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Selection: with tag usle [23 articles] 

 

(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 42

  
(February 2018)
Keywords: inrmm-list-of-tags   tuscany   tuta-absoluta   twig-dieback   two-dimensional-gas-chromatography   two-stage-peer-review   udig   uganda   ukraine   ulex-europaeus   ulmus-americana   ulmus-carpinifolia   ulmus-glabra   ulmus-laevis   ulmus-minor   ulmus-parvifolia   ulmus-procera   ulmus-pumila   ulmus-rubra   ulmus-spp   ulmus-thomasii   umbellularia-californica   umbrella-species   un-framework-convention-on-climate-change   uncertainty   uncertainty-propagation   underfitting   understorey   understorey-species   undisturbed-habitat   uneven-aged-forest   unexpected-effect   unfalsifiability   ungulate   ungulate-browsing   united-kingdom   united-nations   united-states   universal-approximation   unknown   unrealistic-expectations   unsupervised-training   upper-treeline   uprooting   urban-areas   urban-forest   urban-habitats   urban-trees   urgent-hpc   url-decay   urocerus-gigas   ursus-arctos   usda   ushahidi   usle   usle-m   usped   utilization   vaccination   vaccinium-arctostaphylos   vaccinium-myrtillus   vaccinium-oxycoccos   vaccinium-spp   vaccinium-uliginosum   vaccinium-vitis-idaea   vaccinum-myrtillus   validation   valsa-melanodiscus   values-at-stake   values-vs-scientific-evidence   vapour-pressure-deficit   variability   variable-selection   variance-partitioning   variation   vascular-plants   vascular-system   vauable   vegetation   vegetation-buffer   vegetation-changes   vegetation-composition   vegetation-condition   vegetation-diversity   vegetation-dynamics   vegetation-types   vegetative-propagation   vehicle-detection   veneer   venice   verification-vs-corroboration   veronica-micrantha   veronica-officinalis   vertebrate   verticillium-dahliae   vgi   viburnum-lantana   viburnum-opalus   viburnum-opulus   viburnum-orientale  

Abstract

List of indexed keywords within the transdisciplinary set of domains which relate to the Integrated Natural Resources Modelling and Management (INRMM). In particular, the list of keywords maps the semantic tags in the INRMM Meta-information Database (INRMM-MiD). [\n] The INRMM-MiD records providing this list are accessible by the special tag: inrmm-list-of-tags ( http://mfkp.org/INRMM/tag/inrmm-list-of-tags ). ...

 

Soil erosion modelling

  
In Landform Dynamics and Evolution in Romania (2017), pp. 397-423, https://doi.org/10.1007/978-3-319-32589-7_17

Abstract

Surface soil erosion modelling has benefited and continues to benefit from the progress in information technology area and statistical and mathematical processing of spatial data. In Romania, quantitative studies concerning soil erosion have a tradition of over 70 years, beginning with the establishment of experimental runoff plots. An important step in the history of soil erosion research in Romania is the adaptation of the universal soil loss equation (USLE) to the specific environmental and anthropogenic conditions form our country (ROMSEM). This ...

 

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

  
Journal of Iberian Geology, Vol. 42, No. 1. (07 June 2016), https://doi.org/10.5209/rev_jige.2016.v42.n1.49120

Abstract

The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single ...

 

Comparison between the USLE, the USLE-M and replicate plots to model rainfall erosion on bare fallow areas

  
CATENA, Vol. 145 (October 2016), pp. 39-46, https://doi.org/10.1016/j.catena.2016.05.017

Abstract

[Highlights] [::] Examines ability of soil losses from a plot to predict those from another [::] Stochastic and systemic variations observed when replicate model used [::] Replicate model tends to perform better that USLE-M when runoff known. [Abstract] It has been proposed that the best physical model of erosion from a plot is provided by a replicate plot (Nearing, 1998). Event data from paired bare fallow plots in the USLE database were used to examine the abilities of replicate plots, the USLE and the USLE-M to ...

