Since most of the inhabitants in West Africa is working with, or are dependent on agricultural work, accurate weather forecasts are important in their daily work. Knowledge of when to start to sow is one of the most important features from a farmer’s point of view. It can be devastating for the farmers if the soil is not moist enough when planting since the crops risks to dry out, but also planting too late needs to be avoided since it will affect the growing time and therefore might reduce the production. In this thesis, investigations whether the start of the rainy season in Ghana and parts of Burkina Faso is predictable, only with the use of patterns in rainfall and changes in sea surface temperature in the Gulf of Guinea. The region of interest has been divided into four equally sized areas with a latitudinal width of 2  from south to north. The models are first of all predicting the start of the rainy season in the southernmost area by use of four different methods, three that are based on precipitation patterns and one based on changes in sea surface temperature. Thereafter, the three northerly areas are predicted with a linear function based on when the rainy season started in the southernmost area. The results shows that the model is acceptable in its predictability but is very good in indicating if the rainy season will start earlier or later than the year before. This is of major benefits for the farmers in the region. On a long‐range average, the rainy season starts in the southernmost area first and then it starts further north, but this is not always the case in individual years, which makes the models complicated to use in some years. In order to give reliable forecasts to the farmers, the rainy season needs to be defined so it fulfils the conditions that are needed for plants to grow. Therefore, the start of the rainy season is defined as when 40 mm of precipitation is received during a five‐day period with at least 16 mm in one of these five days. Thereafter, the next 30 days cannot contain more than 18 days without precipitation. / Eftersom de flesta invånarna i Västafrika arbetar med, eller är beroende av jordbruksarbete så är väderprognoser till stor hjälp i det dagliga arbetet. Att ha kännedom om när det är lämpligt att börja så är en av de viktigaste aspekterna ur böndernas perspektiv. Att börja så innan marken är tillräckligt fuktig kan leda till förödande konsekvenser för bönderna då grödorna riskerar att torka ut och dö, men även att vänta för länge med att så bör undvikas eftersom det påverkar längden på skördesäsongen och därmed också produktionen. I den här studien har det gjorts undersökningar om det är möjligt att göra prognoser för när regnperioden börjar i Ghana och delar av Burkina Faso med hjälp av nederbördsfördelningen och förändringar i ytvattentemperaturen i Guineabukten. Regionen har delats in i fyra lika stora områden med latitudinell bredd på 2 ° från söder till norr. Modellerna börjar med att göra en prognos för regnperiodens början i det sydligaste området med hjälp av fyra olika metoder, tre som är baserade på nederbördsfördelningen och en som är baserad på ändringar i ytvattentemperaturen. Därefter görs prognoser för de tre nordligare områdena med hjälp av en linjär funktion baserad på när regnperioden började i det sydligaste området. Resultaten visar att modellen är acceptabel när det gäller att komma så nära den verkliga starten som möjligt, men är väldigt bra på att indikera om regnperioden kommer att börja tidigare eller senare än året innan. Detta är till stor nytta för bönderna i området. Över ett längre perspektiv så börjar regnperioden först i det sydligaste området för att sedan börjar längre norrut, men så ser det inte ut i varje enskilt år, vilket gör att modellerna inte är användbara alla år. För att kunna ge bönderna så bra prognoser som möjligt så behöver regnperioden definieras så att den uppfyller de villkor som krävs för att de ska kunna börja så. Därför har regnperiodens början definierats som när 40 mm nederbörd mottagits under en femdagarsperiod med minst 16 mm under en av dessa fem dagar. Därefter får de närmaste 30 dagarna inte innehålla mer än 18 dagar utan nederbörd.

