This research presents three case studies of low temperature anomalies that occurred during the winter–spring seasons and their influence on extreme events and crop production. We investigate causes and effects of each climate event and developed prediction methods for crops based on the climate diagnostic information. The first study diagnosed the driven environmental-factors, including climate pattern, climate change, soils moisture, and sea level height, associated with the 2011 great flood in Thailand and resulting total crop loss. The second study investigated climate circulation and indices that contributed to wet-and-cold (WC) events leading to significant crop damage in Taiwan. We developed empirical–dynamical models based on prominent climate indices to confidently predict WC events as much as 6 months before they occur. The final study extends from the second study and predict chronic damage to rice crops from climate change by using a crop simulation model. The long-term prediction of rice growth and yield effectively illustrated both decreases and increases in yield depending on climate scenarios. The three studies are different in location and circumstances but the methodologies can be applied across Thailand, Taiwan, and other areas with similar agroclimatology.

La filière betteravière française cherche à gagner en productivité afin d'obtenir des rendements en sucre économiquement satisfaisants. La fertilisation azotée est l'un des principaux facteurs influençant le rendement de la betterave sucrière. De nombreux modèles ont pour but de simuler le rendement en sucre de la betterave mais peu prennent en compte l'effet des conditions de nutrition azotée. Dans ce contexte, les objectifs de ce travail étaient: (i) de mener une réflexion conduisant au choix du type de modélisation, (ii) d'identifier les caractéristiques de la plante en réponse à la nutrition azotée pour le paramétrage du modèle, et (iii) d'évaluer notre modèle. La démarche de modélisation s'est concentrée sur l'intégration des effets de la nutrition azotée sur l'élaboration de la surface foliaire, et sur les relations source-puits au sein de la plante. Des expérimentations au champ sur deux années nous ont permis d'acquérir les données nécessaires à l'étude des réponses de la betterave à des conditions contrastées de nutrition azotée et au paramétrage du modèle. Un travail de compilation de données de validation disponibles à l'ITB a permis de prendre en compte la variabilité des paramètres. Nous avons constaté que la betterave répondait à la nutrition azotée comme les autres plantes en C3. Le modèle simule les différences de rendement en sucre en fonction de l'état de nutrition azotée comme annoncé dans la bibliographie. Le modèle permet de retrouver sans les imposer les stades de croissance de la betterave. Couplé au module de fourniture d'azote du modèle STICS, le modèle permet de simuler les grandes tendances des rendements depuis les trente dernières années. / The French sugar beet industry seeks to increase productivity in order to obtain sugar yields economically satisfactory. Nitrogen fertilization is one of the main factors influencing yield of sugar beet. Many models are designed to simulate the yield of sugar beet but few take into account the effect of nitrogen nutrition conditions. In this context, the objectives of this work were: (i) to reflect leading to the choice of the type of modeling, (ii) to identify the plant characteristics in response to nitrogen nutrition for parameterization of the model and (iii) evaluate our model.The modeling approach has focused on the integration of the nitrogen nutrition effects on the leaf area development, and source-sink relationships within the plant. Two years field experiments have enabled us to acquire data necessary for the study of the sugar beet responses under contrasting nitrogen nutrition conditions and parameterization of the model. A compilation of a data set validation at the ITB makes it possible to take into account parameters variability. We found that sugar beet responded to nitrogen nutrition as the other C3 plants. The model simulates the differences in sugar yield based on nitrogen nutrition status as reported in the literature. The model can find growth stages of sugar beet without force them. Coupled to the supply nitrogen module of the STICS crop model, the model simulates the major trends in yields over the past thirty years.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The SimulArroz is an ecophysiological dynamic processes-based model for simulating the growth, development and grain yield of rice. In order to have scientific credibility, a simulation model has to be tested and exposed to different cropping conditions. Although this model is in use, constant studies and improvements have to be pursued so that new versions are released and able to accurately describe the complex interactions of factors that influence the growth, development and grain yield of rice. The objectives of this thesis were (i) to develop a generalized response function to atmospheric CO2 concentration [f(CO2)] for radiation use efficiency (EUR) in rice and (ii) to evaluate the performance of the SimulArroz model for simulating biomass of rice crop in the central region of Rio Grande do Sul State and grain yield in different rice production regions of the Rio Grande do Sul State with the original model and if the incorporation of a Radiation Use Efficiency (RUE) response function that varies with crop development. Independent data on RUE and grain yield from the literature were used to develop a RUE response function to CO2 and to test the ability of the model to predict grain yield. To test the biomass production with model, a field experiment was conducted in Santa Maria, RS, during the 2011/2012 and 2012/2013 growing seasons, with four cultivars IRGA 421 (very early cycle), BRS Querencia (early cycle) , IRGA 424 (mid cycle) and SCSBRS Tio Taka (long cycle) and three sowing dates in the first year (October, 17th, November, 18th, and December, 19th of 2011) and one sowing date in the second year (October 19th, 2012). The SimulArroz model is efficient in simulating the growth, development, and grain yiel of rice in the state of Rio Grande do Sul, being able to do it in climate change scenarios. / O SimulArroz é um modelo ecofisiológico, dinâmico, baseado em processos para simular o crescimento, o