershed
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Kathwas, Amar Kumar, and Nilanchal Patel. "Geomorphic Control on Soil Erosion – a Case Study in the Subarnarekha Basin, India." Polish Journal of Soil Science 54, no. 1 (June 29, 2021): 1. http://dx.doi.org/10.17951/pjss.2021.54.1.1-24.
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<p>Geomorphology depicts the qualitative and quantitative characteristics of both terrain and landscape features combined with the processes responsible for its evolution. Soil erosion by water involves processes, which removes soil particles and organic matter from the upper sheet of the soil surface, and then transports the eroded material to distant location under the action of water. Very few studies have been conducted on the nature and dynamics of soil erosion in the different geomorphologic features. In the present investigation, an attempt has been made to assess the control of geomorphologic features on the soil loss. Universal Soil Loss Equation (USLE) was used to determine soil loss from the various geomorphological landforms. Principal component analysis (PCA) was implemented on the USLE parameters to determine the degree of association between the individual principal components and the USLE-derived soil loss. Results obtained from the investigation signify the influence of the various landforms on soil erosion. PC5 is found to be significantly correlated with the USLE-derived soil loss. The results ascertained significant association between the soil loss and geomorphological landforms, and therefore, suitable strategies can be implemented to alleviate soil loss in the individual landforms.</p>
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Lane, LJ, KG Renard, GR Foster, and JM Laflen. "Development and application of modern soil erosion prediction technology - The USDA experience." Soil Research 30, no. 6 (1992): 893. http://dx.doi.org/10.1071/sr9920893.
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Erosion prediction efforts are described to provide a synopsis of the USDA's experience in developing and applying soil erosion prediction technology in its research and development activities and its soil conservation programs. For almost five decades, equations to predict soil erosion by water have been useful m developing plans for controlling soil erosion and sedimentation. The Universal Soil Low Equation (USLE) is the most widely known and used of the erosion prediction equations. The USLE presents a simply understood and easily applied technology which has been of incalculable benefit to soil conservation and land management. The Chemicals, Runoff, and Erosion from Agricultural Management Systems Model (CREAMS) contains a sophisticated erosion component based, in part, on the USLE and on flow hydraulics and the processes of sediment detachment, transport, and deposition. In 1985, the USDA in cooperation with BLM and several universities initiated a national project called the Water Erosion Prediction Project (WEPP) to develop a next generation water erosion prediction technology. The Revised Universal Soil Loss Equation (RUSLE) is an update of the USLE to improve erosion prediction in the interim before WEPP is adopted and to provide and adjunct technology thereafter.
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Pampalone, Vincenzo, Alessio Nicosia, Vincenzo Palmeri, Maria Angela Serio, and Vito Ferro. "Rill and Interrill Soil Loss Estimations Using the USLE-MB Equation at the Sparacia Experimental Site (South Italy)." Water 15, no. 13 (June 28, 2023): 2396. http://dx.doi.org/10.3390/w15132396.
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A reliable prediction of event soil loss at the plot scale can be obtained by Universal Soil Loss Equation (USLE)-type models. For the Sparacia site (South Italy), the USLE-MB model was recently developed, in which the effect of the erosive agent is modeled using the rainfall erosivity index of the USLE by a power b1 > 1 of the runoff coefficient QR. In this investigation, the model is parameterized separately using plot data collected for rill and interrill events that occurred in the Sparacia experimental area. The values b1 = 1.406 and b1 = 1.012 were obtained for the interrill and rill databases, respectively, which revealed a different effect of the runoff coefficient on soil loss due to the two erosive processes. Different relationships expressive of topographic factors were also deduced. The USLE-MB estimation performance significantly improved when operating the distinction between the two databases compared with the model parameterized on the complete database. The model was particularly reliable in estimating the highest event soil loss values, which were associated with the occurrence of rills. Finally, the proposed parameterization procedure lends itself to being tested in the framework of empirical soil loss modeling.
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Nuranto, Sindu, Suci Nur Ustriyati, Ifa Nadya Putri, Pratama Tirza Surya Sembada, and Estu Wijayanti. "Sedimentation Analysis in the Tambakboyo Retention Basin Using the USLE Method and Eco Sounder Measurements to Support the Optimization of Water Availability." E3S Web of Conferences 468 (2023): 08008. http://dx.doi.org/10.1051/e3sconf/202346808008.
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The Tambakboyo Dam has been operated for more than 10 years, resulting in increased sedimentation and reduced storage capacity from 400,000 m3 to 300,285 m3. Therefore, to support the optimization of water availability, the age of the reservoir needs to be known. This research analyzes the volume of sediment in the Tambakboyo Reservoir to determine the effective age of the reservoir by estimating the rate of erosion that occurs. The USLE method is used to determine the rate of erosion that occurs in the Tambakboyo Dam catchment area and bathymetry measurements are used to determine the volume of reservoir sediment directly. Using the USLE method, the DTA erosion rate was 13,864 tonnes/ha/year, while direct echo sounding measurements were 11,254 tonnes/ha/year. The remaining age of the reservoir based on the USLE method is 23.02 years, while direct measurements reach 28.359 years. So it can be concluded that the erosion rate in the Tambakboyo watershed is included in the very light erosion category, however the SDR results comparing sediment entering the reservoir with sediment calculated using the USLE method show that sediment control is still not effective.
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Silburn, D. M. "Hillslope runoff and erosion on duplex soils in grazing lands in semi-arid central Queensland. III. USLE erodibility (K factors) and cover - soil loss relationships." Soil Research 49, no. 2 (2011): 127. http://dx.doi.org/10.1071/sr09070.
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Measured Universal Soil Loss Equation (USLE) soil erodibility (K) values are not available for soils in grazing lands in northern Australia. The K values extrapolated from croplands are used in national and river-basin scale assessments of hillslope erosion, using an assumption that the cover factor (C) equals 0.45 for undisturbed (uncultivated) bare soil. Thus, the K needed for input into the models is the measured K for undisturbed soil (KU) divided by 0.45. Runoff and erosion data were available for 7 years on 12 hillslope plots with cover of 10–80%, with and without grazing, with and without tree canopy cover, on a variety of soils according to various soil classification systems. Soils were grouped into those derived from sandstone (SS), mudstone (MS), and eroded mudstone (MSe). These data were used to determine USLE KU, K, and C factor–cover relationships. Methods used to fit the parameters affected the results; minimising the sum of squares of errors in soil losses gave better results than fitting an exponential equation. The USLE LS (length–slope) factor explained the increase in measured average annual soil loss with slope, for plots with low cover. Erodibility (K) was 0.042 for SS and MS soils, irrespective of Australian Soil Classification (Chromosol, Kandosol, Rudosol, Sodosol, Tenosol); K was 0.062 for exposed, decomposing mudstone (MSe Leptic Rudosol). The measured K factor for SS and MS soils was close to that used in catchment-wide soil loss estimation for the site (0.039). This indicates that the method used for estimating K from soil properties (derived from cultivated soils) gave a reasonable estimate of K for the main duplex soils at the study site, as long as the correction for undisturbed soil is used in deriving K from measured data and in applying the USLE model. A 20% increase in K (0.050) for SS and MS soils may be warranted for heavy grazing by cattle. The C factor–cover relationship was different from the standard revised USLE (RUSLE) relationship, requiring a greater exponent (‘bcov’) of 0.075, rather than the default for cropland of 0.035. Increasing cover is therefore more effective at the site than suggested by the USLE. Parameters of USLE were also derived for bedload, allowing suspended load to be calculated by subtracting bedload from total soil loss.
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Suryawanshi, Ashwini, Snehil Dubey, and Mahima Sharma. "Evaluating Soil Erosion through Geospatial Techniques: Difficulties and Prospects in the Context of the Central Indian Chambal River Basin." International Journal of Environment and Climate Change 13, no. 11 (December 8, 2023): 4518–33. http://dx.doi.org/10.9734/ijecc/2023/v13i113632.