By using the finite element method to solve the appropriate momentum and energy equations the friction factors and Nusselt numbers for fully developed laminar flow were determined for one- and two-dimensional flow systems. The Nusselt numbers were determined for domain boundaries subjected to a constant heat flux (H1) or a constant surface temperature (T) around the computational boundaries and in the axial directions. C++ programs, that were rewritten and extended from previous programs, were used to solve the laminar flow and to determine the values. The required wall shear stresses and heat fluxes were directly obtained for a duct as part of the primary finite-element solution; these values were then used to determine the Nusselt number and friction factor for the specific duct. The computations were performed for circular-, annular-, trapezoidal-, rectangular- and triangular ducts. Special emphasis was placed on trapezoidal ducts since only a limited number of studies have been performed on trapezoidal duct shapes and none of these studies employed the finite element method. Excellent agreement was found when the determined values were compared with the values reported in the literature. In general, the agreement of the values improved as the number of elements was increased. It was, therefore, concluded that the methods used in this study yielded friction factors and Nusselt numbers that are very accurate and usable. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2009.

By using the finite element method to solve the appropriate momentum and energy equations the friction factors and Nusselt numbers for fully developed laminar flow were determined for one- and two-dimensional flow systems. The Nusselt numbers were determined for domain boundaries subjected to a constant heat flux (H1) or a constant surface temperature (T) around the computational boundaries and in the axial directions. C++ programs, that were rewritten and extended from previous programs, were used to solve the laminar flow and to determine the values. The required wall shear stresses and heat fluxes were directly obtained for a duct as part of the primary finite-element solution; these values were then used to determine the Nusselt number and friction factor for the specific duct. The computations were performed for circular-, annular-, trapezoidal-, rectangular- and triangular ducts. Special emphasis was placed on trapezoidal ducts since only a limited number of studies have been performed on trapezoidal duct shapes and none of these studies employed the finite element method. Excellent agreement was found when the determined values were compared with the values reported in the literature. In general, the agreement of the values improved as the number of elements was increased. It was, therefore, concluded that the methods used in this study yielded friction factors and Nusselt numbers that are very accurate and usable. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2009.

Lake surface temperature (LSTlake) can be obtained and studied in different ways: using in situ measurements, satellite imagery and modeling. Collecting spatially representative in situ data over lakes, especially for large and deep ones, is a real challenge. Satellite data products provide the opportunity to collect continuous data over very large geographic areas even in remote regions. Numerical modeling is also an approach to study the response and the role of lakes in the climate system. Satellite instruments provide spatial information unlike in situ measurements and one-dimensional (1-D) lake models that give vertical information at a single point or a few points in lakes. The advantage of remote sensing also applies to land where temperature measurements are usually taken at meteorological stations whose network is extremely sparse in northern regions. This thesis therefore examined the value of land/lake surface (skin) temperature (LSTland/lake) measurements from satellites as a complement to in situ point measurements and numerical modeling. The thesis is organized into two parts. The first part tested, two 1-D numerical models against in situ and satellite-derived LST measurements. LSTlake and ice phenology were simulated for various points at different depths on Great Slave Lake (GSL) and Great Bear Lake (GBL), two large lakes located in the Mackenzie River Basin in Canada’s Northwest Territories, using the 1-D Freshwater Lake model (FLake) and the Canadian Lake Ice Model (CLIMo) over the 2002-2010 period. Input data from three weather stations (Yellowknife, Hay River and Deline) were used for model simulations. LSTlake model results are compared to those derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Earth Observing System Terra and Aqua satellite platforms. The main goal was to examine the performance of the FLake and CLIMo models in simulating LSTlake and ice-cover under different conditions against satellite data products. Both models reveal a good agreement with daily average MODIS LSTlake from GSL and GBL on an annual basis. CLIMo showed a generally better performance than FLake for both lakes, particularly during the ice-cover season. Secondly, MODIS-derived lake and land surface temperature (LSTland/lake) products are used to analyze land and lake surface temperature patterns during the open-water and snow/ice growth seasons for the same period of time in the regions of both GBL and GSL. Land and lake temperatures from MODIS were compared with near-surface air temperature measurements obtained from nearby weather stations and with in situ temperature moorings in GBL. Results show a good agreement between satellite and in situ observations. MODIS data were found to be very useful for investigating both the spatial and temporal (seasonal) evolution of LSTland/lake over lakes and land, and for improving our understanding of thermodynamic processes (heat gains and heat loses) of the lake/land systems. Among other findings, the MODIS satellite imagery showed that the surface temperature of lakes is colder in comparison to the surrounding land from April-August and warmer from September until spring thaw.