desenvolvimento e a produtividade da cultura do arroz. Um modelo matemático para ter credibilidade científica, precisa ser testado e exposto à diferentes situações de cultivo. Apesar de este modelo estar em uso, necessita constante estudo e aperfeiçoamento para que novas versões sejam lançadas e consigam descrever com precisão as complexas interações dos fatores que influenciam o crescimento, o desenvolvimento e a produtividade de grãos da cultura do arroz. Os objetivos desta tese foram (i) desenvolver uma função matemática de resposta generalizada à concentração de CO2 atmosférico [f (CO2)] pela eficiência de uso de radiação (EUR) em arroz e (ii) avaliar o desempenho do modelo SimulArroz em simular a produção de biomassa da cultura do arroz na região central do Rio Grande do Sul e a produtividade grãos em diferentes regiões orizícolas do Rio Grande do Sul com a EUR original do modelo e com a incorporação de uma função de EUR dependente do ciclo de desenvolvimento da cultura. Dados independentes de EUR e produtividade de grãos na literatura foram usados para construir a f (CO2) e testar a predição de produtividade de grãos do modelo SimulArroz. Para testar a produção de biomassa do modelo, foi conduzido um experimento de campo em Santa Maria, RS, nos anos agrícolas 2011/2012 e 2012/2013, com quatro cultivares, IRGA 421 (ciclo muito precoce), BRS Querência (ciclo precoce), IRGA 424 (ciclo médio) e SCSBSS Tio Taka (ciclo tardio) e três datas de semeadura no ano agrícola 2011/12 (17 de outubro, 18 de novembro e 19 de dezembro de 2011) e uma data de semeadura no ano agrícola 2012/2013 (19 de outubro de 2012). O modelo SimulArroz é eficiente em simular o crescimento, desenvolvimento, produtividade da cultura do arroz no Estado do Rio Grande do Sul, sendo capaz de fazê-lo em cenários de mudança climática

Conselho Nacional de Desenvolvimento Científico e Tecnológico / Projections of a possible climate change indicate that the current CO2 concentration is expected to double and air temperature increase by up to 6°C by the end of this century, leading to changes in crops yield. The impact of climate change on irrigated rice in conditions of Southern Brazil should be positive, with increases in potential grain yield. However, there are few studies to assess the impact of climate change in Rio Grande do Sul, a State with an important role in rice production in the country. Thus, the objective of this study was to simulate the impact of climate change on rice grain yield in Rio Grande do Sul in a climate change scenario based on the IPCC A1B scenario. The grain yield was simulated with the SimulArroz model for three maturity groups (early, middle and late), seven sowing dates (01/08, 01/09, 01/10, 01/11, 01/12, 01/01 and 01/02) at different levels of crop management (technological level), in the six rice production regions of the State. The results indicate that climate change expected for the A1B scenario will have a positive effect on grain yield of rice in Rio Grande do Sul State, mainly at the end of the century, when the sowing period may be anticipated. There were variations on the effect of climate change on yield among the rice production regions with the West part of the State the least favored region and the Southern part of the State the most favored in the future scenario. / Projeções sobre possíveis mudanças climáticas indicam que a atual concentração de CO2 deverá dobrar e a temperatura do ar aumentar em até 6°C até o final deste século, proporcionando alterações na produtividade das culturas agrícolas. O impacto da mudança climática na cultura do arroz irrigado nas condições do Sul do Brasil deverá ser positivo, com aumento na produtividade potencial de grãos. No entanto, ainda há poucos estudos para avaliação do impacto da mudança climática no Rio Grande do Sul, estado com importante participação na produção de arroz do país. Assim, este trabalho teve como objetivo simular o impacto da mudança climática na produtividade de grãos de arroz irrigado no Rio Grande do Sul, em um cenário de mudança climática baseado no cenário A1B do IPCC. A produtividade de grãos foi simulada com o modelo SimulArroz para três grupos de maturação (precoce, médio, tardio), sete datas de semeadura (01/08, 01/09, 01/10, 01/11, 01/12, 01/01, 01/02) em diferentes níveis de manejo da lavoura (níveis tecnológicos) nas seis regiões orizícolas do estado. Os resultados indicam que a mudança climática prevista no cenário A1B terá efeito positivo na produtividade de grãos de arroz irrigado do estado do Rio Grande do Sul, principalmente no final do século XXI, quando o período de semeadura poderá ser antecipado. Entre as regiões orizícolas houve variação do efeito da mudança no clima sobre a produtividade, sendo a Fronteira Oeste menos favorecida e a Zona Sul a mais favorecida no cenário futuro.

<p>The presented work quantifies the impacts of inundated land area (ILA) on streamflow and crop development in the Upper Midwest, which is experiencing a changing climate with observed increases in temperature and precipitation. Quantitative information is needed to understand how upland and downstream stakeholders are impacted by ILA; yet the temporal and spatial extent of ILA and the impact of water storage on flood propagation is poorly understood. Excess water in low gradient agricultural landscapes resulting in ILA can have opposing impacts. The ILA can negatively impact crop development causing financial loss from a reduction or total loss in yield while conversely, ILA can also benefit downstream stakeholders by preventing flood damage from the temporary surface storage that slows water movement into channels. This research evaluates the effects of ILA on streamflow and crop development by leveraging the utility of remotely sensed observations and models.