<p> This thesis provides a means of measuring the type and number of livestock on a given farm in southern Ontario using as a data base aerial photographs of medium scale. The feasibility of making such measurements is shown to be an extension of past work in the field of agricultural air photo interpretation. The methodology is presented in the form of a model. The inputs from aerial photographs are crop acreages, building type and dimensions, and silo sizes. Average yields in each study area, in combination with crop acreage gives feed available. A comparison is made between feed weight and housing space available and required feed weights and stabling facilities (taken as constants in southern Ontario) to support cattle of a given type. This comparison technique, within the model, yields an output of farm type and actual numbers of cattle. The accuracy of prediction so obtained is high and is independent of the location or attributes of the widely spaced sample areas.</p> / Thesis / Master of Arts (MA)

Thesis (M.Sc. (Soil Science)) --University of Limpopo, 2001 / Refer to document

The current study has been conducted in response to the growing problem of water scarcity and the need for more effective methods of irrigation water management. Remote sensing techniques have been used to match spatially and temporally distributed crop water demand to water application rates. Remote sensing approaches using Landsat imagery have been applied to estimate the components of a soil water balance model for an agricultural field by determining daily values of surface/root-zone soil moisture, evapotranspiration rates, and losses and by developing a forecasting model to generate optimal irrigation application information on a daily basis. Incompatibility of coarse resolution Landsat imagery (30m by 30m) with heterogeneities within the agricultural field and potential underestimation of field variations led the study to its main objective, which was to develop models capable of representing spatial and temporal variations within the agricultural field at a compatible resolution with farming management activities. These models support establishing real-time management of irrigation water scheduling and application. The AggieAirTM Minion autonomous aircraft is a remote sensing platform developed by the Utah Water Research Laboratory at Utah State University. It is a completely autonomous airborne platform that captures high-resolution multi-spectral images in the visual, near infrared, and thermal infrared bands at 15cm resolution. AggieAir flew over the study area on four dates in 2013 that were coincident with Landsat overflights and provided similar remotely sensed data at much finer resolution. These data, in concert with state-of-the-art supervised learning machine techniques and field measurements, have been used to model surface and root zone soil volumetric water content at 15cm resolution. The information provided by this study has the potential to give farmers greater precision in irrigation water allocation and scheduling.

Η σύγχρονη υφαλοκρηπίδα διατηρεί πολύτιμα αρχεία καταγραφής της ανθρώπινης ιστορίας, ως συνέπεια της επίκλυσης της θάλασσας σε μεγάλο τμήμα της χέρσου μετά το τέλος της τελευταίας παγετωνικής περιόδου. Επιπλέον, ο θαλάσσιος πυθμένας βρίθει ενδείξεων για τις ναυτικές δραστηριότητες του παρελθόντος, συχνά σε βάθη που ξεπερνούν το ανώτατο όριο αυτόνομης κατάδυσης. Οι θαλάσσιες γεωφυσικές μέθοδοι εφαρμόζονται με επιτυχία στην ενάλια αρχαιολογία, καταργώντας τους περιορισμούς και απλοποιώντας σημαντικά τις συμβατικές μεθόδους υποβρύχιας έρευνας. Συγκεκριμένα, χρησιμοποιούνται στον ακριβή εντοπισμό σε οποιοδήποτε βάθος και στη λεπτομερή χαρτογράφηση σε σύντομο χρονικό διάστημα (α) αρχαίων ναυαγίων και (β) καταβυθισμένων ανθρωπογενών κατασκευών και παλαιοακτών στην επιφάνεια του πυθμένα ή θαμμένων κάτω από χαλαρά ιζήματα. Μέσω αυτών επιτυγχάνεται η παλαιογεωγραφική ανάπλαση παράκτιων περιοχών. Στην παρούσα εργασία παρουσιάζονται τα προκαταρκτικά αποτελέσματα της θαλάσσιας γεωφυσικής έρευνας που πραγματοποίησε το 2012 το Ε.