Hydrologic and climate models predict variables through a simplification of the underlying complex natural processes. Model development involves minimising predictive uncertainty. Predictive uncertainty arises from three broad sources which are measurement error in observed responses, uncertainty of input variables and model structural error. This thesis introduces ways to improve predictive accuracy of hydroclimatic models by considering input and structural uncertainties. The specific methods developed to reduce the uncertainty because of erroneous inputs and model structural errors are outlined below. The uncertainty in hydrological model inputs, if ignored, introduces systematic biases in the parameters estimated. This thesis presents a method, known as simulation extrapolation (SIMEX), to ascertain the extent of parameter bias. SIMEX starts by generating a series of alternate inputs by artificially adding white noise in increasing multiples of the known input error variance. The resulting alternate parameter sets allow formulation of an empirical relationship between their values and the level of noise present. SIMEX is based on the theory that the trend in alternate parameters can be extrapolated back to the notional error free zone. The case study relates to erroneous sea surface temperature anomaly (SSTA) records used as input variables of a linear model to predict the Southern Oscillation Index (SOI). SIMEX achieves a reduction in residual errors from the SOI prediction. Besides, a hydrologic application of SIMEX is demonstrated by a synthetic simulation within a three-parameter conceptual rainfall runoff model. This thesis next advocates reductions of structural uncertainty of any single model by combining multiple alternative model responses. Current approaches for combining hydroclimatic forecasts are generally limited to using combination weights that remain static over time. This research develops a methodology for combining forecasts from multiple models in a dynamic setting as an improvement of over static weight combination. The model responses are mixed on a pair wise basis using mixing weights that vary in time reflecting the persistence of individual model skills. The concept is referred here as the pair wise dynamic weight combination. Two approaches for forecasting the dynamic weights are developed. The first of the two approaches uses a mixture of two basis distributions which are three category ordered logistic regression model and a generalised linear autoregressive model. The second approach uses a modified nearest neighbour approach to forecast the future weights. These alternatives are used to first combine a univariate response forecast, the NINO3.4 SSTA index. This is followed by a similar combination, but for the entire global gridded SSTA forecast field. Results from these applications show significant improvements being achieved due to the dynamic model combination approach. The last application demonstrating the dynamic combination logic, uses the dynamically combined multivariate SSTA forecast field as the basis of developing multi-site flow forecasts in the Namoi River catchment in eastern Australia. To further reduce structural uncertainty in the flow forecasts, three forecast models are formulated and the dynamic combination approach applied again. The study demonstrates that improved SSTA forecast (due to dynamic combination) in turn improves all three flow forecasts, while the dynamic combination of the three flow forecasts results in further improvements.

Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-08-14T11:48:17Z No. of bitstreams: 1 RONI VALTER DE SOUZA GUEDES - TESE (PPGMet) 2016.pdf: 13257786 bytes, checksum: 624133c9b10421f7ba2d7cf8d0eacf79 (MD5) / Made available in DSpace on 2018-08-14T11:48:17Z (GMT). No. of bitstreams: 1 RONI VALTER DE SOUZA GUEDES - TESE (PPGMet) 2016.pdf: 13257786 bytes, checksum: 624133c9b10421f7ba2d7cf8d0eacf79 (MD5) Previous issue date: 2015-12-18 / CNPq / A identificação e classificação de áreas susceptíveis à ocorrência de eventos críticos, chuvosos ou secos, tornaram-se uma necessidade frequente no contexto da variabilidade climática, responsável por muitos desastres naturais em diversos países do mundo. O diagnóstico com base nos impactos meteorológicos, agrícolas e hidrológicos pode ser aferido através de índices climáticos. O Índice de Precipitação Padronizado (SPI) foi desenvolvido para diagnosticar e categorizar a variabilidade da precipitação com base em diferentes escalas temporais. A aplicação da metodologia do SPI para 57 postos distribuídos sobre o estado de Pernambuco, Nordeste do Brasil, com séries de 1963 a 2015, foi capaz de destacar e classificar as principais anomalias das chuvas através da sua intensidade e duração. As escalas menores do SPI (mensal e trimestral) indicaram o início e tendência de cada evento; a escala semestral identificou o comportamento do período chuvoso e as escalas anual e bienal definiram os eventos mais fortes e duradouros. Foram diagnosticados eventos positivos e negativos nas categorias de fraco, moderado, severo e extremo. Foram analisados os eventos que ocorreram de forma mais generalizada e, portanto, mais significativos. Foram destacados os eventos chuvosos críticos de 1963, 1973, 1984 e os eventos secos de 1993, 1998 e 2012. A análise de agrupamento utilizando a métrica de Ward foi aplicada aos SPIs para delimitar dois grupos bem definidos para qualquer escala temporal do SPI. A divisão do estado de Pernambuco ficou assim: Grupo 1, do Litoral ao Agreste e o Grupo 2 representando todo o Sertão. Os valores das anomalias de temperatura da superfície do mar foram correlacionados com cada escala do SPI e usados como entrada nos modelos baseados em Redes Neurais Artificiais (RNA) para predizer as variações deste índice na área de estudo. Os resultados mostraram que o modelo apresentou uma boa previsão com o padrão de comportamento da escala trimestral do SPI, e não obteve o mesmo nível de desempenho para as escalas mensais e semestrais, porém, o modelo de RNA conseguiu absorver a tendência dos valores destas escalas e encontrar uma boa associação. / The identification and classification of areas susceptible to critical events be it rainy or dry events, has become a frequent need in the current context of climate variability, esponsible for natural disasters in several countries in the world. The diagnosis based on meteorological, agricultural and hydrological impacts can be measured by climatic indices. The Standardized Precipitation Index (SPI) was developed to categorize and make the diagnostic the variability of the rainfall based on different temporal scales. The application of SPI methodology to 57 stations distributed about the state of Pernambuco, Northeastern Brazil, for the years 1963 to 2015, was able to highlight and rank the main anomalies of rainfall through its intensity and duration. Smaller scales the SPI (monthly and quarterly) indicated the start and trend of each event, the semiannual scale identified the behavior of rainy period and the annual and biennial scales it defined the strongest and most enduring events. Positive and negative events were diagnosed in the scale categories: low, moderate, severe and extreme. Were analyzed the events that occurred more widely and thus more significant. Were highlighted the critical rainfall events of 1963, 1973, 1984 and the dry events of 1993, 1998, 2012. The cluster analysis using the metric of Ward was applied to SPIs to delimit the two well-defined groups to any timescale of the SPI. The division of Pernambuco state was as follows: Group 1, from Coast to Agreste and Group 2 represents the entire Sertão. The values of the temperature anomalies of the sea surface were correlated with each SPI scale and used as input in models based on Artificial Neural Networks (ANN) to predict the variations of this index in the study area. The results showed that the model had a good forecast with the standard of behavior of the quarterly SPI scale, but did not get the same level of performance for the monthly and semi-annual scales, but the model the ANN was able to absorb the trend of the values of these scales and find a good association.

Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-08-30T13:43:17Z No. of bitstreams: 1 ANA PAULA NUNES DA SILVA - TESE (PPGMet) 2016.pdf: 25525790 bytes, checksum: 973f4462b19d6c6616cfec5845906a37 (MD5) / Made available in DSpace on 2018-08-30T13:43:17Z (GMT). No. of bitstreams: 1 ANA PAULA NUNES DA SILVA - TESE (PPGMet) 2016.pdf: 25525790 bytes, checksum: 973f4462b19d6c6616cfec5845906a37 (MD5) Previous issue date: 2016-05-06 / CNPq / O objetivo deste trabalho foi verificar a ocorrência de ilha de calor urbana (ICU) e sua influência no microclima na Região Metropolitana de Macapá (RMM), situada no Nordeste da Amazônia Legal, já que esta região vem apresentando um rápido processo de urbanização. Este processo de crescimento urbano provoca mudanças na cobertura e uso do solo, que podem modificar diretamente o balanço de energia em superfície gerando modificações na atmosfera que podem variar da escala local até a regional. Para verificar o crescimento urbano da RMM utilizou-se imagens do LANDSAT TM e OLI/TIRS de cinco diferentes épocas e através da classificação supervisionada MAXVER, verificou-se a expansão da classe área construída entre 1986 e 2015, classe que subentende a malha urbana. Uma análise climática com dados de precipitação e temperatura, permitiu verificar que possivelmente a variabilidade da temperatura e precipitação encontrada deve estar mais associado com eventos como El Niño do que com mudanças climáticas, entretanto, as tendências de aquecimento observadas podem estar relacionadas com o crescimento urbano. Para entender os impactos do crescimento urbano na modificação do microclima da RMM analisou-se índices de extremos climáticos de duas estações meteorológicas: uma situada no perímetro urbano e outra numa área rural da RMM. Verificou-se que as maiores mudanças térmicas ocorreram na área mais afastada da cidade, fato devido às mudanças de uso do solo na região periférica da RMM, enquanto que os índices relacionados a precipitação foram mais significativos na área urbana. Foram instalados termo-higrômetros em quatro pontos da RMM em áreas suburbanas e rurais para analisar os índices ICU, verificou-se que o índice sazonal de ICU foi maior (menor) nos meses de março a abril (outubro a dezembro), enquanto o índice horário obteve diferentes resultados de acordo com a época do ano: no mês chuvoso (seco) foi mais intenso no início da noite (do dia) com valor para a RMM atingiram valores máximos de 6°C (4,9°C). Na análise da Ilha de Calor Urbana em Superfície (ICUS) utilizaram-se cinco imagens de satélite e se verificou que em todas as imagens houve a comprovação de ICUS com núcleos nos centros da malhas urbanas das duas cidades da RMM e num distrito situado entre os dois centros urbanos analisados. Verificando os índices de conforto térmico gerados pela formação de ICU na RMM, comprovou-se que a região central da RMM apresenta os maiores valores e, que os índices de calor e de temperatura efetiva apresentaram boa relação com a percepção térmica da população de RMM, entrando o índice de conforto humano não se mostrou aplicabilidade na região em estudo. / The goal of the this Doctoral Thesis is to verify the occurrence of the Urban Heat Island (UHI) in the Macapá Metropolitan Area (RMM) Micro climate, which is placed in the Legal Amazon Northeast, due to the fact of the fast urbanization of the area. The development of the urban areas causes changes on the cover and use of the soil which could have a direct effect on the surface energy balance that may result in atmospheric modification in a local, or even regional,scale. In order to verify the RMM urban development, were used images from LANDSAT TM and OLI/TIRS of five different periods. Therefore, through the supervised classification MAXVER, it was possible to verify a expansion of the build-up area, the class of soil that covers the urban sheet, between 1986 and 2015. A climatic Analysis containing precipitation and temperature data showed that, probably, the variation of precipitation and temperature which appeared in the numbers presented are more likely to be associated with specific events, e.g. El Niño, than with the climatic changes. How ever, the growing heat trend observed during the research may be related to the urban development. In order to understand the impact of the development of the urban areas in the modification of the RMM micro climate, extreme climatic levels from two meteorologic bases were adopted: one of the those was placed within the urban perimeter; while the other was located in the RMM rural area. The data collected showed the biggest thermal changes took place further from the city, due to changes in the use of the soil in the isolated region of the RMM. About the levels related to precipitation, they were more significant in the urban areas. Term-hygrometers were installed in four different spots of the RMM, in suburban and rural areas, with the objective of analyzing the UHI levels. It was possible to verify that the season UHI levels were bigger (smaller) between March and April (October and December). The schedule levels showed different results along the year: during the rainy month (dry) it was more intense in the beginning of night (day) reaching maximum levels, in the RMM, of 6.0ºC (4.9ºC). For the analysis of the Urban Heat Island on Surface (SUHI) 5 satellite images were used and it was possible to verify in all of them the existence of ICUS with their cores located in the center of the urban sheets of the two cities that form the RMM and in a district placed between them. Trough the verification of the heat levels generated by the UHI formation in the RMM, it was possible to probe that the central area of the RMM presents the biggest values, and the IC and ITE levels are well connected to the RMM population's thermal perception. Considering the ICH it was evident the applicability of this Thesis in the area of the research.