</p><p> </p><p>The influence of ILA on streamflow is investigated in the Red River basin, a predominantly agricultural basin with a history of damaging flood events. An inundation depth-area (IDA) parameterization was developed to parameterize the ILA in a hydrologic model, the Variable Infiltration Capacity (VIC) model, using remotely sensed observations from the MODIS Near Real-Time Global Flood Mapping product and discharge data. The IDA parameterization was developed in a subcatchment of the Red River basin and compared with simulation scenarios that did and did not represent ILA. The model performance of simulated discharge and ILA were evaluated, where the IDA parameterization outperformed the control scenarios. In addition, the simulation results using the IDA parameterization were able to explain the dominant runoff generation mechanism during the winter-spring and summer-fall seasons. The IDA parameterization was extended to the Red River basin to analyze the effects of ILA on the timing and magnitude of peak flow events where observed discharge revealed an increasing trend and magnitude of summer peak flow events. The results also showed that the occurrence of peak flow events is shifting from unimodal to bimodal structure, where peak flow events are dominant in the spring and summer seasons. By simulating ILA in the VIC model, the shift in occurrence of peak flow events and magnitude are better represented compared to simulations not representing ILA.</p><p> </p><p>The impacts of ILA on crop development are investigated on soybean fields in west-central Indiana using proximal remote sensing from unmanned aerial systems (UASs). Models sensitive to ILA were developed from the in-situ and UAS data at the plot scale to estimate biomass and percent of expected yield between the R4-R6 stages at the field scale. Low estimates of biomass and percent of expected yield were associated with mapped observations of ILA. The estimated biomass and percent of expected yield were useful early indicators to identify soybean impacted by excess water at the field scale. The models were applied to satellite imagery to quantify the impacts of ILA on soybean development over larger areas and multiple years. The estimated biomass and percent of expected yield correlated well with the observed data, where low model estimates were also associated with mapped observations of ILA and periods of excessive rainfall. The results of the work link the impacts of ILA on streamflow and crop development, and why it is important to quantify both in a changing climate. By representing ILA in hydrologic models, we can improve simulated streamflow and ILA and represent dominant physical process that influence hydrologic responses and represent shift and seasonal occurrence of peak flow events. In the summer season, where there is an increased occurrence of peak flow events, it is important to understand the impacts of ILA on crop development. By quantifying the impacts of ILA on soybean development we can analyze the spatiotemporal impacts of excess water on soybean development and provide stakeholders with early assessments of expected yield which can help improvement management decisions.</p>

This thesis consists of three chapters, each dealing with a different aspect of the impact of climate change on agriculture: the analysis of past evidence, the possible new solutions and the anticipation of future problems. The topics chosen are different but complementary and reflect the complex and multifaceted impact of this phenomenon on agriculture. This work uses global spatial data and information from the literature, combines weather forecast with a crop model, and uses an economic model coupled with robust econometric estimation approaches. The findings indicate that major crop yields in tropical and subtropical regions will likely suffer adverse effects, while temperate and continental areas, historically less favourable for agriculture, may experience mainly positive impacts. Under a medium development scenario, global crop production is projected to remain largely unaffected, masking a compensatory mechanism between tropical and temperate regions. Adaptation covers a significant positive role, and short- and medium-range weather forecasting can be an important and affordable tool for farmers to adapt their agricultural practices, if they know how to use it. The adoption of such meteorological information can enable rural households in developing countries to increase yields of staple crops, although the potential contribution of it may be hampered by social and economic barriers. However, adaptation in agriculture can have negative externalities, potentially creating a vicious circle, and the livestock sector is particularly vulnerable. Indeed, changing climate conditions may induce farmers to adjust the distribution of grazing livestock per unit of land in order to maximise profits. Temperate and continental countries may increase the number of grazing livestock per unit of land as climatic conditions improve for agricultural purposes, thereby increasing carbon dioxide emissions. On the other hand, tropical areas, mainly populated by developing countries, will see a deterioration of agricultural conditions and less livestock can be raised on rangelands and pasturelands. Once again, countries with pressing agricultural productivity needs bear a disproportionate burden of climate change effects, exacerbating already precarious living conditions. Conversely, northern countries, primarily developed, are likely to experience more beneficial effects.

Les légumineuses sont souvent considérées comme des cultures clés pour une agriculture durable. Dans ce cadre, elles sont souvent cultivées en association avec les céréales et présentent de nombreux avantages d'ordres agronomique, environnemental et socio-économique. Cependant, malgré ces nombreux avantages, leur part dans l'agriculture européenne est encore très limitée. Dans la région Midi-Pyrénées (sud-ouest de la France), la superficie occupée par les légumineuses ne représente que 1 à 3% de la superficie totale cultivée, traduisant la réticence des agriculteurs à cultiver ce type de culture. Dans ce contexte, l'objectif de la thèse étaient de: i) identifier les principales contraintes pour la production de légumineuses dans la région Midi-Pyrénées, ii) identifier les principaux leviers techniques et socio-économiques (exprimés sous forme de scénarios) afin de promouvoir les légumineuses dans les systèmes de cultures actuels et iii) évaluer, en utilisant la chaîne de modélisation APES-FSSIM-indicateurs, les impacts de ces scénarios en calculant des indicateurs socio-économiques et environnementaux au niveau de trois exploitations représentatives (FT1, FT2 et FT3) de la diversité observée au niveau de la zone d'étude.L'identification des principales contraintes a été basée sur la bibliographie et les dires d'experts locaux. Ces contraintes traduisent la sensibilité des légumineuses aux types de sols et de climat, les