998 resultados para USLE model


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La erosión hídrica en España es un problema grave, por las consecuencias que comporta en términos de pérdida del recurso suelo, sobre el que se sustenta la vida. Desde la década de los años ochenta del pasado siglo, la Administración Central ha realizado dos inventarios de erosión del suelo a nivel nacional: Los Mapas de Estados Erosivos (MEEs) y el Inventario Nacional de Erosión del Suelo (INES). En la presente Tesis Doctoral se han abordado las siguientes cuestiones: - Se ha profundizado en el análisis y aplicación de nuevas herramientas en la estimación del factor topográfico y del factor vegetación, que intervienen en los modelos de cálculo de las pérdidas de suelo, para mejorar la precisión en los resultados de la estimación de las tasas de erosión con los mismos. - Se ha establecido un procedimiento que permita realizar un inventario continuo de los Estados Erosivos de España, fijando como premisa el tiempo para su actualización. La Tesis desarrolla un procedimiento que permite comprobar que, la precisión utilizada en la cartografía base para determinar el factor vegetación y el factor topográfico del modelo USLE, influye en los resultados de la estimación de las tasas de erosión. También se ha realizado un estudio multi-temporal, analizado cuatro períodos: desde 1982 a 2014, con el fin de investigar las posibilidades de implementar un inventario continuo de los Estados Erosivos a nivel nacional; utilizando sensores remotos y técnicas de teledetección como herramienta para la actualización de los usos del suelo, factor determinante para estudiar la evolución de las tasas de erosión a lo largo del tiempo. Los resultados obtenidos de las investigaciones mencionadas, se han aplicado al tramo medio de la cuenca del río Jarama en la provincia de Guadalajara y han permitido comprobar que, la precisión de los datos utilizados en la aplicación del modelo USLE, influyen de una forma determinante en la estimación de las tasas de erosión y, además, hacen posible que la metodología, propuesta en esta Tesis, contribuya a establecer un inventario continuo de la evolución de los Estados Erosivos en un espacio multitemporal y a nivel de escenarios que abarcan una gran superficie. Gracias a este inventario se ha podido aportar información de la evolución de la cubierta vegetal y las pérdidas de suelo en la zona de estudio en el período analizado 1984-2015. ABSTRACT Water erosion in Spain is a serious problem and the consequences in terms of loss of soil resources on which life is based. Since the early eighties of last century, the central government has made two inventories of soil erosion nationwide: Maps of Erosive States (MEES) and the National Inventory of Soil Erosion (INES). In this Doctoral Thesis we have addressed the following issues: - It has deepened in the analysis and implementation of new tools in estimating the topographic factor and vegetation factor involved in the calculation models of soil loss, to improve accuracy in the results of the estimation of rates erosion therewith. - It has established a procedure allowing a continuous inventory of Erosion States of Spain, setting premised time for update. The thesis develops a method that allows to check that the precision used in the base map to determine the vegetation factor and topographical factor USLE model, influences the results of estimating erosion rates. There has also develop a multi-temporal study analyzed four periods: from 1982-2014, in order to investigate the possibilities of implementing a continuous inventory of erosion states at national level; using remote sensing techniques as a tool for updating land use, determining to study the evolution of erosion rates along the time factor. The results of the investigations referred to, have been applied to area around the middle reach of the Jarama river basin in the province of Guadalajara and would have shown that the accuracy of the data used in the model application USLE influence of decisive way estimating erosion rates and also make it possible that the methodology proposed in this thesis, help establish a continuous inventory of the evolution of erosive states in a multi-temporal space and level scenarios covering a large area. Thanks to this inventory was it able to provide information on the evolution of the vegetation cover and soil loss in the study area in the analyzed period 1984-2015.

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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 (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Accelerated soil erosion is, at present, one of the most widespread environmental problems in the world. Geographic Information Systems (GIS) have become an essential tool in soil erosion studies and consequently in the development of appropriate soil conservation strategies. The objective of this paper was to assess the degree of soil erosion associated with land cover dynamics through GIS analysis and to validate the modeling with indicators of soil erosion. Universal Soil Loss Equation (USLE) model, GIS technology and ground-truth dataset (erosion indicators) were employed to elaborate the soil loss maps for four dates at Sorocaba Municipality (SP, Brazil). It was verified that, although the predicted soil loss rate is normally small along the study area, such rate is significantly greater than the soil formation rate. This shows a non-sustainable situation of soil and land cover management. Unplanned urban expansion seems be the main driving force that acts in increasing the erosion risk/occurrence along the study area.

