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Journal articles on the topic 'Equation Universal Soil Loss'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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1

B. Yu. "ACOMPARISON OF THE R-FACTOR IN THE UNIVERSAL SOIL LOSS EQUATION AND REVISED UNIVERSAL SOIL LOSS EQUATION." Transactions of the ASAE 42, no. 6 (1999): 1615–20. http://dx.doi.org/10.13031/2013.13327.

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2

Erol, A., Ö. Koşkan, and M. A. Başaran. "Socioeconomic modifications of the universal soil loss equation." Solid Earth 6, no. 3 (2015): 1025–35. http://dx.doi.org/10.5194/se-6-1025-2015.

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Abstract. While social scientists have long focused on socioeconomic and demographic factors, physical modelers typically study soil loss using physical factors. In the current environment, it is becoming increasingly important to consider both approaches simultaneously for the conservation of soil and water, and the improvement of land use conditions. This study uses physical and socioeconomic factors to find a coefficient that evaluates the combination of these factors. It aims to determine the effect of socioeconomic factors on soil loss and, in turn, to modify the universal soil loss equat

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3

Risse, L. M., M. A. Nearing, J. M. Laflen, and A. D. Nicks. "Error Assessment in the Universal Soil Loss Equation." Soil Science Society of America Journal 57, no. 3 (1993): 825–33. http://dx.doi.org/10.2136/sssaj1993.03615995005700030032x.

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4

Chandramohan, T., and Dilip G. Durbude. "Estimation of soil erosion potential using Universal Soil Loss Equation." Journal of the Indian Society of Remote Sensing 30, no. 4 (2002): 181–90. http://dx.doi.org/10.1007/bf03000361.

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5

Azaiez, Naima. "Improved Modelling of Soil Loss in El Badalah Basin: Comparing the Performance of the Universal Soil Loss Equation, Revised Universal Soil Loss Equation and Modified Universal Soil Loss Equation Models by Using the Magnetic and Gravimetric Prospection Outcomes." Journal of Geoscience and Environment Protection 09, no. 04 (2021): 50–73. http://dx.doi.org/10.4236/gep.2021.94005.

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6

Effendi Rahim, Supli, Ahmad Affandi Supli, and Nurhayati Damiri. "Soil Loss Prediction on Mobile Platform Using Universal Soil-Loss Equation (USLE) Model." MATEC Web of Conferences 97 (2017): 01066. http://dx.doi.org/10.1051/matecconf/20179701066.

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7

Erol, A., Ö. Koşkan, and M. A. Başaran. "Socio-economic modifications of the Universal Soil Loss Equation." Solid Earth Discussions 7, no. 2 (2015): 1731–59. http://dx.doi.org/10.5194/sed-7-1731-2015.

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Abstract. While social scientists have long focused on socio-economic and demographic factors, physical modelers typically study soil loss using physical factors. In the current environment, it is becoming increasingly important to consider both approaches simultaneously for the conservation of soil and water, and the improvement of land use conditions. This study uses physical and socio-economic factors to find a coefficient that evaluates the combination of these factors. It aims to determine the effect of socio-economic factors on soil loss and, in turn, to modify the Universal Soil Loss Eq

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8

Hood, S. M., S. M. Zedaker,, W. M. Aust, and D. W. Smith. "Universal Soil Loss Equation (USLE)-Predicted Soil Loss for Harvesting Regimes in Appalachian Hardwoods." Northern Journal of Applied Forestry 19, no. 2 (2002): 53–58. http://dx.doi.org/10.1093/njaf/19.2.53.

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Abstract Soil erosion from forest harvesting is a major environmental concern. While there has been research comparing soil erosion on clearcut regeneration harvests with that on uncut forests, there has been little focus on the differences among common silvicultural harvests. Forest certification standards that are currently being evaluated for adoption across the country often encourage uneven-aged systems over even-aged or two-aged systems. We estimated soil loss using the Universal Soil Loss Equation (USLE) for forest land on five harvested treatments in the southern Appalachians. Treatmen

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9

Joshi, Veena, Nilesh Susware, and Debasree Sinha. "Estimating soil loss from a watershed in Western Deccan, India, using Revised Universal Soil Loss Equation." Landscape & Environment 10, no. 1 (2016): 13–25. http://dx.doi.org/10.21120/le/10/1/2.

