<?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>S1405-31952018000700911</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Pronóstico de sequías meteorológicas con filtro de Kalman discreto en la cuenca del río Fuerte, México]]></article-title>
<article-title xml:lang="en"><![CDATA[Meteorological drought forecasting using discrete Kalman filter in the Fuerte river watershed, Mexico]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Castillo-Castillo]]></surname>
<given-names><![CDATA[Mónica]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ibáñez-Castillo]]></surname>
<given-names><![CDATA[Laura A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Valdés]]></surname>
<given-names><![CDATA[Juan B.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Arteaga-Ramírez]]></surname>
<given-names><![CDATA[Ramón]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vázquez-Peña]]></surname>
<given-names><![CDATA[Mario A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma Chapingo  ]]></institution>
<addr-line><![CDATA[Chapingo Estado de México]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,University of Arizona Department of Hydrology and Water Resources ]]></institution>
<addr-line><![CDATA[Tucson ]]></addr-line>
<country>USA</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>11</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>11</month>
<year>2018</year>
</pub-date>
<volume>52</volume>
<numero>7</numero>
<fpage>911</fpage>
<lpage>932</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-31952018000700911&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-31952018000700911&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-31952018000700911&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El monitoreo y pronóstico de sequías es importante para evaluar riesgos, tomar decisiones, acciones efectivas y oportunas para evitar y reducir sus efectos negativos. Por lo tanto, el objetivo de este estudio fue realizar el pronóstico de los índices de sequía SPI (Standard Precipitation Index) y SPEI (Standard Precipitation Evapotranspiration Index) para 14 estaciones meteorológicas de la cuenca del río Fuerte en el Noroeste de México. La hipótesis fue que es posible lograr tal objetivo mediante la implementación del algoritmo del filtro de Kalman discreto (DKF). La cuenca del río Fuerte, Sinaloa, México, es importante por su producción agrícola y por su generación de energía hidroeléctrica. El pronóstico de los índices de sequía SPI y SPEI se realizó para escalas temporales (duraciones de sequías) de 3, 6, 12 y 24 meses, durante el periodo 1961-2011, y con 1, 2, 3 y 4 meses de anticipación. Dos modelos se implementaron utilizando el filtro de Kalman Discreto: un autorregresivo de segundo orden (DKF-AR2), y un autorregresivo de segundo orden con entrada exógena (DKF-ARX). Las variables climáticas probadas como exógenas fueron la precipitación (Pt), las temperaturas máximas y mínimas (Tmax y Tmin) y la evapotranspiración de referencia (ET0); la variable exógena precipitación, Pt, presentó mejores resultados. La metodología DKF-AR2 presentó el mejor resultado en el pronóstico de los índices para seis estaciones localizadas en la parte alta de la cuenca, con predominancia de climas templados y semifríos. La metodología DKF-ARX-Pt fue mejor en las ocho estaciones restantes de la parte media y baja, ubicadas en climas cálidos. Los mejores pronósticos se obtuvieron para escalas (duraciones de sequías) de 12 y 24 meses, y el pronóstico de SPEI fue mejor que el de SPI. Los índices de Nash-Sutcliffe (E) para 12 y 24 meses llegaron a ser hasta de 0.92 y 0.96; en el caso de 3 y 6 meses, los índices de Nash-Sutcliffe fueron aproximadamente 0.5. La anticipación del pronóstico fue mejor para 1 y 2 meses.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The monitoring and forecasting of droughts are important to evaluate risks, take decisions, as well as undertake effective and timely actions to avoid and reduce their negative effects. Therefore, the objective of this study was to forecast the SPI (Standard Precipitation Index) and SPEI (Standard Precipitation Evapotranspiration Index) drought indices for 14 meteorological stations in the Fuerte River watershed in northwest Mexico. Our hypothesis was that it is possible to achieve such objective through the implementation of the Discrete Kalman filter algorithm (DKF). The Fuerte River watershed, Sinaloa, Mexico, is important for its agricultural production and generation of hydroelectric power. We did the forecast of the SPI and SPEI drought indices for time scales (drought durations) of 3, 6, 12 and 24 months, during the period 1961-2011, and with 1, 2, 3 and 4 months in advance. Two models were implemented using the Discrete Kalman filter: a second-order autoregressive (DKF-AR2), and a second-order autoregressive with exogenous input (DKF-ARX). The climatic variables tested as exogenous were precipitation (Pt), maximum and minimum temperatures (Tmax and Tmin) and reference evapotranspiration (ET0); the exogenous variable precipitation, Pt, recorded better results. The DKF-AR2 methodology presented the best result in the forecast of the indices for six stations located in the upper part of the watershed, with predominance of temperate and semi-cold climates. The DKF-ARX-Pt methodology proved better in the remaining eight stations of the middle and lower parts, located in warm climates. The best forecasts were obtained for scales (drought durations) of 12 and 24 months, and the SPEI forecast was better than that of SPI. The Nash-Sutcliffe indices (E) for 12 and 24 months reached up to 0.92 and 0.96; in the case of 3 and 6 months, the Nash-Sutcliffe indices were approximately 0.5. The anticipation of the prognosis was better for 1 and 2 months.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[filtro de Kalman Discreto]]></kwd>