ΘΑ.ΓΕ.Φ.Ω. του Πανεπιστημίου Πατρών στον κόλπο Caska της νήσου Pag στην Κροατία, με τη χρήση τομογράφου υποδομής πυθμένα 3.5kHz υψηλής διακριτικής ικανότητας και ηχοβολιστή πλευρικής σάρωσης E.G&G 272TD διπλής συχνότητας (100 & 500 kHz), στο πλαίσιο του γεω-αρχαιολογικού ερευνητικού προγράμματος “Cissa Antiqua” που διεξάγει το Πανεπιστήμιο του Zadar σε συνεργασία με το Centre Camille Jullian (CNRS). Στις σεισμικές τομογραφίες αναγνωρίστηκαν τρεις σεισμικές ενότητες πρόσφατων ιζημάτων πάχους 12μ. που επικάθονται στο ήπια πτυχωμένο γεωλογικό υπόβαθρο. Σύμφωνα με τη σεισμική στρωματογραφία και τη σύγχρονη παράκτια γεωμορφολογία της περιοχής, προτείνεται η ύπαρξη συνθηκών απόθεσης γλυκού και υφάλμυρου νερού πριν από τη σταδιακή επίκλυση της θάλασσας στον κόλπο της Caska κατά το Ολόκαινο. Επιπλέον, τα τελευταία 2.000 χρόνια διαπιστώνεται στην περιοχή μια επεισοδιακή συν-σεισμική καταβύθιση. Τέλος, η ταξινόμηση με το λογισμικό TargAn και η στατιστική ανάλυση των στόχων που αναγνωρίστηκαν στην επιφάνεια του πυθμένα, ανέδειξε έξι στόχους πιθανού αρχαιολογικού ενδιαφέροντος που προτείνονται για οπτική επαλήθευση. / Marine geophysical techniques can be successfully applied to underwater archaeology, speeding up survey and making it possible to detect features of archaeological interest lying on the seafloor or embedded in sediments even beyond conventional diving limits. There are two general approaches regarding the application of these techniques in underwater archaeology: they are being used to identify, locate and map (a) ancient shipwrecks and (b) submerged sites of archaeological interest (ancient settlements, ports, man-made structures and palaeo-shorelines), thus enabling the palaeogeographic reconstruction of coastal areas. The applicability of marine remote sensing techniques in underwater archaeology is high-lighted through the current study case. In the framework of the geo-archaeological research project “Cissa Antiqua”, directed by the University of Zadar and Centre Camille Jullian (CNRS) a detailed marine remote sensing survey was carried out by the Laboratory of Marine Geology and Physical Oceanography of the University of Patras in Caska bay, Pag island, Croatia. The data collected by high resolution 3.5kHz subbottom profiling and towed E.G&G dual frequency (100 & 500kHz) side-scan sonar system have been analysed for the objectives of this study. According to the 3.5kHz profiles, the upper 12m of sediments consist of three distinct seismic sequences overlapping the gentle folded acoustic basement. The results of the seismic data in correlation to the present coastal geomorphology of the area suggest that these sequences correspond to phases of inundation by brackish water, before sea-water flooded the gulf, as consequence of the rapid sea-level rise of the Holocene. Furthermore, archaeological and geological data of the area suggest an episodical co-seismic submergence during the last 2 kyrs. The side-scan sonar survey revealed a large number of targets lying on the seafloor. Six of them have been selected by TargaAn software as targets of potential archaeological interest.

Thesis (PhD. (Geography)) --University of Limpopo, 2019 / Of late climate change and consequently, the spread of crop diseases has been identified as one of the major threat to crop production and food security in subSaharan Africa. This research, therefore, aims to evaluate the role of in situ hyperspectral and new generation multispectral data in detecting maize crop viral and fungal diseases, that is maize streak virus and grey leaf spot respectively. To accomplish this objective; a comparison of two variable selection techniques (Random Forest’s Forward Variable, (FVS) and Guided Regularized Random Forest: (GRRF) was done in selecting the optimal variables that can be used in detecting maize streak virus disease using in-situ resampled hyperspectral data. The findings indicated that the GRRF model produced high classification accuracy (91.67%) whereas the FVS had a slightly lower accuracy (87.60%) based on Hymap when compared to the AISA. The results have shown that the GRRF algorithm has the potential to select compact feature sub sets, and the accuracy performance is better than that of RF’s variable selection method. Secondly, the utility of remote sensing techniques in detecting the geminivirus infected maize was evaluated in this study based on experiments in Ofcolaco, Tzaneen in South Africa. Specifically, the potential of hyperspectral data in detecting different levels of maize infected by maize streak virus (MSV) was tested based on Guided Regularized Random Forest (GRRF). The findings illustrate the strength of hyperspectral data in detecting different levels of MSV infections. Specifically, the GRRF model was able to identify the optimal bands for detecting different levels of maize streak disease in maize. These bands were allocated at 552 nm, 603 nm, 683 nm, 881 nm, and 2338 nm. This study underscores the potential of using remotely sensed data in the accurate detection of maize crop diseases such as MSV and its severity which is critical in crop monitoring to foster food security, especially in the resource-limited subSaharan Africa. The study then investigated the possibility to upscale the previous findings to space borne sensor. RapidEye data and derived vegetation indices were tested in detecting and mapping the maize streak virus. The results revealed that the use of RapidEye spectral bands in detection and mapping of maize streak virus disease yielded good classification results with an overall accuracy of 82.75%. The inclusion of RapidEye derived vegetation indices improved the classification accuracies by 3.4%. Due to the cost involved in acquiring commercial images, like xviii RapidEye, a freely available Landsat-8 data can offer a new data source that is useful for maize diseases estimation, in environments which have limited resources. This study investigated the use of Landsat 8 and vegetation indices in estimating and predicting maize infected with maize streak virus. Landsat 8 data produced an overall accuracy of 50.32%. The inclusion of vegetation indices computed from Landsat 8 sensor improved the classification accuracies by 1.29%. Overally, the findings of this study provide the necessary insight and motivation to the remote sensing community, particularly in resource-constrained regions, to shift towards embracing various indices obtained from the readily-available and affordable multispectral Landsat-8 OLI sensor. The results of the study show that the mediumresolution multispectral Landsat 8-OLI data set can be used to detect and map maize streak virus disease. This study demonstrates the invaluable potential and strength of applying the readily-available medium-resolution, Landsat-8 OLI data set, with a large swath width (185 km) in precisely detecting and mapping maize streak virus disease. The study then examined the influence of climatic, environmental and remotely sensed variables on the spread of MSV disease on the Ofcolaco maize farms in Tzaneen, South Africa. Environmental and climatic variables were integrated together with Landsat 8 derived vegetation indices to predict the probability of MSV occurrence within the Ofcolaco maize farms in Limpopo, South Africa. Correlation analysis was used to relate vegetation indices, environmental and climatic variables to incidences of maize streak virus disease. The variables used to predict the distribution of MSV were elevation, rainfall, slope, temperature, and vegetation indices. It was found that MSV disease infestation is more likely to occur on low-lying altitudes and areas with high Normalised Difference Vegetation Index (NDVI) located at an altitude ranging of 350 and 450 m.a.s.l. The suitable areas are characterized by temperatures ranging from 24°C to 25°C. The results indicate the potential of integrating Landsat 8 derived vegetation indices, environmental and climatic variables to improve the prediction of areas that are likely to be affected by MSV disease outbreaks in maize fields in semi-arid environments. After realizing the potential of remote sensing in detecting and predicting the occurrence of maize streak virus disease, the study further examined its potential in mapping the most complex disease; Grey Leaf Spot (GLS) in maize fields using WorldView-2, Quickbird, RapidEye, and Sentinel-2 resampled from hyperspectral data. To accomplish this objective, field spectra were acquired from healthy, moderate and xix severely infected maize leaves during the 2013 and 2014 growing seasons. The spectra were then resampled to four sensor spectral resolutions – namely WorldView-2, Quickbird, RapidEye, and Sentinel-2. In each case, the Random Forest algorithm was used to classify the 2013 resampled spectra to represent the three identified disease severity categories. Classification accuracy was evaluated using an independent test dataset obtained during the 2014 growing season. Results showed that Sentinel-2 achieved the highest overall accuracy (84%) and kappa value (0.76), while the WorldView-2, produced slightly lower accuracies. The 608 nm and 705nm were selected as the most valuable bands in detecting the GLS for Worldview 2, and Sentinel-2. Overall, the results imply that opportunities exist for developing operational remote sensing systems for detection of maize disease. Adoption of such remote sensing techniques is particularly valuable for minimizing crop damage, improving yield and ensuring food security.

Submitted by Mariana Dornelles Vargas (marianadv) on 2015-03-18T11:55:37Z No. of bitstreams: 1 estimativa_stress.pdf: 6383745 bytes, checksum: b75cefd5d9b805b18bd9e34bd4e507b6 (MD5) / Made available in DSpace on 2015-03-18T11:55:37Z (GMT). No. of bitstreams: 1 estimativa_stress.pdf: 6383745 bytes, checksum: b75cefd5d9b805b18bd9e34bd4e507b6 (MD5) Previous issue date: 2008 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A evapotranspiração compreende trocas hídricas no sistema solo - planta - atmosfera, as quais ocorrem como resposta à demanda evaporativa atmosférica. Neste processo, o solo atua como fonte de abastecimento de água, a vegetação corresponde ao compartimento intermediário, enquanto a atmosfera é o destino final da umidade liberada na forma de vapor. A eventual escassez hídrica do solo reflete-se nos processos ecofisiológicos das plantas, cuja resposta é o fechamento dos estômatos como forma de evitar o ressecamento e a morte do tecido vegetal. Não havendo transpiração foliar, parte da energia absorvida do sol é convertida para a forma de calor, elevando-se a temperatura das folhas. Este fenômeno permite detectar o stress hídrico (SH) através das variações de temperatura da vegetação (Tv), aqui utilizando-se para isto imagens AVHRR - NOAA (espectro termal) e sua correlação com a cobertura vegetal (espectro visível e infra-vermelho próximo). Foram gerados um total de 10 mapas regionais de SH nos anos 2003 e 2005, nos quais cinco deles do ano 2005 estão vinculados e validados com dados de 5 estações meteorológicas da rede do Centro de Previsão do Tempo e Estudos Climáticos do Instituto Nacional de Pesquisas Espaciais (CPTEC - INPE). Além disso se geraram 10 mapas de SH da Bacia Hidrográfica do Rio dos Sinos (BHRS), relacionados com dados de precipitação da Estação Meteorológica Campo Bom do Instituto Nacional de Meteorologia (INMET). Os resultados mostraram uma disparidade na distribuição do SH tanto a nível regional (Rio Grande do Sul (RS)) como na BHRS, com zonas de stress hídrico permanentemente alto o baixo independente dos valores de precipitação (PPT), e umbrais de máximos e mínimos SH, o que indicaria a presença de condicionantes ambientais naturais na área de estudo. / The evapotranspiration includes hydrous interchanges between ground-plant-atmosphere, which is possible as a reply from a evaporative atmospheric demand. In this process, the ground is like a spring of water providing, the vegetation is an intermediate compartment, and the atmosphere is the place where an unit is liberated like vapor. The eventual scarcity of ground water is reflected in plant's physiologic process, which close its stomas to avoid getting dirty and the eventually vegetation tissue decease. Without foliage transpiration, some of the sun ´s energy is absorbed becoming heat, increasing the leaf´ s temperature. This phenomenon allows to detect the hydro stress through change of vegetation ´s temperature using AVHRR-NOAA satellite images (thermal spectrum) and its correlation with the vegetation cover (nearly visible and infrared spectrum). Between 2003 and 2005 10 hydro stress regional maps were made, which five ones were in 2005 and are entailed and validated with dates from five meteorological stations of Weather ´s Foresight Center & Climates Studies of Brazilian Space Investigation National Institute (CPTEC-INPE). Also, from the Hydrographic dos Sinos Basin 10 hydro stress maps were made relating to rain fall dates from Campo Bon Meteorological Station of Meteorology National Institute (INMET). Results show disparity on hydro stress distribution as many on regional level (Rio Grande do Sul (RS)) as on Hydrographic dos Sinos Basin, which permanent high or low levels zones of hydric stress, independent from rain fall values, and minimum and maximum hydro stress threshold, which indicate natural environment conditioning in the study area.

MEnv.Sc / Department of Geography and Geo-Information Sciences

A gestão de recursos hídricos tornou-se cada vez mais complexa devido ao rápido crescimento sócio-econômico e as mudanças ambientais nas bacias hidrográficas nas últimas décadas. Modelos computacionais são importantes ferramentas de suporte na gestão de recursos hídricos e tomada de decisões devido a sua funcionalidade, provendo informações importantes sobre os principais processos físicos, químicos e biológicos, e permitindo melhorar o entendimento desses processos, os quais ocorrem em diferentes escalas espaciais e temporais. Na presente tese, o objetivo foi compreender o funcionamento hidrológico do sistema integrado bacia hidrográfica - lagoa, e os efeitos na hidrodinâmica do lago, utilizando como suporte o acoplamento da modelagem hidrológica - hidrodinâmica, e o uso de técnicas de sensoriamento remoto para o monitoramento de parâmetros de qualidade da água (e.g., clorofilaa, temperatura da superfície d’água e níveis da água). A área de estudo é a bacia hidrográfica da Lagoa Mirim, localizada no sul do Brasil, possuindo uma área total de 58.000 km2 (56% no Uruguai e o restante no Brasil). Foram propostos e testados modelos empíricos para estimativa de clorofila-a emumlago raso subtropical, baseados em imagens do sensor MODIS e técnicas estatísticas. Além disso, foi desenvolvido e avaliado o acoplamento da modelagem hidrológica-hidrodinâmica de grande escala e o sensoriamento remoto. O modelo hidrológico distribuído de grande escala MGBIPH acoplado com o modelo hidrodinâmico IPH-ECO foi utilizado para simular a bacia hidrográfica e os principais componentes hidrodinâmicos da Lagoa Mirim. O modelo mostrou bom desempenho quando comparado com observações de vazões, além de dados provenientes de sensoriamento remoto, através de altimetria espacial. As simulações mostraram importantes aspectos sobre a estrutura de fluxo, campos de velocidade e níveis d’água na lagoa, assim como a influência de grandes rios, forçantes externas como o vento (intensidade e direção) e o impacto do estressor antrópico (retiradas para irrigação) no sistema. As simulações permitiram avaliar aspectos relacionados com as variações espaciais e temporais (diurna, mensal, sazonal e inter-anual) da temperatura da superfície da água, a dinâmica dos fluxos de calor (sensível e latente) e os efeitos de eventos meteorológicos de pequena escala como frentes frias, os quais têm um impacto significativo sobre a temperatura superficial da água e os fluxos de calor na lagoa. Quanto aos modelos empíricos para estimativa de clorofila-a a partir do MODIS, os resultados mostram que um simples e eficiente modelo desenvolvido a partir de análise de regressão múltipla, apresentou ligeiras vantagens sobre os modelos de redes neurais artificiais, modelos multiplicativos não paramétricos e modelos empíricos (e.g., Appel, Kahru, FAI e O14a) usualmente utilizados na estimativa de Chl-a em ambientes aquáticos. Resultados também indicam que é inapropriado generalizar um único modelo desenvolvido a partir do conjunto total de dados, para estimar concentrações de Chl-a na lagoa, o que corrobora a heterogeneidade espacial na distribuição de Chl-a e as diferenças entre regiões (litoral e pelágica). A modelagem hidrológica-hidrodinâmica de grande escala apoiada por informação de sensoriamento remoto, mostrou ser uma abordagem promissora para o entendimento da estrutura e funcionamento de lagoas rasas de grande porte e longo prazo, úteis para a gestão integrada dos recursos hídricos. / The last decade, the water resource management is being complex due to the rapid socioeconomic development and environmental changes in river basins. Computations models are important support tools in water resource management and make decision providing important information and allowing a better comprehension of the physical, chemical and biologic processes, which occur in di erent temporal/spatial scales. In this thesis, the objective was to understand the hydrological functioning of the integrated basin- lake system and its e ects on hydrodynamics, using hydrodynamic - hydrodynamic modeling and water quality monitoring (e.g., chlorophyll-a, water surface temperature and water levels) from remote sensing techniques. The study area is the Lake Mirim basin, located between Brazil and Uruguay (basin total area 58.000 km2). Empirical models were proposed and tested to chlorophyll-a estimation in a shallow subtropical lake, based on MODIS imagery and statistics techniques. In addition, we developed and assessed the coupling of large scale hydrological/hydrodynamic modeling and remote sensing techniques. The large-scale distributed hydrological model MGB-IPH coupled with the hydrodynamic model IPHECO were used to simulate the river basin and the hydrodynamic components of the Lake Mirim. The coupled model showed good performance when compared to in-situ measurements and satellite altimetry data. The simulations showed important aspects relate to flow structure, velocity fields and lake water levels, as well as the influence of large rivers, external forcing as such the wind (intensity and direction), and the impact of anthropogenic stressors (irrigation withdrawals) in the system. The simulations allowed assessing the spatial and temporal variations (diurnal, monthly, seasonal and inter-annual) in the water surface temperature, heat fluxes dynamics (sensible and latent) and the e ects of short time-scale events, as such cold fronts passages over the lake, which cause strong impacts on the water surface temperature and heat fluxes in the lake. Regarding the empirical models developed to chlorophyll-a estimation from MODIS imagery, the results showed that a simple and e cient model developed from multiple regression analysis, performed best in comparison with artificial neural network models, non-parametric multiplicative models, and empirical models (e.g., Appel, Kahru, FAI and O14a) common used in the Chl-a estimation in aquatics environments. Results also indicated that is inappropriate to generalize a single model developed from the total datasets to estimates Chl-a in the lake, which corroborates the spatial heterogeneity (Chl-a distribution) and the di erences among regions (littoral and pelagic). The synergy between large-scale hydrological-hydrodynamic modeling, in situ measurements and remote sensing techniques provided a promising approach to improve the comprehension of the structure and ecosystem functioning of large shallow lakes in long-term time scale, useful to water resources management.