A geada é um fenômeno meteorológico adverso que causa perdas severas ao setor agrícola, em especial no Sul do Brasil. A baixa distribuição espacial da rede de estações meteorológicas dificulta o monitoramento e a previsão do fenômeno. O propósito principal desta tese foi o desenvolvimento de um modelo matemático para quantificar de forma direta e simples a probabilidade do risco de ocorrência de geada tendo como base em dados de fácil obtenção como altitude, latitude, continentalidade e temperatura do ar. O modelo criado, denominado Risco Geral de Geada (RGG), foi idealizado a partir de dois riscos básicos, o risco geográfico e o risco advindo da temperatura mínima do local, ambos com o mesma contribuição para a ocorrência de geada. O risco geográfico de geada (RGeo) foi obtido a partir do somatório dos riscos atribuídos aos fatores geográficos altitude, latitude e continentalidade. Cada um destes fatores contribui de forma diferente para a formação da geada e suas contribuições foram estimadas a partir de um modelo de regressão linear múltipla para a estimativa da temperatura mínima do ar climatológica de inverno no Rio Grande do Sul. No risco de geada associado à temperatura mínima (RTmín) foi feita a atribuição de riscos em um intervalo de temperatura entre 0 e 6°C. O modelo final obtido, válido apenas para o Rio Grande do Sul, foi testado com dados coletados em estações meteorológicas de superfície da mesorregião do Sudeste Rio-grandense, localizadas em Encruzilhada do Sul, Rio Grande e Santa Vitória do Palmar. Dados de temperatura mínima do ar nos meses de junho, julho e agosto, coletados entre os anos de 1961 e 2015, comprovaram a utilidade do modelo RGG para a definição da probabilidade do risco de ocorrência de geada, mesmo diante de incertezas atribuídas a outros fatores não descritos no modelo. Na região de teste também foi avaliada a qualidade de dados orbitais de temperatura da superfície terrestre (TST), obtidos do produto MDY11A1 da passagem noturna do sensor MODIS/AQUA, na detecção de temperaturas baixas relacionadas com a ocorrência de geada. A frequência de dias com TST inferiores a 3°C mostrou coerência tanto com os dados observados em estação meteorológica, quanto com o risco determinado pelo RGG. A coerência entre os resultados obtidos do modelo RGG e os dados reais observados em superfície e obtidos por satélite torna o modelo útil na descrição da probabilidade do risco de ocorrência de geada sobre o Rio Grande do Sul. / Frost is an adverse meteorological phenomenon that causes severe losses to the agricultural sector, especially in Southern Brazil. Low spatial distribution of the network of meteorological stations hinders monitoring and forecast phenomenon. The main purpose of this thesis was to develop a mathematical model to measure directly and easily the probability of the risk of frost based on readily available data such as altitude, latitude, continentality and air temperature. The model, called Frost General Risk (RGG), was designed from two basic risk, geographic risk and risk arising out of the local minimum temperature, both with the same contribution to the occurrence of frost. The geographical risk of frost (RGeo) was obtained from the sum of the risks attributed to geographical factors altitude, latitude and continental influence. Each of these factors contributes differently to the formation of frost and their contributions were estimated from a multiple linear regression model to estimate the minimum air temperature winter climatological in Rio Grande do Sul. In the frost risk associated with minimum temperature (RTmín) assigning risk was taken in a temperature range between 0 and 6° C. The final model obtained, valid only for the Rio Grande do Sul, has been tested with data collected from weather stations surface of the middle region of Sudeste Rio-grandense, located in Encruzilhada do Sul, Rio Grande and Santa Vitória do Palmar. Minimum temperature, the air in the months of june, july and august, collected between 1961 and 2015, have proved the usefulness of the model RGG to define the probability of the risk of frost, even in the face of uncertainty attributed to other factors not described in the model. In the test region was also evaluated the quality of satellite data of the land surface temperature (LST), the product obtained MDY11A1 the night passage of MODIS / AQUA sensor to detect low temperatures related to the occurrence of frost. The frequency of days with LST below 3° C showed much consistency with the observed data in weather station, and with the particular risk for the RGG. Consistency between the results obtained from the RGG model and the actual data observed in surface and from satellites makes the model useful in describing the probability of the risk of frost on the Rio Grande do Sul.