<kwd lng="es"><![CDATA[modelos autorregresivos]]></kwd>
<kwd lng="es"><![CDATA[índices de sequía]]></kwd>
<kwd lng="en"><![CDATA[Discrete Kalman filter]]></kwd>
<kwd lng="en"><![CDATA[autoregressive models]]></kwd>
<kwd lng="en"><![CDATA[drought indices]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Al-Qinna]]></surname>
<given-names><![CDATA[M. I.]]></given-names>
</name>
<name>
<surname><![CDATA[Hammouri]]></surname>
<given-names><![CDATA[N. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Obeidat]]></surname>
<given-names><![CDATA[M. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Ahmad]]></surname>
<given-names><![CDATA[F. Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Drought analysis in Jordan under current and future climates]]></article-title>
<source><![CDATA[Climatic Change]]></source>
<year>2011</year>
<volume>106</volume>
<page-range>421-40</page-range></nlm-citation>
</ref>
<ref id="B2">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Beguería]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Vicente]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
</person-group>
<source><![CDATA[Calculation of the Standardized Precipitation-Evapotranspiration Index. Package SPEI]]></source>
<year>2014</year>
</nlm-citation>
</ref>
<ref id="B3">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Beguería]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Vicente&#8208;Serrano]]></surname>
<given-names><![CDATA[S. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Reig]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Latorre]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring]]></article-title>
<source><![CDATA[International J. Climatol.]]></source>
<year>2014</year>
<volume>34</volume>
<page-range>3001-23</page-range></nlm-citation>
</ref>
<ref id="B4">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Castillo-Castillo]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Ibáñez-Castillo]]></surname>
<given-names><![CDATA[L. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Valdes]]></surname>
<given-names><![CDATA[J. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Arteaga-Ramírez]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Vázquez-Peña]]></surname>
<given-names><![CDATA[M. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Análisis de sequías meteorológicas en la cuenca del río Fuerte, México]]></article-title>
<source><![CDATA[Rev. Tecnol. Ciencias del Agua]]></source>
<year>2017</year>
<volume>8</volume>
<page-range>35-52</page-range></nlm-citation>
</ref>
<ref id="B5">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Chatfield]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<source><![CDATA[The Analysis of Time Series: An Introduction]]></source>
<year>2004</year>
<edition>Six edition</edition>
<publisher-name><![CDATA[Chapman &amp;Hall]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B6">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Dehghani]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Saghafian]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Nasiri Saleh]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Farokhnia]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Noori]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Uncertainty analysis of streamflow drought forecast using artificial neural networks and Monte&#8208;Carlo simulation]]></article-title>
<source><![CDATA[Int. J. Climatol.]]></source>
<year>2014</year>
<volume>34</volume>
<page-range>1169-80</page-range></nlm-citation>
</ref>
<ref id="B7">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Eicker]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Schumacher]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Kusche]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Döll]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Schmied]]></surname>
<given-names><![CDATA[H. M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Calibration/data assimilation approach for integrating GRACE data into the WaterGAP Global Hydrology Model (WGHM) using an ensemble Kalman filter: First results]]></article-title>
<source><![CDATA[Surveys in Geophysics]]></source>
<year>2014</year>
<volume>35</volume>
<page-range>1285-309</page-range></nlm-citation>
</ref>
<ref id="B8">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[González-Leiva]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Ibáñez-Castillo]]></surname>
<given-names><![CDATA[L. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Valdés]]></surname>
