. "Environmental sciences"@en . . "English"@en . . "Modelling, uncertainty and data for engineers"@en . . "12" . "This module comprises two interlinked parts. The Theory, Application and Coding (TAC) part focuses on teaching and applying\nthe fundamental concepts on modelling, uncertainty and data (MUD), as well as coding skills. In the Q1 Project part students\nwork in multidisciplinary teams on cases in the context of a smart society, where they will apply the knowledge and skills from\nthe TAC. In the Q2 project, the students work at the interface areas where the three topics overlap, creating opportunities for\nmore integrated applications and the ability to focus on fields of interest per programme (when needed) while satisfying the same\nset of learning objectives. A gradually increasing complexity and openness of inquiry will be applied.\nStudy Goals After successfully completing the MUDE a student\nGeneral\nis able to describe and formulate a research question (or alternatively, design requirements) given a set problem and select the\nappropriate methodology and tools\nis able to present a fitting work plan to investigate a set of research questions or design requirements\nis able to compose a technical document using appropriate academic language and citation with references\nis able to work in a collaborative group environment effectively\nis able to code according to basic coding standards (e.g., consistency, readability, conciseness, structure, etc.) and collaborate\nwith their peers via distributed control software (e.g., git)\ncan perform spatial / temporal / multivariate analysis of data to extract knowledge via physics-based modelling tools, data-\ndriven approaches, and uncertainty quantification methods\ncan present and communicate with peers in Civil Engineering and Geosciences, results of analyses using specific modelling,\nuncertainty and data approaches with appropriate metrics and visualization techniques\nModeling\ncan design a modelling framework (from problem conceptualization to governing equation setup) for a physical/engineering\nprocess\ncan translate the modelling framework into discretized equations and computer code\ncan mathematically formulate and solve an optimization problem and discuss its properties\ncan assess optimization and simulation models performance using a set of indicators\nUncertainty\ncan derive relevant models and complete probability and statistic calculations for faculty-wide applications\ncan construct relevant models for probabilistic dependence, for example using bivariate distributions or discrete Bayesian\nPage 5 of134\nNetworks\nuse deterministic models with probabilistic inputs to evaluate engineering questions to quantify model output uncertainty (in\ntime and/or space)\nuse risk and reliability analyses concepts to describe systems, their characteristics and behaviour in time and space to support\ndecision making under uncertainty\nData\ncan identify parameters of interest, describe the functioning of common field/remote sensors used for measuring them, and\nexplain resolution implications in space and time\nis able to apply parameter estimation using observations and perform a quality assessment\ncan illustrate the procedure of gathering data from different sources, pre-processing it for analysis purposes, and sharing it\naccording to FAIR principles" . . "no data"@en . "TRUE" . . "Earth system, natural resources and climate"@en . . "7" . "In this module, students will first be introduced to the Earth System and human interventions in the Earth System, including the\nexploitation of natural resources and greenhouse-gas emissions that caused climate change, and the societal challenge of moving\ntowards a carbon-neutral world. Through three narratives, students will study through which processes and on what temporal and\nspatial scales the different Earth system components interact.\nThe first story line is named Solid Earth & Resources and looks at the deep level dynamic processes that make the Earth a unique\nbody in the solar system. These processes will be outlined in terms of the plate tectonic theory which provides a unified\nframework for the evolution of the solid Earth. We will examine how these processes have evolved through time and how they\nhave been responsible for the distribution of the continents and the formation of mountain belts, volcanoes and the evolution of\nour natural resources.\nThe second story line is named the Climate System, in which students will gain a basic understanding of the Earths energy\nbudget and the natural and anthropogenic influences on past (paleo-)climates and our current and future climate. They will be\nfamiliarized with the carbon cycle and study the role of the global atmospheric and oceanic circulation in setting climate zones\nand weather.\nThe third story line is named Source to Sink and starts at mountains and follows the pathway of water and sediment towards the\nriver, delta and coastal-oceanic basins. Along the way we will investigate formation of sediment, the water cycle, formation of\nstratigraphy, vegetation and land use changes, and how all this is affected by the past and current climate and weather.\nFinally, students will appraise and reflect on the societal and ethical implications of past or future human interventions related to\nresources and the climate of the Earth System. After completing this module, students will be able to:\nAnalyse the different components of the Earth system and the processes and time and spatial scales on which the different\ncomponents of the Earth system interact. \nExamine the processes that generate and deplete the availability of natural resources.