DEGRADACIÓN POR EROSIÓN HÍDRICA Erosión Hídrica ¿QUE ES? Bibliografía %C3%B3n_h%C3%. EROSION “Erosion es un proceso de movilización y transporte de partículas por agentes erosivos.” Ellison, Agentes erosivos Impacto de gotas de lluvia. La erosion hidrica de los suelos. Causas y remedios. D’Onofrio, G. Lietaert, F. Perez, C. FAO, Rome (Italy). Direccion de Fomento de Tierras y AguasMinisterio .
|Published (Last):||17 December 2011|
|PDF File Size:||17.84 Mb|
|ePub File Size:||4.23 Mb|
|Price:||Free* [*Free Regsitration Required]|
Soil erosion can be accelerated by agricultural intensification, and the soil loss can alter the quality of water bodies. Sustainable agricultural production therefore requires the management of erosion and potential water pollution.
In Uruguay, where there is heavy use of soil for agriculture, there is a need to continually develop and update erosion management policies. The results include the following values: The drainage basin characteristics allowed the identification of 4 homogeneous regions based on their erosion behavior.
The northern-western-southern basins cluster and Sierras del Este basins clusters indicate the possibility of managing their erosion through control of vegetation cover, which is represented by the C-factor.
In general, this forecast of soil erosion by water Los resultados incluyen los siguientes valores: Over hirrica past 10 yr, Uruguay has developed important land use changes, one of the most important being the expansion and intensification of its agriculture production of grains soybeans, wheat, sorghumfromha in to 1. These land cover changes had the potential of promoting fresh water pollution with run-off sediments.
Potential environmental impacts seemed to be under control until Situations became more complex when Carrasco-Letelier et al. In this framework, it is now understood that freshwater protection actions have been insufficient and that there are not enough tools for the identification and the forecast of potential water pollution situations at basin scale.
There are several international studies focused in the estimation of soil erosion by water at regional scale in which the USLE was used through a geographic information system GIS Kouli et al, ; Farhan et al, ; Panagos et al, ; Medeiros et al.
By multiplicative operation of these geo-referenced information, the mean annual soil erosion by water per land use and egosion mean annual soil erosion of basin by area-weight, can be obtained.
These basins were delineated by applying the r. However, this automatic definition of basin polygons was later confirmed or modified manually depending on the position chose to water sampling by Project INIA Sa27 to help in the development of a model for freshwater pollution Figure 1. Watersheds are denoted by blue polygons with black erosioj and departments are delineated by red lines.
The estimation of soil loss was estimated by the multiplicative product of the all factors in the model Eq. The rainfall erosivity factor information was incorporated into the GIS by creating a raster file using the isoerodents of Uruguay Puentes and Szogi, and the R-factor used by Erosion 6.
The raster layer was built by interpolation with a triangular model, using the rasterization tool of the QGIS program QGIS Development Team,in which it was specified that the raster file contained 10, columns and 10, rows. For this study, we used the Beretta-Blanco and Carrasco-Letelier ‘s K-factors, based on the K values assigned by Puentes for 99 modal soils. The K-factor information was handled at a scale of 1: The slope gradient factor S-factor expressed in degrees, radians and percent was estimated by applying the second-degree polygons with free GIS software gvSIG www.
The results were used to generate a raster layer of slope gradients expressed in percent. Subsequently, a mean slope gradient was assigned to each polygon of study zone using the Polygon grid tool of free GIS software gvSIG www.
The slope length factor L-factor was calculated using the function proposed by McCool et al. The C-factors allocated for each crop management are listed in Table 1. These C-factors correspond to a time-weighted C-factor of each land use of every crop rotation scheme.
The erosion control practice factor P-factor in this study was assumed to be equal to 1 because management practices that reduce erosion are not frequently used in Uruguay. The basins were analyzed by a cluster analysis for definition of homogeneous regions, and in each cluster, the factors that contribute in an important manner in the erosion process was determined. For this last analysis, a regression adjustment was done using the stepwise procedure Zar, The average values of the factors in each cluster were compared using the Tukey statistic, and differences were considered significant if p was less than 0.
The incorporation of the different information layers to GIS generate some results that will describe in the next paragraphs. Information layer of soil erodibility factor information: The K-factors in the study area ranged from 0.
Information layer of rainfall erosivity factor information: Information layer of crop management factor: The C-factors in this new raster file were used to estimate the mean of the crop management of each polygon. The C-factor noted in Table 1 corresponds to a mean C-factor for a type of crop rotation developed with no tillage, according to the land cover identified by shapefile LCCS and soil aptitude information Molfino, These C-factors in the studied basins ranged from 0 to 0.
Information layer of topographic information: The digital terrain model allowed a geo-referenced LS-factor for each soil polygon in the studied basins.
The LS-factor exhibited a mean value was 0. In addition, mean annual soil erosion of each basin was obtained by weighting the erosion of each soil unit within the basin, erision shown in Figure edosion.
This forecast of soil erosion by water indicated that The basins clusters were named as follows: The clusters shown in Figure 3c are named as follows: Finally, it was not possible to attribute any dominant factor in basins cluster 4.