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Soil erosion is the greatest threat to the ecosystem which gets accelerated due to environmental agents such as water and wind as well as anthropogenic activities. Effective estimation of soil degradation plays an important role in planning preventive measures and conserving the soil. This study was carried out to provide decision-makers with a picture of soil erosion in Madhya Pradesh's Chambal basin and to identify environmentally hot areas to assist in planning effective conservation measures. By using a few input parameters to create raster maps of the Rainfall erosivity factor (R), Soil erodibility factor (K), Topographic factor (LS), Cover and management factor (C), and Support practice factor (P), the Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) models were applied. The classification of soil erosion and the area portion in each class was then acknowledged. According to the USLE and RUSLE models, the average soil loss for the entire basin is 2.00 t ha-1 yr-1 and 3.04 t ha-1 yr-1, respectively. According to the USLE and RUSLE models, the ranges under severe risk are 0.33% and 0.76%, while the ranges under extremely severe risk are 0.45% and 0.78%, respectively. The land use/land cover (LULC) map for the study area was acquired from satellite data in the USLE, and the Normalized Difference Vegetation Index (NDVI) map was incorporated into the RUSLE model to enhance the comprehension and identification of vegetation. This integration is crucial for capturing detailed information in the RUSLE model. Consequently, RUSLE yields superior results compared to the USLE model, underscoring the significance of incorporating finer details, especially those related to vegetation, for more accurate outcomes
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Suryawanshi, Ashwini, Anupam Kumar Nema, Rahul Kumar Jaiswal, Sukant Jain, and Saswat Kumar Kar. "Identification of Soil Erosion Prone Areas of Madhya Pradesh using USLE/ RUSLE." Journal of Agricultural Engineering 58, no. 02 (June 30, 2021): 177–91. http://dx.doi.org/10.52151/jae2021581.1744.
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Soil erosion is caused due to the dynamic action of erosive agents, mainly water, and is a major threat to the environment. Primary aim of the present study was to study the soil loss dynamics, and identify the environmental hotspots in Madhya Pradesh to aid decision-makers to plan and prioritize appropriate conservation measures. Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) models were applied for erosion rate estimation by generating thematic maps of R (Rainfall erosivity factor), K (Soil erodibility factor), LS (Topographic factor), C (Cover and management factor), and P (Support practice factor) factors by using several input parameters in QGIS software. Subsequently, the different classes of soil erosion and percentage area under these classes were identified. The average annual soil erosion for the entire state as obtained from the USLE and RUSLE model were 5.80 t.ha-1.yr-1 and 6.64 t.ha-1.yr-1, respectively. The areas under severe risk were 1.09 % and 1.80 %, and very severe risk areas were 1.57 % and 1.83 % as estimated by USLE and RUSLE model, respectively. As compared to RUSLE model, USLE model underestimated rate of soil erosion for most river basins of the state as well as for the entire state
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Pontes, Samuel Ferreira, Yuri Jacques Agra Bezerra da Silva, Vanessa Martins, Cácio Luiz Boechat, Ademir Sérgio Ferreira Araújo, Jussara Silva Dantas, Ozeas S. Costa, and Ronny Sobreira Barbosa. "Prediction of Soil Erodibility by Diffuse Reflectance Spectroscopy in a Neotropical Dry Forest Biome." Land 11, no. 12 (December 2, 2022): 2188. http://dx.doi.org/10.3390/land11122188.
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The USLE and the RUSLE are two common erosion prediction models that are used worldwide, and soil erodibility (K-factor) is one parameter used to calculate them. The objectives of this study were to investigate the variability of soil-erodibility factors under different soil-texture classes and evaluate the efficiency of diffuse reflectance spectroscopy (DRS) in the near-infrared range at predicting the USLE and RUSLE K-factors using a partial least squares regression analysis. The study was conducted in Fluvisols in dry tropical forest (the Caatinga). Sampling was undertaken in the first 20 cm of soil at 80 sites distributed 15 m apart on a 70 m × 320 m spatial grid. Results show that the clay fraction is represented mainly by 2:1 phyllosilicates. Soil organic matter content is low (<0.2%), which is typical of tropical dry forests, and this is reflected in the high values of the calculated USLE and RUSLE K-factors. An empirical semivariogram was used to investigate the spatial dependence of both K-factors. Pedometric modeling showed that DRS can be used to predict both USLE (R2adj = 0.53; RMSE = 8.37 10−3 t h MJ−1 mm−1) and RUSLE (R2adj = 0.58; RMSE = 6.78 10−3 t h MJ−1 mm−1) K-factors.
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Suharto, Bambang, Fajri Anugroho, and Bachtiar Arifin. "Analisis Tingkat Bahaya Erosi Pada Lahan Pertanian di Desa Ranu Pani Taman Nasional Bromo Tengger Semeru." Jurnal Sumberdaya Alam dan Lingkungan 10, no. 2 (August 1, 2023): 88–96. http://dx.doi.org/10.21776/ub.jsal.2023.010.02.5.
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Ranu Pani merupakan objek wisata berupa danau di desa Ranu Pani di kecamatan Senduro, Kabupaten Lumajang, Jawa Timur yang merupakan bagian dari Taman Nasional Bromo Tengger Semeru (TNBTS). Kegiatan warga di bidang pertanian merupakan salah satu faktor terjadinya penyempitan di Danau Ranu Pani. Perubahan karakteristik lahan dan intensitas curah hujan yang cukup tinggi serta perubahan penggunaan lahan juga merupakan faktor yang ikut berperan dalam munculnya erosi. Mengetahui besarnya erosi yang terjadi di suatu wilayah merupakan hal yang penting, karena selain dapat mengetahui banyaknya tanah yang tererosi juga dapat digunakan sebagai salah satu jalan untuk mencari sebuah solusi dari permasalahan tersebut. Penelitian ini menggunakan metode USLE dan metode petak kecil untuk menghitung erosi yang terjadi pada lahan pertanian kubis dan kentang yang berukuran ¼ hektar. Petak kecil yang digunakan berukuran 4x2 meter yang berada pada topografi curam (25-40%). Metode ini digunakan untuk validasi terhadap perhitungan USLE dengan catatan jenis tanah dan kemiringan tanahnya sama. Pengukuran menggunakan petak kecil dilakukan selama 1 bulan setiap kejadian hujan. Pada metode petak kecil di lahan campuran kubis dan kentang diperoleh nilai erosi sebesar 21.27 ton.ha-1.tahun-1, sedangkan metode USLE sebesar 74.23 ton.ha-1.tahun-1. Berdasarkan hasil dari pehitungan tersebut, lahan pertanian ini memiliki klasifikasi berat pada metode USLE dan sedang pada metode petak kecil.
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Benavidez, Rubianca, Bethanna Jackson, Deborah Maxwell, and Kevin Norton. "A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates." Hydrology and Earth System Sciences 22, no. 11 (November 27, 2018): 6059–86. http://dx.doi.org/10.5194/hess-22-6059-2018.
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Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape to address the problem strategically. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviews the different sub-factors of USLE and RUSLE, and analyses how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with (R)USLE and related approaches. Within each sub-factor section, the strengths and limitations of the different equations are discussed, and guidance is given as to which equations may be most appropriate for particular climate types, spatial resolution, and temporal scale. We investigate some of the limitations of existing (R)USLE formulations, such as uncertainty issues given the simple empirical nature of the model and many of its sub-components; uncertainty issues around data availability; and its inability to account for soil loss from gully erosion, mass wasting events, or predicting potential sediment yields to streams. Recommendations on how to overcome some of the uncertainties associated with the model are given. Several key future directions to refine it are outlined: e.g. incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and compiling consistent units for the future literature to reduce confusion and errors caused by mismatching units. The potential of combining (R)USLE with the Compound Topographic Index (CTI) and sediment delivery ratio (SDR) to account for gully erosion and sediment yield to streams respectively is discussed. Overall, the aim of this paper is to review the (R)USLE and its sub-factors, and to elucidate the caveats, limitations, and recommendations for future applications of these soil erosion models. We hope these recommendations will help researchers more robustly apply (R)USLE in a range of geoclimatic regions with varying data availability, and modelling different land cover scenarios at finer spatial and temporal scales (e.g. at the field scale with different cropping options).