\nDistinguish the processes that play a role in the Earth's energy (im)balance and calculate their impact on climate. \nIdentify the processes that underlie impacts of anthropogenic activities on the Earth System. \nReflect on social and ethical implications of human interventions in the Earth System." . . "Presential"@en . "TRUE" . . "Dynamics of solids and fluids"@en . . "5,5" . "This course provides students with an understanding of basic concepts and mathematical solutions of fluid and solid dynamics\nwith applications to atmosphere, oceans and the Solid Earth, preparing them for in-depth study of processes in specific Earth\ncomponents. Students will learn how to derive the governing equations of fluid dynamics and solid dynamics, to explain how\nthese are applied and simplified for flow and solid dynamics in the atmosphere, ocean and the solid Earth. Students will also\ncarry out exercises as group assignments using python notebooks and model codes that exemplify simple models built on these\ngoverning equations. After completing this module, students will be able to:\nDistinguish flows and deformation in different parts of the Earth system (atmosphere, ocean and solid Earth). \nPerform dimensional analysis of flows in different media and explain appropriate approximations to the equation of motion.\nCharacterise and derive the physical equations that underlie advection, diffusion, convection, conduction, elasticity, brittle and\nductile deformation, and consider their application in models of Earth System components. \nApply the physical equations to examples of flow and deformation in different media using python notebooks. \nAnalyse and compare the behaviour of flow and deformation phenomena in the Earth System using simple python models." . . "Presential"@en . "TRUE" . . "Physical principles of earth system observation"@en . . "5,5" . "Measuring is essential to characterize and explain processes in the Earth system, and a first step to assess, model and predict\nnatural processes and human activities in and their impact on the Earth system. Electromagnetic, seismic and gravity potential-\nfield observations inform us about a wide range of phenomena in the ocean, atmosphere, land surface, cryosphere and sub-\nsurface. The measurements can be acquired from spaceborne, airborne, surface and sub-surface-based sensors.\nThis programme core module aims to enable students i) to explain and apply the physical principles underlying the\nmeasurements, and ii) to assess what type of measurement could be used best to determine certain geophysical variables. For\nexample, students will learn how electromagnetic theory allows to use the intensity of radar echoes to yield information about\nrain rate, soil moisture, ocean roughness, or the layering of the subsurface. Similarly, they will learn how potential field theory\ncan be applied to quantify mass changes of, e.g., the ice sheets. Students will be able to weigh the advantages and disadvantages\nof, for example, microwave versus visible and near-infrared observations for monitoring the Earth surface, and seismic and\nelectromagnetic imaging in mapping the subsurface" . . "Presential"@en . "TRUE" . . "Atmosphere dynamics and air-sea coupling"@en . . "6" . "This discipline core will provide students with the deeper physical understanding to comprehend and study the complex\natmospheric flows that define climate and weather. The module will use interactive lectures to introduce advanced dynamical\nprinciples to explain global climate, the planetary circulation, weather systems in the tropics and extratropics and coupled\natmosphere-ocean phenomena that set weather and climate variability.\nIn these lectures, laboratory experiments with a rotating tank or visualizations of atmospheric flows are a starting point to\ndescribe the complex flows in our atmosphere. Each week, the students will be guided during practical lab work/assignments in\nwhich material collected during the tank experiments, toy models or observational datasets are used and analyzed to describe\nuncoupled and coupled phenomena in the atmosphere.\nStudy Goals After completing this module, students will be able to:\n1. Analyse data of the horizontal and vertical structure of atmospheric pressure, temperature, humidity and wind to explain the\ngeneral circulation of the atmosphere and climate zones \n2. Apply conservation of heat, moisture and momentum to explain the origin and features of tropical and extratropical weather\nphenomena \n3. Assess the role of air-sea coupling on atmospheric dynamics on short (weather) and long (climate) timescales \n4. Analyse and evaluate the sensitivity of circulations and climate by running experiments with idealized simulations and toy\nmodels \n5. Design a hypothetical lab experiment to study the influence of climate change on atmosphere dynamics \n6. Discuss processes that cause uncertainty in weather and climate prediction" . . "Presential"@en . "TRUE" . . "Earth observation technologies"@en . . "6" . "The goal of this module is to familiarize students with the process of specifying and designing an observational\nmission/campaign (e.g., a new satellite mission or a ground measurement campaign). This process includes the interpretation and\nanalysis of user needs and their translation to observational requirements, the high-level design of possible technical solutions,\nand the evaluation of the expected observational performance with respect to user requirements.