Process-based models are used in a diverse array of fields, including environmental engineering to provide supporting information to engineers, policymakers and stakeholdes. Recent advances in remote sensing and data storage technology have provided opportunities for improving the application of process-based models and visualizing data, but also present new challenges. The availability of larger quantities of data may allow models to be constructed and calibrated in a more thorough and precise manner, but depending on the type and volume of data, it is not always clear how to incorporate the information content of these data into a coherent modeling framework. In this context, using process-based models in new ways to provide decision support or to produce more complete and flexible predictive tools is a key task in the modern data-rich engineering world. In standard usage, models can be used for simulating specific scenarios; they can also be used as part of an automated design optimization algorithm to provide decision support or in a data-assimilation framework to incorporate the information content of ongoing measurements. In that vein, this thesis presents and demonstrates extensions and refinements to leverage the best of what process-based models offer using Differential Evolution (DE) the Extended Kalman Filter (EKF). Coupling multi-objective optimization to a process-based model may provide valuable information provided an objective function is constructed appropriately to reflect the multi-objective problem and constraints. That, in turn, requires weighting two or more competing objectives in the early stages of an analysis. The methodology proposed here relaxes that requirement by framing the model optimization as a sensitivity analysis. For demonstration, this is implemented using a surface water model (HEC-RAS) and the impact of floodplain access up and downstream of a fixed bridge on bridge scour is analyzed. DE, an evoutionary global optimization algorithm, is wrapped around a calibrated HEC-RAS model. Multiple objective functions, representing different relative weighting of two objectives, are used; the resulting rank-orders of river reach locations by floodplain access sensitivity are consistent across these multiple functions. To extend the applicability of data assimilation methods, this thesis proposes relaxing the requirement that the model be calibrated (provided the parameters are still within physically defensible ranges) before performing assimilation. The model is then dynamically calibrated to new state estimates, which depend on the behavior of the model. Feasibility is demonstrated using the EKF and a synthetic dataset of pendulum motion. The dynamic calibration method reduces the variance of prediction errors compared to measurement errors using an initially uncalibrated model and produces estimates of calibration parameters that converge to the true values. The potential application of the dynamic calibration method to river sediment transport modeling is proposed in detail, including a method for automated calibration using sediment grain size distribution as a calibration parameter.

Orientador: José Luiz Stape / Resumo: O Brasil é um dos líderes mundiais na produção de celulose, papel e painéis de madeira. Este sucesso se deve a diversos fatores, tais como: às condições edafoclimáticas favoráveis ao desenvolvimento de espécies de alto rendimento; aos investimentos nos setores de pesquisa e inovação; ao estabelecimento de parcerias entre empresas e instituições de pesquisa e ensino. Desde a chegada das primeiras árvores de eucalipto, no início do século XX, a produtividade da espécie e a quantidade de área plantada cresceram no país, por outro lado, a busca por melhorias deve ser constante. O uso de modelos baseados em processos tem sido direcionado à compreensão da influência de fatores edafoclimáticos em parâmetros da espécie. Desta forma, é possível simular ambientes em situações adversas e prever possíveis impactos das mudanças climáticas na produtividade da espécie, assim como selecionar áreas aptas à cultura, além de determinar fatores que limitam o crescimento. Os objetivos deste trabalho foram parametrizar e validar o modelo 3-PG para o clone de eucalipto de maior plasticidade fenotípica para diferentes regiões do Brasil; e estimar a produtividade deste mesmo clone para diferentes ciclos climáticos em uma região onde a setor de florestas plantadas ainda não está estabelecido, como o estado de Rondônia. A parametrização do modelo foi eficiente quanto a predição de produção de biomassa de lenho (R2 = 0,93), diâmetro a altura do peito (R2 = 0,94) e área basal (R2 = 0,93), o mesmo não aco... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Brazil is one of the world leaders in the production of pulp, paper and wood panels. This success is due to several factors, such as: the edaphoclimatic conditions favorable to the development of high yield species; the investments in research and innovation sectors; the establishment of partnerships between companies, research and education institutions. Since the arrival of the first Eucalyptus trees at the beginning of the 20th century, the productivity of the species and the amount of planted area have grown in the country, in addition, the search for improvement must be constant. Technologies related to remote sensing, genetic sequencing, genetically modified organisms, ecophysiology and modeling of forest systems enable the filling of previously unknown gaps. The use of process-based models has been directed at understanding the influence of edafoclimatic factors on species parameters. In this way, it is possible to simulate environments in adverse situations and predict possible impacts of climate change on the productivity of the species, as well as to select areas suitable for cultivation, and to determine factors that limit growth. The objectives of this study were to parameterize and validate the 3-PG model for the Eucalyptus clone of higher phenotypic plasticity for different regions of Brazil; and to estimate the productivity of this same clone for different climatic cycles in a region where the planted forest sector is not yet established, state of Rondônia. The... (Complete abstract click electronic access below) / Doutor

L'effetto dei gas serra sul cambiamento climatico ha portato molti esperti a considerare la riduzione delle emissioni di gas serra come strategia per il riscaldamento globale. In particolare tale fenomeno è causato dall’anidride carbonica (CO2), metano (CH4) e il protossido di azoto (N2O). E 'ampiamente accettato che la principale fonte antropica di gas a effetto serra (tranne CO2) è dovuta alle attività agricole. Lo scopo di questo studio è quello di definire concetti e strumenti per facilitare il settore agricolo a ridurre le emissioni di gas serra. In particolare, abbiamo posto la nostra attenzione ai sistemi di misurazione delle emissioni dal suolo, testando un nuovo sistema (SASSFlux) e le sue caratteristiche a confronto con due strumenti ampiamente utilizzati (Bruel & Kjaer e gascromatografia). Inoltre abbiamo testato due modelli di simulazione (DNDC e SPACSYS) valutando i dati simulati e quelli misurati su un esperimento effettuato su lisimetri. In fine abbiamo applicato le conoscenze acquisite in pieno campo per la valutazione delle emissioni di CO2 e N2O con diversi concimi e lavorazione del terreno. La tesi si propone di fornire una visione completa dei diversi aspetti da affrontare nella valutazione delle emissioni di gas serra provenienti da diversi scenari di gestione agricola. / The effect of greenhouse gases (GHG) on climate change led many experts to consider the reduction of GHGs emissions as a crucial strategy to tackle the predicted global warming. In particular, atmospheric warming is caused mainly by carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). It is widely accepted that the main anthropogenic source of GHG (except CO2) is due to agriculture activities. The purpose of this study was to help define concepts and tools to facilitate agricultural sector to reduce greenhouse gas emissions. In particular we based our focus on measuring systems for CO2 emissions, testing the performance of novel system (SASSFlux) and its features in different condition with two widely used instruments (Bruel&Kjaer and gas chromatography). Moreover we testing two process-based models, DNDC and SPACSYS, evaluating their performance and the agreement between simulated and measured data on a experiment carried out on lysimeters. At the end we applied all the knowledge acquired on a field experiment evaluating CO2 and N2O emissions from different organic and mineral fertilizers and tillage. The complete thesis aims to provide a comprehensive view of the different aspects to be addressed in the assessment of GHG emissions from different scenarios of agricultural management.