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USLE (Universal Soil Loss Equation) is the original and the most widely accepted soil loss estimation technique till date which has evolved from a design tool for conservation planning to a research methodology all across the globe. The equation has been revised and modified over the years and became a foundation for several new soil loss models developed all around the world. The equation has been revised as RUSLE by Renard et al. (1991) and is computed in GIS environment. The Revised equation is landuse independent which makes it a useful technique to apply in a variety of environment. The p

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10

Wang, Guangxing, George Gertner, Xianzhong Liu, and Alan Anderson. "Uncertainty assessment of soil erodibility factor for revised universal soil loss equation." CATENA 46, no. 1 (2001): 1–14. http://dx.doi.org/10.1016/s0341-8162(01)00158-8.

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11

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 (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 Los

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12

Kinnell, P. I. A. "Event soil loss, runoff and the Universal Soil Loss Equation family of models: A review." Journal of Hydrology 385, no. 1-4 (2010): 384–97. http://dx.doi.org/10.1016/j.jhydrol.2010.01.024.

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13

Erskine, Wayne D., A. Mahmoudzadeh, C. M. Browning, and C. Myers. "Sediment yields and soil loss rates from different land uses on Triassic shales in western Sydney, NSW." Soil Research 41, no. 1 (2003): 127. http://dx.doi.org/10.1071/sr01078.

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Sedimentation surveys of small dams demonstrate that land use is the dominant factor generating high sediment yields in the ungullied shale catchments of western Sydney where rainfall erosivity and soil erodibility are relatively constant. A single urban catchment produced 6.5 t/ha.year and cropped catchments an average of 6.7 ± 1.99 t/ha.year, whereas grazed woodland/forest and grazed pasture exported averages of only 2.5 ± 0.57 and 2.9 ± 1.02 t/ha.year, respectively. These yields are high by Australian standards and the farm dam sediments are enriched in both clay and phosphorus, in comparis

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14

Sonneveld, B. G. J. S., and M. A. Nearing. "A nonparametric/parametric analysis of the Universal Soil Loss Equation." CATENA 52, no. 1 (2003): 9–21. http://dx.doi.org/10.1016/s0341-8162(02)00150-9.

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15

D. K. McCool, G. R. Foster, C. K. Mutchler, and L. D. Meyer. "Revised Slope Length Factor for the Universal Soil Loss Equation." Transactions of the ASAE 32, no. 5 (1989): 1571–76. http://dx.doi.org/10.13031/2013.31192.

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16

D. K. McCool, L. C. Brown, G. R. Foster, C. K. Mutchler, and L. D. Meyer. "Revised Slope Steepness Factor for the Universal Soil Loss Equation." Transactions of the ASAE 30, no. 5 (1987): 1387–96. http://dx.doi.org/10.13031/2013.30576.

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17

Loch, RJ, and CJ Rosewell. "Laboratory methods for measurement of soil erodibilities (K-factors) for the universal soil loss equation." Soil Research 30, no. 2 (1992): 233. http://dx.doi.org/10.1071/sr9920233.

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This paper reports a comparison of several methods for estimating the K (erodibility) factor for the Universal Soil Loss Equation (USLE) on the basis of laboratory measurements of soil properties. All methods used the nomograph of Wischmeier et al. (J. Soil Water Cons., 1971, 26, 189-93) to calculate K on the basis of laboratory data, but the data inputs ranged from: dispersed particle sizes as originally used in the nomograph; non-dispersed particle size, measured after shaking in water; and equivalent sand size distributions, based on settling velocity distributions of particles (aggregates

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18

Zonunsanga, R. "Estimation of Soil Loss in Teirei Watershed of Mizoram by using Universal Soil Loss Equation Model." Science & Technology Journal 4, no. 1 (2016): 43–47. http://dx.doi.org/10.22232/stj.2016.04.01.06.

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19

Montgomery, J. A., A. J. Busacca, B. E. Frazier, and D. K. McCool. "Evaluating Soil Movement Using Cesium-137 and the Revised Universal Soil Loss Equation." Soil Science Society of America Journal 61, no. 2 (1997): 571. http://dx.doi.org/10.2136/sssaj1997.03615995006100020029x.

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20

Fleming, Kim L., William L. Powers, Alice J. Jones, and Glenn A. Helmers. "Alternative production systems' effects on the K-factor of the Revised Universal Soil Loss Equation." American Journal of Alternative Agriculture 12, no. 2 (1997): 55–58. http://dx.doi.org/10.1017/s0889189300007244.