\nAfter completing this module, students will be able to:\n-Formulate user requirements that can be assessed based on parameter estimation\n-Evaluate the principles and limitations of generic classes of observation techniques, observation platforms, and data processing\ntechniques \n-Analyse third-party user requirements and translate these into system requirements of an observational system (mathematical\nand physical) \n-Design an observational mission to gather the requested observations \n-Analyse results from an observation mission by estimating the parameters of interest, including quality assessment \n-Reflect on the analysis results in relation to third-party stakeholders \n-Contribute to effective group work and communicate orally and in written form on the project results at an academic level" . . "Presential"@en . "TRUE" . . "Geo-energy engineering applications"@en . . "6" . "This module will provide a general overview of the application areas of geothermal energy, petroleum exploration and\nproduction, and energy storage in the subsurface. The students will learn in this core module how these geo-energy application\nareas contribute to the energy demand of the world, in what way they can contribute to the transition towards a carbon-neutral\nworld, what the opportunities, boundary conditions and consequences are of these applications. The students will learn the basic\ntechniques and principles of reservoir characterization and single phase flow.After completing this module, students will be able to:\nExplain what the field of Geo-Energy entails, how the subsurface can be utilised and what its role is in the energy transition.\n\nAnalyse the basic concepts of single-phase flow and reservoir characterization in relation to geothermal energy, subsurface\nstorage, petroleum exploration and production applications and the effects of engineering in this subsurface \nEvaluate how single-phase flow and subsurface characterisation interact at different temporal and spatial scales \nDevelop a conceptual plan that compares and integrates the different applications utilizing the subsurface for the energy demand\ntowards the future. Quantify the components of the conceptual plan using the physic principles that describe subsurface\nphenomena. Test this problem towards the sensitivity of different components/issues (flow, mechanics, heterogeneity) \nUse written and oral communication skills to effectively exchange results and opinions with researchers, engineers, and Applied\nEarth Sciences stakeholders." . . "Presential"@en . "TRUE" . . "Economic and structural geology"@en . . "6" . "This module will equip students with the theory and knowledge to understand the nature, origin and factors controlling primary\nsolid/mineral raw materials in order to understand the physical and chemical characteristics that influence and control the behaviour in terms of recovery of value and utilisation. After completing this module, students will be able to:\nClassify the variety of mineral resource commodities of primary/secondary origin and discuss the relevance to society.\nIllustrate the spatial and temporal distribution of mineral resources in the Earth crust by means of specific examples (Precious\nmetals, base metals, ferrous metals, non-metallics, secondaries). \nCompare evolutionary concepts about the origin of mineral deposits by means of specific examples (Precious metals, base\nmetals, ferrous metals, non-metallics, secondaries).\nClassify different mineral deposit styles based on geological features. \nRelate different processes that give rise to different ore deposit styles to their genetic classification based on the observed\ngeological features. \nDefine rock stress and strength and how rocks respond to different styles of deformation.\nReconstruct the structural evolution of multiscale rock bodies on the basis of documents such as stress-strain diagrams, seismic\nsections and outcrop data. \nAppraise the significant processes that lead to formation of an ore deposit during structural deformation.\nWork effectively in a team to define, plan and execute a project assignment and to report the outcomes by means of oral\npresentation and written report." . . "Presential"@en . "TRUE" . . "Climate physics"@en . . "9" . "This module is aimed at students with an interest in the field of applied meteorologym such as wind and solar energy prediction\nor climate impacts on land use), and students interested in the design, analysis and assessment of weather and climate models. After completing this module, students will be able to:\n1. Explain the physics and dynamics of the transport of energy, water and momentum between the surface, the atmospheric\nboundary layer and the broader atmospheric circulation \n2. Apply simplified models of turbulence and energy and water exchange, including convection and clouds \n3. Reflect on the parameterization and coupling of atmospheric processes in general circulation models and their role in current\nuncertainties in climate prediction \n4. Analyse climate simulations for the purpose of process understanding as well as assessment of climate change impacts and\nmitigation/adaptation policies \n5. Assess the influence of land-atmosphere coupling, turbulence, convection and clouds on large-scale circulations (weather) and\nclimate.\n6. Hypothesize how land-atmosphere coupling, turbulence and convection and clouds are influenced by changes in weather and\nclimate" . . "Presential"@en . "TRUE" . . "Geo-data analysis and geodesy"@en . . "9" . "his module targets students interested in learning how to rigorously use geo-data to estimate and monitor changes in the shape\nof the Earth's surface and its gravity field. The signals of interests can be related to local human activities, such as gas or ground-\nwater extraction, or, for example, related to climate change, such as ice-mass losses in Greenland or Antarctica. In this data-\noriented module, students will acquire the skills and theoretical background required to process Earth observation data in order to\nretrieve the signals of interest, in particular by using Fourier analysis methods. After completing this module, students will be able to:\nAssess the quality of EO data and derived products\nDesign and apply hypothesis testing procedures to select the model which best represents physical reality\nApply spectral analysis techniques to extract relevant geophysical information from EO data\nApply geodetic observation and analysis techniques to quantify and characterize changes in the shape of the Earth and its gravity\nfield\nAnalyse the link between geodetic observables