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Payuyu, Efendy, Fitriyane Lihawa, and Iswan Dunggio. "APLIKASI MODEL BUILDER PADA SISTEM INFORMASI GEOGRAFI UNTUK MENDUGA POTENSI EROSI DI SUB DAS MARISA KABUPATEN GORONTALO." Gorontalo Journal of Forestry Research 6, no. 1 (April 10, 2023): 34. http://dx.doi.org/10.32662/gjfr.v6i1.2504.
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ABSTRAK Sub DAS Marisa merupakan salah satu sub DAS yang mengalami kerusakan. Adanya perubahan penggunaan lahan menjadi lahan pertanian mengakibatkan peningkatan terjadinya erosi. Tujuan penelitian adalah untuk menduga potensi erosi dengan aplikasi model Builder pada Sistem Informasi Geografis. Pengukuran potensi erosi menggunakan metode USLE (Universal Soil Loss Equation). Berdasarkan hasil analisis USLE bahwa Sub DAS Marisa nilai erosi tertinggi berada di Kecamatan Limboto Barat dengan luas 7.539,30 Ha. Faktor erosi yang paling berpengaruh di Sub DAS Marisa yaitu faktor CP dan LS. Mayoritas masyarakat merupakan petani sehingga banyaknya lahan pertanian di daerah tersebut. Faktor LS yaitu rata-rata keadan topografi di Sub DAS Marisa yaitu curam dengan kelas kemiringan lereng IV (25%-40%). Di Sub DAS Marisa kurangnya tindakan konservasi yang dilakukan masyarakat, sehingga banyaknya partikel tanah yang terdegradasi terbawa aliran oleh air hujan. Adapun tindakan konservasi yang dapat diterapkan antara lain pemberian mulsa dan penanaman dengan pola sistem agroforestry. Kata kunci: Erosi; USLE; Aplikasi Builder. ABSTRACT Marisa sub-watershed is one of the damaged sub-watersheds. The change in land use to agricultural land resulted in an increase in erosion. The purpose of this research is to estimate the erosion potential with the application of the Builder model in Geographic Information Systems. Measurement of erosion potential using the USLE (Universal Soil Loss Equation) method. Based on the results of USLE analysis that the Marisa Sub-watershed has the highest erosion value in the West Limboto District with an area of 7,539.30 Ha. The most influential erosion factors in the Marisa sub-watershed are CP and LS factors. The majority of people are farmers so there is a lot of agricultural land in the area. The LS factor is the average topography in the Marisa sub-watershed, which is steep with slope class IV (25%-40%). In the Marisa Sub-watershed, there is a lack of conservation action taken by the community, so that many degraded soil particles are carried away by rainwater. The conservation actions that can be applied include providing mulch and planting with an agroforestry system pattern. Keywords: Erosion; USLE; Builder Application
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Carra, Bruno Gianmarco, Giuseppe Bombino, Manuel Esteban Lucas-Borja, Pietro Denisi, Pedro Antonio Plaza-Álvarez, and Demetrio Antonio Zema. "Modelling the Event-Based Hydrological Response of Mediterranean Forests to Prescribed Fire and Soil Mulching with Fern Using the Curve Number, Horton and USLE-Family (Universal Soil Loss Equation) Models." Land 10, no. 11 (October 31, 2021): 1166. http://dx.doi.org/10.3390/land10111166.
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The SCS-CN, Horton, and USLE-family models are widely used to predict and control runoff and erosion in forest ecosystems. However, in the literature there is no evidence of their use in Mediterranean forests subjected to prescribed fire and soil mulching. To fill this gap, this study evaluates the prediction capability for runoff and soil loss of the SCS-CN, Horton, MUSLE, and USLE-M models in three forests (pine, chestnut, and oak) in Southern Italy. The investigation was carried out at plot and event scales throughout one year, after a prescribed fire and post-fire soil mulching with fern. The SCS-CN and USLE-M models were accurate in predicting runoff volume and soil loss, respectively. In contrast, poor predictions of the modelled hydrological variables were provided by the models in unburned plots, and by the Horton and MUSLE models for all soil conditions. This inaccuracy may have been due to the fact that the runoff and erosion generation mechanisms were saturation-excess and rainsplash, while the Horton and MUSLE models better simulate infiltration-excess and overland flow processes, respectively. For the SCS-CN and USLE-M models, calibration was needed to obtain accurate predictions of surface runoff and soil loss; furthermore, different CNs and C factors must be input throughout the year to simulate the variability of the hydrological response of soil after fire. After calibration, two sets of CNs and C-factor values were suggested for applications of the SCS-CN and USLE-M models, after prescribed fire and fern mulching in Mediterranean forests. Once validated in a wider range of environmental contexts, these models may support land managers in controlling the hydrology of Mediterranean forests that are prone to wildfire risks.
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Zhang, Hong Ming, Qin Ke Yang, Shu Qin Li, Mei Li Wang, Ming Ying, Huan Lang, and Xue Wen Dong. "Design and Implementation of Regional LS Factor Computing Tool Based on GIS and Array Operation." Applied Mechanics and Materials 394 (September 2013): 509–14. http://dx.doi.org/10.4028/www.scientific.net/amm.394.509.
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For over 40 years, the universal soil loss equation (USLE) and its revised version the revised universal soil loss equation (RUSLE) have been used all over the world for soil mean annual loss per area unit. Because of the watershed erosion models are under developing, many researchers applied the USLE and RUSLE to estimate soil loss in watershed estimations. However, a major limitation is the difficulty in extracting the LS factor. The geographic information system-based (GIS-based) methods which have been developed for estimating the slope length for USLE and RUSLE model also have limitations. A series of ARC/INFO AML program was created that can calculate LS factor for the USLE, however the program need a very long time to run in wide-ranging areas. The flowpath and cumulative cell length-based method (FCL) overcomes this disadvantage but does not consider the following questions: (1) Some original AML program functions are not achieved, so results are different. (2) Using USLE to calculate LS factor that do not adapt to the erosion environment of China. (3) There isnt a friendly graphic user interface. The purpose of this research was to overcome these limitations and extend the FCL method through Integrating CSLE equation. We developed a LS calculation tool (LS-TOOL) in Microsofts .NET environment using C# with a user-friendly interface. Comparing the LS factor calculated with the FCL method and AML method, LS factor values generated by using LS-TOOL method delivers improved results. The LS-TOOL algorithm can automatically calculate slope length, slope steepness, L factor, S factor, and LS factors, providing the results as ASCII files which can be easily used in some GIS software. This study is an important step forward in conducting fast large-scale erosion evaluation.
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Yusuf, Sri Malahayati, Kukuh Murtilaksono, and Dwi Mei Lawaswati. "Pemetaan sebaran erosi tanah prediksi melalui integrasi model USLE ke dalam Sistem Informasi Geografis." Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) 10, no. 4 (December 31, 2020): 594–606. http://dx.doi.org/10.29244/jpsl.10.4.594-606.