compétences techniques demandées pour cultiver convenablement des légumineuses, la compétitivité économique des légumineuse par rapport aux autres cultures et à l'actuel prix et rendement des légumineuses et surtout leurs variabilité inter-annuelle. Pour promouvoir les légumineuses, des scénarios alternatifs ont été définis et comparés à la situation actuelle (scénario de référence). Les scénarios alternatifs, se différencie par rapport au scénario de référence par les paramètres suivantes: l'introduction de nouvelles rotations à base de légumineuses dans les systèmes de culture actuels (Stec.innov), l'octroie d'une prime spécifique aux légumineuses (Spremium), l'augmentation du prix de vente ( Sprice) et du rendement (Syield) des légumineuses, la réduction de la variabilité du prix (Sprice.var) et du rendement (Syield.var) des légumineuses et enfin, la combinaison de tous ces paramètres dans un seul scénario (Scomb). Tous les scénarios ont été simulés et comparés en utilisant la chaîne de modèles APES-FSSIM-indicateurs. Cette chaine de modèles a permis de calculer des indicateurs environnementaux et socio-économiques.Les résultats ont montré que, contrairement aux attentes, l'introduction de nouvelles rotations et la réduction de la variabilité des rendements ou des prix (Stec.innov, Sprice.var et Syield.var) n'entrainent pas l'augmentation de la superficie des légumineuses. Toutefois, une augmentation de la superficie des légumineuses a été observée pour les scénarios Spremium, Sprice, Syield et Scomb. Le scénario combiné (Scomb) a été jugé comme le plus efficace, montrant une augmentation importante de la superficie des légumineuses, soit 34 ha, 32 ha et 7 ha respectivement pour FT2, FT3 et FT1. Ce changement a entrainé également une modification significative au niveau des valeurs des indicateurs socio-économiques et environnementaux. L'augmentation de la superficie des légumineuses et la variation des indicateurs économiques et environnementaux dépendent des caractéristiques structurelles des exploitations, de la part de la surface irriguable, des systèmes de culture présents et des types de sol au niveau de chaque exploitation.Les résultats de cette étude montrent que l'application d'une nouvelle politique pour promouvoir les légumineuses, peut conduire, selon les stratégies de production adoptées par les agriculteurs afin de maximiser leurs revenus, à plusieurs changements économiques et environnementaux. Ces stratégies se traduisent principalement par la modification des superficies allouées / Grain legumes are generally considered as key crops for sustainable agriculture. They offer many agronomic, environmental and socio-economic benefits when grown in succession with cereals. Although grain legumes have many advantages, their share in European agriculture is still very limited. In the Midi-Pyrénées region (south-west of France), their area varies from 1 to 3% of the total cultivated area, moreover farmers show little interest in growing grain legumes on their farms. In this context, the objectives of the thesis were to; i) identify the main constraints for grain legume production in the Midi-Pyrénées region, ii) identify key technical and socio-economic levers (expressed as scenarios) to promote grain legumes in current cropping systems and iii) assess, by using the APES-FSSIM-Indicators modelling chain, the impacts of these scenarios on the socio-economic and environmental behaviours of three representative arable farm types (FT1, FT2 and FT3) of the Midi-Pyrénées region.The main constraints have been identified based on bibliography and in consultation with local experts. These constraints are derived from the grain legumes sensitivity to: soils and climatic conditions, farmer technical skill and expertise for sowing and harvesting the grain legumes, economic competitiveness in comparison with cereals and their yield and market prices amounts and fluctuations. From the above statement, the alternative scenarios, in comparison to the current situation (reference scenario) have been identified to promote grain legumes. They included, the introduction of new grain legumes rotations in current cropping systems of the region (Stec.innov), provision of more premiums to grain legumes (Spremium), increase in sale price (Sprice) and yield (Syield) of grain legumes, reduction in price (Sprice.var) and yield (Syield.var) variability of grain legumes, and combination of all these components (Scomb). All scenarios have been assessed with quantitative environmental and socio-economic indicators and are calculated with the APES-FSSIM-Indicators modeling chain.Results show that, contrary to expectation, the introduction of new legumes rotations or the reduction of yield or price variability (Stec.innov, Sprice.var and Syield.var) did not increase the grain legumes area. However, an increase in grain legumes area was observed for Spremium, Sprice, Syield and Scomb. The combined scenario (Scomb) was found to be most efficient, showing an important increase in grain legumes area by 34 ha, 32 ha and 7 ha respectively for FT2, FT3 and FT1 with a significant change in socio-economic and environmental indicators for all three farm types. The increase in grain legumes area and modification in economic and environmental indicators depend on the farm characteristics and can be explained by the differences in irrigable area between irrigated crops (i.e. maize, peas and soybean), cropping pattern, soil types and climatic conditions (rainfed and irrigation) on the three farms types.The results obtained from this study show that the modification of policies or the inclusion of new technologies, may lead to several economic and environmental changes, which reveal the adaptation strategies adopted by farmers in order to optimize their farm income. These strategies are mainly implemented by modifying the areas allocated to different crops on different soil types and by changes of management practices. The grain legumes area can be increased on Midi-Pyrénées farming system by the combination of slightly increase in premium, sale price and crop yield of the grain legumes. This methodology can easily be adapted to other regions of France and also EU for identifying the main developmental conditions for grain legumes production provided the skilled experts are properly selected and sufficient data are available for parameterization of the modeling chain.