and the underlying geodynamical processes" . . "Presential"@en . "TRUE" . . "Geo-data and geo-informatics"@en . . "9" . "This is the module for students interested in exploring, mining and communicating the wealth of relevant information in state-of-\nthe-art geospatial data. Different ways to visualize and process geospatial data, in different formats and projections, on\ngeographic information systems will be explored. It will be discussed how to assess the quality of input Earth observation data,\nand how this quality propagates through a processing chain towards a quality description of a final product. Methodology will be\nanalysed to assess the spatial-temporal contents of data in terms of repetitive patterns and the scales at which information is\npresent in both the spatial and temporal domain. Finally, it will be discussed how such different information can be extracted\nfrom data, and how the significance of the extracted information can be accessed and communicated to different stakeholders in\neffective and attractive ways. After completing this module, students will be able to:\nAssess the quality of EO data and derived products \nDesign and apply hypothesis testing procedures to select the model which best represents physical reality \nApply spectral analysis techniques to extract relevant geophysical information from EO data \nModel and estimate the spatial and temporal variability of EO data and relate it to the underlying geophysical processes \nSelect and apply appropriate geo-informatics tools to extract, process and communicate information from EO data\nPresent findings in a precise and organized way, both numerically as well as graphically" . . "Presential"@en . "TRUE" . . "Flow and simulation of subsurface processes"@en . . "9" . "In this module, students acquire the necessary tools and knowledge to accurately model the building blocks of subsurface\nreservoirs and to accurately model flow of fluids/energy through these subsurface reservoirs. After completing this module, students will be able to:\nEvaluate how to build process and stochastic reservoir models and choose appropriate rock properties or facies distribution [ILO\nA,C]\nAnalyse the physics and develop an analytical model for two-phase flow, thermal processes and poroelasticity through porous\nmedia with different assumptions and for different applications \nDesign a stable and consistent numerical method for modelling of flow and transport in porous rocks \nImplement and create the three model types (reservoir model, analytical two-phase flow, numerical flow model) with geo-energy\nrelated software and codes\nApply the models to geo-energy related test cases and analyse the solutions with respect to the role of uncertainties, sensitivities,\nrelationships and consequences critically for the different test cases \nWork as a team on subject related problems and report findings and interpretations, including codes and choices made, in a\nstructured and consistent way." . . "Presential"@en . "TRUE" . . "Characterisation of the subsurface"@en . . "9" . "This module focusses on the structural and sedimentological architecture of the rocks in the Earth that are important for Geo-\nEnergy Engineering applications. The properties of rocks, as well as their variabilities on all scales, are assessed and quantified.\nKnowledge of the various processes taking place in the Earth and at the Earth's surface help the students assess and predict\nsubsurface architecture and properties. The units consists of an understanding and modelling of how subsurface reservoirs are\nbuild up with respect to reservoir properties and facies distributions. How those changes in properties and distributions can be\ncorrelated to variations in sedimentary deposition due to past climate fluctuations within different tectonic settings. How those\nchanges can be complemented within the structural framework in the subsurface (tectonics, deformation, compaction, faulting\nand folding). After completing this module, students will be able to:\nEvaluate and quantify process controlling spatial and temporal changes in sedimentological and structural properties of\nsedimentary successions. [ILO A,C]\nEvaluate and quantify state of stress in sedimentary basins, the way rocks deform and the mechanic factors controlling their\nresponse to geo-energy activities. Predict spatial and temporal changes of stress, strain and mechanic properties in the\nsubsurface. [ILO A,C]\nInterpret the various sedimentary successions and structural features from theory, field, seismic and borehole data. [ILO A,C]\nEvaluate how to build sedimentary and structural reservoir models and choose appropriate rock properties and property\ndistributions to characterise the model (including sources of uncertainties) \nAnalyse the origin and scales of heterogeneities in sedimentary deposits and structural features and integrate these into\nrepresentative elementary volumes \nAppraise the models in geo-energy related test cases and analyse the solution and investigate the role of uncertainties,\nsensitivities and relationships for the different test cases\nWork as a team on subject-related assignments and report findings and interpretations, including codes and choices made, in a\nstructured and consistent way. \nEducation Method See Brightspace for more detailed information on th" . . "Presential"@en . "TRUE" . . "Extraction processes and consequences of raw materials"@en . . "9" . "This module contains three interrelated units namely Extraction Methodologies, Residual Materials from Post Extraction\nProcessing and the Impact of Primary and Secondary Mineral Raw Materials on the environment.