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Penerapan model USLE pada beberapa Daerah Aliran Sungai (DAS) di Indonesia menunjukkan keragaman proses yang mempengaruhi terjadinya erosi tanah. Integrasi model USLE ke dalam Sistem Informasi Geografis (SIG) mampu memberikan gambaran spasial dari sebaran kelas erosi tanah. Penelitian ini bertujuan untuk memprediksi besarnya erosi tanah pada berbagai tutupan lahan di sub DAS Ciesek dengan mengintegrasikan model USLE ke dalam SIG. Pengambilan sampel tanah utuh dan terganggu dilakukan berdasarkan SPT, disertai pengamatan sifat fisik tanah di lapangan. Prediksi erosi tanah dilakukan menggunakan menu raster calculator dengan input data berbasis raster yang memiliki resolusi spasial tertentu. Analisis sebaran kelas erosi pada berbagai jenis tutupan lahan dan kelas lereng dilakukan dengan metode tabulasi silang. Hasil penelitian menunjukkan bahwa kelas erosi tanah sangat rendah dominan di lokasi penelitian yaitu pada area dengan tutupan lahan hutan. Erosi tanah prediksi tertinggi dihasilkan dari tutupan lahan terbuka, diikuti oleh lahan tegalan, dan kebun campuran
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WILSON, JOHN P. "SOIL EROSION FROM AGRICULTURAL LAND IN THE LAKE SEMCOE–COUCHICHING BASIN, 1800–1981." Canadian Journal of Soil Science 69, no. 1 (February 1, 1989): 137–51. http://dx.doi.org/10.4141/cjss89-013.
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Soil losses from agricultural land in the Lake Simcoe–Couchiching Basin between 1800 and 1981 are estimated with the universal soil loss equation (USLE). Existing methods and data are used to estimate and combine the six USLE factors with one exception. A new method that is consistent with the USLE slope definitions was developed and used to estimate the topographic factor. The results of the present study add to earlier erosion assessments because they describe the erosion hazard throughout the basin from the first days of forest clearance and agricultural settlement to the present. In particular, they indicate that soil loss rates on agricultural land have gone almost full circle from high to low and back to high rates in the past 130 yr. This result indicates the need to continue our search for permanent and more viable systems of land use. Key words: Soil erosion, potential soil loss, regional assessment
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Souza, Bruna Alves de, Vinícius de Oliveira Ribeiro, Nelison Ferreira Correa, João Lucas Alves da Silva, Jonailce Oliveira Diodato, and Lucimara Gonçalves Narcizo. "Carta de áreas prioritárias à recuperação para a microbacia do córrego Curupaí, Mato Grosso do Sul." Research, Society and Development 11, no. 6 (May 4, 2022): e47011629416. http://dx.doi.org/10.33448/rsd-v11i6.29416.
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Dados que compõem a Equação Universal de Perdas de Solo (USLE), bem como a Temperatura de Superfície Terrestre (TST) são fatores qualiquantitativos fundamentais no uso e conservação do solo, e, em geral, analisados individualmente. O objetivo deste trabalho foi identificação de áreas prioritárias à recuperação na bacia hidrográfica do Córrego Curupaí/ MS. Para tanto, elaboraram-se cartas específicas referentes a cada fator componente da USLE, além da confecção da carta de Temperatura de Superfície Terrestre (TST), em ambiente SIG. Na sequência, as cartas de estimativa de perda anual de solo (Fator A) e de temperatura de superfície foram reclassificadas para obtenção da carta de áreas prioritárias para recuperação. Como resultado, a Carta de Índice de Áreas Prioritárias para Recuperação (IAP) apontou áreas de média e alta prioridades, que, isoladamente, as componentes de USLE e TST indicavam como de baixa prioridade. A integração dos fatores mencionados mostrou potencial para identificação de áreas ambientalmente sensíveis com análise de múltiplos parâmetros simultâneos.
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FIRMINO GOMES, FRANCISCO EMANOEL, George Leite Mamede, and Fernando Bezerra Lopes. "ALTERNATIVA PARA O CÁLCULO AUTOMÁTICO E ESPACIALIZADO DO FATOR TOPOGRÁFICO DA USLE EM BACIAS HIDROGRÁFICAS." IRRIGA 1, no. 2 (October 10, 2018): 6–13. http://dx.doi.org/10.15809/irriga.2018v1n2p6-13.
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ALTERNATIVA PARA O CÁLCULO AUTOMÁTICO E ESPACIALIZADO DO FATOR TOPOGRÁFICO DA USLE EM BACIAS HIDROGRÁFICAS
FRANCISCO EMANOEL FIRMINO GOMES1; GEORGE LEITE MAMEDE2 E FERNANDO BEZERRA LOPES3
1Departamento de engenharia agrícola/UFC, Doutorando em engenharia agrícola, Fortaleza, CE, Fone:(85)99238-2819, CEP:60440-900, e-mail: emanoelfg@hotmail.com.
2Instituto de Engenharias e Desenvolvimento Sustentável/ UNILAB, Professor Doutor, Redenção, CE, CEP: 62790-000, e-mail: georgemamede@hotmail.com
3Departamento de Engenharia Agrícola, UFC, Professor Doutor, Fortaleza, CE, CEP:60440-900, e-mail: lopesfb@ufc.br
1 RESUMO
Dentre os fatores da Universal Soil Loss Equation (USLE), o fator topográfico é que menos se aproxima da realidade e, em geral, os modelos apresentam elevada complexidade para sua determinação. Neste estudo, portanto objetivou-se calcular o fator topográfico da USLE de maneira simplificada usando técnicas de Sistema de Informações Geográficas (SIG). Para tanto, foi utilizado dados do Modelo Digital de Elevação - MDE obtido a partir do (SRTM -Shuttle Radar Topography Mission), assim foram calculadas as declividades e os comprimentos de rampas usando processamento dos dados matriciais do MDE, para então estimar o fator topográfico. Os valores de fator topográfico variaram de 0,21 a 9,88 com média de 1,97. As técnicas de sistema de informação geográficas mostraram-se eficientes para o cálculo do fator topográfico a partir do MDE.
Palavras-chave: erosão, topografia de encosta, geoprocessamento.
GOMES, F. E. F.; MAMEDE, G. L.; LOPES, F. B.
ALTERNATIVE FOR THE AUTOMATIC AND SPACIALIZATION OF USLE TOPOGRAPHIC FACTOR IN WATERSHEDS
2 ABSTRACT
Among the factors of the Universal Soil Loss Equation (USLE), the topographic factor is that it is less close to reality and, usually, the models used for its determination presents high complexity. In this study, therefore, the main objective was to calculate the topographic factor of the USLE in a simplified way using techniques geographic information system (sig). For that, data from the Digital Elevation Model – DEM was used, derived from the SRTM (Shuttle Radar Topography Mission), so slopes and slope length were calculated by processing of the DEM matrix data, so the topographic factor was estimated. The topographic factor values varying from 0.21 to 9.88 with an average of 1.97. The GIS techniques showed efficient for estimating the topographic factor derived from DEM data base.
Keywords: erosion, topography of hillside, geoprocessing.
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Steinhoff-Knopp, Bastian, and Benjamin Burkhard. "Mapping Control of Erosion Rates: Comparing Model and Monitoring Data for Croplands in Northern Germany." One Ecosystem 3 (June 12, 2018): e26382. http://dx.doi.org/10.3897/oneeco.3.e26382.
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Control of erosion rates (CER) is a key ecosystem service for soil protection. It is mandatory for sustaining the capacity, especially of agroecosystems, to provide ecosystem services. By applying an established framework to assess soil regulating services, this study compares two approaches to assess CER provision for 466 ha of cropland in Lower Saxony (Central Northern Germany). In a "sealed modelling approach", the structural and the mitigated structural impact were modelled by applying the Universal Soil Loss Equation (USLE). The second approach uses spatially explicit long-term monitoring data on soil loss rates obtained in the investigation area as an alternative to the USLE-based modelled mitigated structural impact. Assuming that the monitoring data have a higher reliability than the modelled data, the comparison of both approaches demonstrated the uncertainties of the USLE-based assessment of CER. The calculated indicators based on a sound monitoring database on soil loss rates showed that, due to limitations of the USLE model, the structural impact in thalwegs has been underestimated. Incorporating models with the ability to estimate soil loss by rilling und gullying can help to overcome this uncertainty. The produced set of complementary large-scale CER maps enables an integrated analyses of CER. In the entire investigation area, the provision of CER regulating ecosystem services was generally high, indicating good management practices. Differences at the field scale and between the different regions can be explained by variations of the structural impact and the management practices.