<p>The focus of this thesis is on groundwater vulnerability assessment by process-based simulation models and data acquisition for these assessments. A modelling system for intrinsic groundwater vulnerability assessment in water supply areas was developed, consisting of flow- and transport models for the unsaturated zone and the groundwater zone, coupled to a geographical informa-tion system. The system was applied to a water supply area located close to a major road south of Stockholm. Chloride was used as an indicator in determining the vulnerability for groundwater contamination from the road. The approach was useful to illustrate the dynamic change of chlo-ride concentrations both during the stage of continuous application and after the applications was terminated. A structure and content of a database for flow and transport modelling, based on hydrogeological environments, was outlined. An existing hydrogeological parameter database, HPAR at the Geological Survey of Sweden (SGU), was examined as a potential source of data for the new database. Values for some important parameters needed for groundwater modelling, such as hydraulic conductivity and effective porosity, were lacking in the three municipal HPAR databases that were studied. It was suggested that these data should be added, together with information on the hydrogeological environments, for all geographical positions of interest. Without such minimum information, the efficient use of modelling tools could not be expected.</p><p>Typical profiles of three common Swedish hydrogeological environments (sand deposits, glacial till and clay covered areas) were used to represent generic input data to model simulations in the unsaturated zone so that the importance of soil, vegetation type and groundwater levels on turn-over times of conservative contaminants transported by natural recharge could be examined. The same profiles were used to predict the penetration depth of accidental liquid spills that occur at the land surface level. In the case of contaminant transport by natural recharge, water storage in the soil profile and vegetation type played an important role for turnover times. For liquid spills, the hydraulic con-ductivity was found to be of major importance, while the water retention properties were of less importance. Modelling, together with available data sources, were successfully used to demon-strate the vulnerability of different environmental conditions.</p>

Les modèles génétiques de réservoirs sont construits par la simulation des principaux processus de sédimentation dans le temps. En particulier, les modèles tridimensionnels de systèmes chenalisés méandriformes peuvent être construits à partir de trois processus principaux : la migration du chenal, l’aggradation du système et les avulsions, comme c’est réalisé dans le logiciel Flumy pour les environnements fluviatiles. Pour une utilisation opérationnelle, par exemple la simulation d'écoulements, ces simulations doivent être conditionnées aux données d'exploration disponibles (diagraphie de puits, sismique, …). Le travail présenté ici, basé largement sur des développements antérieurs, se concentre sur le conditionnement du modèle Flumy aux données de puits.Deux questions principales ont été examinées au cours de cette thèse. La première concerne la reproduction des données connues aux emplacements des puits. Cela se fait actuellement par une procédure de "conditionnement dynamique" qui consiste à adapter les processus du modèle pendant le déroulement de la simulation. Par exemple, le dépôt de sable aux emplacements de puits est favorisé, lorsque cela est souhaité, par une adaptation des processus de migration ou d'avulsion. Cependant, la manière dont les processus sont adaptés peut générer des effets indésirables et réduire le réalisme du modèle. Une étude approfondie a été réalisée afin d'identifier et d'analyser les impacts indésirables du conditionnement dynamique. Les impacts ont été observés à la fois à l'emplacement des puits et dans tout le modèle de blocs. Des développements ont été réalisés pour améliorer les algorithmes existants.La deuxième question concerne la détermination des paramètres d’entrée du modèle, qui doivent être cohérents avec les données de puits. Un outil spécial est intégré à Flumy - le "Non-Expert User Calculator" (Nexus) - qui permet de définir les paramètres de simulation à partir de trois paramètres clés : la proportion de sable, la profondeur maximale du chenal et l’extension latérale des corps sableux. Cependant, les réservoirs naturels comprennent souvent plusieurs unités stratigraphiques ayant leurs propres caractéristiques géologiques. L'identification de telles unités dans le domaine étudié est d'une importance primordiale avant de lancer une simulation conditionnelle avec des paramètres cohérents pour chaque unité. Une nouvelle méthode de détermination des unités stratigraphiques optimales à partir des données de puits est proposée. Elle est basée sur la Classification géostatistique hiérarchique appliquée à la courbe de proportion verticale (VPC) globale des puits. Les unités stratigraphiques ont pu être détectées à partir d'exemples de données synthétiques et de données de terrain, même lorsque la VPC globale des puits n'était pas visuellement représentative. / Process-based reservoir models are generated by the simulation of the main sedimentation processes in time. In particular, three-dimensional models of meandering channelized systems can be constructed from three main processes: migration of the channel, aggradation of the system and avulsions, as it is performed in Flumy software for fluvial environments. For an operational use, for instance flow simulation, these simulations need to be conditioned to available exploration data (well logging, seismic, …). The work presented here, largely based on previous developments, focuses on the conditioning of the Flumy model to well data.Two main questions have been considered during this thesis. The major one concerns the reproduction of known data at well locations. This is currently done by a "dynamic conditioning" procedure which consists in adapting the model processes while the simulation is running. For instance, the deposition of sand at well locations is favored, when desired, by an adaptation of migration or avulsion processes. However, the way the processes are adapted may generate undesirable effects and could reduce the model realism. A thorough study has been conducted in order to identify and analyze undesirable impacts of the dynamic conditioning. Such impacts were observed to be present both at the location of wells and throughout the block model. Developments have been made in order to improve the existing algorithms.The second question is related to the determination of the input model parameters, which should be consistent with the well data. A special tool is integrated in Flumy – the Non Expert User calculator (Nexus) – which permits to define the simulation parameters set from three key parameters: the sand proportion, the channel maximum depth and the sandbodies lateral extension. However, natural reservoirs often consist in several stratigraphic units with their own geological characteristics. The identification of such units within the studied domain is of prime importance before running a conditional simulation, with consistent parameters for each unit. A new method for determining optimal stratigraphic units from well data is proposed. It is based on the Hierarchical Geostatistical Clustering applied to the well global Vertical Proportion Curve (VPC). Stratigraphic units could be detected from synthetic and field data cases, even when the global well VPC was not visually representative.