 

Soil erosion assessment and its verification using the Universal Soil Loss Equation and geographic information system: a case study at Boun, Korea

  
In Environmental Geology, Vol. 45, No. 4. (2004), pp. 457-465, https://doi.org/10.1007/s00254-003-0897-8

Abstract

This study is aimed at the evaluation of the hazard of soil erosion and its verification at Boun, Korea, using a Geographic Information System (GIS) and remote sensing. Precipitation, topographic, soil, and land use data were collected, processed, and constructed into a spatial database using GIS and remote sensing data. Areas that had suffered soil erosion were analysed and mapped using the Universal Soil Loss Equation (USLE). The factors that influence soil erosion are rainfall erosivitiy (R) from the precipitation database, ...

 

Application of Universal Soil Loss Equation (USLE) to mountainous forests in Japan

  
Journal of Forest Research, Vol. 5, No. 4. (2000), pp. 231-236, https://doi.org/10.1007/bf02767115

Abstract

Universal Soil Loss Equation (USLE), originally developed by the USDA for agricultural lands and then used throughout the world, was applied in mountainous forest terrain in Japan. The slope length and steepness factors were extended for long slope lengths and steep slopes by recalculating the data from available literature in Japan and by using data from supplementary erosion experiments. As such, we conclude that the USLE can be used successfully to estimate surface erosion on long, steep mountainous forest slopes. The ...

 

Assessment of soil erosion under woodlands using USLE in China

  
Frontiers of Earth Science, Vol. 5, No. 2. (2011), pp. 150-161, https://doi.org/10.1007/s11707-011-0158-1

Abstract

Universal Soil Loss Equation (USLE), originally developed by the USDA for agricultural lands and then used throughout the world, was applied in mountainous forest terrain in China. The woodland area was divide into 100 m × 100 m grid cells. The ArcInfo 9.2 GIS software provided spatial input data was used to predict the spatial distribution of the average annual soil loss on grid basis. The average rainfall erositivity factor (R) for national woodlands was found to be 21–1798 MJ·mm·ha−1·h−1·a−1. The ...

 

Error Assessment in the Universal Soil Loss Equation

  
Soil Science Society of America Journal, Vol. 57, No. 3. (1993), 825, https://doi.org/10.2136/sssaj1993.03615995005700030032x
Keywords: errors   modelling-uncertainty   usle  

Abstract

Although nearly three decades of widespread use have confirmed the reliability of the Universal Soil Loss Equation (USLE), very little work has been done to assess the error associated with it. This study was conducted to develop a set of statistics that would measure the performance of the USLE. Estimates of soil loss using the USLE were compared with measured values on 208 natural runoff plots, representing >1700 plot years of data, to assess the error associated with the USLE predictions. ...

 

Ideas for physical interpretation of the USLE

  
No. LNS0418027. (2003)

Abstract

[Excerpt: Soil Erosion by Water - Extend, Processes and Model for Conservation Planning] In order to develop sustainable systems of agriculture that satisfy the present and the future needs of the mankind, there must be reliable information on the constrains and potential of the land resource. The UNEP Project GLASOD (GLobal Assessment of SOil Degradation) recognized erosion by water as the most important soil degradation type, representing more than a half of all soil degradation (Oldeman et al., 1991). Soil erosion by water refers to a series of ...

 

Validation of a 3-D enhancement of the Universal Soil Loss Equation for prediction of soil erosion and sediment deposition

  
CATENA, Vol. 64, No. 2-3. (December 2005), pp. 281-296, https://doi.org/10.1016/j.catena.2005.08.010

Abstract

A study was conducted on three U.S. military training areas to validate the Unit Stream Power Erosion and Deposition (USPED) model, a 3-dimensional enhancement to the Universal Soil Loss Equation (USLE). The USPED model differs from other USLE-based models in the manner in which it handles the influence of topography on the erosion process. As a result, the USPED model predicts both erosion and deposition, while most other USLE-based models are limited to predictions of erosion only. Erosion and deposition from ...

 

Sediment-yield prediction with Universal Equation using runoff energy factor

  
In Present and Prospective Technology for Predicting Sediment Yield and Sources, Vol. ARS-S-40 (1975), pp. 244-252
Keywords: energy   modelling   runoff   sediment-yield   usle  

Abstract

[Excerpt] The universal soil loss equation was developed for predicting field soil loss as a guide to conservation farm planning, but it can be used to predict sediment yield from watersheds when a delivery ratio is applied. Delivery ratios (the sediment yield at any point along a channel divided by the source erosion above that point) have been computed for some physiographic areas and related to watershed characteristics. However, the few areas studied represent only a small portion of the United ...