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AbstractThe soil erodibility factor (K) of the Revised Universal Soil Loss Equation is currently considered a constant for all soils in the same type, regardless of production practice. To examine the effect of alternative production systems on the K-factor we compared pairs of alternatively and conventionally farmed fields on a Judson silt loam (Fine-silty, mixed, mesic Cumulic Hapludolls), a Yutan silty clay loam (Fine-silty, mixed, mesic Mollic Hapludalf), and a Wann fine sandy loam (Coarse-loamy, mixed, mesic Fluvaquentic Haplustolls). Soil cores were taken from the surface 10 cm and analy

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21

Schnitzer, S., F. Seitz, A. Eicker, A. Güntner, M. Wattenbach, and A. Menzel. "Estimation of soil loss by water erosion in the Chinese Loess Plateau using Universal Soil Loss Equation and GRACE." Geophysical Journal International 193, no. 3 (2013): 1283–90. http://dx.doi.org/10.1093/gji/ggt023.

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22

Tavares, André Silva, Velibor Spalevic, Junior Cesar Avanzi, Denismar Alves Nogueira, Marx Leandro Naves Silva, and Ronaldo Luiz Mincato. "Modeling of water erosion by the erosion potential method in a pilot subbasin in southern Minas Gerais." Semina: Ciências Agrárias 40, no. 2 (2019): 555. http://dx.doi.org/10.5433/1679-0359.2019v40n2p555.

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Soil losses due to water erosion threaten the sustainability of agriculture and the food security of current and future generations. This study estimated potential soil losses and sediment production under different types of land uses in a subbasin in the Municipality of Alfenas, southern Minas Gerais, southeastern Brazil. The objective of this research was to evaluate the application of the Potential Erosion Method by the Intensity of Erosion and Drainage program and correlate the findings with the results obtained by the Revised Universal Soil Loss Equation as well as geoprocessing technique

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23

Kadam, Ajaykumar, B. N. Umrikar, and R. N. Sankhua. "Assessment of Soil Loss using Revised Universal Soil Loss Equation (RUSLE): A Remote Sensing and GIS Approach." Remote Sensing of Land 2, no. 1 (2018): 65–75. http://dx.doi.org/10.21523/gcj1.18020105.

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A comprehensive methodology that combines Revised Universal Soil Loss Equation (RUSLE), Remote Sensing data and Geographic Information System (GIS) techniques was used to determine the soil loss vulnerability of an agriculture mountainous watershed in Maharashtra, India. The spatial variation in rate of annual soil loss was obtained by integrating raster derived parameter in GIS environment. The thematic layers such as TRMM [Tropical Rainfall Measuring Mission] derived rainfall erosivity (R), soil erodibility (K), GDEM based slope length and steepness (LS), land cover management (C) and factor

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24

Park, Soyoung, Cheyoung Oh, Seongwoo Jeon, Huicheul Jung, and Chuluong Choi. "Soil erosion risk in Korean watersheds, assessed using the revised universal soil loss equation." Journal of Hydrology 399, no. 3-4 (2011): 263–73. http://dx.doi.org/10.1016/j.jhydrol.2011.01.004.

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25

A.H, Johari, Law P.L., Taib S.N.L., and Yong L.K. "ASSESSMENT OF SOIL EROSION BY SIMULATING RAINFALL ON AN EQUATORIAL ORGANIC SOIL." Journal of Civil Engineering, Science and Technology 8, no. 2 (2017): 72–81. http://dx.doi.org/10.33736/jcest.440.2017.

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Soil erosion occurs on construction sites partly due to site clearing that exposes the land to the erosive power of rainfall. A proposed construction project requires the submission of an Environmental Impact Assessment EIA) to assess the impact of the project on the environment. Assessment of soil erosion is included in the EIA, but the equation to estimate soil erosion known as the Universal Soil Loss Equation (USLE) is only applicable to a soil containing up to four percent organic matter. This limitation of USLE requires an alternative that can predict soil erosion on an organic soil. This

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26

Lu and Chiang. "Assessment of Sediment Transport Functions with the Modified SWAT-Twn Model for a Taiwanese Small Mountainous Watershed." Water 11, no. 9 (2019): 1749. http://dx.doi.org/10.3390/w11091749.