A gestão de recursos hídricos tornou-se cada vez mais complexa devido ao rápido crescimento sócio-econômico e as mudanças ambientais nas bacias hidrográficas nas últimas décadas. Modelos computacionais são importantes ferramentas de suporte na gestão de recursos hídricos e tomada de decisões devido a sua funcionalidade, provendo informações importantes sobre os principais processos físicos, químicos e biológicos, e permitindo melhorar o entendimento desses processos, os quais ocorrem em diferentes escalas espaciais e temporais. Na presente tese, o objetivo foi compreender o funcionamento hidrológico do sistema integrado bacia hidrográfica - lagoa, e os efeitos na hidrodinâmica do lago, utilizando como suporte o acoplamento da modelagem hidrológica - hidrodinâmica, e o uso de técnicas de sensoriamento remoto para o monitoramento de parâmetros de qualidade da água (e.g., clorofilaa, temperatura da superfície d’água e níveis da água). A área de estudo é a bacia hidrográfica da Lagoa Mirim, localizada no sul do Brasil, possuindo uma área total de 58.000 km2 (56% no Uruguai e o restante no Brasil). Foram propostos e testados modelos empíricos para estimativa de clorofila-a emumlago raso subtropical, baseados em imagens do sensor MODIS e técnicas estatísticas. Além disso, foi desenvolvido e avaliado o acoplamento da modelagem hidrológica-hidrodinâmica de grande escala e o sensoriamento remoto. O modelo hidrológico distribuído de grande escala MGBIPH acoplado com o modelo hidrodinâmico IPH-ECO foi utilizado para simular a bacia hidrográfica e os principais componentes hidrodinâmicos da Lagoa Mirim. O modelo mostrou bom desempenho quando comparado com observações de vazões, além de dados provenientes de sensoriamento remoto, através de altimetria espacial. As simulações mostraram importantes aspectos sobre a estrutura de fluxo, campos de velocidade e níveis d’água na lagoa, assim como a influência de grandes rios, forçantes externas como o vento (intensidade e direção) e o impacto do estressor antrópico (retiradas para irrigação) no sistema. As simulações permitiram avaliar aspectos relacionados com as variações espaciais e temporais (diurna, mensal, sazonal e inter-anual) da temperatura da superfície da água, a dinâmica dos fluxos de calor (sensível e latente) e os efeitos de eventos meteorológicos de pequena escala como frentes frias, os quais têm um impacto significativo sobre a temperatura superficial da água e os fluxos de calor na lagoa. Quanto aos modelos empíricos para estimativa de clorofila-a a partir do MODIS, os resultados mostram que um simples e eficiente modelo desenvolvido a partir de análise de regressão múltipla, apresentou ligeiras vantagens sobre os modelos de redes neurais artificiais, modelos multiplicativos não paramétricos e modelos empíricos (e.g., Appel, Kahru, FAI e O14a) usualmente utilizados na estimativa de Chl-a em ambientes aquáticos. Resultados também indicam que é inapropriado generalizar um único modelo desenvolvido a partir do conjunto total de dados, para estimar concentrações de Chl-a na lagoa, o que corrobora a heterogeneidade espacial na distribuição de Chl-a e as diferenças entre regiões (litoral e pelágica). A modelagem hidrológica-hidrodinâmica de grande escala apoiada por informação de sensoriamento remoto, mostrou ser uma abordagem promissora para o entendimento da estrutura e funcionamento de lagoas rasas de grande porte e longo prazo, úteis para a gestão integrada dos recursos hídricos. / The last decade, the water resource management is being complex due to the rapid socioeconomic development and environmental changes in river basins. Computations models are important support tools in water resource management and make decision providing important information and allowing a better comprehension of the physical, chemical and biologic processes, which occur in di erent temporal/spatial scales. In this thesis, the objective was to understand the hydrological functioning of the integrated basin- lake system and its e ects on hydrodynamics, using hydrodynamic - hydrodynamic modeling and water quality monitoring (e.g., chlorophyll-a, water surface temperature and water levels) from remote sensing techniques. The study area is the Lake Mirim basin, located between Brazil and Uruguay (basin total area 58.000 km2). Empirical models were proposed and