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Le, Trung Van, Hoang Thi Kim Nguyen, and Anh Thi Ngoc Nguyen. "GIS and Remote Sensing solution for Dalat city’s soil erosion mapping." Science and Technology Development Journal 19, no. 2 (June 30, 2016): 46–54. http://dx.doi.org/10.32508/stdj.v19i2.700.
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This paper introduces the solution for Dalat city’s soil erosion mapping using the integration of GIS, Remote Sensing and the Universal Soil Loss Equation (USLE). Each of the USLE factors with associated attribute data are dicussed and the soil erosion parameters were selected and encoded in a GIS database to produce thematic layers. The result demonstrates the soil erosion map that indicates the potential annual soil loss located in each area of land. This map is used to confirm the severe level of soil erosion risk need immediate attention from soil conservation point of view.
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Arévalo, Diana, Ramón Bienes, and Marta Ruiz-Colmenero. "Application of three erosion prediction models in the center of the Iberian Peninsula: incorporation and evaluation of new parameters with influence on soil losses / Aplicación de tres modelos de predicción de la erosión en el centro de la Península Ibérica: incorporación y evaluación de nuevos parámetros con influencia en las pérdidas de suelo." Brazilian Journal of Animal and Environmental Research 5, no. 2 (April 26, 2022): 1829–43. http://dx.doi.org/10.34188/bjaerv5n2-030.
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Erosion prediction models are useful tools for assessing the impact of land use practices on soil and water conservation. These models are often used by environmental protection authorities for the establishment of guidelines. This study examines the application of three erosion models of different complexity to predict soil loss in a small basin located in the center of the Iberian Peninsula, under a semi-arid Mediterranean climate. The models applied are: the Universal Soil Loss Equation (USLE), the Revised Universal Soil Loss Equation (RUSLE) and an adaptation of the USLE model, which we have called AUSLE, to include soil characteristics not included in the original model. The average value of erosion at the watershed level obtained by the AUSLE model does not show significant differences with respect to the value obtained with RUSLE 1.06c, while the USLE shows an overestimation with respect to the other two models. The AUSLE model allows obtaining values similar to the more complex model (RUSLE) in a simple way, which makes it interesting for its application in conservation plans.
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Csáfordi, Péter, Andrea Pődör, Jan Bug, and Zoltán Gribovsyki. "Soil Erosion Analysis in a Small Forested Catchment Supported by ArcGIS Model Builder." Acta Silvatica et Lignaria Hungarica 8, no. 1 (December 1, 2012): 39–56. http://dx.doi.org/10.2478/v10303-012-0004-5.
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Abstract - To implement the analysis of soil erosion with the USLE in a GIS environment, a new workflow has been developed with the ArcGIS Model Builder. The aim of this four-part framework is to accelerate data processing and to ensure comparability of soil erosion risk maps. The first submodel generates the stream network with connected catchments, computes slope conditions and the LS factor in USLE based on the DEM. The second submodel integrates stream lines, roads, catchment boundaries, land cover, land use, and soil maps. This combined dataset is the basis for the preparation of other USLE-factors. The third submodel estimates soil loss, and creates zonal statistics of soil erosion. The fourth submodel classifies soil loss into categories enabling the comparison of modelled and observed soil erosion. The framework was applied in a small forested catchment in Hungary. Although there is significant deviation between the erosion of different land covers, the predicted specific soil loss does not increase above the tolerance limit in any area unit. The predicted surface soil erosion in forest subcompartments mostly depends on the slope conditions.
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Kinnell. "A Review of the Science and Logic Associated with Approach Used in the Universal Soil Loss Equation Family of Models." Soil Systems 3, no. 4 (September 24, 2019): 62. http://dx.doi.org/10.3390/soilsystems3040062.
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Soil erosion caused by rain is a major factor in degrading agricultural land, and agricultural practices that conserve soil should be used to maintain the long-term sustainability of agricultural land. The Universal Soil Loss Equation (USLE) was developed in the 1960s and 1970s to predict the long-term average annual soil loss from sheet and rill erosion on field-sized areas as an aid to making management decisions to conserve soil. The USLE uses six factors to take account of the effects of climate, soil, topography, crops, and crop management, and specific actions designed to conserve soil. Although initially developed as an empirical model based on data from more than 10,000 plot years of data collected in plot experiments in the USA, the selection of the independent factors used in the model was made taking account of scientific understanding of the drivers involved in rainfall erosion. In addition, assumptions and approximations were needed to make an operational model that met the needs of the decision makers at that time. Those needs have changed over time, leading to the development of the Revised USLE (RUSLE) and a second version of that, the Revised USLE, Version 2 (RUSLE2). While the original USLE model was not designed to predict short-term variations in erosion well, these developments have involved more use of conceptualization in order to deal with the time-variant impacts of the drivers involved in rainfall erosion. The USLE family of models is based on the concept that the “unit” plot, a bare fallow area 22.1 m long on a 9% slope gradient with cultivation up and down the slope, provides a physical situation where the effect of climate and soil on rainfall erosion can be determined without the need to consider the impact of the four other factors. The science and logic associated with this approach is reviewed. The manner by which the soil erodibility factor is determined from plot data ensures that the long-term average annual soil loss for the unit plot is predicted well, even when the assumption that event soil loss is directly related to the product of event rainfall energy, and the maximum 30-min intensity is not wholly appropriate. RUSLE2 has a capacity to use CLIGEN, the weather generator used in WEPP, and so can predict soil losses based on individual storms in a similar way to WEPP. Including a direct consideration of runoff in determining event erosivity enhances the ability to predict event soil losses when runoff is known or predicted well, but similar to more process-based models, this ability is offset by the difficulty in predicting runoff well.
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KACHANOSKI, R. G., and E. de JONG. "EVALUATION OF THE EROSION INDEX FOR THE PRAIRIES." Canadian Journal of Soil Science 65, no. 1 (February 1, 1985): 225–28. http://dx.doi.org/10.4141/cjss85-024.
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Ateshian’s (1974) equation, used by Wall et al. (1983) to calculate the USLE rainfall erosion index (R) for Canada, appears to considerably overestimate the actual R value for Saskatchewan. An alternative equation derived using a generalized distribution curve for prairie rainstorms given by McKay (1970) predicted an R value of 350 for Saskatoon which was close to the 12-yr average (R = 340) for Saskatoon calculated from tipping bucket rain data. More R values need to be calculated from existing climatological data to determine which (if any) estimation equation is satisfactory. Key words: Rainfall factor, prediction, USLE
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Dang, Xinghai, and Yajie Sun. "Estimation of soil erosion in loess plateau based on geographic information system." Journal of Geography and Cartography 5, no. 1 (November 11, 2021): 1. http://dx.doi.org/10.24294/jgc.v5i1.1410.
Full textAbstract:
One of the core problems in soil erosion research is the estimation of soil erosion. It is a feasible method and technical approach to estimate soil erosion in Loess Plateau region by using USLE model, GIS and RS technology and using DEM data, meteorological data and land-use type data. With the support of GIS and RS technology, the USLE factors and soil erosion in Loess Plateau region were estimated, and the soil erosion intensity was classified according to the Chinese soil erosion intensity classification standard. The results can provide reference for the development of soil erosion control measures in the Loess Plateau.
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Selmy, Salman A. H., Salah H. Abd Al-Aziz, Raimundo Jiménez-Ballesta, Francisco Jesús García-Navarro, and Mohamed E. Fadl. "Modeling and Assessing Potential Soil Erosion Hazards Using USLE and Wind Erosion Models in Integration with GIS Techniques: Dakhla Oasis, Egypt." Agriculture 11, no. 11 (November 10, 2021): 1124. http://dx.doi.org/10.3390/agriculture11111124.