Sich ändernde Klima- und Wetterbedingungen in Verbindung mit einer begrenzt ausdehnbaren Ackerfläche werden den Druck auf Nahrungsmittelproduktionssysteme weiter erhöhen. Um dieser Herausforderung gerecht zu werden, ist eine Erhöhung und Stabilisierung der Ernteerträge unverzichtbar. Dies erfordert aber ein tieferes Verständnis der Einflussfaktoren, die auf die Ertragsvariabilität wirken. Diese Dissertation leistet einen Forschungsbeitrag zu Ertragsmodellen in Deutschland, Tansania und auf globaler Ebene. Dazu analysiere und kombiniere ich statistische und prozessbasierte Ertragsmodelle in fünf Schritten: (i) Zunächst entwickele ich einen statistischen Modellansatz, um den Einfluss von Wetter und agronomischem Management auf Winterweizenerträge in Deutschland zu separieren. (ii) Auf der Grundlage dieses Modells erweitere ich die statistischen Methoden und wende sie für Winterweizen und Silomais auf regionale Ebene an. (iii) Diesen erweiterten Modellansatz verwende ich daraufhin zum Testen einer Kreuz-Validierung um zukünftige Ertragsänderungen unter Klimawandel zu projizieren. (iv) Anschließend wird in einer globalen statistischen Anwendung dieses Modell für kurzfristige Ertragsprognosen getestet. (v) Schließlich kombiniere ich für das Fallbeispiel Mais in Tansania statistische und prozessbasierte Ertragsmodelle, um wetterbedingte Ertragsverluste von nicht-wetterbedingten Ertragsverlusten zu separieren. Als Ergebnis lässt sich zusammenfassen, dass der Anteil der wetterbedingten Ertragsvariabilität in Deutschland höher ist als in Tansania. Dementsprechend sind die Ertragsschwankungen in Tansania eher auf das agronomische Management und sozioökonomische Einflüsse zurückzuführen. Für beide Länder stelle ich fest, dass der Anteil der wetterbedingte Ertragsvariabilität auf aggregierter Ebene höher ist als auf regionaler Ebene. Der kombinierte statistisch-prozessbasierte Ansatz zur Bewertung von wetterbedingten Ertragsverlusten kann für Versicherungszwecke genutzt werden. / Due to changing climate and weather patterns in combination with limitations to extend global arable land area, the pressure on food production systems will increase. To cope with this challenge, it will be indispensable to increase and stabilize crop yields. This requires, however, a deeper understanding of the factors influencing crop yield variability. This dissertation contributes to that research need as I further develop and apply crop models to assess regional wheat and maize yield variability in Germany, Tanzania and on a global scale. For this, I analyze and combine statistical and process-based crop models within five steps: (i) First, I develop a statistical crop modeling approach to decompose the influence of weather and agronomic management on winter wheat yields in Germany. (ii) Based on the first step, I expand the statistical methods and apply augmented models for winter wheat and silage maize on a disaggregated level. (iii) Then this model approach is used to investigate an out-of-sample cross validation to demonstrate the models’ capability to project future yield changes under climate change. (iv) In a global statistical application, this models’ capability of projecting yields is tested for short-term yield forecasts. (v) Finally, I combine statistical and process-based crop modeling to decompose weather-related maize yield losses from losses caused by non-weather factors for the case of Tanzania. Across these five steps, I find that the share of weather-related yield variability is higher in Germany than in Tanzania. Accordingly, crop yield variability in Tanzania is to a higher share attributable to agronomic management and socio-economic influences. For both countries, I find that the share of explained weather-related yield variability is higher on an aggregated level than on the regional level. Finally, this combined statistical-process-based approach can be used for assessing weather-related crop yield losses for insurance purposes.

Ein computergestütztes Simulationsmodell für die Schnittblumen-Steinwollkultur der Gerbera jamesonii (H. Bolus ex Hook.) wurde am Beispiel der Sorte 'Moana' erstellt. Aufbauend auf Messdaten morphologischer und physiologischer Parameter an Versuchspflanzen ließ sich das Wachstum von Blättern, Wurzeln und Blumen modellieren. Unter Berücksichtigung äußerer Einflussgrößen konnte mit dem Modell die Entwicklung eines Gerberabestandes hinsichtlich des Wachstums der Blätter, Blumen und Wurzeln einschließlich der wichtigsten Ertragskomponente, dem kumulativen Blumenertrag, in Abhängigkeit von physiologischen Leistungskriterien wie Atmung, Kohlendioxid- und Stickstoffaufnahme simuliert werden. Die Auswertungen des zeitlichen und räumlichen Wachstums der Gerbera der Sorte 'Moana' zeigten, dass die Blattverteilung unter Berücksichtigung des Alters Einfluss auf die Photosyntheseleistung des Bestandes nahm. Ebenso wurde eine Abhängigkeit der Blumenentwicklung von der Blattbildung nachgewiesen. Diese Ergebnisse waren die Basis für die Entwicklung der Modellstruktur. Teile von in der Literatur beschriebenen Modellen konnten erfolgreich in eine übergeordnete Modellstruktur eingebunden werden. Für den Wechsel zwischen vegetativem und generativem Wachstum unter Berücksichtigung der Blattalterung wurden für die Gerbera spezifische Modellfunktionen entwickelt. Bislang nicht verfügbare Gleichungssysteme zur Definition des Einflusses der Umweltparameter auf die Kohlendioxid- und Stickstoffaufnahme waren das Ergebnis von Gaswechsel- und Stickstoffaufnahmeanalysen. Die mit dem Modell berechneten Wachstumswerte für die Blattentwicklung und den Blumenertrag stimmten bei Verwendung gleicher Umweltbedingungen mit denen einer Gewächshauskultur überein. Des weiteren erwies sich das Modell für die Analyse der Auswirkungen eines simulierten Blattbrechvorgangs mit seinen Prognosen als geeignet. Die Verwendung des Modells zur Bestimmung optimaler Klima- und Wachstumsparameter für die Kultur der Sorte 'Moana' führte zu Werten, die bei konstanter Einhaltung eine 60 prozentige Ertragssteigerung gegenüber anfänglich eingesetzten Parametern bedingten. Für den Praktiker stellt das Modell ein Hilfsmittel dar, in einer Gerberakultur mit der Sorte 'Moana' die Sollwerte der Klimaführung bei gegebenen nicht beeinflussbaren Kulturbedingungen zu optimieren, um größtmögliche Erträge zu erzielen. Dem Versuchsansteller in Forschungseinrichtungen wird damit ein Rüstzeug gegeben, klima- und kulturtechnische Einflussgrössen und deren Kombinationen vorab mit dem Modell zu überprüfen, Extremwerte zu identifizieren und somit sinnvolle Versuchsparameter in Abhängigkeit des Versuchszieles zu definieren. / A computer based crop simulation model for a cut flower rockwool cultivation of Gerbera jamesonii (H. Bolus ex Hook.) has been developed for the cultivar 'Moana'. Basing on measurements of morphological and physiological parameters at experimental plants growth of leaves, roots and flowers has been modelled. In consideration of different physical environmental conditions the model was able to simulate the development of a Gerbera crop concerning growth of leaves, flowers and roots including the most important yield component the cumulative flower yield in dependence on physiological efficiency parameters like respiration, carbon dioxide and nitrogen assimilation. The evaluation of time and space dependent growth of Gerberas of the cultivar 'Moana' showed the influence of leaf distribution with regard to leaf age on the photosynthetic efficiency of the crop. Furthermore there was evidence of a dependency of flower growth on leaf development. On the the basis of these results the model structure has been worked out. Elements of already in the relevant literature descripted models were successfully incorporated into the superior model structure. To switch between vegetative and generative growth with regard to leaf aging a special submodel has been developed for the Gerbera crop. Till now not available mathematical functions to define the influence of the environmental conditions on carbon dioxide and nitrogen assimilation resulted form gas exchange and nitrogen uptake analysis. Growth data for leaf development and flower yield calculated by the model corresponded to the observed data when the same values for the environmental parameters have been used. Furthermore the model was able by means of its predictions to analyse the effects of simulated leaf picking. The use of the model to calculate optimized climatic and growth parameters for a cultivation of the cultivar 'Moana' led to values that produced an increase in yield of about 60 percent in comparison to initially applied parameters. For the practice the model represents a tool for seeking optimal combinations of environmental control and crop management strategies for a Gerbera crop using the cultivar 'Moana' to maximise yield. For the research engineer in experimental stations an equipment is provided to test environmental control and crop management strategies in advance to identify extremes and senseful experimental parameters in dependence on the objective of the trial.

