<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-3195</journal-id>
<journal-title><![CDATA[Agrociencia]]></journal-title>
<abbrev-journal-title><![CDATA[Agrociencia]]></abbrev-journal-title>
<issn>1405-3195</issn>
<publisher>
<publisher-name><![CDATA[Colegio de Postgraduados]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-31952016000100015</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Ajuste de las distribuciones GVE, LOG y PAG con momentos L depurados (1,1) en 21 registros de crecientes anuales de la region hidrológica no. 10 (Sinaloa), México]]></article-title>
<article-title xml:lang="en"><![CDATA[Fitting of the GEV, GLO and GPA distributions with trimmed L moments (1, 1) in 21 annual flood records of the hydrological region no. 10 (Sinaloa), Mexico]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Campos-Aranda]]></surname>
<given-names><![CDATA[Daniel F.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma de San Luis Potosí Facultad de Ingeniería ]]></institution>
<addr-line><![CDATA[San Luis Potosí San Luis Potosí]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>02</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>02</month>
<year>2016</year>
</pub-date>
<volume>50</volume>
<numero>1</numero>
<fpage>15</fpage>
<lpage>31</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-31952016000100015&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-31952016000100015&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-31952016000100015&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El dimensionamiento y seguridad hidrológica de todas las obras hidráulicas de aprovechamiento o control depende de las crecientes de diseño. La estimación confiable de esas magnitudes hidrológicas está asociada con la disponibilidad de datos de gastos máximos anuales y su representación, lo más exacta posible, en una función de distribución de probabilidades (FDP). El método de los momentos L, que son combinaciones lineales de los estadísticos de orden, es uno de los procedimientos de ajuste más exactos que permite la estimación de los parámetros de una FDP. Versiones robustas se han propuesto de los momentos L, al dar peso nulo a los valores extremos de la muestra; es el caso de los momentos L depurados (1,1) que no toman en cuenta el dato menor ni el mayor. En este estudio, se exponen ambos métodos de ajuste para las FDP general de valores extremos (GVE), logística generalizada (LOG) y Pareto generalizada (PAG), que son modelos probabilísticos con aceptación mundial en el análisis de frecuencia de datos hidrológicos extremos. Mediante el error estándar de ajuste (EEA) se realizó el contraste de la aplicación de las FDP citadas, a los 21 registros de crecientes anuales disponibles en la Región Hidrológica No. 10 (Sinaloa, México). Los resultados indicaron que las FDP condujeron a los EEA menores en tres, siete y once de los registros procesados. El método de ajuste por momentos L depurados (1,1) logró un EEA menor en diez de los registros procesados. Por lo tanto, se recomienda su aplicación sistemática en los análisis de frecuencia de datos hidrológicos extremos.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The hydrological dimensioning and security of all water use or control works depend on the flood design. The reliable estimation of those hydrologic magnitudes is related to the availability of the most accurate possible maximum annual discharge data and their representation, in a probability distribution function (PDF). The method of L moments, which are linear combinations of the order statistics, is one of the most accurate fitting procedures that allow to estimate the parameters of an PDF. Robust versions have been proposed for L moments, since they give no weight to the extreme values of the sample; such is the case of the trimmed L moments (1,1), which do not take into account the lowest nor the highest data. This study presents both fitting methods for the PDFs general extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA), which are probability models with worldwide acceptance in the frequency analysis of hydrological extreme data. Using the standard error of fit (SEF) the contrast was performed for the application of the mentioned PDFs, to 21 records of annual floods available in the Hydrological Region No. 10 (Sinaloa, Mexico). The results indicated that the PDFs led to the lowest SEFs in three, seven, and eleven of the records processed. The method of adjustment by trimmed L moments (1,1) achieved a lower SEF in ten of the records processe. Therefore, its systematic use is recommended in the frequency analyses of extreme hydrological data.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[momentos L]]></kwd>
<kwd lng="es"><![CDATA[momentos L depurados (1,1)]]></kwd>
<kwd lng="es"><![CDATA[distribuciones GVE]]></kwd>
<kwd lng="es"><![CDATA[LOG y PAG]]></kwd>
<kwd lng="es"><![CDATA[error estándar de ajuste]]></kwd>
<kwd lng="es"><![CDATA[gráficos de diagnóstico]]></kwd>
<kwd lng="en"><![CDATA[L moments]]></kwd>
<kwd lng="en"><![CDATA[trimmed L moments (1,1)]]></kwd>
<kwd lng="en"><![CDATA[GEV]]></kwd>
<kwd lng="en"><![CDATA[GLO]]></kwd>
<kwd lng="en"><![CDATA[and GPA distributions]]></kwd>
<kwd lng="en"><![CDATA[Fitting Standard Error]]></kwd>
<kwd lng="en"><![CDATA[diagnosis graphs]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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