These models, however, have been used to evaluate and manage watershed erosion, most likely because of their simplicity and the availability of existing information for use in a GIS Ersoion et al. The model factors were derived from field experiments; thus, our estimate may approach the real value and allow to highlight the regions and basins with high demand of an environmental management in the short term.
In the departments along the southwestern and southern coast, which were grouped into cluster 1 basins cluster of northern-western-southern and where the crop management factor is dominant Table 3there was a clear need for an incentive to rotate crops, specifically those with pastures, as a mitigation measure.
Crop rotation has immediate effects on erosion through the change of C-factor and a long-term effect in changing the physical properties of the soil, particularly the K-factor. This last factor seems an hidgica property of soil, but since it has a relationship with the soil organic carbon, any increasing of it could reduce the erodibility factor.
In this framework, the results of a year experiment on crop rotations of Experimental Station Alberto Boerger INIA La Estanzuela Colonia, Uruguay Quincke et al, suggest that crop rotation in the short term reduces soil eorsion and, in the long term, increases the soil organic carbon and therefore indirectly should reduce the erodibility. For these reasons, in recent years the Uruguayan Ministry of Livestock, Agriculture and Fishing has enforced that agricultural areas higher than ha.
Values with different lowercase letters denote statistically significant differences. Estimation of mean annual soil loss hideica performed based on a specific situation regarding the soil cover information obtained from satellite imagery FAO et al, It would be valuable to build on this finding both in retrospective terms and in terms of updated yearly information to reconstruct the recent erosion history of the soils and generate an annual forecast of national hidriva.
It would be convenient, in addition, for the C-factors to be agreed on by experts because these values can vary based on several factors. The geo-referenced C-factor should be updated every year and perhaps adapt it to assess the hidriac crop rotation in each region using NDVI satellite data, as was done hidricq Jordan by Farhan et al.
Similarly, it would erksion beneficial to update the other factors in the equation, for example, the L and S-factors erosioh increasing the resolution of the digital terrain model, the R-factor through updating of climate data and the K-factor based on new measurements. Updates that can increase the spatial resolution would increase the scope of soil erosion hhidrica i. Updates are required to reduce the potential errors in present estimations.
From the cluster analysis Figure 3c and results of regression adjustment using the stepwise procedure Table 3it is possible to identify two main topics for the Uruguayan environmental management: Therefore, management of soil erosion by water can be significantly improved by rotating crops on a scale of properties in these two clusters, with a greater impact in the Sierras del Este basins cluster.
In contrast, in the eastern plains and knolls basins cluster cluster 3, Figure 3 c and northern sandstones basins cluster cluster 4, Figure 3cmodification of crop rotation system is not expected to modify soil erosion because in these regions, the topographic factor or rainfall erosivity are the main factors.
A second aspect that arose from this cluster analysis and the results of soil erosion in the basins Hhidrica 3b is that the basins that need a modification of their land use to protect the freshwater quality are in the South, a region currently dominated by soybean crop rotations and dairy production. The main conclusions are as follows. This study proved that Uruguay has enough information to create mean annual soil loss forecast for the entire country base on public databases.
Inthere was land cover that promoted a mean annual soil loss higher than tolerable values in the northern, western and southern regions that was probably linked to soybean crop rotations and dairy production. The studied basins can be grouped into 4 clusters, and only the northern-western-southern and Sierras del Este basins clusters showed the possibility of erosion control at plot basin scale though land use management.
The information and strategy developed could help create new forecasts of soil erosion and guide public policies that protect freshwater quality and soil conservation. We gratefully acknowledge Dr. Beretta Blanco, and G.
DEGRADACIÓN POR EROSIÓN HÍDRICA by Noel Gonzalez Checa on Prezi
Primer mapa nacional de la calidad del agua de Uruguay. Hemisferio Sur, Montevideo, Uruguay. Atlas de Cobertura del Suelo del Uruguay. Conversion of the erosioj soil loss equation to SI metric units.
Agrociencia Uruguay 2 1: Slope length and steepness factors LS. The new assessment of soil loss by water erosion in Europe. A framework for the use of the universal soil loss equation in Uruguay.
La erosion hidrica de los suelos. Causas y remedios
Departamento de Suelos, Ministerio de Agricultura y Pesca. Open Source Geospatial Foundation Project.
From isolated to integrated long-term experiments: Integrated Crop Livestock Symposium. Pearson New International Edition. All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License. Research Paper Soil erosion by water estimated for 99 Uruguayan basins. Abstract Soil erosion can be accelerated by agricultural intensification, and the soil loss can alter the quality of water bodies.
Rainfall erosivity factor R-factor The rainfall erosivity factor information was incorporated into the GIS by creating a raster file using the isoerodents of Uruguay Puentes and Szogi, and the R-factor used by Erosion 6. Topographic factor LS-factor The slope gradient factor S-factor expressed in degrees, radians and percent was estimated by applying the second-degree polygons with free GIS software gvSIG www. Erosion control practice factor P-factor The erosion control practice factor P-factor in this study was assumed to be equal to 1 because management practices that reduce erosion are not frequently used in Uruguay.
Data analysis The basins were analyzed by a cluster analysis for definition of homogeneous regions, and in each cluster, the factors that contribute in an important manner in the erosion process was determined. June 13, ; Accepted: