Orientador: Paulo Jose Rocha de Albuquerque / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e Urbanismo / Made available in DSpace on 2018-08-27T16:49:40Z (GMT). No. of bitstreams: 1 Garcia_JeanRodrigo_D.pdf: 14218038 bytes, checksum: cdf7e3c252a38593da86399a1b22a73a (MD5) Previous issue date: 2015 / Resumo: Nesta pesquisa, analisou-se o comportamento de quatro radiers estaqueados, executados a partir de conjuntos de blocos compostos por estacas mecanicamente escavadas a trado, com 5 m de comprimento e 0,25 m de diâmetro (D), executados em solo de diabásio da região de Campinas/SP. Para tanto, foram executados blocos de fundação tipo radier estaqueado, compostos de uma, duas, três e quatro estacas, espaçadas de 5D. Esses blocos de fundação foram ensaiados a partir de provas de carga do tipo estática e lenta (SML), seguindo as prescrições da NBR12131/2006. As estacas foram instrumentadas em profundidade com strain-gages posicionados no topo e na ponta, com a finalidade de avaliar o mecanismo de distribuição de carga em profundidade, assim como avaliar as parcelas de contribuição de cada elemento (estaca e radier) na capacidade do radier estaqueado. Para melhor entender o comportamento desse tipo de fundação utilizou-se de análises tridimensionais (3D) por elementos finitos, por meio do software LCPC-Cesar. O modelo constitutivo utilizado foi de Mohr-Coulomb, que leva em consideração o comportamento elastoplástico do solo. Os resultados experimentais apontaram uma contribuição média devido ao contato radier-solo de 21% e 79% devido às estacas (lateral + ponta), em relação à capacidade total delas. Os resultados numéricos, justificados pela dificuldade em representar o efeito de escorregamento do contato entre o elemento de fundação e o solo, demonstraram maior participação pelo contato (36%) e menor parcela devido às estacas (64%). As análises numéricas de grupos de estacas, comparadas aos radiers estaqueados, demonstraram que a maior participação da resistência de ponta é gerada em função da existência do efeito de contato / Abstract: This research analyzed the behavior of four piled rafts executed from sets of blocks composed by mechanically augered piles. The piles, with 5m long, 0.25m diameter (D) were executed in diabase soil from the region of Campinas/SP. With this purpose, foundation blocks comprising one, two, three and four piles with spacing of 5D were executed in contact with the soil. These foundation blocks underwent slow maintained load tests (SML) per prescriptions of NBR12131/2006. The piles were instrumented at depth with strain-gages placed at the top and at the tip in order to assess the mechanism of load distribution in depth, and also to asses the percentage of contribution of each element (pile and radier) on the capacity of the piled rafts. To get a better understanding of this type of foundation, three-dimensional (3D) finite element analyses were made by means of the LCPC-Cesar software program. The constitutive model used was the Mohr-Coulomb, which takes the elastoplastic behavior of the soil in consideration. The experimental results indicated a mean contribution via contact of 21% and 79% due to the piles (lateral + tip) in comparison to their total capacity. The numerical results, justified by the difficulty to represent the effect of 'breaking' the contact between the foundation element and the soil, demonstrated greater participation of the contact (36%) and a smaller percentage due to the piles (64%). In comparison with the foundation blocks with contact, the numerical analyses from which the contact was eliminated demonstrated that the greater participation of tip resistance is generated as a function of the existence of the contact effect / Doutorado / Estruturas e Geotécnica / Doutor em Engenharia Civil

A nanotecnologia tem sido aplicada para o desenvolvimento de materiais para diversas aplicações inclusive na inativação de patógenos. As nanopartículas de sílica (npSi) destacam-se pela alta área superficial, facilidade na alteração da superfície para aumento da eficiência adsortiva, penetrabilidade e toxicidade para bactérias gram-negativas sendo biocompatíveis para células de mamíferos e mais foto-estáveis que a maioria dos compostos orgânicos. Devido as suas vantagens, as npSi podem ser usadas para veicular fotossensibilizadores (FSs) uma vez que permitem sua utilização em solução aquosa em que os FSs geralmente são insolúveis. Além disso, o uso de FSs em vez de antibióticos, permite a inativação microbiológica pela Terapia Fotodinâmica sem que as bactérias adquiram resistência por mecanismos genéticos. Esse processo ocorre pela interação entre um FS, luz e oxigênio molecular produzindo oxigênio singleto que é extremamente reativo danificando estruturas celulares. O objetivo desse estudo foi otimizar a fotoinativação dinâmica de E .coli utilizando Azul de Metileno (AM) e Azul de Toluidina O (ATO) veiculados por npSi. As npSi foram preparadas pela metodologia sol-gel, caracterizadas por microscopia eletrônica de varredura (MEV) e submetidas à adsorção de AM e ATO em sua superfície. A presença de AM e ATO na superfície das npSi foram analisadas por espectroscopia no infravermelho; espectroscopia de fluorescência por raio-X e análise termogravimétrica. O planejamento experimental, iniciado pelo fatorial 23 e modelado ao composto central em busca das condições ótimas foi adotado pela primeira vez nessa aplicabilidade, visando a fotoinativação de E. coli empregando AM e ATO em solução e em seguida com npSi. AM e ATO veiculados por npSi permitem a fotoinativação em concentrações mais baixas de FS (20 e 51% respectivamente), causando desestruturação da integridade bacteriana demonstrada por MEV. Os resultados sugerem que a veiculação de AM e ATO por npSi é extremamente efetiva para a fotoinativação dinâmica de E. coli e que o planejamento composto central pode levar à completa inativação das bactérias. / Nanotechnology has been applied to the development of materials for several apllications inclusive inactivation of pathogens. The silica nanoparticles (npSi) are distinguished by high surface area, ease of change the surface in order to increase the adsorption efficiency, penetrability and toxicity in gram-negative bacteria being biocompatible with mammalian cells and more photo-stable than most the organic compounds. Due to its advantages, npSi can be used to carry photosensitizers (PSs) since they allow its use in aquous solution in which PSs are frequently insoluble. Furthermore, the use of PSs instead of antibiotics, allows the microbiological inactivation by Photodynamic Therapy without bacteria to develop resistance by genetic mechanisms. This process occurs by the interaction among a PS, light and molecular oxygen producing singlet oxygen, which is extremely reactive, causing damage to cellular structures. The aim of this study was to optimize the photoinactivation of E. coli using Methylene Blue (MB) and Toluidine Blue O (TBO) carried by npSi using the central composite design. The npSi were prepared by sol-gel method, characterized by scanning electron microscopy (SEM) and subjected to adsorption of MB and TBO on its surface. The presence of FSs on the surface of npSi were analyzed by infrared spectroscopy, fluorescence X-ray spectroscopy and thermogravimetric analysis. The experimental design, initiated by the factorial 23 and modeled by the central composite in search of the optimal conditions was adopted for the first-time for this applicability, aiming the E. coli photoinactivation employing MB and TBO in solution and then with npSi. MB and TBO carried by npSi allowed the photoinactivation in lower concentrations of PS (20 and 51% respectively), causing disruption of bacterial integrity demonstrated by SEM. The results suggest that MB and TBO carried by npSi are extremely effective for dynamic photoinactivation of E. coli and the central composite design can lead to complete inactivation of bacteria.