<p>Kvantifikovanjem uticaja klimatskih promena na biljnu proizvodnju stiče se mogućnost obrazovanja dugoročnih planova u poljoprivrednoj proizvodnji kako bi se održao visok i stabilan prinos ključnih gajenih kutura (p&scaron;enice, kukuruz). Najpre su urađene analize klime i agroklimatskih pokazatelja za sada&scaron;nje uslove 1971-2000. i očekivane uslove za 2030. i 2050. godinu za 11 lokaliteta Republike Srbije. Tek nakon analize klime uzima se u obzir poznata činjenica da postoji međusobna interakcija između meteorolo&scaron;kih uslova, zemlji&scaron;ta i biljke. Na ovoj interakciji zasnivaju se modeli biljne proizvodnje i upotrebljavaju se u cilju kvantifikovanja uticaja klimatskih promena na biljnu proizvodnju tj. na dinamiku vegetacije i prinos.<br />U radu su kori&scaron;ćeni osmotreni dnevni meteorolo&scaron;ki podaci sa jedanaest stanica sakupljenih u Republičkom Hidrometeorolo&scaron;kom Zavodu Srbije. Za buduće stanje klime kori&scaron;ćeni su izlazni podaci globalnih klimatskih modela (ECHAM, HadCM, NCAR) i njihovom statističkom regionalizacijom Met &amp; Roll vremenskim generatorom dobijeni su podaci o budućem stanju klime na području jedanaest izabranih lokaliteta. Podaci o zemlji&scaron;tu (mehaničke i hemijske osobine) preuzeti su od Agencije za za&scaron;titu životne sredine iz Beograda. Ulazni podaci o biljnoj vrsti i njenoj agrotehnologiji, neophodni u radu sa modelom biljne proizvodnje (kalibraciji i validaciji), obezbeđeni su sa vi&scaron;egodi&scaron;njih ogleda zasnovanih na oglednim poljima Rimskih &Scaron;ančeva Insituta za ratarstvo i povrtarstvo u Novom Sadu.<br />Kao metod kori&scaron;ćeni su modeli za određivanje agroklimatskih parametara Agriclim i model biljne proizvodnje DSSAT v. 4.2.<br />4<br />Analizom buduće klime, temperature vazduha i padavina, utvrđeno je da se može očekivati porast temperature vazduha na godi&scaron;njem nivou i tokom svih delova vegetacinog perioda, a količina padavina se očekuje da bude vi&scaron;a tokom zimskog perioda, dok u prolećnom periodu (mart &ndash; april - maj) ne&scaron;to niža do 10 mm, a tokom letnjih meseci jun-jul-avgust značajno niža.<br />Analizom rezultata DSSAT 4.2 modela biljne proizvodnje, utvrđeno je da u očekivanim klimatskim uslovima 2030. i 2050. godine pri koncentraciji CO2 od 330 ppm prinos zrna ozime p&scaron;enice ostaje nepromenjen u većini lokaliteta izuzev Kru&scaron;evcu, Somboru i Vranju gde prinos opada do 12% u 2030. i do 11% u 2050. godini. Uzrok visokih i stabilnih prinosa su povećane količine padavina i povećanje temperature vazduha u zimskom periodu, manji broj mraznih i ledenih dana. Jedan od najvažnijih faktora stabilnosti prinosa je i dovoljna količina rezerve vlage u zemlji&scaron;tu za prolećni period i količina padavina za prolećni period, koji je u literaturi određen kao kritični period potrebe p&scaron;enice za vodom. U budućim uslovima analizom rezultata broja dana potrebnih od setve do cvetanja i od setve do zrelosti, ustanovljeno je da se očekuje manji broj dana, tj. da će fenofaze kraće trajati do cvetanja i zrelosti &scaron;to je posledica očekivanih vi&scaron;ih temperatura vazduha i suma efektivnih temperatura. U uslovima 2030. i 2050. godine i očekivane koncentracije CO2 po IPCC izve&scaron;taju iz 2007. godine, uticaj povi&scaron;ene koncentracije CO2 na prinos zrna p&scaron;enice je pozitivan. Prinosi kod većine lokaliteta ostaju nepromenjeni dok je mali pad prinosa zrna bio primećen na lokalitetima Kru&scaron;evac i Sombor, gde neznatno opada do 7% u 2030. godini i 2050. godini. U Somboru se očekuje nepromenjena količina padavina za mart &ndash; april - maj period i mnogo manja količina padavina u periodu jun &ndash; jul - avgust, a u Kru&scaron;evcu ne&scaron;to manja količina padavina u periodu mart &ndash; april &ndash; maj i do 40% manja količina u periodu jun &ndash; jul - avgust u 2050. godini.<br />Analizom rezultata prinosa zrna kukuruza za 2030. i 2050. godinu pri koncentracije CO2 od 330 ppm dobijen je veoma značajan pad prinosa i u uslovima bez navodnjavanja i u uslovima navodnjavanja normom od 180 mm za sve lokalitete. U 2030. i 2050. godini u uslovima povi&scaron;ene koncentracije CO2 uticaj očekivane koncentracije CO2 na prinos zrna kukuruza simulacijama ocenjen je kao negativan, jer je dobijeni prinos zrna kukuruza bio jo&scaron; niži nego pri koncentraciji CO2 od 330 ppm.