tested to chlorophyll-a estimation in a shallow subtropical lake, based on MODIS imagery and statistics techniques. In addition, we developed and assessed the coupling of large scale hydrological/hydrodynamic modeling and remote sensing techniques. The large-scale distributed hydrological model MGB-IPH coupled with the hydrodynamic model IPHECO were used to simulate the river basin and the hydrodynamic components of the Lake Mirim. The coupled model showed good performance when compared to in-situ measurements and satellite altimetry data. The simulations showed important aspects relate to flow structure, velocity fields and lake water levels, as well as the influence of large rivers, external forcing as such the wind (intensity and direction), and the impact of anthropogenic stressors (irrigation withdrawals) in the system. The simulations allowed assessing the spatial and temporal variations (diurnal, monthly, seasonal and inter-annual) in the water surface temperature, heat fluxes dynamics (sensible and latent) and the e ects of short time-scale events, as such cold fronts passages over the lake, which cause strong impacts on the water surface temperature and heat fluxes in the lake. Regarding the empirical models developed to chlorophyll-a estimation from MODIS imagery, the results showed that a simple and e cient model developed from multiple regression analysis, performed best in comparison with artificial neural network models, non-parametric multiplicative models, and empirical models (e.g., Appel, Kahru, FAI and O14a) common used in the Chl-a estimation in aquatics environments. Results also indicated that is inappropriate to generalize a single model developed from the total datasets to estimates Chl-a in the lake, which corroborates the spatial heterogeneity (Chl-a distribution) and the di erences among regions (littoral and pelagic). The synergy between large-scale hydrological-hydrodynamic modeling, in situ measurements and remote sensing techniques provided a promising approach to improve the comprehension of the structure and ecosystem functioning of large shallow lakes in long-term time scale, useful to water resources management.

A gestão de recursos hídricos tornou-se cada vez mais complexa devido ao rápido crescimento sócio-econômico e as mudanças ambientais nas bacias hidrográficas nas últimas décadas. Modelos computacionais são importantes ferramentas de suporte na gestão de recursos hídricos e tomada de decisões devido a sua funcionalidade, provendo informações importantes sobre os principais processos físicos, químicos e biológicos, e permitindo melhorar o entendimento desses processos, os quais ocorrem em diferentes escalas espaciais e temporais. Na presente tese, o objetivo foi compreender o funcionamento hidrológico do sistema integrado bacia hidrográfica - lagoa, e os efeitos na hidrodinâmica do lago, utilizando como suporte o acoplamento da modelagem hidrológica - hidrodinâmica, e o uso de técnicas de sensoriamento remoto para o monitoramento de parâmetros de qualidade da água (e.g., clorofilaa, temperatura da superfície d’água e níveis da água). A área de estudo é a bacia hidrográfica da Lagoa Mirim, localizada no sul do Brasil, possuindo uma área total de 58.000 km2 (56% no Uruguai e o restante no Brasil). Foram propostos e testados modelos empíricos para estimativa de clorofila-a emumlago raso subtropical, baseados em imagens do sensor MODIS e técnicas estatísticas. Além disso, foi desenvolvido e avaliado o acoplamento da modelagem hidrológica-hidrodinâmica de grande escala e o sensoriamento remoto. O modelo hidrológico distribuído de grande escala MGBIPH acoplado com o modelo hidrodinâmico IPH-ECO foi utilizado para simular a bacia hidrográfica e os principais componentes hidrodinâmicos da Lagoa Mirim. O modelo mostrou bom desempenho quando comparado com observações de vazões, além de dados provenientes de sensoriamento remoto, através de altimetria espacial. As simulações mostraram importantes aspectos sobre a estrutura de fluxo, campos de velocidade e níveis d’água na lagoa, assim como a influência de grandes rios, forçantes externas como o vento (intensidade e direção) e o impacto do estressor antrópico (retiradas para irrigação) no sistema. As simulações permitiram avaliar aspectos relacionados com as variações espaciais e temporais (diurna, mensal, sazonal