Diversos estudos têm demonstrado o potencial de utilização de fungos filamentosos na degradação de poluentes ambientais, no entanto, ainda são escassos. O presente trabalho teve como objetivo avaliar o potencial biotecnológico de 174 fungos filamentosos isolados a partir de seis espécies de esponjas marinhas, os quais foram submetidos ao screening em meio sólido contendo corante RBBR e guaiacol; a ensaios em meio líquido, na presença dos corantes preto sulfuroso, índigo blue e reativo black 5, na avaliação da produção das enzimas lacase, manganês peroxidase (MnP) e lignina peroxidase (LiP), utilizando siringaldazina, álcool veratrílico e o vermelho de fenol como substratos enzimáticos, respectivamente; a ensaios de degradação de pireno e benzo[a]pireno; a delineamentos experimentais; e à análise de metabólitos formado na degradação. O fungo selecionado Chaunopycnis alba CBMAI 1346 apresentou 94,54% de degradação em 35 de salinidade, evidenciando o potencial biotecnológico deste fungo em processos de degradação de poluentes ambientais em condições salinas. / Several studies have demonstrated the potential use of filamentous fungi in the degradation of environmental pollutants, however, are still scarce. This study aimed to evaluate the biotechnological potential of 174 filamentous fungi isolated from six species of marine sponges, which were subjected to screening on solid medium containing RBBR dye and guaiacol; the tests in liquid medium in the presence of sulfur black, indigo blue and reactive black 5 dyes, the evaluation of the production of enzymes laccase, manganese peroxidase (MnP) and lignin peroxidase (LiP), using syringaldazin, veratryl alcohol and phenol red as enzyme substrates, respectively; tested for degradation of pyrene and benzo [a] pyrene; the experimental designs; and analysis of metabolites formed in the degradation. The fungus selected Chaunopycnis alba CBMAI 1346 showed 94.54% of pyrene degradation in 35 salinity, highlighting the biotechnological potential of this fungus in the process of degradation of environmental pollutants in saline conditions.

A presente pesquisa teve por objetivos principais: (1) estudar a bioacumulação do metal cromo (40-50 \'mü\'g/L) na Clorophyceae Pseudokirchneriella subcapitata (Korshikov) Hindak 1990 e dos metais cobre (2-10 \'mü\'g/L) e cromo (1-6 mg/L) na macrófita Pistia stratiotes L.; (2) avaliar os mecanismos de detoxificação, as estratégias de defesa e tolerância de Pistia stratiotes L., visando recomendar seu uso na fitorremediação; ambos através do uso do Delineamento Composto Central (DCC) e Metodologia de Superficie de Resposta (MSR), e (3) estudar a dinâmica de remoção de nutrientes em wetlands construídos, plantados e não plantados com as macrófitas Typha sp. e Phragmites sp., submetidos a diferentes regimes de fluxo e condições hidráulicas de operação. A bioacumulação de cromo em P. subcapitata e sua relação com o biovolume demonstraram uma possível estratégia de detoxificação. P. stratiotes desenvolve uma bioacumulação mais intensa nas raízes, resultados que são confirmados pela peroxidação de lipídios e a indução do estresse oxidativo causado pelo cromo. As enzimas catalase e glutationa redutase, induzidas pelo cobre em P. stratiotes, também apresentaram atividade mais intensa nas raízes. O teor de clorofila, em geral apresentou aumento nos tempos iniciais e decresceu no decorrer do tempo, em concentrações mais elevadas de cromo e cobre. Na análise da emissão de fluorescência da clorofila, o rendimento fotossintético e o índice de vitalidade foram os parâmetros mais sensíveis ao estresse causado por cromo em P. stratiotes. Os resultados obtidos na pesquisa com o DCC e a MSR permitem recomendar seu uso na ecotoxicologia aquática, pois podem gerar modelos preditivos de toxicidade; ampliar a compreensão dos mecanismos de detoxicaçao; reduzir o número de experimentos sem perder a confiabilidade dos dados e reduzir a geração de resíduos. Nos estudos realizados com os wetlands construídos, os parâmetros físico-químicos avaliados revelaram variação sazonal durante o período experimental (verão/2007, invemo/2008 e verão/2008). Typha sp. e Phragmites sp. estão entre as plantas mais comumente utilizadas nos wetlands construídos e sua presença amplia as condições de filtração do sistema, mas a eficiência da espécie na remoção dos nutrientes (amônia e fosfato) depende do regime de fluxo e das condições hidráulicas aplicadas. Os sistemas com fluxo subsuperficial com a superfície livre de água foram os wetlands que desempenharam melhor capacidade na remoção de nutrientes. Uma vez que a poluição dos corpos d\'água tem sido um problema constante na atualidade, estudos como estes oferecem subsídios para propostas futuras de preservação e recuperação ambiental, além de ampliar os conhecimentos sobre as macrófitas e sua aplicação na descontaminação ambiental em corpos d\'água e em sistemas de depuração de águas residuárias. / This research had as main objectives: (1) study the bioaccumulation of chromium metal (40- 50 \'mü\'g/L) in Clorophyceae Pseudokirchneriella subcapitata (Korshikov) Hindak 1990 and of copper (2-10 \'mü\'g/L) and chromium (1-6 mg/L) in the macrophyte Pistia stratiotes L. (2) study the mechanisms of detoxification, defense strategies and tolerance of Pistia stratiotes L. in order to recommend their use in phytoremediation, both through the use of Central Composite Design (DCC) and Response Surface Methodology (RSM), and (3) study the dynamics of nutrient removal in constructed wetlands, planted and unplanted with macrophytes: Typha sp. and Phragmites sp. subjected to different flow regimes and hydraulic conditions of operation. The bioaccumulation of chromium in P. subcapitata and its relation to biovolume shows a possible strategy for detoxification. P. stratiotes develops a more intense bioaccumulation in roots and these results are confirmed by lipid peroxidation and induction of oxidative stress caused by chromium. The enzymes catalase and glutathione reductase induced by copper in P. stratiotes, also showed the strongest activity in the roots. The chlorophyll content in general showed an increase in early and decreased over time, in higher concentrations of chromium and copper. In analyzing the fluorescence emission of chlorophyll, the photosynthetic yield and the index of vitality were the parameters most sensitive to stress caused by chromium in P. stratiotes. The results obtained in research with the DCC and MSR allowed to recommend their use in aquatic ecotoxicology, because they allow: to generate predictive models of toxicity, the simulation of such models expanding the understanding of the mechanisms of detoxification; reduce the number of experiments without losing the reliability of data and reducing waste generation. In studies with constructed wetlands, the physicochemical parameters evaluated showed seasonal variation observed during the experimental period (summer/2007, winter/2008, summer/2008). Typha sp. and Phragmites sp. are among the most commonly used plants in constructed wetlands, and its presence extends the conditions of filtration system, but the efficiency of the species in the removal of nutrients (ammonia and phosphate) depends on the flow regime and hydraulic conditions applied in the system. The systems with subsurface flow with free surface water wetlands that have been played better capacity in removing nutrients. Pollution of water bodies has been a constant problem at the moment, and studies like these provi de input for future proposals for the preservation and environmental restoration, in addition to expanding our knowledge on the macrophytes, and its application in environmental remediation in water bodies and systems purification of wastewater.