\nStudy Goals After completing this module, students will be able to:\nExplain the environmental and societal implications associated with the mining related processes to enable the development of\ninnovative management strategies for geo-resources. \nExplain the different extraction methodologies and consequences and implications associated with them. \nEvaluate the nature of the residual materials from post extraction processing specifically the origin, handling, stacking and\nstorage of mining residues. \nExplain the physical, chemical and fluid Interactions and dynamics for mining residues. \nAnalyse and interpret appropriate geophysical and InSAR monitoring data to detect anomalies and consequences over different\ntime scales of mining residues. es in solid waste management into scientific research questions\nand/or engineering opportunities. \nDesign an integrated plan for the extraction, waste storage and handling, targeting minimal waste and mitigation type strategies\nfor risk/hazards associated with mine waste. \nConsider the UN, ICMM and EU goals and regulations when developing engineering solutions for waste management options.\nWork effectively in a team to define, plan and execute a project assignment and to report the outcomes structured and consistent\nby means of oral presentations and written report." . . "Presential"@en . "TRUE" . . "Earth deformation processes across scales"@en . . "9" . "This module provides the knowledge and skills to understand, predict and characterise Earth deformation processes from\ncontinental (e.g., glacial isostatic adjustments and plate tectonics) towards reservoir scales (e.g., folding, faulting and\ncompaction). Geodetic and geophysical observation techniques will be used to quantify these deformation processes, by\nextracting physical parameters and assessing their uncertainties. In addition, students will learn to relate the observed movements\nto subsurface engineering (e.g., resource extraction, storage, tunnelling) or natural processes (e.g., plate tectonics, earthquakes).\nThe module contains three components, 1) Statistical geo-data analysis, 2) Geodesy and Geodynamics, and 3) Geomechanics and\nStructural Geology.\nStudy Goals After completing this module, students will be able to:\nDesign and apply hypothesis testing procedures to select the model which best represents physical reality \nApply geodetic observation and analysis techniques needed to quantify, characterize and explain changes in the shape of the\nEarth and its gravity field, and changes and expressions of crustal structures \nEvaluate the mechanical and deformation response and expressions of rocks to varying stresses within the shallow part of the\nEarth's crust \nAnalyse the link between geodetic observables and the underlying geodynamical and geomechanical processes from reservoir to\nglobal scales, including the effects of subsurface engineering activities" . . "Presential"@en . "TRUE" . . "Climate modelling and remote sensing"@en . . "9" . "This module complements the Climate & Weather core module. It is aimed at students from the Climate & Weather learning line\nwho are interested in the synergy offered by the combination of remote sensing and climate models to understand, predict and\nmodel the wide range of processes governing our present-day coupled climate system. After completing this module, students will be able to:\nFormulate, consolidate, and prioritize remote sensing data requirements to study processes in the coupled climate system and\nvalidate and inform their parametrization in climate models\nSelect a suitable observation technique to observe the variable(s) of interest, drawing on their prior/existing understanding of the\nunderlying physical principles \nCharacterize real or synthetic observation data, perform a quality assessment, estimate the parameters of interest and reflect on\nthe ability of the available data to meet their requirements. \nConstruct (simplified) models of climate variables and evaluate these with remote sensing data. \nAnalyse climate simulations for the purpose of process understanding (climate science) as well as for the interpretation of remote\nsensing data records.\nReflect on how integration of remote sensing data in climate modelling may improve our understanding and prediction of\nclimate variables." . . "Presential"@en . "TRUE" . . "Climate change and dynamic landforms"@en . . "9" . "This module is aimed at students with an interest in the physics of climate change, its effects on the natural environment and how\nthose can be analysed through geospatial data. In the climate modelling unit, student will learn about the numerical,\ncomputational and modelling concepts than underlie general circulation models and coupled climate models, which are the\nprimary tools to explain and/or predict the dynamics of past and future climate. The natural environment is here represented by\nrivers and deltas, which provide an instructive and societal-relevant study case to learn about the interaction between climate\nchange and the surface of the solid Earth. After completing this module, students will be able to:\nAnalyse the interaction between climate change and the solid Earths surface, with particular attention to the timescales involved.\nExplain the origin of present-day morphodynamic features by integrating geological and geospatial data. \nAnalyse climate simulations for the purpose of understanding the driving physical processes. \nAnalyse source-to-sink sedimentary systems and records in relation to tectonics and climate amongst other parameters. \nExtract geophysical parameters from geospatial data." . . "Presential"@en . "TRUE" . . "Climate and weather b-module"@en . . "15" . "After completing the module students will be able to:\n- Identify open issues in the processing and/or interpretation of Earth system data records based on the outcomes of the lab\nproject and design a development roadmap to address them.