<br />Veoma značajan pad prinosa posledica je vi&scaron;ih temperatura vazduha u JJA periodu, povećanja fiziolo&scaron;kog stresa kod biljaka usled povećanja broja letnjih i tropskih dana, značajno smanjenje količine padavina, posebno u periodu jun &ndash; jul &ndash; avgust i povećanje broja su&scaron;nih dana tokom istog perioda. Analizom dužine trajanja vegetativne sezone za oba režima uzgajanja kukuruza moglo se zapaziti da se u budućim uslovima očekuje skraćenje perioda vegetacije zbog vi&scaron;ih temperatura vazduha i sume temperatura. Analizom rezultata simulacije prinosa zrna soje za 2030. i 2050. godinu pri koncentraciji CO2 od 330 ppm, očekuje se nepromenjen prinos zrna u lokalitetima Ćuprija, Ni&scaron;, Vranje i Prizren, ili neznatno vi&scaron;i do 9 % u lokalitetima Kraljevo, Kru&scaron;evac, Novi Sad, Sombor i Zaječar. Samo u istočnom lokalitetu Dimitrovgrad i centralnom Požega se očekuje značajno vi&scaron;i prinos do 14% u 2030. godini i do 23% u 2050. godini. U 2030. i 2050. godini pri povi&scaron;enoj koncentracije CO2 po IPCC izve&scaron;taju iz 2007. godine očekuje se veoma značajno vi&scaron;i prinos u svim lokalitetima, a posebno je nagla&scaron;eno u lokalitetima Dimitrovgrad i Požega gde su dobijene najniže srednje temperature vazduha za AMJ i JJA period, najmanji broj letnjih i tropskih dana. Nakon dobijenih rezultata prinosa zrna za izabrane biljne kulture, rezultati prinosa zrna kukuruza ukazivali su na potrebu definisanja i uvođenja mera adaptacija u dosada&scaron;nju agrotehnologiju. DSSAT model biljne proizvodnje je izabran u istraživanju i kvantifikovanju mera adpatacija, jer se potrebe i fiziolo&scaron;ke reakcije biljke u simulacijama mogu pratiti na dnevnom nivou (Wang et al., 2011). Kao mere adaptacije analizirane su adaptacija roka setve i navodnjavanje. Adaptacija roka setve urađena je za kukuruz u uslovima bez navodnjavanja, da bi se ocenio isključivo uticaj primene ranijeg roka setve na prinos, a ne i navodnjavanje. Na osnovu analize<br />5<br />rezultata relativne promene prinosa za sve lokalitete, pokazalo se da se u uslovima ranijeg roka setve očekuju vi&scaron;i prinosi nego u uslovima uobičajenog datuma setve. Međutim, u svim lokalitetima i dalje se očekuje veoma značajan pad prinosa, izuzev u Dimitrovgradu, Vranju i Prizrenu, gde se očekuje značajan porast u odnosu na prinose perioda 1971-2000. godina.<br />Na osnovu analize rezultata simuliranih prinosa za ozimu p&scaron;enicu, kukuruz i soju, konstatovano je da se p&scaron;enica može proizvoditi u uslovima bez navodnjavanja, a prolećni usevi kukuruz i soja bi morali da se navodnjavaju zbog očekivanog velikog smanjenja količine padavina u letnjem periodu. Da bi se procenila adekvatna norma navodnjavanja u proizvodnji kukuruza u simulacijama u DSSAT modelu biljne proizvodnje izabrana je opcija 50 % dostupne vode biljci. Simulacije proizvodnje kukuruza u uslovima 50% dostupne vode biljci dale su pozitivne rezultate prinosa. Prinosi su bili nepromenjeni u lokalitetima Ćuprija, Kru&scaron;evac, Kraljevo, Ni&scaron;, Novi Sad, Sombor, Vranje, Zaječar u 2030. godini i 2050. godini izuzev u Kraljevu gde je prinos bio niži do 17% u 2050. godini. U lokalitetima Dimitrovgrad, Požega i Prizren prinos je bio vi&scaron;i oko 9% u 2030. godini i nepromenjen u 2050. godini. Uvećanje norme navodnjavanja je bilo veoma značajno na većini lokaliteta od 20% do 30% sa maksimumom u Požegi do 45% u 2030. i 84% u 2050. godini. Lokalitet Požega imao je zemlji&scaron;te tipa ilovasti fluvisol i izmeren visok procenat peska, iznad 50% u svom mehaničkom sastavu, &scaron;to je uslovilo i veću propusnost vode, njeno kraće zadržavanje u profilu zemlji&scaron;ta i potrebu za većom količinom vode u navodnjavanju. Simulacije prinosa soje odmah su urađene u uslovima navodnjavanja od 50% dostupne vode biljci, jer je opcija u uslovima bez navodnjavanja davala jako niske prinose, a opcija 50% dostupne vode je davala takve norme navodnjavanja koje su bile slične u na&scaron;im uslovima na Institutu za ratarstvo i povrtarstvoPri takvoj opciji navodnjavanja u svim lokalitetima norma navodnjavanja je u budućim uslovima veoma značajno rasla od 10 do 40% u 2030. godini i od 13 do 110% u 2050. godini, a rezultati relativne promene prinosa ukazivali su na veoma značajno povećanje prinosa u budućim&nbsp;uslovima.</p> / <p>DSSAT 4.0 is a crop model commonly used to quantify the climate change impact on agriculture production. The model predictions are very important for long term planning in agriculture to keep high and stable yield production. At the first, the climate was analysed for 1971-2000 period, 2030 and 2050 year. After these analyses the crop model was run. Crop model is based on interaction between climate, soil and plant. Simulations were predicted the yield and dynamic in vegetation for 2030 and 2050 climate conditions. As input parameters were used observed daily weather data from eleven weather stations for 1971-2000 period. For 2030 and 2050, the data were used from global climatology models ECHAM5, HadCM3 and NCAR-PCM for two scenarios A1B and A2. Before crop simulations, the out results from global climatology models had to be regionalised and downscaled with Met &amp; Roll weather generator. The soil input data were assumed from Agency for Environmental Safety from Belgrade. The data were consist of mechanical and chemical characteristics of soil which were chosen near the weather station. The crop input data were collected from the literature and personal communication of Institute of Field and Vegetable Crops and their long term period experiments. A current and future agroclimatic indices were calculated with Agriclim model. As a crop model, DSSAT v. 4.2. was chosen for crop simulations of major field crops: winter wheat, maize and soybean.