@InProceedings{BiasottoJohaRichBeck:2017:DeSéHi,
               author = "Biasotto, Giovane and Johann, Jerry Adriani and Richetti, Jonathan 
                         and Becker, Willyan Ronaldo",
                title = "Determina{\c{c}}{\~a}o da s{\'e}rie hist{\'o}rica mensal do 
                         balan{\c{c}}o h{\'{\i}}drico para o estado do Paran{\'a} 
                         utilizando o modelo ECMWF",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "5545--5551",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The meteorological elements are becoming more and more important 
                         to the agricultural scene, being a strategical matter for decision 
                         making and agricultural planning in the country. The water balance 
                         is the difference between rainfall and evapotranspiration, being 
                         another important element, thus, knowing the soils water storing 
                         capacity its possible to determine if the plant is suffering from 
                         water shortage. The most common way to obtain these information is 
                         from surface meteorological stations, however, financial and 
                         logistics problems can difficult the process. Atmosphere models 
                         such as ECMWF can be used as an alternative to the surface 
                         stations for obtaining these data, this specific model make them 
                         available in real time and free of cost, ending with the surface 
                         stations problems. This papers objective was, by using remote 
                         sensing technology and the ECMWF model, to determine the monthly 
                         historical series of the water balance between the years of 2008 
                         and 2016 in Paran{\'a} State. Using the CyMP software, the ECMWF 
                         data had to be transformed from a decennial to a monthly scale, 
                         the water balance calculation and the images classification were 
                         made in ArcGis. The results points to some more expressive 
                         variations during the years, which may be the effects from El Niño 
                         and La Niña, causing rainy and rainless periods, respectively. It 
                         was concluded that the average water balance kept positive during 
                         the summer crops in practically the entire state, during the 
                         winter this value decreased, mainly at the northern parts of the 
                         state, matching with the Koppen climatic classification.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59975",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMBA7",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMBA7",
           targetfile = "59975.pdf",
                 type = "An{\'a}lise de s{\'e}ries temporais de imagens de 
                         sat{\'e}lite",
        urlaccessdate = "27 abr. 2024"
}