\n- Present analyses, interpretations and conclusions, as well as ethical implications, of the Lab and Fieldwork projects in a clear\nand convincing manner, both orally and written. \nTheory/Lab (module specific):\n- Explain which techniques are needed to measure or model specific geophysical parameters governing the processes relevant to\na societal challenge. \n- Evaluate the temporal and spatial requirements for measurements or models to monitor and predict these processes. \n- Combine and analyse data records to understand processes and their relationships on relevant scales \n- Distinguish the different sources of uncertainty in observational and in model data. \n- Analyse the skills and errors of a model by comparing with observations. \n- Evaluate the sensitivity of geophysical models to key parameters and boundary conditions. \n- Analyse, visualize and interpret and present findings in a clear and convincing manner.\nFieldwork:\n- Plan and design a field campaign that is appropriate for the physical process to be measured. \n- Collect data in the field using different measurement techniques. \n- Explain and quantify the error sources associated with the field measurements. \n- Process and analyse the data collected in the field to give meaningful constraints on the physical process. \n- Effectively communicate with peers, assessors and clients. \n- Contribute to a project as a team player and to the overall project management." . . "Presential"@en . "TRUE" . . "Earth observation"@en . . "15" . "During the fieldwork, students will work in teams and receive the terms of reference as defined by a (virtual) client, with the aim\nto analyse local to regional deformations and/or mass displacements due to various natural and/or human-induced causes. They\nneed to design a fieldwork campaign accordingly; the design will be reviewed during the project planning review. In the second\nphase, students collect the data in the field and process historical and newly acquired data. Thereafter they will analyse and\ninterpret the data, present their findings and provide recommendations for future work.\nStudy Goals After completing the module students will be able to:\nGeneral:\n1. Identify open issues in the processing and/or interpretation of Earth system data records based on the outcomes of the lab\nproject and design a development roadmap to address them.\n2. Present analyses, interpretations and conclusions, as well as ethical implications, of the Lab and Fieldwork projects in a clear\nand convincing manner, both orally and written.\nTheory/Lab (module specific):\n3. Assess the value and limitations of Earth observation data in addressing a societal challenge related to geohazards or climate\nimpacts.\n4. Select Earth observation data suitable for the study of a phenomenon of interest.\n5. Design, implement and validate a workflow to derive/extract geophysical parameters from Earth observation data.\n6. Quantify and assess the input data uncertainties and the quality of the results.\n7. Characterize temporal and spatial variations of geophysical parameters using Earth observation data.\n8. Analyse, visualize and interpret findings in a clear and convincing manner.\nFieldwork:\n9. Plan and design a field campaign that is appropriate for the physical process to be measured.\n10. Collect data in the field using different measurement techniques.\n11. Explain and quantify the error sources associated with the field measurements.\n12. Process and analyse the data collected in the field to give meaningful constraints on the physical process.\n13. Effectively communicate with peers, assessors and clients.\n14. Contribute to a project as a team player and to the overall project management." . . "Presential"@en . "TRUE" . . "Geo-energy"@en . . "15" . "After completing the module students will be able to:\nGeneral:\nIdentify open issues in the processing and/or interpretation of Earth system data records based on the outcomes of the lab project\nand design a development roadmap to address them. \nPresent analyses, interpretations and conclusions, as well as ethical implications, of the Lab and Fieldwork projects in a clear and\nconvincing manner, both orally and written.\nEnergy Transition and Geohazards Lab + Theory\nDefine and solve a research topic related to the Energy Transition or Geohazards challenge. \nAnalyse Earth system processes through a combination of data, observations and model outputs (geophysical data, subsurface\ndata, petrophysical data, and monitoring data).\nExtract subsurface characteristics and evaluate the options and limitations of data types for present-day and future societal\nchallenges in Energy Transition or Geohazards.\nPresent analyses, interpretations and conclusions, as well as ethical implications, of the Lab project in a clearly written and\nconvincing manner. \nFieldwork:\nDesign and execute a fieldwork campaign appropriate for the Earth system processes and/or applications to be studied. [ILO\nB,C,H,J]\nDescribe, identify and measure sedimentary heterogeneities, faults, fractures, folds, and 2D rock property trends at different\nscales (10-1 to 103m) and qualitatively predict their architecture and their potential impact on dynamic behaviour. \nLink field observations of rock property trends at different sub-seismic scales to geophysical data and include the impact of scale\nto model uncertainty. \nExtract subsurface characteristics and evaluate the options and limitations of data types for present-day and future societal\nchallenges in Energy Transition and Geohazards. \nPresent analyses, interpretations and conclusions of the Fieldlab project in a clearly written and convincing manner.