Le contrôle des procédés représente un enjeu majeur pour les industries chimiques et pétrochimiques afin de garantir la qualité des produits, le contrôle des coûts, le maintien de la productivité et la maîtrise des risques. L'analyse menée directement au coeur des procédés constitue la voie la plus efficace. Cependant, dans la majorité des applications, les analyses élémentaires sont réalisées essentiellement en laboratoire et très rarement en ligne, par la mise en oeuvre de différentes technologies, le plus souvent lourdes et onéreuses. Ce travail de thèse s'inscrit dans le cadre d'un grand projet d'innovation qui couvre le champ de l'analyse élémentaire en ligne, domaine actuellement peu étudié. La technique d'analyse retenue est la spectrométrie LIBS en raison de sa rapidité et de son application à tout état de la matière sans préparation d'échantillon, ce qui lui offre un fort potentiel pour l'analyse en ligne. Cette technique est investiguée afin de réaliser des analyses en ligne d'éléments présents dans des matrices liquides : saumures, huiles silicone et produits pétroliers. L'optimisation des différents paramètres de mesure est réalisée et une approche d'optimisation s'appuyant sur un plan d'expériences est proposée. Différents modes d'échantillonnage de liquide et plusieurs montages LIBS sont étudiés afin de répondre aux problématiques évoquées. Enfin, une transposition au monde industriel est présentée avec le suivi du soufre en ligne dans des produits pétroliers sur un pilote industriel. Les résultats sont encourageants, mais la stabilité perfectible des mesures dans le temps implique d'explorer de nouvelles pistes d'amélioration / Process control is a major challenge for chemical and petrochemical industries so as to ensure product quality, cost control, sustainable productivity and risk management. To do so, carrying out the analysis directly at the core of the process is the most efficient way. However, for most applications, elemental analyzes are mainly performed in the laboratory and rarely on-line, which requires the implementation of different technologies, usually complex and expensive. This work is part of a large innovative project that covers the field of on-line elemental analysis, a research area still understudied to this day. The analytical technique selected here is the Laser Induced Breakdown Spectroscopy. Indeed, its speed and its capability to analyze all states of matter without sample preparation, gives it a great potential for on-line analysis. This technique is investigated in order to achieve on-line analysis of elements contained in various liquid matrices: brines, silicone oils and petroleum products. The optimization of different measurement parameters is performed, including an experimental design based approach. Different liquid sampling configurations and several LIBS setups are designed in order to tackle the issues encountered. Finally, a transposition to the industrial world is presented through on-line monitoring of sulfur in petroleum products on an industrial pilot process. The results are promising, but improving the stability of measurements over time still requires further research

This study presents a set of data analysis approaches for single subject designs (SSDs). The primary purpose is to establish a series of statistical models to supplement visual analysis in single subject research using Bayesian estimation. Linear modeling approach has been used to study level and trend changes. I propose an alternate approach that treats the phase change-point between the baseline and intervention conditions as an unknown parameter. Similar to some existing approaches, the models take into account changes in slopes and intercepts in the presence of serial dependency. The Bayesian procedure used to estimate the parameters and analyze the data is described. Researchers use a variety of statistical analysis methods to analyze different single subject research designs. This dissertation presents a series of statistical models to model data from various conditions: the baseline phase, A-B design, A-B-A-B design, multiple baseline design, alternating treatments design, and changing criterion design. The change-point evaluation method can provide additional confirmation of causal effect of the treatment on target behavior. Software codes are provided as supplemental materials in the appendices. The applicability for the analyses is demonstrated using five examples from the SSD literature.

Experimental design is a practice operating at the limit between craftmanship, art and technology. In collaboration with the studio breadeEscalope (Vienna, Austria) this project oscillates between research and production to study the link between industrial and experimental approach to design.  Hitherto initiated from an impulse or a problem requiring solution, the action of designing suggest a product or a service to fulfill needs. In industrial design, the creative process follows contextually anchored steps to frame, define, develop and deliver. For the sake of a pragmatic answer, the delivery is centred around the user and its needs, often leading to an opaque finished product.  Home’s basic, the coat rack was selected to support this study as a concrete product base for trend and consumer behavior analysis. From shared ornamental and functional object placed in the entrance of houses, the coat rack previously “hatstand”, is today an unnoticed domestic object. The final product was hand manufactured with recycled and raw component, allowing transparency on the production process and used material. Stacking up coats on the produced rack create a private space for the user to sit in, questioning the relationship between user and product (ownership, trust, value). Based on architectural concept and design theory, the product aims to bridge creative and technical disciplines to suggest a functional yet questionable product as dialogue starter.  How sustainable are the objects that surround us every day? What is the story of the product? With those question in head the experimental design thinking studio breadedEscalope based in Vienna (Austria), offers an alternative approach to design. Always starting projects with the production process as a story of formations, offering unique and playful outcome to the act of designing. / Experimentell design är en praxis som fungerar på gränsen mellan hantverk, konst och teknik. I samarbete med studio breadeEscalope (Wien, Österrike) pendlar detta projekt mellan forskning och produktion för att studera sambandet mellan industriell och experimentell strategi för design.  Hittills initierad från en impuls eller ett problem som kräver lösning, föreslår åtgärden att designa en produkt eller en tjänst för att uppfylla behoven. Inom industriell design följer den kreativa processen kontextuellt förankrade steg för att rama in, definiera, utveckla och leverera. För ett pragmatiskt svar är leveransen centrerad kring användaren och dess behov, vilket ofta leder till en ogenomskinlig färdig produkt.  Hemmets grund, klädhänget valdes för att stödja denna studie som en konkret produktbas för trend- och konsumentbeteendeanalys. Från delat prydnads- och funktionellt föremål placerat i ingången till hus är klädhänget tidigare "hatstand", idag ett obemärkt inhemskt föremål. Slutprodukten tillverkades för hand med återvunnen och rå komponent, vilket gav insyn i produktionsprocessen och använt material. Att stapla upp rockar på det producerade racket skapar ett privat utrymme för användaren att sitta i och ifrågasätter förhållandet mellan användare och produkt (ägande, förtroende, värde). Baserat på arkitektoniska koncept och designteori syftar produkten till att överbrygga kreativa och tekniska discipliner för att föreslå en funktionell men tvivelaktig produkt som dialogstartare.  Hur hållbara är de objekt som omger oss varje dag? Vad är historien om produkten? Med dessa frågor i huvudet erbjuder den experimentella designtänkande studion breadedEscalope baserad i Wien (Österrike), ett alternativt tillvägagångssätt för design. Alltid starta projekt med produktionsprocessen som en berättelse om formationer, erbjuder unikt och lekfullt resultat till handlingen att designa.