Levando em consideração a influência das variáveis meteorológicas no desenvolvimento dos cultivos e na definição do rendimento de grãos, o monitoramento da resposta da cultura da soja frente às condições ambientais se torna necessário devido sua importância tanto no cenário internacional quanto nacional. Sabe-se que para a cultura da soja, a estiagem é a causa mais frequente das perdas em safras no Rio Grande do Sul. Neste contexto, testar ferramentas de monitoramento em tempo quase real das condições hídricas das lavouras de soja ao longo do ciclo torna-se relevante e permite verificar se a cultura está em adequadas condições de crescimento e desenvolvimento. Os objetivos deste estudo foram avaliar a aptidão do índice TVDI em representar as condições de disponibilidade hídrica em áreas de cultivo de soja no Rio Grande do Sul; caracterizar e analisar a sensibilidade dos parâmetros da relação entre a temperatura de superfície (TS) e o índice de vegetação por diferença normalizada (NDVI) e, por fim, comparar as abordagens por cena e por safra no processo de parametrização do índice TVDI para a cultura da soja. Para tanto, foram utilizados os produtos MODIS TS (MOD11A2) e NDVI (MOD13A2) com resolução espacial de 1.000 m e temporal de 8 e 16 dias, respectivamente, assim como dados de precipitação pluvial de 3 estações meteorológicas localizadas na área de estudo e dados oficiais do IBGE de área e de rendimento. Os resultados mostraram que a abordagem de parametrização por cena possibilita o entendimento da distribuição espacial das condições hídricas da área de estudo frente aos limites hídricos de cada imagem. Os parâmetros "b" e “TSmin” utilizados para determinar as retas dos limites seco e úmido do triângulo evaporativo na determinação do TVDI com parametrização por cena podem auxiliar na compreensão do perfil temporal deste índice ao longo da safra. Já a parametrização por safra, mostrou aptidão do índice em representar o momento e a frequência de ocorrência de restrição hídrica ao longo do ciclo da cultura. O método do triângulo evaporativo para a obtenção do índice TVDI mostra-se eficiente, pois permite a partir de dados de sensoriamento remoto, o entendimento do padrão espacial e temporal de resposta da vegetação frente à disponibilidade hídrica, além de informações de grande utilidade para sistemas de monitoramento e estimativas de safras. / In view of the influence of meteorological variables on crop growth and grain yield, monitoring the response of soybean to different environmental conditions is essential, given the international and domestic importance of this crop. Drought is the leading cause of soybean crop losses in the Brazilian state of Rio Grande do Sul. In this context, testing tools for monitoring in near real time the water conditions of soybean fields throughout their cycle becomes relevant and allows for checking if the crop is under proper conditions for growth and development. The objectives of this study were: to assess the adequacy of the temperature–vegetation dryness index (TVDI) to represent water availability status in soybean growing areas in Rio Grande do Sul; to characterize and analyze the sensitivity of the surface temperature (TS)/normalized difference vegetation index (NDVI) ratio; and to compare the scene-specific and crop-specific approaches for parameterization of TVDI. To this end, the MODIS TS (MOD11A2) and NDVI (MOD13A2) products were used, with a spatial resolution of 1000 m and a temporal resolution of 8 and 16 days respectively, as well as precipitation data from 3 weather stations located in the study area and official area and yield data from the Brazilian Institute of Geography and Statistics (IBGE). Results showed that the scene-specific parameterization approach was able to provide an understanding of the spatial distribution of water status in the area of interest as derived from the dry and wet edges of each image. With scene-based parameterization, the “b” and “TSmin” parameters used to determine the dry and wet edges of the TS/NDVI can help elucidate the temporal profile of this index throughout the harvest period. With crop-type parameterization, the TVDI was able to represent the timing and frequency of limited water availability during the crop cycle. The triangle method proved effective in deriving the TVDI, as it provides a means of using remote sensing data to understand the spatiotemporal response pattern of vegetation to water availability, as well as other information that can be highly useful for monitoring systems and crop estimation.