 

A rainfall erosion index for a Universal Soil-Loss Equation

  
Soil Science Society of America Journal, Vol. 23, No. 3. (1959), 246, https://doi.org/10.2136/sssaj1959.03615995002300030027x

Abstract

Extensive regression analyses of basic soil-loss data were designed to determine the best indicator of the capacity of a storm to erode soil. The rainstorm characteristic found to be outstanding as such an indicator is the variable whose value is the product of the rainfall energy and maximum 30-minute intensity of the storm (designated as EI). This variable explained from 72 to 97% of the variation in individual-storm erosion from tilled continuous fallow on 6 soils. Seasonal rainfall erosion index values ...

 

Estimation of the USLE cover and management factor C using satellite remote sensing: A review

  
In Geoinformatics, 2011 19th International Conference on (June 2011), pp. 1-5, https://doi.org/10.1109/geoinformatics.2011.5980735
Keywords: c-factor   remote-sensing   review   usle  

Abstract

Soil erosion has been one of the worldwide environmental disasters which severely threaten the sustainable development of socio-economic, natural resources, and the environment. The Universal Soil Loss Equation (USLE) is the most widely used model to quantify soil erosion. The cover and management factor C is perhaps the most important USLE factor because it represents conditions that can most easily be managed to reduce erosion. Satellite remote sensing can contribute through providing spatial data to assessment of C factor. Thus, many ...

 

Soil erosion assessment of Slovakia at a regional scale using GIS

  
Ecology (Bratislava), Vol. 21, No. 4. (2002), pp. 404-422
Keywords: clc   gis   slovakia   soil-erosion   soil-resources   usle  

Abstract

The study presents an assessment of potential and actual soil erosion at a regional scale (1:500 000) covering the whole area of Slovakia (49 030 km2) by the GIS data integration and analysis. Potential soil erosion indicates the inherent susceptibility of land to erosion irrespective of contemporary existing land cover/management. Actual soil erosion refers to estimated contemporary erosion, taking into account the land cover and management practices that modify potential erosion. The calculation is based on principles defined in the Universal ...

 

Erodibility Indices Compared to Measured Values of Selected Trinidad Soils

  
Soil Science Society of America Journal, Vol. 46, No. 2. (1982), 393, https://doi.org/10.2136/sssaj1982.03615995004600020037x

Abstract

The most suitable erodibility index for tropical soils has not been determined. This study was therefore carried out with 10 selected Trinidad soils to compare three erodibility indices previously used with soils in different parts of the world. The erodibility of the soils was determined by the USDA Erodibility Nomograph, the Australian Erodibility Index, and the Modified Raindrop Technique and their suitability evaluated by comparison with the erodibility measured directly on four of the 10 soil types in the field. The USDA ...

 

Soil erodibility and its estimation for agricultural soils in China

  
Journal of Arid Environments, Vol. 72, No. 6. (June 2008), pp. 1002-1011, https://doi.org/10.1016/j.jaridenv.2007.11.018

Abstract

Soil erodibility (the K factor in the Universal Soil Loss Equation, USLE) is an important index to measure soil susceptibility to water erosion, and an essential parameter needed for soil erosion prediction. To evaluate the appropriateness of the nomograph and other methods for estimating the K factor for the USLE and to develop a relationship for soil erodibility estimation for Chinese soils, a set of soil erodibility values was calculated using soil loss data from natural runoff plots at 13 sites ...

 

Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed, Nan Province, Thailand

  
Environmental Geology In Environmental Geology, Vol. 57, No. 3. (2009), pp. 695-705, https://doi.org/10.1007/s00254-008-1348-3

Abstract

Land degradation is still a very common problem in the mountains of Asia because of inappropriate land use practice in steep topography. Many studies have been carried out to map shifting cultivation and areas susceptible to soil erosion. Mostly, estimated soil loss is taken as the basis to classify the level of soil loss susceptibility of area. Factors that influence soil erosion are: rainfall erosivity, soil erodibility, slope length and steepness, crop management and conservation practices. Thus the reliability of estimated ...

 

Use and misuse of the K factor equation in soil erosion modeling: An alternative equation for determining USLE nomograph soil erodibility values

  

Abstract

The K factor of the Universal Soil Loss Equation is the most important measure of soil erodibility that was adopted in many erosion models. The K factor can be estimated from simple soil properties by a nomograph. Later, the classical K factor equation was published to assist the calculation of K. This equation, however, does not fully agree with the nomograph, which still has to be used in these deviating cases. Here we show for a large soil data set from ...