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In Taiwan, the steep landscape and highly vulnerable geology make it difficult to predict soil erosion and sediment transportation via variable transport conditions. In this study, we integrated the Taiwan universal soil loss equation (TUSLE) and slope stability conditions in the soil and water assessment tool (SWAT) as the SWAT-Twn model to improve sediment simulation and assess the sediment transport functions in the Chenyulan watershed, a small mountainous catchment. The results showed that the simulation of streamflow was satisfactory for calibration and validation. Before model calibratio

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27

W. C. Hession, D. E. Storm, and C. T. Haan. "Two-phase Uncertainty Analysis: An Example Using the Universal Soil Loss Equation." Transactions of the ASAE 39, no. 4 (1996): 1309–19. http://dx.doi.org/10.13031/2013.27622.

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28

Kitahara, Hikaru, Yoichi Okura, Toshiaki Sammori, and Akiko Kawanami. "Application of Universal Soil Loss Equation (USLE) to Mountainous Forests in Japan." Journal of Forest Research 5, no. 4 (2000): 231–36. http://dx.doi.org/10.1007/bf02767115.

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29

Falk, M. G., R. J. Denham, and K. L. Mengersen. "Estimating Uncertainty in the Revised Universal Soil Loss Equation via Bayesian Melding." Journal of Agricultural, Biological, and Environmental Statistics 15, no. 1 (2010): 20–37. http://dx.doi.org/10.1007/s13253-009-0005-y.

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30

Di Stefano, Costanza, Vincenzo Pampalone, Francesca Todisco, Lorenzo Vergni, and Vito Ferro. "Testing the Universal Soil Loss Equation‐MB equation in plots in Central and South Italy." Hydrological Processes 33, no. 18 (2019): 2422–33. http://dx.doi.org/10.1002/hyp.13478.

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31

CHOW, T. L., H. CORMIER, J. L. DAIGLE, and I. GHANEM. "EFFECTS OF POTATO CROPPING PRACTICES ON WATER RUNOFF AND SOIL EROSION." Canadian Journal of Soil Science 70, no. 2 (1990): 137–48. http://dx.doi.org/10.4141/cjss90-016.

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Using runoff-erosion plots (10 m wide × 30 m long), the effects of cropping practices on surface runoff and soil loss were examined on a Hommesville gravelly loam soil to evaluate the applicability of the Universal Soil Loss Equation in New Brunswick. The amount of water runoff and soil loss from continuous fallow, up-and-down slope planting of potatoes (Solanum tuberosum), and clover (Trifolium pratense) on 8 and 11% slopes were measured from 1983 to 1985. In addition, runoff and soil loss from contour planting of potatoes were measured on the 11% slope. Slope planting of potatoes resulted in

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32

Y.W., Oon, Chin N.J., and Law P.L. "Soil Erosian and Sediment Yield of a Sanitary Landfill Site - A Case Study." Journal of Civil Engineering, Science and Technology 2, no. 2 (2011): 23–34. http://dx.doi.org/10.33736/jcest.91.2011.

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This research presents the results of a study on soil erosion rates and sediment yields of a proposed Level 4 Sanitary Landfill construction site located in Sibu, Sarawak. Assessments on potential soil erosion rates and sediment yields during pre-construction, construction and operation stages were carried out using the Revised Universal Soil Loss Equation (RUSLE) and Modified Universal Soil Loss Equation (MUSLE), respectively. It was found that soil erosion rates during construction and operation stages fell under "Moderately High" category, whereby highest sediment yield occurred during cons

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33

BARBOSA, A. F., E. F. OLIVEIRA, C. L. MIOTO, and A. C. PARANHOS FILHO. "The Application of the Universal Soil Loss Equation by Using Free and Available Softwares." Anuário do Instituto de Geociências - UFRJ 38, no. 1 (2015): 170. http://dx.doi.org/10.11137/2015_1_170_179.

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34

Auliyani, Diah, and Wahyu Wisnu Wijaya. "PERBANDINGAN PREDIKSI HASIL SEDIMEN MENGGUNAKAN PENDEKATAN MODEL UNIVERSAL SOIL LOSS EQUATION DENGAN PENGUKURAN LANGSUNG (Comparison of sediment yield from prediction using Universal Soil Loss Equation with direct measurement)." Jurnal Penelitian Pengelolaan Daerah Aliran Sungai 1, no. 1 (2017): 61–71. http://dx.doi.org/10.20886/jppdas.2017.1.1.61-71.