Submitted by Jordan (jordanbiblio@gmail.com) on 2017-05-04T15:21:36Z No. of bitstreams: 1 DISS_2015_Heloisa Oliveira Marques.pdf: 2431288 bytes, checksum: c4ba706130378caa4ae9d3e7171b7849 (MD5) / Approved for entry into archive by Jordan (jordanbiblio@gmail.com) on 2017-05-04T15:44:04Z (GMT) No. of bitstreams: 1 DISS_2015_Heloisa Oliveira Marques.pdf: 2431288 bytes, checksum: c4ba706130378caa4ae9d3e7171b7849 (MD5) / Made available in DSpace on 2017-05-04T15:44:04Z (GMT). No. of bitstreams: 1 DISS_2015_Heloisa Oliveira Marques.pdf: 2431288 bytes, checksum: c4ba706130378caa4ae9d3e7171b7849 (MD5) Previous issue date: 2015-02-24 / CNPq / A Amazônia tem importante papel na biodiversidade,possui a maior extensão de floresta tropical úmida do planeta. Recentemente, o uso das geotecnologias possibilitaa identificação em tempo real as alterações que ocorrem na superfície terrestre, resultantes dos fenômenos naturais e vários processos antrópicos. Muitas alterações deste nível podem ser detectadas a partir do monitoramento e determinação das trocas radiativas que se processam à superfície. Neste sentido, o presente estudo objetivou-se a determinar a dinâmica do saldo da radiação à superfície por meio de imagens geradas pelo sensor TM do satélite Landsat 5, em uma Floresta de Transição entre Amazônia e Cerrado, na Fazenda Maracaí, localizada próximo a Sinop – MT; com órbita 226 e 227, ponto 68 para os anos de 2005 a 2008. Foram geradas as cartas para os índices de vegetação, albedo e temperatura da superfície, saldo de radiação instantâneo e médio diário em 24 horas, utilizando o algoritmo SEBAL. Os dados obtidos foram validados com medições realizadas na torre micrometeorológica que estava instalada na área de estudo. Foram selecionadas as imagens para cada ano analisado, para melhor avaliar os fluxos radiativos e as estimativas daquele ambiente. Identificou-se menor valor para o saldo de radiação instantâneo durante o período seco, devido as névoa seca decorrente de queimadas no local. Para o Rninst e Rn24h à superfície, com relação aos dados medidos, foram obtidos os seguintes erros médios relativos e absolutos com valores de 2,4% e 2,0 %; 18,2 Wm-2 e 14,3 Wm-2; com “r” de 0,938 e 0,604 e “d” de 0,966 e 0,703 respectivamente. De acordo com os resultados obtidos neste trabalho pode-se afirmar que a metodologia para estimativa do Rn foi eficaz. / The Amazon has an important role in biodiversity, has the largest expanse of tropical rainforest in the world. Recently, the use of geotechnologies possible to identify in real time the changes that occur in the Earth's surface, resulting from natural and anthropogenic processes several phenomena. Many changes of this level can be detected by monitoring and determination of radiative exchanges that take place on the surface. In this sense, the present study aimed to determine the dynamics of the balance of radiation to the surface by means of images generated by the satellite Landsat 5 TM sensor in a Transition Forest between Amazon and Cerrado, in Maracaí Farm, located near Sinop - MT; orbit with 226 and 227, paragraph 68 for the years 2005 to 2008 were generated letters to vegetation indices, albedo and surface temperature, instantaneous radiation balance and average daily in 24 hours using the SEBAL algorithm. The data were validated with measurements carried out in micrometeorological tower that was installed in the study area. Images for each year analyzed, to better evaluate the radiative fluxes and estimates that environment selected. One can see smaller value for the balance of instantaneous radiation during the dry season, due to haze resulting from burned on site. For Rninst and Rn24h the surface with respect to the measured data were obtained the following relative and absolute mean errors with values of 2,4% and 2,0%; 18,2 Wm-2 and 14,3 Wm-2; "r", and 0,604 to 0,938 and "d" of 0.966 and 0.703 respectively. According to the results obtained in this work can be said that the methodology for estimation of Rn was effective.