Full textAbstract:
Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. The current study proposed a spatial-based model that integrated geographic information systems (GIS) techniques with both the universal soil loss equation (USLE) model and the Index of Land Susceptibility to Wind Erosion (ILSWE). The proposed Spatial Soil Loss Model (SSLM) was designed to generate the potential soil erosion maps based on water erosion and wind erosion by integrating factors of the USLE and ILSWE models into the GIS environment. Hence, the main objective of this study is to predict, quantify, and assess the soil erosion hazards using the SSLM in the Dakhla Oasis as a case study. The water soil loss values were computed by overlaying the values of five factors: the rainfall factor (R-Factor), soil erodibility (K-Factor), topography (LS-Factor), crop types (C-Factor), and conservation practice (P-Factor). The severity of wind-driven soil loss was calculated by overlaying the values of five factors: climatic erosivity (CE-Factor), soil erodibility (E-Factor), soil crust (SC-Factor), vegetation cover (VC-Factor), and surface roughness (SR-Factor). The proposed model was statistically validated by comparing its outputs to the results of USLE and ILSWE models. Soil loss values based on USLE and SSLM varied from 0.26 to 3.51 t ha−1 yr−1 with an average of 1.30 t ha−1 yr−1 and from 0.26 to 3.09 t ha−1 yr−1 with a mean of 1.33 t ha−1 yr−1, respectively. As a result, and according to the assessment of both the USLE and the SSLM, one soil erosion class, the very low class (<6.7 t ha−1 yr−1), has been reported to be the prevalent erosion class in the study area. These findings indicate that the Dakhla Oasis is slightly eroded and more tolerable against water erosion factors under current management conditions. Furthermore, the study area was classified into four classes of wind erosion severity: very slight, slight, moderate, and high, representing 1.0%, 25.2%, 41.5%, and 32.3% of the total study area, respectively, based on the ILSWE model and 0.9%, 25.4%, 43.9%, and 29.9%, respectively, according to the SSLM. Consequently, the Dakhla Oasis is qualified as a promising area for sustainable agriculture when appropriate management is applied. The USLE and ILSWE model rates had a strong positive correlation (r = 0.97 and 0.98, respectively), with the SSLM rates, as well as a strong relationship based on the average linear regression (R2 = 0.94 and 0.97, respectively). The present study is an attempt to adopt a spatial-based model to compute and map the potential soil erosion. It also pointed out that designing soil erosion spatial models using available data sources and the integration of USLE and ILSWE with GIS techniques is a viable option for calculating soil loss rates. Therefore, the proposed soil erosion spatial model is fit for calculating and assessing soil loss rates under this study and is valid for use in other studies under arid regions with the same conditions.
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Jones, Bilal G., Buddhi R. Gyawali, Demetrio Zourarakis, Maheteme Gebremedhin, and George Antonious. "Soil Loss Analysis of an Eastern Kentucky Watershed Utilizing the Universal Soil Loss Equation." Environments 9, no. 10 (October 4, 2022): 126. http://dx.doi.org/10.3390/environments9100126.
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Soil erosion is the displacement of soil’s upper layer(s) triggered by a variation in topography, land use and soil types, and anthropogenic activities. This study selected the Marrowbone Creek-Russel Fork watershed in eastern Kentucky to estimate the mean annual soil loss over eight years (from 2013 to 2020) utilizing the Universal Soil Loss Equation (USLE). We included monthly precipitation, soil survey, digital elevation model (DEM), and land cover data to estimate the parameters of the USLE. The mean annual soil loss for the study area ranged from 1.77 to 2.91 Mg ha−1 yr−1 with an eight-year mean of 2.31 Mg ha−1 yr−1. In addition, we observed that developed land cover classes were less erosion-resistant than undeveloped land cover classes over the observation period. The results of this case study in our small watershed that has been historically impacted by upstream coal-mining activities are comparable to the results from similar studies in other geographic regions. However, we suggest other researchers conduct similar studies using robust data to determine the applicability of the USLE model and validate the results in developing measures to address soil loss issues.
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Brath, Armando, Attilio Castellarin, and Alberto Montanari. "Assessing the effects of land-use changes on annual average gross erosion." Hydrology and Earth System Sciences 6, no. 2 (April 30, 2002): 255–65. http://dx.doi.org/10.5194/hess-6-255-2002.
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Abstract. The effects of land-use changes on potential annual gross erosion in the uplands of the Emilia-Romagna administrative region, a broad geographical area of some 22 000 km2 in northern-central Italy, have been analysed by application of the Universal Soil Loss Equation (USLE). The presence of an extended mountain chain, particularly subject to soil erosion, makes the estimation of annual gross erosion relevant in defining regional soil-conservation strategies. The USLE, derived empirically for plots, is usually applied at the basin scale. In the present study, the method is implemented in a distributed framework for the hilly and mountainous portion of Emilia-Romagna through a discretisation of the region into elementary square cells. The annual gross erosion is evaluated by combining morphological, pedological and climatic information. The stream network and the tributary area drained by each elementary cell, which are needed for the local application of the USLE, are derived automatically from a Digital Elevation Model (DEM) of grid size 250 x 250 m. The rainfall erosivity factor is evaluated from local estimates of rainfall of six-hour storm duration and two-year return period. The soil erodibility and slope length-steepness factors are derived from digital maps of land use, pedology and geomorphology. Furthermore, historical land-use maps of the district of Bologna (a large portion — 3720 km2 — of the area under study), allow the effect of actual land use changes on the soil erosion process to be assessed. The analysis shows the influence of land-use changes on annual gross erosion as well as the increasing vulnerability of upland areas to soil erosion processes during recent decades. Keywords: USLE, gross erosion, distributed modelling, land use changes, northern-central Italy
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Pongsai, S., D. Schmidt Vogt, R. P. Shrestha, R. S. Clemente, and A. Eiumnoh. "Calibration and validation of the Modified Universal Soil Loss Equation for estimating sediment yield on sloping plots: A case study in Khun Satan catchment of Northern Thailand." Canadian Journal of Soil Science 90, no. 4 (December 1, 2010): 585–96. http://dx.doi.org/10.4141/cjss09076.
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In this study, model testing, calibration, and validation of the Modified Universal Soil Loss Equation (MUSLE) model were carried out in Khun Satan catchment, Thailand, for the estimation of sediment yield in plots of different slopes using the S factor from the classic Universal Soil Loss Equation (USLE) and the McCool model, as the calibration parameter. In situ experimental plots were established with five different inclinations (9, 16, 25, 30, and 35%), with the other model parameters (e.g., erodibility, conservation practice, etc) being treated as constants. Sediment yields were recorded from 27 rainfall events between July and October 2003. It was found that both the classic USLE and the McCool models over-estimated sediment yields at all slope angles. However, the classic USLE produced a smaller relative error (RE) than the McCool model at plots with slopes of 9 and 16%, while the McCool model performed better at plots with slopes over 16% inclination. The calibration of the model using the S factor was then made for two slope range intervals, and the slope algorithm was later modified. The calibrated S factors were used in the prototype model for slope ranges of 9 to 16% using classic USLE and for slopes from 16 to 35% using the McCool model. The results revealed that an acceptable accuracy can be obtained through model calibration. The model validation based on paired t-test, on the other hand, showed that there was no difference (α = 0.05) between measured and estimated sediment yield using both models. This result indicates that if data on various slope gradients are limited, MUSLE needs to be calibrated before application, especially with respect to topographic factors, in order to obtain an accurate estimate of the sediment yield from individual rainfall events.