e inter-anual) da temperatura da superfície da água, a dinâmica dos fluxos de calor (sensível e latente) e os efeitos de eventos meteorológicos de pequena escala como frentes frias, os quais têm um impacto significativo sobre a temperatura superficial da água e os fluxos de calor na lagoa. Quanto aos modelos empíricos para estimativa de clorofila-a a partir do MODIS, os resultados mostram que um simples e eficiente modelo desenvolvido a partir de análise de regressão múltipla, apresentou ligeiras vantagens sobre os modelos de redes neurais artificiais, modelos multiplicativos não paramétricos e modelos empíricos (e.g., Appel, Kahru, FAI e O14a) usualmente utilizados na estimativa de Chl-a em ambientes aquáticos. Resultados também indicam que é inapropriado generalizar um único modelo desenvolvido a partir do conjunto total de dados, para estimar concentrações de Chl-a na lagoa, o que corrobora a heterogeneidade espacial na distribuição de Chl-a e as diferenças entre regiões (litoral e pelágica). A modelagem hidrológica-hidrodinâmica de grande escala apoiada por informação de sensoriamento remoto, mostrou ser uma abordagem promissora para o entendimento da estrutura e funcionamento de lagoas rasas de grande porte e longo prazo, úteis para a gestão integrada dos recursos hídricos. / The last decade, the water resource management is being complex due to the rapid socioeconomic development and environmental changes in river basins. Computations models are important support tools in water resource management and make decision providing important information and allowing a better comprehension of the physical, chemical and biologic processes, which occur in di erent temporal/spatial scales. In this thesis, the objective was to understand the hydrological functioning of the integrated basin- lake system and its e ects on hydrodynamics, using hydrodynamic - hydrodynamic modeling and water quality monitoring (e.g., chlorophyll-a, water surface temperature and water levels) from remote sensing techniques. The study area is the Lake Mirim basin, located between Brazil and Uruguay (basin total area 58.000 km2). Empirical models were proposed and tested to chlorophyll-a estimation in a shallow subtropical lake, based on MODIS imagery and statistics techniques. In addition, we developed and assessed the coupling of large scale hydrological/hydrodynamic modeling and remote sensing techniques. The large-scale distributed hydrological model MGB-IPH coupled with the hydrodynamic model IPHECO were used to simulate the river basin and the hydrodynamic components of the Lake Mirim. The coupled model showed good performance when compared to in-situ measurements and satellite altimetry data. The simulations showed important aspects relate to flow structure, velocity fields and lake water levels, as well as the influence of large rivers, external forcing as such the wind (intensity and direction), and the impact of anthropogenic stressors (irrigation withdrawals) in the system. The simulations allowed assessing the spatial and temporal variations (diurnal, monthly, seasonal and inter-annual) in the water surface temperature, heat fluxes dynamics (sensible and latent) and the e ects of short time-scale events, as such cold fronts passages over the lake, which cause strong impacts on the water surface temperature and heat fluxes in the lake. Regarding the empirical models developed to chlorophyll-a estimation from MODIS imagery, the results showed that a simple and e cient model developed from multiple regression analysis, performed best in comparison with artificial neural network models, non-parametric multiplicative models, and empirical models (e.g., Appel, Kahru, FAI and O14a) common used in the Chl-a estimation in aquatics environments. Results also indicated that is inappropriate to generalize a single model developed from the total datasets to estimates Chl-a in the lake, which corroborates the spatial heterogeneity (Chl-a distribution) and the di erences among regions (littoral and pelagic). The synergy between large-scale hydrological-hydrodynamic modeling, in situ measurements and remote sensing techniques provided a promising approach to improve the comprehension of the structure and ecosystem functioning of large shallow lakes in long-term time scale, useful to water resources management.