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Soil erosion is a natural process that occurs when the force of wind, raindrops or running water on the soil surface exceeds the cohesive forces that bind the soil together. In general, vegetation cover protects the soil from the effects of these erosive forces. However, land management activities such as ploughing, burning or heavy grazing may disturb this protective layer, exposing the underlying soil. The decision making process in rural catchment management is often supported by the predictive modelling of soil erosion and sediment transport processes within the catchment, using established techniques such as the Universal Soil Loss Equation [USLE] and the Agricultural Nonpoint Source pollution model [AGNPS]. In this article, the authors examine the range of erosion models currently available and describe the application of one of these to the Burrishoole catchment on the north-west coast of Ireland, which has suffered heavy erosion of blanket peat in recent years.

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Soil erosion is a naturally occurring process that involves the detachment, transport, and deposition of soil particles. Disturbances such as thinning and wildfire can reduce cover greatly and increase erosion rates. Forest managers may use erosion prediction tools, such as the Universal Soil Loss Equation (USLE) and Water Erosion Prediction Project (WEPP) to estimate erosion rates and develop techniques to manage erosion. However, it is important to understand the differences and the applications of each model. Erosion rates were generated by each model and the model most applicable to the study site, Los Alamos, New Mexico was determined. It was also used to find the amount of cover needed to stabilize soil. The USLE is a simpler model and less complicated than a computer model like WEPP, and thus easier to manipulate to estimate cover values. Predicted cover values were compared to field cover values. Cover is necessary to establish effective erosion control guidelines.

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Soil erosion is one of the most pressing issues facing developing countries. The need for soil erosion assessment is paramount as a successful and productive agricultural base is necessary for economic growth and stability. In Ghana, a country with an expanding population and high potential for economic growth, agriculture is an important resource; however, most of the crop production is restricted to low technology shifting cultivation agriculture. The high intensity seasonal rainfall coincides with the early growing period of many of the crops meaning that plots are very susceptible to erosion, especially on steep sided valleys in the region south of Lake Volta. This research investigated the processes of soil erosion by rainfall with the aim of producing a sediment yield model for a small semi-agricultural catchment in rural Ghana. Various types of modelling techniques were considered to discover those most applicable to the sub-tropical environment of Southern Ghana. Once an appropriate model had been developed and calibrated, the aim was to look at how to enable the scaling up of the model using sub-catchments to calculate sedimentation rates of Lake Volta. An experimental catchment was located in Ghana, south west of Lake Volta, where data on rainstorms and the associated streamflow, sediment loads and soil data (moisture content, classification and particle size distribution) was collected to calibrate the model. Additional data was obtained from the Soil Research Institute in Ghana to explore calibration of the Universal Soil Loss Equation (USLE, Wischmeier and Smith, 1978) for Ghanaian soils and environment. It was shown that the USLE could be successfully converted to provide meaningful soil loss estimates in the Ghanaian environment. However, due to experimental difficulties, the proposed theory and methodology of the sediment yield model could only be tested in principle. Future work may include validation of the model and subsequent scaling up to estimate sedimentation rates in Lake Volta.

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Fleck and Johnson (Int. J. Mech. Sci. 29 (1987) 507) and Fleck et al. (Proc. Inst. Mech. Eng. 206 (1992) 119) have developed foil rolling models which allow for large deformations in the roll profile, including the possibility that the rolls flatten completely. However, these models require computationally expensive iterative solution techniques. A new approach to the approximate solution of the Fleck et al. (1992) Influence Function Model has been developed using both analytic and approximation techniques. The numerical difficulties arising from solving an integral equation in the flattened region have been reduced by applying an Inverse Hilbert Transform to get an analytic expression for the pressure. The method described in this paper is applicable to cases where there is or there is not a flat region.