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Xiong, Muqi, Ranhao Sun, and Liding Chen. "Global analysis of support practices in USLE-based soil erosion modeling." Progress in Physical Geography: Earth and Environment 43, no. 3 (March 13, 2019): 391–409. http://dx.doi.org/10.1177/0309133319832016.
Full textAbstract:
Support practices (SPs) influence the magnitude of soil loss and can be readily influenced by human interventions to mitigate soil loss. The SPs factor is expressed as the P-factor in the widely used soil erosion model – the universal soil loss equation (USLE) – and its revised version. Although the effects of SPs on soil erosion are well recognized, the quantification of the P-factor for soil loss modeling remains challenging. This limitation of the P-factor particularly restricts the applicability of USLE-based models at large scales. Here, we analyzed the P-factor values in USLE-based models from 196 published articles. The results were as follows: (a) an increasing trend in the number of studies has been observed in recent years, especially at large scales; (b) the P-factor values for paddy fields, orchards, and croplands were 0.16 ± 0.15, 0.47 ± 0.12, and 0.49 ± 0.21, respectively, and in terms of different types of SPs, the P-factor values for terracing, contouring, and strip-cropping were 0.28 ± 0.18, 0.52 ± 0.24, and 0.49 ± 0.28, respectively; (c) various methods have been developed for P-factor qualification, although the methods that consider SP conditions were most frequently used in studies with relatively smaller areas (< 100 km2), suggesting that USLE-based models are in need of improvement via the quantification of the P-factor, particularly with respect to the regional and global scale; and (d) further improvements of the P-factor for soil erosion modeling should concentrate on building P-factor datasets at the regional level according to data on the effectiveness of SPs on soil loss control based on field experiments in published articles, using advanced image processing techniques based on higher-resolution satellite imagery and developing proxy indicators for P-factors at large scales.
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Agustina, Hilda, and Vita Ayu Kusuma Dewi. "Analisa Erosi Metode USLE pada Lahan Sawit Kabupaten Muara Enim." Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) 9, no. 3 (September 30, 2020): 157. http://dx.doi.org/10.23960/jtep-l.v9i3.157-162.
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Manusia sangat menentukan tindakan kelestarian lingkungan terutama pada tanah dan air. Manusia sebagai pengguna pada tanah untuk berbagai macam keperluan, terutama sebagai pemukiman dan usaha. Guna menjaga kelestarian pada tanah maka diperlukan pengelolaan tanah yang juga mengikutsertakan tindakan konservasi di dalam kegiatan pengelolaan dan pemanfaatan tanah. Sebelum dapat menentukan tindakan konservasi untuk kelestarian tanah, maka diperlukan analisa erosi yang dapat diaplikasikan sebagai media untuk menentukan besarnya erosi pada suatu lahan. Metode USLE (Universal Soil Loss Equation) adalah metode yang dapat diaplikasikan pada wilayah Indonesia sampai sekarang. Perkembangan intensifikasi lahan perkebunan terutama tanaman sawit sangat mempengaruhi kelestarian lingkungan. Sehingga diperlukan tindakan penanggulangan dini dengan menganalisa erosi dari lahan perkebunan sawit dengan menggunakan metode USLE.
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Wang, Ai Juan, and Zhi Guang Li. "Spatial Distribution of Soil Erodibility in Upper Yangtze River Region." Advanced Materials Research 610-613 (December 2012): 2944–47. http://dx.doi.org/10.4028/www.scientific.net/amr.610-613.2944.
Full textAbstract:
Soil erodibility is the K factor in the universal soil loss equation (USLE). It is generally characterized through soil physical properties-based indices. The soil erodibility of the Upper Yangtze River basin was determined by the national second soil survey data of China. The results shown that the formula calculated K in USLE model has its limitation in the area when the soil organic matter content is bigger than 12 %. An updating relation was developed by 26 sample points’ properties data. The mean value of soil erodibility in study area is 0.0344, and the biggest value distributed in Sichan basin due to the influence of terrain. Soil erodibility in the study area distributes evenly.
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Silva, Ana Clara Alves, Hugo José Ribeiro, Gustavo Rodrigues dos Santos, and Kátia Alcione Kopp. "ANÁLISE TEMPORAL DA SUSCETIBILIDADE DO ENTORNO DO PARQUE NACIONAL DA CHAPADA DOS VEADEIROS – GOIÁS." Geoambiente On-line, no. 37 (July 13, 2020): 261–81. http://dx.doi.org/10.5216/revgeoamb.vi37.64070.
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O Parque Nacional da Chapada dos Veadeiros (PNCV), considerado uma das unidades mais importantes do mundo, encontra-se no Cerrado brasileiro, o segundo bioma que mais sofre alterações devido à ocupação humana. A Equação Universal de Perdas de Solo (USLE) permite estimar a perda média anual de solo por erosão laminar considerando fatores naturais e antrópicos, tornando possível identificar áreas suscetíveis. Para este estudo verificou-se o nível de suscetibilidade ambiental no PNCV através de análises do uso e ocupação do solo e da perda de solos, aplicando-se a USLE via Sistemas de Informações Geográficas (SIG). Através da álgebra de mapas utilizando softwares de geoprocessamento obteve-se os resultados da USLE cujos valores médios de perda de solo, para o período os anos de 2000 a 2017, correspondem a uma diminuição de aproximadamente 1 tonelada para o interior do parque, enquanto na região do entorno da unidade tais perdas evoluíram cerca de 0,3 toneladas. Realizou-se análises temporais de uso e cobertura do solo por meio de dados do MapBiomas, os resultados apontam um aumento das áreas destinadas à agropecuária e espaço urbano consolidado de 3%, ao passo que para o interior do Parque as áreas destinadas aos mesmos usos diminuíram aproximadamente 4%.
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Hariyanto, Rendika Dwi, Tricahyono Nur Harsono, and Fadiarman Fadiarman. "Prediksi Laju Erosi Menggunakan Metode USLE (Universal Soil Loss Equation) Di Desa Karang Tengah Kecamatan Babakan Madang Kabupaten Bogor." Jurnal Geografi, Edukasi dan Lingkungan (JGEL) 3, no. 1 (July 30, 2019): 31. http://dx.doi.org/10.29405/jgel.v3i1.3580.
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Penelitian dilakukan di Desa Karang Tengah, Kecamatan Babakan Madang, Kabupaten Bogor yang memiliki morfologi beragam, mulai dari daerah dataran rendah sampai pegunungan dengan ketinggian mencapai 800 mdpl. Wilyah penelitian memiliki kelerengan dari miring sampai curam yang sangat berpotensi untuk terjadinya erosi, dan ditambah dengan adanya perubahan penggunaan lahan yang intensif dari area hijau ke pertanian. Untuk itu, tujuan penelitian untuk memprediksikan besarnya laju erosi di wilayah penelitian menggunakan Metode USLE. Jenis penelitian ini adalah penelitian survey dengan deskriptif. Populasi dalam penelitian ini adalah seluruh lahan di wilayah penelitian dengan sampel adalah lahan yang diambil berdasarkan data kemiringan lereng, penggunaan lahan, dan jenis tanah. Penetapan lokasi sampling menggunakan area sampling, sedangkan analisa hasil data menggunakan metode USLE (Universal Loss Soil Equation) yaitu memberi skor pada setiap parameter lahan, sehingga diperoleh klasifikasi bahaya erosi berdasarkan perhitungan menggunakan metode USLE. Hasil penelitian diketahui bahwa lahan di wilayah penelitian mempunyai klasifikasi bahaya erosi sangat ringan pada satuan lahan PLL meliputi wilayah Dusun Wangun bagian Utara, satuan lahan SLL meliputi wilayah Dusun Wangun bagian Timur, dan satuan lahan HLM di wilayah Dusun Wangun bagian Barat. Satuan lahan yang memiliki bahaya erosi ringan yaitu satuan lahan PkLL diwilayah Dusun Wangun bagian Selatan dan Dusun Tegalluhur bagian Utara, dan satuan lahan yang memiliki bahaya erosi sedang yaitu satuan lahan HLAm.