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35

Auliyani, Diah, and Wahyu Wisnu Wijaya. "PERBANDINGAN PREDIKSI HASIL SEDIMEN MENGGUNAKAN PENDEKATAN MODEL UNIVERSAL SOIL LOSS EQUATION DENGAN PENGUKURAN LANGSUNG (Comparison of sediment yield from prediction using Universal Soil Loss Equation with direct measurement)." Jurnal Penelitian Pengelolaan Daerah Aliran Sungai 1, no. 1 (2017): 61–71. http://dx.doi.org/10.20886/jppdas.v1i1.2570.g2078.

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36

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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37

Maqsoom, Ahsen, Bilal Aslam, Usman Hassan, et al. "Geospatial Assessment of Soil Erosion Intensity and Sediment Yield Using the Revised Universal Soil Loss Equation (RUSLE) Model." ISPRS International Journal of Geo-Information 9, no. 6 (2020): 356. http://dx.doi.org/10.3390/ijgi9060356.

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Land degradation caused by soil erosion is considered among the most severe problems of the 21stcentury. It poses serious threats to soil fertility, food availability, human health, and the world ecosystem. The purpose of the study is to make a quantitative mapping of soil loss in the Chitral district, Pakistan. For the estimation of soil loss in the study area, the Revised Universal Soil Loss Equation (RUSLE) model was used in combination with Remote Sensing (RS) and Geographic Information System (GIS). Topographical features of the study area show that the area is more vulnerable to soil los

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38

Mohammed, Issamaldin, Hatim Nuh, and Ahmed Abdalla. "Coupling Universal Soil Loss Equation and GIS Techniques for Estimation of Soil Loss and Sediment Yield in Algash Basin." International Journal of Advanced Remote Sensing and GIS 6, no. 1 (2017): 2050–67. http://dx.doi.org/10.23953/cloud.ijarsg.36.

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39

Siddiqui, Saima, Mirza Wajid Ali Safi, Aqil Tariq, Naveed Ur Rehman, and Syed Waseem Haider. "GIS Based Universal Soil Erosion Estimation in District Chakwal Punjab, Pakistan." International Journal of Economic and Environmental Geology 11, no. 2 (2020): 30–36. http://dx.doi.org/10.46660/ijeeg.vol11.iss2.2020.443.

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Soil erosion is a serious environmental problem faced by district Chakwal. Unpredictable short term and high intensity rainfall, improper cultivation and deforestation have accelerated the soil erosion in the district. The agricultural productivity of the study area can be enhanced by understanding, estimating and controlling the root causes of soil erosion. This study was undertaken to estimate and spatially represent the rate of average annual soil erosion in Chakwal using GIS/RS techniques. The soil erosion was estimated using Universal Soil Loss Equation (USLE) model. To find out parameter

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40

Moore, Ian D., and Gordon J. Burch. "Physical Basis of the Length-slope Factor in the Universal Soil Loss Equation." Soil Science Society of America Journal 50, no. 5 (1986): 1294–98. http://dx.doi.org/10.2136/sssaj1986.03615995005000050042x.

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41

Lense, Guilherme Henrique Expedito, Rodrigo Santos Moreira, Taya Cristo Parreiras, Derielsen Brandão Santana, Talyson De Melo Bolelli, and Ronaldo Luiz Mincato. "Water erosion modeling by the Erosion Potential Method and the Revised Universal Soil Loss Equation: a comparative analysis." Ambiente e Agua - An Interdisciplinary Journal of Applied Science 15, no. 4 (2020): 1. http://dx.doi.org/10.4136/ambi-agua.2501.

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Water erosion is the principal degradation process of tropical soils, and its effects can be measured by modeling techniques. Erosion models provide a diagnosis of the soil loss intensity and can support the planning of soil conservation practices. Models with low data requirements, such as the Revised Universal Soil Loss Equation (RUSLE) and, more recently, the Erosion Potential Method (EPM), are mainly applied in Brazil. Thus, the objective of this work was to estimate water erosion soil-loss rates using the EPM and RUSLE models on a tropical subbasin, followed by a comparison of their outco

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42

Posch, Maximilian, and Seppo Rekolainen. "Erosivity factor in the Universal Soil Loss Equation estimated from Finnish rainfall data." Agricultural and Food Science 2, no. 4 (1993): 271–79. http://dx.doi.org/10.23986/afsci.72650.