The focus of this thesis is on groundwater vulnerability assessment by process-based simulation models and data acquisition for these assessments. A modelling system for intrinsic groundwater vulnerability assessment in water supply areas was developed, consisting of flow- and transport models for the unsaturated zone and the groundwater zone, coupled to a geographical informa-tion system. The system was applied to a water supply area located close to a major road south of Stockholm. Chloride was used as an indicator in determining the vulnerability for groundwater contamination from the road. The approach was useful to illustrate the dynamic change of chlo-ride concentrations both during the stage of continuous application and after the applications was terminated. A structure and content of a database for flow and transport modelling, based on hydrogeological environments, was outlined. An existing hydrogeological parameter database, HPAR at the Geological Survey of Sweden (SGU), was examined as a potential source of data for the new database. Values for some important parameters needed for groundwater modelling, such as hydraulic conductivity and effective porosity, were lacking in the three municipal HPAR databases that were studied. It was suggested that these data should be added, together with information on the hydrogeological environments, for all geographical positions of interest. Without such minimum information, the efficient use of modelling tools could not be expected. Typical profiles of three common Swedish hydrogeological environments (sand deposits, glacial till and clay covered areas) were used to represent generic input data to model simulations in the unsaturated zone so that the importance of soil, vegetation type and groundwater levels on turn-over times of conservative contaminants transported by natural recharge could be examined. The same profiles were used to predict the penetration depth of accidental liquid spills that occur at the land surface level. In the case of contaminant transport by natural recharge, water storage in the soil profile and vegetation type played an important role for turnover times. For liquid spills, the hydraulic con-ductivity was found to be of major importance, while the water retention properties were of less importance. Modelling, together with available data sources, were successfully used to demon-strate the vulnerability of different environmental conditions. / QC 20101020

Soil fertility is an important component of forest ecosystem, yet evaluating soil fertility remains one of the least understood aspects of forest science. Phytocentric and geocenctric approaches were used to assess soil fertility in loblolly pine plantations throughout their geographic range in the United States. The model to assess soil fertility using a phytocentric approach was constructed using the relationship between site index and aboveground productivity. Geocentric models used physical and chemical properties of the A-horizon. Soil geocentric models were constructed using two modeling approaches. In the first approach, ordinary least squares methods of multiple regression were used to derive soil fertility estimated from site index using soil physical and chemical properties from the A-horizon. Ordinary least squares methods were found unsuitable due to multicollinearity among the soil variables. In the second approach, a multivariate modeling approach, partial least squares regression, was used to mitigate multicollinearity effects. The best model to quantify soil fertility using soil physical and chemical properties included N, Ca, Mg, C, and sand percentage as the significant predictors. The 3-PG process-based model was evaluated for simulating the response of loblolly pine to changes in soil fertility. Fertility rating (FR) is a parameter in 3-PG that scales soil fertility in the range of 0 to 1. FR values estimated from phytocentric and geocentric approaches were tested against observed production. The 3-PG model prediction of aboveground productivity described 89% percent of the variation in observed aboveground productivity using FR derived from site index and 84% percent of the vari- ation in observed aboveground productivity using FR derived from physical and chemical properties of the A-horizon. A response function to model dynamics of FR (∆FR) due to one time midrotatoin fertilization of N and P was developed using the Weibull function. The magnitude of ∆FR varied with intensity of N and time since application of fertilizer. The hypothesis that repeated fertilization with N and P eliminate major nutrient deficiency in the southeastern US was tested and a relationship between baseline fertility rating and fertilizer response was developed. An inverse relationship was observed between fertilizer response and baseline FR. / Ph. D.

