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@PhDThesis{Falck:2015:AvInEs,
               author = "Falck, Aline Schneider",
                title = "Avalia{\c{c}}{\~a}o da incerteza nas estimativas de 
                         precipita{\c{c}}{\~a}o por sat{\'e}lite e sua 
                         propaga{\c{c}}{\~a}o no modelo hidrol{\'o}gico 
                         distribu{\'{\i}}do MHD-INPE",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2015",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2015-02-26",
             keywords = "precipita{\c{c}}{\~a}o, sat{\'e}lite, vaz{\~a}o, modelos 
                         hidrol{\'o}gicos, precipitation, satellite, runoffs, hydrology 
                         models.",
             abstract = "A estimativa de precipita{\c{c}}{\~a}o por sat{\'e}lite tem se 
                         mostrado uma importante alternativa para o monitoramento da 
                         precipita{\c{c}}{\~a}o, principalmente devido {\`a}s suas altas 
                         resolu{\c{c}}{\~o}es espacial e temporal. Dentre as principais 
                         aplica{\c{c}}{\~o}es desse tipo de produto destaca-se a 
                         modelagem hidrol{\'o}gica em {\'a}reas onde a rede convencional 
                         de pluvi{\^o}metros, ou mesmo aquela destinada ao monitoramento 
                         em tempo real, {\'e} prec{\'a}ria no que se refere {\`a} sua 
                         cobertura espacial e/ou temporal. Nesse contexto, esta pesquisa 
                         avaliou as estimativas de precipita{\c{c}}{\~a}o por 
                         sat{\'e}lite em aplica{\c{c}}{\~o}es hidrol{\'o}gicas na bacia 
                         dos rios Tocantins e Araguaia, e investigou como a 
                         propaga{\c{c}}{\~a}o dos erros nas estimativas de 
                         precipita{\c{c}}{\~a}o por sat{\'e}lite s{\~a}o traduzidas em 
                         vaz{\~a}o. Para isso foi implementado o modelo estoc{\'a}stico 
                         multidimensional de propaga{\c{c}}{\~a}o do erro das estimativas 
                         de precipita{\c{c}}{\~a}o por sat{\'e}lite SREM2D (do 
                         ingl{\^e}s \emph{Two-Dimensional Satellite Rainfall Error 
                         Model)} a partir de dados di{\'a}rios de precipita{\c{c}}{\~a}o 
                         observados e estimados por sat{\'e}lite provenientes dos 
                         algoritmos CMORPH (do ingl{\^e}s \emph{Climate Prediction Center 
                         morphing technique)}, 3B42RT (do ingl{\^e}s \emph{Tropical 
                         Rainfall M easuring Mission real-time 3B42 product)}, HYDROE (do 
                         ingl{\^e}s \emph{Hydroestimator)} e GSMAP (do ingl{\^e}s 
                         \emph{Global Satellite Mapping of Precipitation)}, para o 
                         per{\'{\i}}odo de 2008 {\`a} 2011. Os campos de 
                         precipita{\c{c}}{\~a}o por conjuntos gerados pelo modelo 
                         estoc{\'a}stico mencionado foram utilizados para for{\c{c}}ar o 
                         Modelo Hidrol{\'o}gico Distribu{\'{\i}}do do Instituto Nacional 
                         de Pesquisas Espaciais (MHD-INPE), previamente calibrado e 
                         validado nos per{\'{\i}}odos de 2000 {\`a} 2008 e 2008 {\`a} 
                         2011, respectivamente. Os resultados obtidos durante as 
                         esta{\c{c}}{\~o}es chuvosas e secas ao longo dos tr{\^e}s anos 
                         (2008-2011) mostram que o modelo estoc{\'a}stico multidimensional 
                         de propaga{\c{c}}{\~a}o do erro das estimativas de 
                         precipita{\c{c}}{\~a}o por sat{\'e}lite utilizado neste estudo 
                         gera conjuntos de precipita{\c{c}}{\~a}o real{\'{\i}}sticos, 
                         que podem ser utilizados para for{\c{c}}ar o modelo 
                         hidrol{\'o}gico distribu{\'{\i}}do (MHD-INPE) e permitir o 
                         monitoramento de hidrol{\'o}gico em tempo real. ABSTRACT: 
                         Satellite precipitation estimations are an important alternative 
                         for monitoring of pre-cipitation due to its high spatial and 
                         temporal resolution. This type of product can be applied in 
                         hydrological modeling in areas with poor spatial and temporal 
                         coverage ofthe conventional rain gauges and/or or the automatic 
                         (real time) networks. In this context, this study evaluated the 
                         satellite rainfall estimation in hydrological applications in the 
                         Araguaia and Tocantins rivers basin, and investigated how the 
                         propagation of errors in satellite rainfall estimates impacted 
                         river discharges. To achieve this goal, the multidimensional 
                         stochastic model erro r propagation SREM2D (TwoDimensional 
                         Satellite Rainfall Error Model) was implemented using observed 
                         daily rainfall data and satellite estimates from the CMORPH 
                         (Cl{\'{\i}}mate Prediction Center morphing technique); 3B42RT 
                         (Tropical Rainfall Measuring Mission real time 3B42 product); 
                         HYDROE (Hydroestimator); and GSMAP (Global Satellite Mapping of 
                         Precipitation) algorithms, for the period 2008 to 2011. 
                         Precipitations fields generated using the stochastic model were 
                         used to force the Distributed Hydrological Model of the National 
                         Institute for Space Research (MHD-INPE), which was calibrated and 
                         validated in the periods 2000-2008 and 2008-2011, respectively. 
                         The results obtained during the rainy and dry seasons over a three 
                         years period (2008-2011) showed that the multidimensional 
                         stochastic error propagation of satellite precipitation estimates 
                         used in this study generates realistic precipitation sets, which 
                         can be used to force the distributed hydrological model (MHD-INPE) 
                         and allow real-time hydrological monitoring.",
            committee = "Angelis, Carlos Frederico de (presidente) and Vila, Daniel 
                         Alejandro (orientador) and Tomasella, Javier (orientador) and 
                         Rodriguez, Daniel Andres and Beneti, Cesar Augustus Assis and 
                         Maggioni, Viviana",
           copyholder = "SID/SCD",
         englishtitle = "Evaluation of satellite rainfall estimates uncertainty and its 
                         impact on streamflow simulation in the distributed hydrological 
                         model MHD-INPE",
             language = "pt",
                pages = "183",
                  ibi = "8JMKD3MGP3W34P/3J3C842",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34P/3J3C842",
           targetfile = "publicacao.pdf",
        urlaccessdate = "29 nov. 2020"
}


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