<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="es">
<Esri>
<CreaDate>20211215</CreaDate>
<CreaTime>16592400</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
<MapLyrSync>TRUE</MapLyrSync>
</Esri>
<dataIdInfo>
<idCitation>
<resTitle>Perdida de Suelo</resTitle>
</idCitation>
<idAbs>La Pérdida Máxima de Suelo se determina a partir de la aplicación de la
Ecuación Universal de Pérdida de Suelos (U. S. L. E.) de Wischmeier y Smith
(1962)1. Esta ecuación trata de cuantificar la erosión hídrica a partir de los
factores que considera implicados en este proceso los cuales son la erosividad
de la lluvia, la erosionabilidad del suelo, la topografía, la cobertura y las
prácticas de conservación. Esta ecuación es una fórmula empírica, resultado
de 10.000 datos de pérdida de suelo en parcelas experimentales tipo, con
lluvia artificial.
El estudio de la Pérdida Máxima de Suelo tiene como objetivo el localizar las
áreas que por sus diferentes características de suelo, pendiente, lluviosidad y
cobertura son más sensibles de ser erosionadas, con base en esta información
establecer los correctivos y plantear las soluciones requeridas.</idAbs>
<searchKeys>
<keyword>Cali</keyword>
<keyword>Valle del Cauca</keyword>
<keyword>Colombia</keyword>
<keyword>Pérdida Suelo</keyword>
<keyword>cobertura</keyword>
<keyword>erosión</keyword>
</searchKeys>
<idPurp>Pérdida máxima de suelo del Valle del Cauca</idPurp>
<idCredit>CVC 2021</idCredit>
<resConst>
<Consts>
<useLimit>&lt;DIV STYLE="text-align:Left;font-size:12pt"&gt;&lt;P&gt;&lt;SPAN&gt;Derechos reservados de autor&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;</useLimit>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">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</Data>
</Thumbnail>
</Binary>
</metadata>