Orientador: Alessandra Turini Bolsoni-Silva / Resumo: Estudos em Psicologia do desenvolvimento têm enfatizado a importância de um repertório habilidoso para que as crianças estabeleçam interações sociais saudáveis. Sabe-se que o comportamento da criança é multideterminado e influenciado pelos comportamentos das demais pessoas que fazem parte de seus contextos (familiares, professores, pares). O objetivo da pesquisa foi avaliar os efeitos de uma intervenção em grupo com crianças para promover habilidades sociais infantis nos contextos familiar e escolar, em um delineamento experimental de grupo, com grupo experimental e grupo controle (Estudos 1, 2 e 3) e delineamento de sujeito como controle dele mesmo (Estudo 4). Foi utilizado o procedimento de intervenção Promove-Crianças (FALCÃO; BOLSONI-SILVA, 2016). Os participantes foram 41 crianças que cursavam o primeiro ano do ensino fundamental de escolas municipais de uma cidade no norte paranaense e que apresentavam diagnóstico clínico, em comorbidade, para problemas de comportamento interalizantes, externalizantes e totais, de acordo com relatos de mães/pais e de professores. As crianças foram distribuídas randomicamente em grupo experimental (21 crianças) e grupo controle (20 crianças). Para mensurar efeitos da intervenção foram aplicados instrumentos que avaliassem os comportamentos das crianças (habilidades sociais e problemas de comportamento), de suas mães/pais e de seus professores (práticas educativas e indicadores de saúde mental) em três momentos para o grupo experimental (... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Studies in Developmental psychology have emphasized the importance of a skillful repertoire for children to establish healthy social interactions. Since the behavior is multidetermined and the behavior of children is influenced by the behavior of other people who are part of their contexts (family, teachers, peers), the aim was to assess whether, by promoting changes in the child's repertoire, one can also influence the behavior of those around him/her. The objective of the research was to evaluate the effects of a group intervention with children to promote children's social skills in the family and school contexts, in an experimental group design. The intervention procedure Promove-Crianças (FALCÃO; BOLSONI-SILVA, 2016) was used. The participants were 41 children who were attending the first year of elementary school in municipal schools in a city in the north of Paraná and who had a clinical diagnosis, in comorbidity, for internalizing, externalizing and total behavior problems, according to mothers and teachers reports. Children were randomly assigned to an experimental group (21 children) and a control group (20 children). To measure the intervention effects, instruments to assess the behaviors of children (social skills and behavior problems), their mothers and teachers (educational practices and mental health indicators) were applied in three moments for the experimental group (pre-test, post-test and follow-up) and in two moments for the control group (Probe 1 and Pro... (Complete abstract click electronic access below) / Doutor

People can disengage from their internalized moral standards and self-regulation in order to perform immoral behaviour by using different Moral Disengagement mechanisms. These mechanisms within media have a positive effect on immoral behaviour. However, Moral Identity activation is said to counter arguments of Moral Disengagement. In this study, both concepts are applied to the context of war. An additional assumption took into account in how far participants’ internalized moral standards consider war as immoral. This is important since Moral Identity and Moral Disengagement are based on internalized moral standards. To test the hypotheses, this study employed a 2 x 2 RO between-subjects factorial design. The trait variable called Moral Consideration of War was supposed to reflect participants’ internalized moral standards with regard to war. It was used to operationalize the additional assumption. Factor 1 varied the activation of Moral Identity (Moral Identity activation versus control group) and factor 2 varied the depiction of the war scenario (Permissive Scenario versus Prohibitive Scenario). Scenarios were fictive newspaper articles. A Permissive Scenario comprised a higher number of arguments based on Moral Disengagement mechanisms than a Prohibitive Scenario. Main outcome measures were the support of war and war-related Moral Disengagement (questionnaire). In total 86 participants (f=45, m=41) were randomized into four cells and completed the online experiment. The Permissive Scenario failed to increase support of war and Moral Disengagement (questionnaire), on the assumption that war is considered immoral. Moral Identity activation had a negative effect on Moral Disengagement only on the assumption that war was considered moral. Moral Identity activation had no significant effect on support of war, on the premise that war was considered immoral. The interaction term of Moral Identity activation and Permissive Scenario had no significant effect neither on support of war nor on Moral Disengagement, no matter if additional assumption was taken into account or not. Results are discussed with regard to methodological limitations measuring internalized moral standards. Their measurement implied already individual Moral Disengagement. Interaction effect failed, supposedly because Moral Identity activation was not specifically targeted at immoral behaviour and because mediating effects of Moral Identity centrality were not considered.:I. CONTENTS I. Contents 2 II. List of Figures 5 III. List of Tables 6 IV. List of Equations 7 V. Abstract 8 VI. Zusammenfassung 9 1 Introduction 10 2 Theory 12 2.1 Moral Disengagement 12 2.1.1 Socio Cognitive Theory of Morality 12 2.1.2 Mechanisms of Moral Disengagement 13 2.1.3 Moral Disengagement and War 13 2.2 Moral Disengagement and Media 17 2.2.1 Moral Disengagement in Media and Aggressive Behaviour 18 2.2.2 Moral Disengagement in Media and War 19 2.2.3 Operationalization of Scenarios 21 2.3 Moral Identity 22 2.3.1 Moral Identity Centrality 22 2.3.2 Moral Identity Activation and Moral Disengagement 24 2.3.3 Moral Identity Activation in Interaction with Moral Disengagement in Media 26 2.4 Hypotheses 28 2.5 Reasons for this study 30 3 Methods 32 3.1 Experimental Design 32 3.1.1 Participants 33 3.2 Procedures 34 3.2.1 Trait Variables 34 3.2.2 Independent Variables 36 3.2.3 Dependent Variables 38 3.3 Statistical Analysis 39 4 Results 41 4.1 Descriptive Statistics 41 4.1.1 Socio-demographic Characteristics 41 4.1.2 Moral Consideration of War 42 4.1.3 Dependent Variables 42 4.2 Manipulation Check 43 4.3 Hypotheses Tests 44 4.3.1 Hypothesis 1a 47 4.3.2 Hypotheses 2a + 3a 48 4.3.3 Hypothesis 4a 49 4.3.4 Hypotheses 5a + 6a 50 4.3.5 Hypothesis 7a 53 5 Discussion 55 5.1 Moral Disengagement and Support of War 56 5.2 Moral Identity and Support of War 57 5.3 Methodological Problems 58 5.4 Discussion Main Effects without Additional Assumption 60 5.4.1 Moral Disengagement 61 5.4.2 Moral Identity 63 5.5 Limitations 65 5.5.1 Sample 65 5.5.2 Methods 67 5.6 Conclusion 68 6 References 70 7 Annex 76 7.1 Operationalization Permissive Scenario (German) 84 7.2 Operationalization Prohibitive Scenario (German) 86 7.3 Study Description for Participants (German) 88 8 Acknowledgements 89 9 Selbstständigkeitserklärung 90 / Die Mechanismen der Moralischen Entkopplung lösen das Selbst von internalisierten moralischen Standards und verhindern damit die Selbstregulierung des moralischen Verhaltens. Diese Mechanismen kommen auch in Medien vor und tragen zu unmoralischem Verhalten bei. Die Aktivierung der Moralischen Identität wirkt jedoch den Mechanismen der Moralischen Entkopplung entgegen. In dieser Studie werden beide Konzepte auf das Thema Krieg übertragen. Dabei ist wichtig zu beachten, dass internalisierte moralische Standards Krieg als unmoralisch bewerten. Schließlich basieren sowohl Moralische Entkopplung als auch die Aktivierung der Moralischen Identität auf dieser zusätzlichen Annahme. Zur Überprüfung der Hypothesen wurde ein 2 x 2 RO Between-Subjects Design verwendet. Faktor 1 variierte die Aktivierung von Moralischer Identität (Aktivierung Moralische Identität versus Kontrollgruppe). Faktor 2 variierte die Permissivität eines Kriegsszenarios in einem Zeitungsartikel (Permissives Szenario versus Prohibitives Szenario). Dabei wurde Permissivität hinsichtlich der Anzahl der Moralischen Entkopplungsmechanismen operationalisiert (Viele versus Wenig). Als Organismusvariable ist die Moralische Bewertung von Krieg zur Überprüfung der zusätzlichen Annahme notwendig gewesen. Abhängige Variablen waren die Unterstützung von Krieg und Moralische Entkopplung (Fragebogen). Teilnehmerinnen und Teilnehmer (N=86, f=45, m=41) des online Experiments wurden in vier verschiedene Versuchsbedingungen randomisiert. Die Ergebnisse zeigten, dass die Permissivität des Kriegsszenarios keinen Effekt auf Moralische Entkopplung (Fragebogen) oder die