\nContribute to a project as a team player and to the overall project management." . . "Presential"@en . "TRUE" . . "Data assimilation for geosciences"@en . . "5" . "Appplications of data assimilation in oceanography, meteorology, hydrology, seismology, reservoir engineering and/or\ngeotechnics;\nOpen and FAIR science, open interfaces\nStudy Goals 1. To explain the Bayesian principles of data assimilation\n2. To relate selected data assimilation methods to these principles (Strong-constraint\n4Dvar/Weak-constraint 4Dvar/EnRML, ESMDA/EnKF/Particle Filter)\n3. To evaluate existing data-assimilation methods and select the most appropriate method for\na given data-assimilation problem\n4. To design a data-assimilation workflow that connects a selected model of a particular\nearth system (oceanographic, meteorologic, hydrologic, reservoir engineering, seismology,\ngeotechnical) to a data assimilation method, or of another estimation problem (traffic,\nmedical sciences, finance)\n5. To apply open interfaces\n6. To apply a data-assimilation method to a proposed data-assimilation problem" . . "Presential"@en . "FALSE" . . "Climate remote sensing"@en . . "5" . "In this module, students will learn how to process, invert, and combine data, including those of different spatial/temporal\nresolutions. Moreover, they will learn how a proper data weighting can be implemented in order to optimize results of data\ncombination. Using data provided by satellite altimetry and satellite gravimetry missions as an example, students will be able to\nproduce state-of-the-art estimates of large-scale mass change in various Earth system compartments, such as the melting of\nglaciers and ice sheets, climate-driven variability in river basin water storage, and depletion of groundwater stocks.\nStudy Goals After completing this module, students will be able to:\n1. Design a scheme for level-2 satellite gravimetry and satellite altimetry data processing,\ntaking into account data uncertainties\n2. Design stand-alone and joint inversion schemes that take into account stochastic models\nof data errors, as well as possible inconsistencies between datasets\n3. Assimilate data into a simple numerical model and assess the added value of data\nassimilation\n4. Apply stand-alone and joint inversion schemes to quantify and separate processes at\ndifferent time scales in the context of cryosphere, ocean, or hydrology\n5. Summarize and defend the findings of a conducted study of selected Earth system processes" . . "Presential"@en . "FALSE" . . "Microwave remote sensing of the earths surface"@en . . "5" . "By the end of this course, students will be able to work with, and perform research based on real or synthetic data from current\nand imminent microwave missions (e.g. Sentinel-1, ROSE-L, CIMR, Harmony, Metop ASCAT/SG-SCA) to study processes\nrelevant in land, ocean and cryosphere applications, in particular processes related to surface-atmosphere interactions.\nMicrowave dielectric properties of natural materials\nMicrowave remote sensing of soil and vegetation.\nThe relation between surface soil moisture, root zone soil moisture and vegetation water content variations and their role in land-\natmosphere exchanges of water, energy and carbon. Modelling the influence of dielectric properties and geometry on emission\nand scattering from vegetated surfaces.\nSoil moisture estimation from passive and active microwave remote sensing.\nMonitoring biomass and vegetation water status using passive and active microwave remote sensing.\nLand-atmosphere interactions over ice/snow\nThe relation between physical snow/firn/ice properties and land/atmosphere interactions for ice\nThe relation between snow/firn/ice properties and the EM properties in the MW region\nRadiative transfer models to translate snow/firn/ice properties into remote sensing signals for both passive/active MW RS\nsensors\nRetrieval of snow/firn/ice properties from MW RS data\nOcean\nThe relation between wind, marine boundary layer conditions, and directional surface wave spectra.\nTheoretical models relating wave-spectra and the resulting directional roughness to the radar scattering intensities and\nmicrowave emissivity.\nEmpirical Geophysical Model Functions (GMF) relating surface winds and/or wind stress to radar scattering and Doppler\nRetrieval of surface wind and surface wave information using data from radar-scatter meters, Synthetic Aperture Radars, and\nmicrowave radiometers.\nStudy Goals After completing this module, students will be able to:\n1. Explain and describe the relations between surface properties and processes, and observations that can be obtained using\nmicrowave remote sensing.\n2. Apply state-of-the-art models and retrieval techniques to simulate microwave observables and retrieve states of interest in\nland, ocean and cryosphere applications .\n3. Compare different forward modelling or retrieval techniques to estimate variables of interest at the surface\n4. Select and defend the choice of a product/technique/model to capture a process relevant in land, ocean and cryosphere\napplications" . . "Presential"@en . "FALSE" . . "Coastal remote sensing"@en . . "5" . "The Coastal Remote Sensing module will provide students with theoretical background on both remote sensing and coastal\nprocesses. In this module an overview of coastal processes will be given that are relevant in an applied context, from the coastal\nshelf to the dunes. It will be discussed at which spatio-temporal scales coastal processes occur, and how these scales relate to\nremote sensing techniques, from in situ onshore and offshore techniques to satellite systems. An overview will be given of\nremote sensing techniques for measuring bathymetry and topography, including echo-sounding, laser scanning and\nphotogrammetry, but also the role of spectral techniques will be discussed, to e.g., assess sediment load, sea water temperature\nand dune vegetation properties. Finally, processing techniques to extract information from data, including data fusion techniques,\ntime series analysis, uncertainty assessment and relevant machine earning methodology will be covered.\nStudy Goals On completion of this module, the student will be able to:\nExplain which remote sensing techniques are suitable to assess coastal processes in terms of the spatio-temporal scales at which\nthey occur.