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Continuous rainfall data recorded for many years at 8 stations in Finland were used to estimate rainfall erosivity, a quantity needed for soil loss predictions with the Universal Soil Loss Equation (USLE). The obtained erosivity values were then used to determine the 2 parameters of a power-law function describing the relationship between daily precipitation and erosivity. This function is of importance in erosion modeling at locations where no breakpoint rainfall data are available. The parameters of the power-law were estimated both by linear regression of the log-transformed data and by non

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43

Ajibade, Fidelis Odedishemi, Nathaniel Azubuike Nwogwu, Bashir Adelodun, et al. "Application of RUSLE integrated with GIS and remote sensing techniques to assess soil erosion in Anambra State, South-Eastern Nigeria." Journal of Water and Climate Change 11, S1 (2020): 407–22. http://dx.doi.org/10.2166/wcc.2020.222.

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Abstract Soil erosion and mass movement processes spread across Anambra State in Nigeria, therefore making management and conservation techniques expensive and difficult in execution across the entire state. This study employed the Revised Universal Soil Loss Equation (RUSLE) model with the integration of geographic information system (GIS) and remote sensing techniques to assess the risk of soil erosion and hotspots in the area. Remotely sensed data such as Landsat 8 imagery, Shuttle Radar Topography Mission (SRTM) imagery, Era-Interim coupled with world soil database were used as digital dat

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44

Purwaamijaya, I. M. "Multi criteria evaluation for universal soil loss equation based on geographic information system." Journal of Physics: Conference Series 1013 (May 2018): 012153. http://dx.doi.org/10.1088/1742-6596/1013/1/012153.

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45

AN, L. S. "GLOBAL SENSITIVITY ANALYSIS OF THE PARAMETERS OF THE MODIFIED UNIVERSAL SOIL LOSS EQUATION." Applied Ecology and Environmental Research 14, no. 4 (2016): 505–14. http://dx.doi.org/10.15666/aeer/1404_505514.

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46

Chen, Shih-Kai, Chen-Wuing Liu, and Yi-Ron Chen. "Assessing soil erosion in a terraced paddy field using experimental measurements and universal soil loss equation." CATENA 95 (August 2012): 131–41. http://dx.doi.org/10.1016/j.catena.2012.02.013.

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47

Diodato, N. "Estimating RUSLE’s rainfall factor in the part of Italy with a Mediterranean rainfall regime." Hydrology and Earth System Sciences 8, no. 1 (2004): 103–7. http://dx.doi.org/10.5194/hess-8-103-2004.

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Abstract. The computation of the erosion index (EI), which is basic to the determination of the rainfall-runoff erosivity factor R of the Revised Universal Soil Loss Equation (RUSLE), is tedious and time-consuming and requires a continuous record of rainfall intensity. In this study, a power equation(r2 = 0.867) involving annual erosion index (EI30-annual) in the Mediterranean part of Italy is obtained. Data from 12 raingauge stations are used to derive and then test a regional relationship for estimating the erosion index from only three rainfall parameters. Erosivity rainfall data derived fr

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48

Noor, Hamze, Seyed Khalagh Mirnia, Somaye Fazli, Mohamad bagher Raisi, and Mahdi Vafakhah. "Application of MUSLE for the prediction of phosphorus losses." Water Science and Technology 62, no. 4 (2010): 809–15. http://dx.doi.org/10.2166/wst.2010.092.

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Soil erosion in forestlands affects not only land productivity but also the water body down stream. The Universal Soil Loss Equation (USLE) has been applied broadly for the prediction of soil loss from upland fields. However, there are few reports concerning the prediction of nutrient (P) losses based on the USLE and its versions. The present study was conducted to evaluate the applicability of the deterministic model Modified Universal Soil Loss Equation (MUSLE) to estimation of phosphorus losses in the Kojor forest watershed, northern Iran. The model was tested and calibrated using accurate

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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

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Papaiordanidis, S., I. Z. Gitas, and T. Katagis. "Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in Google Earth Engine (GEE) cloud-based platform." Dokuchaev Soil Bulletin, no. 100 (January 3, 2020): 36–52. http://dx.doi.org/10.19047/0136-1694-2019-100-36-52.

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High-quality soils are an important resource affecting the quality of life of human societies, as well as terrestrial ecosystems in general. Thus, soil erosion and soil loss are a serious issue that should be managed, in order to conserve both artificial and natural ecosystems. Predicting soil erosion has been a challenge for many years. Traditional field measurements are accurate, but they cannot be applied to large areas easily because of their high cost in time and resources. The last decade, satellite remote sensing and predictive models have been widely used by scientists to predict soil

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