Unterstützung von Krieg hatte, unter Berücksichtigung der Zusatzannahme. Moralische Identitätsaktivierung verringerte Moralische Entkopplung (Fragebogen) aber nur unter der Bedingung, dass Krieg als moralisch bewertet wurde. Moralische Entkopplung hatte keinen Effekt auf die Unterstützung von Krieg, unter Berücksichtigung der Zusatzannahme. Die Interaktion von Moralischer Identitätsaktivierung mit der Permissivität des Kriegsszenarios war nicht signifikant, unabhängig davon ob die Zusatzannahme berücksichtigt wurde oder nicht. Die Ergebnisse werden in Bezug auf die methodischen Probleme bei der Messung internalisierter moralischer Standards diskutiert. Es fanden vermutlich Prozesse der Moralischen Entkopplung bereits während der Messung dieser Standards statt. Der fehlende Interaktionseffekt kann an der schwachen und unspezifischen Aktivierung der Moralischen Identität liegen, sowie nicht berücksichtigter Mediatoren, wie z.B. die Zentralität von Moralischer Identität.:I. CONTENTS I. Contents 2 II. List of Figures 5 III. List of Tables 6 IV. List of Equations 7 V. Abstract 8 VI. Zusammenfassung 9 1 Introduction 10 2 Theory 12 2.1 Moral Disengagement 12 2.1.1 Socio Cognitive Theory of Morality 12 2.1.2 Mechanisms of Moral Disengagement 13 2.1.3 Moral Disengagement and War 13 2.2 Moral Disengagement and Media 17 2.2.1 Moral Disengagement in Media and Aggressive Behaviour 18 2.2.2 Moral Disengagement in Media and War 19 2.2.3 Operationalization of Scenarios 21 2.3 Moral Identity 22 2.3.1 Moral Identity Centrality 22 2.3.2 Moral Identity Activation and Moral Disengagement 24 2.3.3 Moral Identity Activation in Interaction with Moral Disengagement in Media 26 2.4 Hypotheses 28 2.5 Reasons for this study 30 3 Methods 32 3.1 Experimental Design 32 3.1.1 Participants 33 3.2 Procedures 34 3.2.1 Trait Variables 34 3.2.2 Independent Variables 36 3.2.3 Dependent Variables 38 3.3 Statistical Analysis 39 4 Results 41 4.1 Descriptive Statistics 41 4.1.1 Socio-demographic Characteristics 41 4.1.2 Moral Consideration of War 42 4.1.3 Dependent Variables 42 4.2 Manipulation Check 43 4.3 Hypotheses Tests 44 4.3.1 Hypothesis 1a 47 4.3.2 Hypotheses 2a + 3a 48 4.3.3 Hypothesis 4a 49 4.3.4 Hypotheses 5a + 6a 50 4.3.5 Hypothesis 7a 53 5 Discussion 55 5.1 Moral Disengagement and Support of War 56 5.2 Moral Identity and Support of War 57 5.3 Methodological Problems 58 5.4 Discussion Main Effects without Additional Assumption 60 5.4.1 Moral Disengagement 61 5.4.2 Moral Identity 63 5.5 Limitations 65 5.5.1 Sample 65 5.5.2 Methods 67 5.6 Conclusion 68 6 References 70 7 Annex 76 7.1 Operationalization Permissive Scenario (German) 84 7.2 Operationalization Prohibitive Scenario (German) 86 7.3 Study Description for Participants (German) 88 8 Acknowledgements 89 9 Selbstständigkeitserklärung 90

There is a growing societal concern about excessive water and fertilizer use in agricultural systems. High water productivity while maintaining high crop yields can be achieved with appropriate irrigation scheduling. Moreover, freshwater pollution through nitrogen (N) leaching due to the widespread use of N fertilizers demands for an efficient N fertilization management. However, sustainable crop management requires good knowledge of soil water and N dynamics as well as of crop water and N demand. Crop growth models, which describe physical and physiological processes of crop growth as well as water and matter transport, are considered as powerful tools to assist in the optimization of irrigation and fertilization management. It is of a general nature that the reliability of simulation based predictions depends on the quality and quantity of the data used for model calibration and validation which can be obtained e.g. in field experiments. A lack of data or low data quality for model calibration and validation may cause low performance and large uncertainties in simulation results. The large number of model parameters to be calibrated requires appropriate calibration methods and a sequential calibration strategy. Moreover, a simulation based planning of the field design saves costs and expenditure while supporting maximal outcomes of experiments. An adjustment of crop growth modeling and experiments is required for model improvement and development to reliably predict crop growth and to generalize predicted results. In this research study, a new approach for simulation based optimal experimental design was developed aiming to integrate simulation models, experiments, and optimization methods in one framework for optimal and sustainable irrigation and N fertilization management. The approach is composed of three steps: 1. The preprocessing consists of the calibration and validation of the crop growth model based on existing experimental data, the generation of long time-series of climate data, and the determination of the optimal irrigation control. 2. The implementation comprises the determination and experimental application of the simulation based optimized deficit irrigation and N fertilization schedules and an appropriate experimental data collection. 3. The postprocessing includes the evaluation of the experimental results namely observed yield, water productivity (WP), nitrogen use efficiency (NUE), and economic aspects, as well as a model evaluation. Five main tools were applied within the new approach: an algorithm for inverse model parametrization, a crop growth model for simulating crop growth, water balance and N balance, an optimization algorithm for deficit irrigation and N fertilization scheduling, and a stochastic weather generator. Furthermore, a water flow model was used to determine the optimal irrigation control functions and for simulation based estimation of the optimal field design. The approach was implemented within three case studies presented in this work. The new approach combines crop growth modeling and experiments with stochastic optimization. It contributes to a successful application of crop growth modeling based on an appropriate experimental data collection. The presented model calibration and validation procedure using the collected data facilitates reliable predictions. The stochastic optimization framework for deficit irrigation and N fertilization scheduling proved to be a powerful tool to enhance yield, WP, NUE and profit.:Contents Nomenclature ..............................................................................................................................xii 1 Introduction..................................................................................................................................1 I Fundamentals and literature review ........................................................................................5 2 Water productivity in crop production ....................................................................................7 2.1 Water productivity .................................................................................................................7 2.2 Increase of crop yield ..........................................................................................................9 2.3 Irrigation ...............................................................................................................................10 2.3.1 Irrigation methods ...........................................................................................................10 2.3.2 Irrigation scheduling and irrigation control ................................................................11 2.3.3 The influence of the field design on profitability .......................................................12 2.4 The concept of controlled deficit irrigation ...................................................................14 3 Nitrogen use efficiency in crop production .........................................................................17 3.1 Nitrogen use efficiency ....................................................................................................18 3.2 N fertilization management .............................................................................................18 3.3 Combination of controlled deficit irrigation and deficit N fertilization ......................19 4 Crop growth modeling ............................................................................................................21 4.1 Physiological crop growth models ..................................................................................21 4.1.1 Model description of SVAT model Daisy ....................................................................22 4.1.2 Model description of crop growth model Pilote .........................................................24 4.2 Optimal experimental design for model parametrization ...........................................25 4.2.1 Experimental design ......................................................................................................25 4.2.2 Model parameter estimation ........................................................................................26 4.2.3 