Soil organic carbon (SOC) concentrations and greenhouse gas (GHG) emissions are not uniform across the landscape, but assemble in "hotspots" in specific areas. These differences are mainly driven by human-induced activities such as agricultural management. 40-50% of the Earth's land surface is under agricultural land-use, for instance cropland, managed grassland and permanent crops including agro-forestry and bio-energy crops. Furthermore, 62% of the global soil C stock is SOC and the soil stores more than 3 times more C than the atmosphere. Thus, C sequestration in agricultural soil has a potentially important role in increasing SOC storage and GHG mitigation, and there is considerable interest in understanding the effects of agricultural management on SOC and GHG fluxes in both grasslands and croplands, in order to better assess the uncertainty and vulnerability of terrestrial SOC reservoirs. For the sake of discovering the agricultural management practices relating to the effective and sustainable C sequestration in agricultural lands in Europe, simulating future terrestrial C stocks and GHG budgets under varied agricultural management systems in major European ecosystems is essential. Using models is a useful method with the purpose of this and abundant studies have carried out. However, many model results have not been validated with reliable observed long-term data, while other studies have reported a strong impact of model initialisation on model result. Nevertheless, predictions of annual to decadal variability in the European terrestrial C and GHG ressources largely rely on model results. Consequently, finding the most appropriate and comprehensive model initialisation method for obtaining reliable model simulations became important, especially for process-based ecosystem models. In recent years, Zimmermann et al. (2007) have succeed in initialising the Rothamsted Carbon model (RothC) using a physical and chemical soil fractionation method. For that reason, we hypothesised that measured detailed SOC data would be useful to initialise ecosystem models, and this hypothesis should be tested for different process-based models and agricultural land-use and management. (...)

La concentration de Carbone organique de sol (COS) et les émissions de gaz à effet de serre (GES) ne sont pas uniformes à travers l’espace, mais se regroupent en “hotspots” dans des endroits spécifiques. Ces différences s’expliquent principalement par les activités anthropiques telles que la gestion agricole. 40-50% de la surface de la Terre est utilisé par l’agriculture, par exemple les terres cultivées, les prairies gérées et cultures permanentes, y compris l’agro-foresterie et de bio-cultures énergétiques. En outre, 62% du carbone globale est COS, et le sol conserve plus que 3 fois plus de C que l’atmosphère. Ainsi, la séquestration du carbone dans les sols agricoles joue un rôle potentiellement important dans l’augmentation de stockage de COS et l’atténuation des GES, et il y a un intérêt considérable pour comprendre les effets de la gestion agricole sur le COS et les flux de GES aux prairies et terres cultivées, afin de mieux évaluer l’incertitude et la vulnérabilité des réservoirs de COS. Afin de découvrir les pratiques de gestion agricole qui contribuent à la séquestration efficace et durable du carbone aux terres agricoles en Europe, il est essentiel de simuler les stocks futurs de carbone terrestriel et les budgets de GES par rapport aux systèmes de gestion agricole variés sur les grands écosystèmes européens. Dans ce contexte, la modélisation est une méthode utile, et la modélisation a déjà été utilisée dans beaucoup d’études. Cependant beaucoup de résultats de la modélisation n’ont pas encore été validés avec les données mesurées sur l’horizon long-terme, et d’ailleurs d’autres études ont constaté un fort impact de l’initialisation du modèle sur le résultat du modèle. Néanmoins, la variabilité des prévisions annuelles et décennales concernant le C et le GES en Europe dépendent des résultats du modèle. Par conséquence, il est important de trouver la meilleure méthode d’initialisation des modèles pour obtenir des résultats des modèles fiables, notamment pour les modèles d’écosystèmes dits “process-based”. Au cours des dernières années, Zimmermann et al. (2007) a réussit à initialiser le modèle de Rothamsted carbone (RothC) en utilisant une méthode (physique et chimique) de fractionation des sols. Pour cette raison, j’ai fait l’hypothèse que les données COS détaillées seraient utiles pour initialiser des modèles d’écosystème, et que cette hypothèse doit être testée avec les modèles différents par rapport aux gestions agricoles différentes. Les buts de cette thèse sont les suivants: i) évaluation des influences des gestions agricoles sur le stockage de COS, en utilisant des approches expérimentales et des approches de modélisation; et ii) déterminer la meilleur méthode d’initialisation des modèles. (...) / Soil organic carbon (SOC) concentrations and greenhouse gas (GHG) emissions are not uniform across the landscape, but assemble in “hotspots” in specific areas. These differences are mainly driven by human-induced activities such as agricultural management. 