 

Event soil loss, runoff and the Universal Soil Loss Equation family of models: a review

  
Journal of Hydrology, Vol. 385, No. 1-4. (07 May 2010), pp. 384-397, https://doi.org/10.1016/j.jhydrol.2010.01.024

Abstract

The Universal Soil Loss Equation (USLE) is the most widely used and misused prediction equation in the world. Although it was designed to predict long-term average annual soil loss, it has the capacity to predict event soil losses reasonably well at some geographic locations and not well at others. Its lack of capacity to predict event erosion is highly influenced by the fact the event rainfall–runoff factor used in the USLE and its revisions (RUSLE, RUSLE2) does not consider runoff explicitly. ...

 

A high-resolution soil erosion risk map of Switzerland as strategic policy support system

  
Land Use Policy, Vol. 32 (May 2013), pp. 281-291, https://doi.org/10.1016/j.landusepol.2012.11.006

Abstract

Soil erosion models and soil erosion risk maps are often used as indicators to assess potential soil erosion in order to assist policy decisions. This paper shows the scientific basis of the soil erosion risk map of Switzerland and its application in policy and practice. Linking a USLE/RUSLE-based model approach (AVErosion) founded on multiple flow algorithms and the unit contributing area concept with an extremely precise and high-resolution digital terrain model (2 m × 2 m grid) using GIS allows for a realistic assessment of ...

 

Soil erosion and sediment yield prediction accuracy using WEPP

  
Journal of the American Water Resources Association, Vol. 40, No. 2. (April 2004), pp. 289-297, https://doi.org/10.1111/j.1752-1688.2004.tb01029.x
Keywords: erodibility   precipitation   soil-erosion   storm   usle   wepp  

Abstract

The objectives of this paper are to discuss expectations for the Water Erosion Prediction Project (WEPP) accuracy, to review published studies related to WEPP goodness of fit, and to evaluate these in the context of expectations for WEPP's goodness of fit. WEPP model erosion predictions have been compared in numerous studies to observed values for soil loss and sediment delivery from cropland plots, forest roads, irrigated lands and small watersheds. A number of different techniques for evaluating WEPP have been used, ...

 

Deducing the USLE mathematical structure by dimensional analysis and self-similarity theory

  
Biosystems Engineering, Vol. 106, No. 2. (15 June 2010), pp. 216-220, https://doi.org/10.1016/j.biosystemseng.2010.03.006

Abstract

The Universal Soil Loss Equation (USLE) was originally deduced by a statistical analysis of a large data set of soil loss measurements. The multiplicative structure of the model has been criticised due to the considerable interdependence between the variables. Using the soil erosion representative variables and the reference condition adopted in the USLE, the aim of this paper was to apply dimensional analysis and self-similarity theory to deduce the functional relationship among the selected variables. The analysis yielded a multiplicative equation, ...

 

Modelling soil erosion using the Universal Soil Loss Equation and a geographic information system: the Kinnarasani river watershed, Andhra Pradesh, India

  
(2007)
Keywords: gis   india   land-cover   modelling   soil-erosion   soil-resources   usle  

Abstract

Soil erosion is a global problem, with grave consequences for the environment, human society and the economy. It is possible to identify areas with a high risk of soil erosion using computer models and Geographic Information Systems (GIS). This study models soil erosion on the Kinnarasani river’s watershed, in semi arid tropical India. It uses the Universal Soil Loss Equation (USLE) and establishes the different parameters using mostly freely accessible data. The results are verified visually in the field. Perspectives for ...

This page of the database may be cited as:
Integrated Natural Resources Modelling and Management - Meta-information Database. http://mfkp.org/INRMM/tag/usle

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Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
The library of INRMM related pubblications may be quickly accessed with the following links.
Search within the whole INRMM meta-information database:
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Full-text and abstracts of the publications indexed by the INRMM meta-information database are copyrighted by the respective publishers/authors. They are subject to all applicable copyright protection. The conditions of use of each indexed publication is defined by its copyright owner. Please, be aware that the indexed meta-information entirely relies on voluntary work and constitutes a quite incomplete and not homogeneous work-in-progress.
INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.