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Hariyanto, Rendika Dwi, Tricahyono Nur Harsono, and Fadiarman Fadiarman. "Prediksi Laju Erosi Menggunakan Metode USLE (Universal Soil Loss Equation) Di Desa Karang Tengah Kecamatan Babakan Madang Kabupaten Bogor." Jurnal Geografi, Edukasi dan Lingkungan (JGEL) 3, no. 2 (July 30, 2019): 92. http://dx.doi.org/10.29405/jgel.v3i2.3580.
Full textAbstract:
Penelitian dilakukan di Desa Karang Tengah, Kecamatan Babakan Madang, Kabupaten Bogor yang memiliki morfologi beragam, mulai dari daerah dataran rendah sampai pegunungan dengan ketinggian mencapai 800 mdpl. Wilyah penelitian memiliki kelerengan dari miring sampai curam yang sangat berpotensi untuk terjadinya erosi, dan ditambah dengan adanya perubahan penggunaan lahan yang intensif dari area hijau ke pertanian. Untuk itu, tujuan penelitian untuk memprediksikan besarnya laju erosi di wilayah penelitian menggunakan Metode USLE. Jenis penelitian ini adalah penelitian survey dengan deskriptif. Populasi dalam penelitian ini adalah seluruh lahan di wilayah penelitian dengan sampel adalah lahan yang diambil berdasarkan data kemiringan lereng, penggunaan lahan, dan jenis tanah. Penetapan lokasi sampling menggunakan area sampling, sedangkan analisa hasil data menggunakan metode USLE (Universal Loss Soil Equation) yaitu memberi skor pada setiap parameter lahan, sehingga diperoleh klasifikasi bahaya erosi berdasarkan perhitungan menggunakan metode USLE. Hasil penelitian diketahui bahwa lahan di wilayah penelitian mempunyai klasifikasi bahaya erosi sangat ringan pada satuan lahan PLL meliputi wilayah Dusun Wangun bagian Utara, satuan lahan SLL meliputi wilayah Dusun Wangun bagian Timur, dan satuan lahan HLM di wilayah Dusun Wangun bagian Barat. Satuan lahan yang memiliki bahaya erosi ringan yaitu satuan lahan PkLL diwilayah Dusun Wangun bagian Selatan dan Dusun Tegalluhur bagian Utara, dan satuan lahan yang memiliki bahaya erosi sedang yaitu satuan lahan HLAm.
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Rejman, Jerzy, Ryszard Brodowski, and Iwona Iglik. "Annual variations of soil erodibility of silt loam developed from loess based on 10-years runoff plot studies." Annals of Warsaw University of Life Sciences - SGGW. Land Reclamation 39, no. 1 (January 1, 2008): 77–83. http://dx.doi.org/10.2478/v10060-008-0007-4.
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Annual variations of soil erodibility of silt loam developed from loess based on 10-years runoff plot studies Results of 10-years runoff plot experiments carried out on two sites of the Lublin Upland were presented. Despite similar soils and climatic conditions, studies showed large differences in annual soil erodibility (K factor of the USLE) between both sites. Experimentally derived values of the factor were dependent on tillage direction and time of maintaining runoff-plots in fallow conditions. On a site cultivated in contour direction, 4-year period was insufficient to achieve K values similar to the predicted values from the USLE. In contrast to this, on a site cultivated up-down slope, similar experimental and predicted K values were obtained after 2 years and remained at the same level during next 4 years. Results enabled to identify limitations of the USLE application for erosion prediction in Poland. Studies proved that soil erodibility could be used for prediction of erosion risk for silt loam developed from loess. However, application of soil erodibility approach to the event-base models is questionable for variation of K factor in the initial years. As far, the factors affecting soil erodibility changes are not recognized and need further research.
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Mejía-Marcacuzco, Jesús, Edwin Pino-Vargas, Edilberto Guevara-Pérez, Víctor Olivos-Alvites, and Milagros Condori-Ventura. "Predicción espacial de la erosión del suelo en zonas áridas mediante teledetección. Estudio de caso: Quebrada del Diablo, Tacna, Perú." Revista Ingeniería UC 28, no. 2 (September 1, 2021): 252–64. http://dx.doi.org/10.54139/revinguc.v28i2.24.
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La presente investigación trata sobre la evaluación de la erosión hídrica del suelo en una zona árida de la región Tacna al sur de Perú, tomando como caso de estudio la Quebrada del Diablo. Se usaron los modelos USLE (Universal Soil Loss Equation) y RUSLE (Revised Universal Soil Loss Equation) en conexión con sistemas geográficos de información (GIS) y técnicas de teledetección. Los factores R, K, LS, C y P de los modelos fueron calculados a partir de información pluviométrica local registrada en tres estaciones y de datos provenientes de sensores remotos integrados mediante el GIS, obteniendo así una simple y efectiva herramienta para determinar mapas, áreas y tasas de erosión. Los resultados indican que la máxima tasa de erosión hídrica, debido a la precipitación extraordinaria ocurrida el año 2020, calculada mediante ambos modelos, varía de 0 a 50 t/ha/año, variación considerada en el rango bajo, ligero y moderado. Los modelos USLE y RUSLE arrojan un potencial de erosión menor a 10 t/ha/año para el 71,81 % y el 45,27 % del área de estudio, respectivamente; para tazas de erosión mayores a 10 t/ha/año las áreas calculadas con el modelo RUSLE superan a los estimados con el modelo USLE.
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Robbany, Achmad Zakky, Dhea Sarah Setyorini, Aldino Maulana Riski, and Santhi Widyastuti. "Analisis Karakteristik dan Potensi Tingkat Erosi Daerah Aliran Sungai Blorong Kabupaten Kendal Tahun 2013 dan 2018 Menggunakan Sistem Informasi Geografis dan Pendekatan Universal Soil Lost Equation (USLE)." Jurnal Geosains dan Teknologi 3, no. 2 (July 28, 2020): 63–72. http://dx.doi.org/10.14710/jgt.3.2.2020.63-72.
Full textAbstract:
Peningkatan penduduk yang pesat mengakibatkan suatu daerah terus berkembang, salah satunya yaitu berada di Daerah Aliran Sungai (DAS) Blorong. DAS Blorong dengan luas area 208,20 km2 merupakan salah satu sub DAS bagian timur dari DAS Bodri-Kuto yang berada di kabupaten Semarang dan kabupaten Kendal. Penelitian memiliki tujuan untuk mengetahui karakteristik dan tingkat erosi di DAS Blorong. Metode yang digunakan untuk menghitung tingkat erosi di DAS Blorong yaitu menggunakan USLE (Universal Soil Loss Equation). Metode USLE yang dilakukan dengan Sistem Informasi Geografis (SIG) dengan mencari faktor-faktor untuk mendapatkan nilai USLE tersebut, beserta menganalisa karakteristik DAS dari data digital elevation model (DEM), peta tata guna lahan, peta geologi, dan curah hujan (tahun 2013 dan 2018). Pada DAS Blorong ditentukan karaktersitiknya berdasarkan hulu dan hilir dari DAS tersebut. Tingkat erosi yang terdapat pada DAS Blorong ditinjau dari tata guna lahan di DAS tersebut. Tingkat erosi di DAS Blorong pada tahun 2013 hingga 2018 terjadi peningkatan sebesar 10,78%, dari 852,236,26 ton/Ha/tahun menjadi 944.037,79 ton/Ha/tahun. Berdasarkan identifikasi dan perhitungan, menunjukkan bahwa curah hujan dan perubahan lahan pemukiman, agrikultur, dan ladang merupakan penyumbang terbesar erosi. Rekomendasi yang dapat dilakukan untuk meminimalisir potensi erosi adalah berupa upaya konservasi pada wilayah ini.