40-50% of the Earth’s land surface is under agricultural land-use, for instance cropland, managed grassland and permanent crops including agro-forestry and bio-energy crops. Furthermore, 62% of the global soil C stock is SOC and the soil stores more than 3 times more C than the atmosphere. Thus, C sequestration in agricultural soil has a potentially important role in increasing SOC storage and GHG mitigation, and there is considerable interest in understanding the effects of agricultural management on SOC and GHG fluxes in both grasslands and croplands, in order to better assess the uncertainty and vulnerability of terrestrial SOC reservoirs. For the sake of discovering the agricultural management practices relating to the effective and sustainable C sequestration in agricultural lands in Europe, simulating future terrestrial C stocks and GHG budgets under varied agricultural management systems in major European ecosystems is essential. Using models is a useful method with the purpose of this and abundant studies have carried out. However, many model results have not been validated with reliable observed long-term data, while other studies have reported a strong impact of model initialisation on model result. Nevertheless, predictions of annual to decadal variability in the European terrestrial C and GHG ressources largely rely on model results. Consequently, finding the most appropriate and comprehensive model initialisation method for obtaining reliable model simulations became important, especially for process-based ecosystem models. In recent years, Zimmermann et al. (2007) have succeed in initialising the Rothamsted Carbon model (RothC) using a physical and chemical soil fractionation method. For that reason, we hypothesised that measured detailed SOC data would be useful to initialise ecosystem models, and this hypothesis should be tested for different process-based models and agricultural land-use and management. (...)

<p>Denna rapport syftar till att, på Å&R Carton i Norrköping, analysera de interna flödena och processerna samt ge förslag på hur ledtider ska kunna reduceras väsentligt. Ett sätt att uppfylla syftet är att dela in verksamheten i processer genom olika metoder och kriterier förprocessbestämning. Valda metoder i rapporten är; kvalitativ ansats med hög validitet och reliabilitet, processbaserad verksamhetsanalys och procedurbeskrivning. </p><p>Genom omfattande litteraturstudier, insamlande av data i form av intervjuer, benchmarking, platsundersökningar och interna dokument har nulägesmodeller arbetats fram. Analysen av dessa visar bland annat på att såväl planeringsprocessen som inköpsprocessen idag inte fungerar värdeadderande och bör ses över. Därutöver finns också andra processer som bidrar till ett komplext flöde. Dessa behöver effektiviseras eller ändras för att korta ledtider. Vidare visar analysen på att en omfattande attitydsundersökning behövs, dels för att komma till rätta med vissa stämningar och dels för att på sikt skapa en effektiv arbetsmiljö. </p><p>Till förbättringsförslagen hör, förutom en attitydsundersökning, förslaget att utarbeta tydliga mål och strategier. Sedan måste dessa kommuniceras till samtliga anställda, till exempel genom arbetsgrupper. Vidare föreslås att Å&R Carton tittar på automatisk datafångst som ett mycket kostnadseffektivt sätt att kontrollera det totala flödet. På lång sikt bör också företaget titta på att implementera processorientering. Dock behöver företaget först och främst se till att skapa en förändringsvillig attityd för att nå framgång i sitt effektiviseringsarbete. Slutsatsen blir att Å&R Carton har stor potential att väsentligt förkorta sina ledtider om företaget hanterar situationen rätt. För att lyckas kan delar av denna rapport användas där det viktigaste är att en engagerad ledning visar vägen. </p> / <p>The purpose of this final thesis is to analyse the internal processes at Å&R Carton in Norrköping and give proposals to reduce time in the Supply Chain. One way to fulfill the purpose is to use Process Based Analys and split the organisation in different processes. Process Based Models have then been constructed by studying litterature, benchmarking, internal documents and making a lot of interviews. The analys shows that different processes must be changed to make the flow through the Supply Chain more efficient. The analys give us also recommendations like attitude investigations and implementation of ECR. The conclusion is that Å&R Carton have great potential to reduce time in the Supply Chain if the management are active, follow the recommendations and show the employees the way about.</p>