<br />The results of climate shown that the air temperature should be higher in all vegetation phases, and precipitation should be higher during winter months, lower for 10 mm in spring and significantly lower in summer months June- July-August.<br />In 2030 and 2050 year (CO2=330 ppm) simulations shown that winter wheat yield might be the same as in 1971-2000 period in most locations except in Krusevac, Sombor and Vranje where yield might be lower for 12% in 2030 year and lower for 11% in 2050 year. It is a consequence of expected higher precipitation and higher air temperatures during winter period, less frosty and frozen days, higher precipitation during spring, which is a critical period for winter wheat production. It was analysed the dinamyc in vegetation in future<br />9<br />conditions. The results showed the shorter vegetation, less number of days from seeding to anthesis and seeding to maturity. These changes in vegetation duration were caused by expected higher air temperatures and higher effective temperatures.<br />The yield results were also analysed for expected conditions under future CO2 concentration from IPCC report 2007, and shown that winter wheat yields were not changed for most locations except in Krusevac and Sombor in 2030 and 2050 year.<br />The maize yield results for 2030 and 2050 under CO2 concentration of 330 ppm shown a significant decrease in yield in non irrigated conditiond and irrigated conditions with 180 mm water added per vegetation season. Also, the results given under expected CO2 concentration from IPCC Report 2007, shown great decrease in 2030 and 2050 and lower yield than under CO2 was set on 330 ppm. The significant decrease in yield was caused by expected higher temperatures in JJA period, higher physiologicaly stress caused by more days with extreme high temperatures (summer and tropical days) and very significant decrease in precipitation during JJA period. The results showed the shorter vegetation, less number of days from seeding to anthesis and seeding to maturity. These changes in vegetation duration were caused by expected higher air temperatures and higher effective temperatures.<br />The soybean yield analyses for 2030 and 2050 under CO2 concentration of 330 ppm shown no changes in yield for Cuprija, Nis, Vranje and Prizren, a little higher to 10% in Kraljevo, Krusevac, Novi Sad, Sombor, Zajecar and up to 24% higher in Dimitrovgrad and Pozega. In 2030 and 2050 under future CO2 concentrations from IPCC Report 2007, it is expected a significantly higher yield in all locations especially for Dimitrovgrad and Pozega, where the air temperatures were lowest in AMJ and JJA period. The results showed the shorter vegetation in soybean production, less number of days from seeding to anthesis and seeding to maturity. These changes in vegetation duration were caused by expected higher air temperatures and higher effective temperatures. After all simulations for winter wheat, maize and soybean, it is concluded that maize production need some adaptation measures for future conditions. As an adaptation measure it were chosen two measures: the shift in sowing date and irrigation quantity. The adaptation in sowing date was set for maize under non irrigated conditions, to analyse only the time of sowing not irrigation. The sowing date was set 15 days earlier, on the 5th of April. The yield results shown less decrease than results given at usual sowing date (20th of April), but in all locations the predicted yield decreased except in DM, VR and PR where the yield shown significant increase in a comparison with 1971-2000 yield. The change in irrigation quantity was more efficient for yield. It was done for maize production and soybean, because winter wheat irrigation was estimated as non economic. The irrigation method was set on 50% available water for plant. The maize yield was stable in Ćuprija, Kru&scaron;evac, Kraljevo, Ni&scaron;, Novi Sad, Sombor, Vranje, Zaječar in 2030 and 2050 year except in Kraljevo where the yield decreased up to 17% in 2050 year. In Dimitrovgrad, Požega and Prizren the yield was higher for 9% in 2030 year and not chaged in 2050 year. The water requirements had significantly higher values than in 1971-2000 period up to 20-30% in 2030 year with maximum in Požega up t 45% in 2030 year and 84% in 2050 year. The location Požega has soil with a high percent of sand in structure, above 50%, what caused quick water filtration and more water in irrigation. The soybean simulations were done in irrigation option of 50% available water at the begining, because the non irrigated method did not gave the satisfied yield results in crop model. The 50% irrigation method gave adequate yield and water requirements as in experiments on Institute. The water requirements had significantly higher values in 2030 year from 10-40% and from 13% to 110% in 2050 year than in 1971-2000 period.<br />Key words: climate change, CO2 fertilization, DSSAT v. 4.2. crop model, effective irrigation, maize yield, soybean yield, vegetation, winter wheat yield.</p>