<given-names><![CDATA[J. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Vázquez-Peña]]></surname>
<given-names><![CDATA[M. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Ruiz-García]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Pronóstico de caudales con el filtro de Kalman en el río Turbio]]></article-title>
<source><![CDATA[Tecnol. Ciencias del Agua]]></source>
<year>2015</year>
<volume>6</volume>
<page-range>5-24</page-range></nlm-citation>
</ref>
<ref id="B9">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gupta]]></surname>
<given-names><![CDATA[H. V.]]></given-names>
</name>
<name>
<surname><![CDATA[Kling]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Yilmaz]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Martinez]]></surname>
<given-names><![CDATA[G.F.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling]]></article-title>
<source><![CDATA[J. Hydrol.]]></source>
<year>2009</year>
<volume>377</volume>
<page-range>80-91</page-range></nlm-citation>
</ref>
<ref id="B10">
<nlm-citation citation-type="book">
<collab>Instituto Nacional de Estadística y Geografía</collab>
<source><![CDATA[Continuo de Elevaciones Mexicano 3.0, CEM 3.0]]></source>
<year>2014</year>
<publisher-name><![CDATA[inegi]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B11">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kalman]]></surname>
<given-names><![CDATA[R. E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A new approach to linear filtering and prediction problems]]></article-title>
<source><![CDATA[J. Fluids Eng.]]></source>
<year>1960</year>
<volume>82</volume>
<page-range>35-45</page-range></nlm-citation>
</ref>
<ref id="B12">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kim]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Valdés]]></surname>
<given-names><![CDATA[J. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Aparicio]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Frequency and spatial characteristics of droughts in the Conchos River Basin, Mexico]]></article-title>
<source><![CDATA[Water Int.]]></source>
<year>2002</year>
<volume>27</volume>
<page-range>420-30</page-range></nlm-citation>
</ref>
<ref id="B13">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kim]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
</person-group>
<source><![CDATA[Kalman Filter for Beginners: with Matlab Examples]]></source>
<year>2011</year>
<publisher-loc><![CDATA[Seoul, Korea ]]></publisher-loc>
<publisher-name><![CDATA[CreateSpace]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B14">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Madadgar]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Moradkhani]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A Bayesian framework for probabilistic seasonal drought forecasting]]></article-title>
<source><![CDATA[J. Hydrometeorol.]]></source>
<year>2013</year>
<volume>14</volume>
<page-range>1685-705</page-range></nlm-citation>
</ref>
<ref id="B15">
<nlm-citation citation-type="">
<collab>MathWorks, Inc.</collab>
<source><![CDATA[Software Matlab®]]></source>
<year>2015</year>
</nlm-citation>
</ref>
<ref id="B16">
<nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[McKee]]></surname>
<given-names><![CDATA[T. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Doesken]]></surname>
<given-names><![CDATA[N. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Kleist]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<source><![CDATA[The relationship of drought frequency and duration to time scales]]></source>
<year>1993</year>
<conf-name><![CDATA[ EightConference on Applied Climatology]]></conf-name>
<conf-loc>Anaheim, CA </conf-loc>
<page-range>179-84</page-range></nlm-citation>
</ref>
<ref id="B17">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mishra]]></surname>
<given-names><![CDATA[A. K.]]></given-names>
</name>
<name>
<surname><![CDATA[Singh]]></surname>
<given-names><![CDATA[V. P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A review of drought concepts]]></article-title>
<source><![CDATA[J. Hydrol.]]></source>
<year>2010</year>
<volume>391</volume>
<page-range>202-16</page-range></nlm-citation>
</ref>
<ref id="B18">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mishra]]></surname>
<given-names><![CDATA[A. K.]]></given-names>
</name>
<name>
<surname><![CDATA[Singh]]></surname>
<given-names><![CDATA[V. P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Drought modeling-A review]]></article-title>
<source><![CDATA[J. Hydrol.]]></source>
<year>2011</year>
<volume>403</volume>
<page-range>157-75</page-range></nlm-citation>
</ref>
<ref id="B19">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Morales-Velázquez]]></surname>
<given-names><![CDATA[M. I.]]></given-names>
</name>
<name>
<surname><![CDATA[Aparicio]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Valdés]]></surname>
<given-names><![CDATA[J. B.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Pronóstico de avenidas utilizando el Filtro de Kalman Discreto]]></article-title>
<source><![CDATA[Tecnol. Ciencias del Agua]]></source>
<year>2014</year>
<volume>5</volume>
<page-range>85-110</page-range></nlm-citation>
</ref>