Model parameter estimation based on greenhouse data .......................................27 5 Irrigation and N fertilization scheduling ..............................................................................29 5.1 Irrigation scheduling .........................................................................................................29 5.2 N fertilization scheduling .................................................................................................30 5.3 Combination of irrigation and N fertilization scheduling ............................................30 II New approach for simulation based optimal experimental design ................................33 6 Preprocessing steps ...............................................................................................................37 6.1 Model parametrization and assessment .......................................................................37 6.1.1 Calibration of the soil parameters ...............................................................................38 6.1.2 Calibration of the plant parameters ............................................................................39 6.1.3 Model assessment .........................................................................................................41 6.1.4 Preliminary simulations for an optimal experimental layout ..................................43 6.2 Generation of long time-series of climate data ............................................................44 6.3 Determination of the optimal irrigation control functions ...........................................44 7 Stochastic optimization framework ......................................................................................47 7.1 Stochastic optimization framework .................................................................................47 7.1.1 Optimization algorithm ...................................................................................................47 7.1.2 Generation of the crop water (nitrogen) production functions ................................48 7.1.3 Application of the stochastic optimization framework ..............................................48 7.1.4 Crop growth model requirements ................................................................................49 8 Data collection during the experimentation .......................................................................51 9 Postprocessing steps .............................................................................................................55 9.1 Evaluation of the experimental results ...........................................................................55 9.1.1 Yield and total dry matter ..............................................................................................55 9.1.2 Water productivity and nitrogen use efficiency .........................................................55 9.1.3 Economic aspects ..........................................................................................................55 9.1.4 Evaluation of the model results ....................................................................................56 III Application of the new approach to three case studies ...................................................57 10 Evaluation of model transferability ....................................................................................59 10.1 Objectives and summary ................................................................................................59 10.2 Experimental site and experimental setup .................................................................61 10.3 Data collection during the experimentation ................................................................63 10.4 Calibration and validation of the model parameters .................................................63 10.4.1 Model setup and soil parametrization ......................................................................64 10.4.2 Plant parameter calibration and validation .............................................................67 10.5 Application of the stochastic optimization framework ...............................................75 10.5.1 Generation of the climate data ...................................................................................75 10.5.2 Estimation of the yield potential of wheat ................................................................75 10.5.3 Estimation of the water productivity potential of barley .........................................77 10.6 Discussion and conclusions ..........................................................................................81 11 Real-time irrigation scheduling ..........................................................................................83 11.1 Objectives and summary ................................................................................................83 11.2 Experimental site and field design ...............................................................................85 11.3 Data collection during the experiment ........................................................................86 11.4 Calibration and setup of the crop growth model Pilote .............................................87 11.5 Derivation of optimal irrigation control functions for different drip line spacings 88 11.5.1 Initial Hydrus 2D/3D simulations ...............................................................................88 11.5.2 Determination of the irrigation control functions .....................................................89 11.5.3 Verifying measurements ..............................................................................................92 11.6 Real-time deficit irrigation scheduling .........................................................................93 11.7 Evaluation of the experimental results .........................................................................96 11.7.1 Crop yields .....................................................................................................................96 11.7.2 Water productivity .........................................................................................................97 11.7.3 Prognostic simulations ................................................................................................98 11.7.4 Economic aspects ........................................................................................................99 11.8 Discussion and conclusions ........................................................................................100 12 Multicriterial optimization...................................................................................................103 12.1 Objectives and summary .............................................................................................103 12.2 Experimental site and experimental setup ...............................................................105 12.3 Data collection during the experiment ......................................................................105 12.4 Experimental layout ......................................................................................................106 12.5 Calibration and validation of the model parameters ..............................................107 12.5.1 Calibration of the soil parameters ...........................................................................107 12.5.2 Calibration and validation of the plant parameters .............................................107 12.5.3 Setup of SVAT model Daisy .....................................................................................108 12.6 Generation of the climate data ....................................................................................109 12.7 Optimized irrigation and N fertilization scheduling .................................................109 12.8 Evaluation of the experimental results .......................................................................111 12.8.1 Observed plant variables and weather data .........................................................111 12.8.2 Water productivities and nitrogen use efficiencies ...............................................111 12.8.3 Chlorophyll Meter values ..........................................................................................112 12.8.4 Recalculation of soil parameters .............................................................................113 12.9 Postprocessing simulations of yield and water and N dynamics..........................114 12.9.1 Yield predictions using Daisy 1D ............................................................................114 12.9.2 Yield predictions using Daisy 2D ............................................................................119 12.10 Discussion and conclusions .....................................................................................121 IV General discussion, conclusions and outlook ...............................................................123 13 General discussion ............................................................................................................125 14 General conclusions and outlook ....................................................................................133 Appendix ....................................................................................................................................134 A Tables and Figures ...............................................................................................................137 B Model setup and weather files ...........................................................................................145 List of Tables .............................................................................................................................153 List of Figures ............................................................................................................................153 References ................................................................................................................................159 / In der heutigen Gesellschaft gibt es zunehmend Bedenken gegenüber übermäßigem Wasser- und Düngereinsatz in der Landwirtschaft. Eine hohe Wasserproduktivität kann jedoch durch geeignete Bewässerungspläne mit hohen landwirtschaftlichen Erträgen in Einklang gebracht werden. Die mit der weitverbreiteten Stickstoffdüngung einhergehende Gewässerbelastung aufgrund von Stickstoffauswaschung erfordert zudem ein effizientes Stickstoffmanagement. Eine entsprechende ressourceneffiziente Landbewirtschaftung bedarf präzise Kenntnisse der Bodenwasser- und Stickstoffdynamiken sowie des Pflanzenwasser- und Stickstoffbedarfs. Als leistungsfähige Werkzeuge zur Unterstützung bei der Optimierung von Bewässerungs-und Düngungsplänen werden Pflanzenwachstumsmodelle eingesetzt, welche die physischen und physiologischen Prozesse des Pflanzenwachstums sowie die physikalischen Prozesse des Wasser- und Stofftransports abbilden. Hierbei hängt die Zuverlässigkeit dieser simulationsbasierten Vorhersagen von der Qualität und Quantität der bei der Modellkalibrierung und -validierung verwendeten Daten ab, welche beispielsweise in Feldversuchen erfasst werden. Fehlende Daten oder Daten mangelhafter Qualität bei der Modellkalibrierung und -validierung führen zu unzuverlässigen Simulationsergebnissen und großen Unsicherheiten bei der Vorhersage. Die große Anzahl an zu kalibrierenden Parametern erfordert zudem geeignete Kalibrierungsmethoden sowie eine sequenzielle Kalibrierungsstrategie. Darüber hinaus kann eine simulationsbasierte Planung des Versuchsdesigns Kosten und Aufwand reduzieren und zu weiteren experimentellen Erkenntnissen führen. Die Abstimmung von Pflanzenwachstumsmodellen und Versuchen ist zudem für die Modellentwicklung und -verbesserung sowie für eine Verallgemeinerung von Simulationsergebnissen unabdingbar. Im Rahmen dieser Arbeit wurde ein neuer Ansatz für ein simulationsbasiertes optimales Versuchsdesign entwickelt. Ziel war es, Simulationsmodelle, Versuche und Optimierungsmethoden in einem Ansatz für optimales und nachhaltiges Bewässerungs- und Düngungsmanagement zu integrieren. Der Ansatz besteht aus drei Schritten: 1. Die Vorbereitungsphase beinhaltet die auf existierenden Versuchsdaten basierende Kalibrierung und Validierung des Pflanzenwachstumsmodells, die Generierung von Klimazeitreihen und die Bestimmung der optimalen Bewässerungssteuerung. 2. Die Durchführungsphase setzt sich aus der Erstellung und experimentellen Anwendung der simulationsbasierten optimierten Defizitbewässerungs- und Stickstoffdüngungspläne und der Erfassung der relevanten Versuchsdaten zusammen. 3. Die Auswertungsphase schließt eine Evaluierung der Versuchsergebnisse anhand ermittelter Erträge, Wasserproduktivitäten (WP), Stickstoffnutzungseffizienzen (NUE) und ökonomischer Aspekte, sowie eine Modellevaluierung ein. In dem neuen Ansatz kamen im Wesentlichen folgende fünf Werkzeuge zur Anwendung: Ein Algorithmus zur inversen Modellparametrisierung, ein Pflanzenwachstumsmodell, welches das Pflanzenwachstum sowie die Wasser- und Stickstoffbilanzen abbildet, ein evolutionärer Optimierungsalgorithmus für die Generierung von defizitären Bewässerungs- und Stickstoffplänen und ein stochastischer Wettergenerator. Zudem diente ein Bodenwasserströmungsmodell der Ermittlung der optimalen Bewässerungssteuerung und der simulationsbasierten Optimierung des Versuchsdesigns. Der in dieser Arbeit vorgestellte Ansatz wurde in drei Fallbeispielen angewandt. Der neue Ansatz kombiniert Pflanzenwachstumsmodellierung und Experimente mit stochastischer Optimierung. Er leistet einen Beitrag zu einer erfolgreichen Pflanzenwachstumsmodellierung basierend auf der Erfassung relevanter Versuchsdaten. Die vorgestellte Modellkalibrierung und -validierung unter Verwendung der erfassten Versuchsdaten trug wesentlich zu zuverlässigen Simulationsergebnissen bei. Darüber hinaus stellt die hier vorgestellte stochastische Optimierung von defizitären Bewässerungs- und Stickstoffplänen ein leistungsfähiges Werkzeug dar, um Erträge, WP, NUE und den Profit zu erhöhen.:Contents Nomenclature ..............................................................................................................................xii 1 Introduction..................................................................................................................................1 I Fundamentals and literature review ........................................................................................5 2 Water productivity in crop production ....................................................................................7 2.1 Water productivity .................................................................................................................7 2.2 Increase of crop yield ..........................................................................................................9 2.3 Irrigation ...............................................................................................................................10 2.3.1 Irrigation methods ...........................................................................................................10 2.3.2 Irrigation scheduling and irrigation control ................................................................11 2.3.3 The influence of the field design on profitability .......................................................12 2.4 The concept of controlled deficit irrigation ...................................................................14 3 Nitrogen use efficiency in crop production .........................................................................17 3.1 Nitrogen use efficiency ....................................................................................................18 3.2 N fertilization management .............................................................................................18 3.3 Combination of controlled deficit irrigation and deficit N fertilization ......................19 4 Crop growth modeling ............................................................................................................21 4.1 Physiological crop growth models ..................................................................................21 4.1.1 Model description of SVAT model Daisy ....................................................................22 4.1.2 Model description of crop growth model Pilote .........................................................24 4.2 Optimal experimental design for model parametrization ...........................................25 4.2.1 Experimental design ......................................................................................................25 4.2.2 Model parameter estimation ........................................................................................26 4.2.3 Model parameter estimation based on greenhouse data .......................................27 5 Irrigation and N fertilization scheduling ..............................................................................29 5.1 Irrigation scheduling .........................................................................................................29 5.2 N fertilization scheduling .................................................................................................30 5.3 Combination of irrigation and N fertilization scheduling ............................................30 II New approach for simulation based optimal experimental design ................................33 6 Preprocessing steps ...............................................................................................................37 6.1 Model parametrization and assessment .......................................................................37 6.1.1 Calibration of the soil parameters ...............................................................................38 6.1.2 Calibration of the plant parameters ............................................................................39 6.1.3 Model assessment .........................................................................................................41 6.1.4 Preliminary simulations for an optimal experimental layout ..................................43 6.2 Generation of long time-series of climate data ............................................................44 6.3 Determination of the optimal irrigation control functions ...........................................44 7 Stochastic optimization framework ......................................................................................47 7.1 Stochastic optimization framework .................................................................................47 7.1.1 Optimization algorithm ...................................................................................................47 7.1.2 Generation of the crop water (nitrogen) production functions ................................48 7.1.3 Application of the stochastic optimization framework ..............................................48 7.1.4 Crop growth model requirements ................................................................................49 8 Data collection during the experimentation .......................................................................51 9 Postprocessing steps .............................................................................................................55 9.1 Evaluation of the experimental results ...........................................................................55 9.1.1 Yield and total dry matter ..............................................................................................55 9.1.2 Water productivity and nitrogen use efficiency .........................................................55 9.1.3 Economic aspects ..........................................................................................................55 9.1.4 Evaluation of the model results ....................................................................................56 III Application of the new approach to three case studies ...................................................57 10 Evaluation of model transferability ....................................................................................59 10.1 Objectives and summary ................................................................................................59 10.2 Experimental site and experimental setup .................................................................61 10.3 Data collection during the experimentation ................................................................63 10.4 Calibration and validation of the model parameters .................................................63 10.4.1 Model setup and soil parametrization ......................................................................64 10.4.2 Plant parameter calibration and validation .............................................................67 10.5 Application of the stochastic optimization framework ...............................................75 10.5.1 Generation of the climate data ...................................................................................75 10.5.2 Estimation of the yield potential of wheat ................................................................75 10.5.3 Estimation of the water productivity potential of barley .........................................77 10.6 Discussion and conclusions ..........................................................................................81 11 Real-time irrigation scheduling ..........................................................................................83 11.1 Objectives and summary ................................................................................................83 11.2 Experimental site and field design ...............................................................................85 11.3 Data collection during the experiment ........................................................................86 11.4 Calibration and setup of the crop growth model Pilote .............................................87 11.5 Derivation of optimal irrigation control functions for different drip line spacings 88 11.5.1 Initial Hydrus 2D/3D simulations ...............................................................................88 11.5.2 Determination of the irrigation control functions .....................................................89 11.5.3 Verifying measurements ..............................................................................................92 11.6 Real-time deficit irrigation scheduling .........................................................................93 11.7 Evaluation of the experimental results .........................................................................96 11.7.1 Crop yields .....................................................................................................................96 11.7.2 Water productivity .........................................................................................................97 11.7.3 Prognostic simulations ................................................................................................98 11.7.4 Economic aspects ........................................................................................................99 11.8 Discussion and conclusions ........................................................................................100 12 Multicriterial optimization...................................................................................................103 12.1 Objectives and summary .............................................................................................103 12.2 Experimental site and experimental setup ...............................................................105 12.3 Data collection during the experiment ......................................................................105 12.4 Experimental layout ......................................................................................................106 12.5 Calibration and validation of the model parameters ..............................................107 12.5.1 Calibration of the soil parameters ...........................................................................107 12.5.2 Calibration and validation of the plant parameters .............................................107 12.5.3 Setup of SVAT model Daisy .....................................................................................108 12.6 Generation of the climate data ....................................................................................109 12.7 Optimized irrigation and N fertilization scheduling .................................................109 12.8 Evaluation of the experimental results .......................................................................111 12.8.1 Observed plant variables and weather data .........................................................111 12.8.2 Water productivities and nitrogen use efficiencies ...............................................111 12.8.3 Chlorophyll Meter values ..........................................................................................112 12.8.4 Recalculation of soil parameters .............................................................................113 12.9 Postprocessing simulations of yield and water and N dynamics..........................114 12.9.1 Yield predictions using Daisy 1D ............................................................................114 12.9.2 Yield predictions using Daisy 2D ............................................................................119 12.10 Discussion and conclusions .....................................................................................121 IV General discussion, conclusions and outlook ...............................................................123 13 General discussion ............................................................................................................125 14 General conclusions and outlook ....................................................................................133 Appendix ....................................................................................................................................134 A Tables and Figures ...............................................................................................................137 B Model setup and weather files ...........................................................................................145 List of Tables .............................................................................................................................153 List of Figures ............................................................................................................................153 References ................................................................................................................................159