<ref id="B20">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Moriasi]]></surname>
<given-names><![CDATA[D., N.]]></given-names>
</name>
<name>
<surname><![CDATA[Arnold]]></surname>
<given-names><![CDATA[J. G.]]></given-names>
</name>
<name>
<surname><![CDATA[Liew]]></surname>
<given-names><![CDATA[M. W. Van]]></given-names>
</name>
<name>
<surname><![CDATA[Bingner]]></surname>
<given-names><![CDATA[R. L.]]></given-names>
</name>
<name>
<surname><![CDATA[Harmel]]></surname>
<given-names><![CDATA[R. D.]]></given-names>
</name>
<name>
<surname><![CDATA[Veith]]></surname>
<given-names><![CDATA[T. L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Model evaluation guidelines for systematic quantification of accuracy in watershed simulations]]></article-title>
<source><![CDATA[Soil &amp; Water Division of ASABE]]></source>
<year>2007</year>
<volume>50</volume>
<page-range>885-900</page-range></nlm-citation>
</ref>
<ref id="B21">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mossad]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Alazba]]></surname>
<given-names><![CDATA[A. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Drought forecasting using stochastic models in a hyper-arid climate]]></article-title>
<source><![CDATA[Atmosphere]]></source>
<year>2015</year>
<volume>6</volume>
<page-range>410-30</page-range></nlm-citation>
</ref>
<ref id="B22">
<nlm-citation citation-type="">
<collab>National Drought Mitigation Center</collab>
<source><![CDATA[SPI SL 6.exe: Program to calculate Standardized Precipitation Index]]></source>
<year>2014</year>
</nlm-citation>
</ref>
<ref id="B23">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ravelo]]></surname>
<given-names><![CDATA[A. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Sanz-Ramos]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Douriet-Cárdenas]]></surname>
<given-names><![CDATA[J. C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Detección, evaluación y pronóstico de las sequías en la región del Organismo de Cuenca Pacífico Norte, México]]></article-title>
<source><![CDATA[Agriscientia]]></source>
<year>2014</year>
<volume>31</volume>
<page-range>11-24</page-range></nlm-citation>
</ref>
<ref id="B24">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rhee]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Im]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Meteorological drought forecasting for ungauged areas based on machine learning: Using long-range climate forecast and remote sensing data]]></article-title>
<source><![CDATA[Agric. Forest Meteorol.]]></source>
<year>2017</year>
<volume>237</volume>
<page-range>105-22</page-range></nlm-citation>
</ref>
<ref id="B25">
<nlm-citation citation-type="">
<collab>Servicio Meteorológico Nacional</collab>
<source><![CDATA[Climatología Diaria]]></source>
<year>2014</year>
</nlm-citation>
</ref>
<ref id="B26">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Simon]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Kalman filtering]]></article-title>
<source><![CDATA[Embedded Systems Programming]]></source>
<year>2001</year>
<volume>14</volume>
<page-range>72-9</page-range></nlm-citation>
</ref>
<ref id="B27">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Velasco]]></surname>
<given-names><![CDATA[I.]]></given-names>
</name>
<name>
<surname><![CDATA[Aparicio]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Valdés]]></surname>
<given-names><![CDATA[J. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Velázquez]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Kim]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Evaluación de índices de sequía en las cuencas de afluentes del río Bravo/Grande]]></article-title>
<source><![CDATA[Ing. Hidrául. México]]></source>
<year>2004</year>
<volume>19</volume>
<page-range>37-53</page-range></nlm-citation>
</ref>
<ref id="B28">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Vicente]]></surname>
<given-names><![CDATA[S. S]]></given-names>
</name>
<name>
<surname><![CDATA[Beguería]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[López]]></surname>
<given-names><![CDATA[M. J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A multiscalar drought index sensitive to global warming: the standardized Precipitation Evapotranspiration Index]]></article-title>
<source><![CDATA[J. Climate.]]></source>
<year>2010</year>
<volume>23</volume>
<page-range>1696-718</page-range></nlm-citation>
</ref>
<ref id="B29">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Welch]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Bishop]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<source><![CDATA[An Introduction to the Kalman Filter]]></source>
<year>2006</year>
<publisher-loc><![CDATA[Chapel Hill ]]></publisher-loc>
<publisher-name><![CDATA[Department of Computer Science, University of North Carolina]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B30">
<nlm-citation citation-type="">
<collab>World Meteorological Organization</collab>
<source><![CDATA[Guide to Hydrological Practices]]></source>
<year>2011</year>
<edition>Sixth Edition</edition>
<publisher-loc><![CDATA[Geneva, Swiss ]]></publisher-loc>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