\nDevelop a workflow to answer a research question on coastal processes using a suitable combination of remote sensing\ntechniques.\nExtract information from coastal remote sensing data and evaluate the results to answer a research question\nAssociate an error budget to different kind of coastal remote sensing data products and apply this error budget to assess the\nuncertainty of work-flow outcomes.\nDefend the results of an implemented workflow" . . "Presential"@en . "FALSE" . . "Applied space geodesy"@en . . "5" . "Satellite Earth Observation and Space Geodesy is an increasingly fertile field, with exciting technology that leads to a wide range\nof applications. Pioneers in the field are often young entrepreneurial start-ups that provide solutions that are directly applicable in\nsociety. Examples include, e.g., Planet, Maxar, Iceye, and Capella. What makes those initiatives so successful, and how can we\ndevelop new opportunities and challenges that have high impact?\nIn this course you will create your own start-up based on Satellite Earth Observation. We discuss, e.g., core space technologies,\nvalue proposition design and strategies, data processing, funding, IP, scalability, valuation, and collaborate as a team to develop\na new Earth Observation product or service. We evaluate current European policies to stimulate value creation from Earth\nObservation, and review legal restrictions. We will use guest lectures from space industry leaders and entrepreneurs as well as\nsite visits to learn about the challenges and pitfalls. Our information products will be used to respond to scientific or societal\nchallenges. Examples include information products for the Dutch Urban Search and Rescue (USAR) teams, requiring emergency\nresponse information, or energy sustainability for solar farms.\nStudy Goals After completing this module, students will be able to:\nEvaluate the space technologies available for value creation\nDevelop an idea into an entrepreneurial business model and a new Earth Observation product or service\nCreate a start-up up to a Minimal Viable Product" . . "Presential"@en . "FALSE" . . "Outcrop geology for subsurface characterization"@en . . "5" . "Module I (1 EC): preparation activities.\nStudents will gather essential information on the region (including geological maps and sections, and literature on relevant\nprocesses) and place them in a digital platform such as Google Earth. They will prepare knowledge and tools needed to address\nthe tasks tackled during fieldwork and design the optimal strategy.\nModule II (3.0 EC): Fieldwork\nDuring the first 1-2 days, all participant will be exposed to the area of study defining together the main sedimentary and\nstructural issues. In the following 6-7 days students will work on the tasks which have been defined during Module I. These tasks\nconsist of measurements, observations and interpretations on relevant topics and will last 2-3 days each, which means that each\ngroup will have 2-3 tasks to perform. Gathered data will be processed as much as possible during the evening in order to guide\ndata acquisition in the following days. The acquired data and their preliminary interpretations will be handed in to the course\ninstructors. During the final 1-2 days, the different groups will present their findings in the field to the other participants\nincluding those of different specializations.\nModule III (1EC): Finalization\nDuring module III, students will further process and interpret the data gathered in the field to reach higher-level conclusion\nwhich allows them to predict properties of subsurface rock bodies. This will result in a schematic report. An important part of\nmodule III is the organization of gathered information in a data base which can be used by students of following years.\nStudy Goals After completing this module, students will be able to:\n1) Describe and classify in 3D sedimentary rocks and heterogeneities at various scales in the field\n2) Describe and classify in 3D faults, fractures and folds at various scales in the field\n3) Quantify uncertainty in geomodels based on field observations\n4) Choose predicting and upscaling strategies base on field observations\n5) Present results in a compact and clear manner" . . "Presential"@en . "FALSE" . . "Occupational health and safety management"@en . . "5" . "The course includes the following topics:\n- Safety systems\n- Safety culture\n- Statistics in legal, health and safety\n- History of health and safety\n- Safety structure: Organisation\n- Safety processes: Standards, policies and procedures,\n- Risk assessment and management,\n- Policy support and reinforcement,\n- Toolbox topics\n- Job safety analyses\n- Safe working procedures\n- Health topics: Fatigue management, Noise\n- Incident investigation\n- Legal framework\n- Environmental aspects associated with LHS\nStudy Goals After completing this module, students will be able to:\n1. explain and describe the importance of Health and safety management in the resources industry\n2. find and apply legal requirements and applicable international standards\n3. apply knowledge of safety procedures and standards in the field\n4. prepare a job hazard analysis and risk assessment and develop mitigation and safety procedures\n5. set up an incident investigation" . . "Presential"@en . "FALSE" . . "Master in Applied Earth Sciences"@en . . "https://www.tudelft.nl/onderwijs/opleidingen/masters/applied-earth-sciences/msc-applied-earth-sciences/programme" . "120"^^ . "Presential"@en . "The master Applied Earth Sciences (AES) is a two-year MSc programme. In the first year, you build core competencies through the AES programme core and faculty module on Modelling, Uncertainty and Data for Engineers (MUDE). You also choose your discipline, gaining specialised knowledge in a particular field. Finally, you gain hands on experience by applying the knowledge you are learning in case studies and in the field.\n\nIn the second year, you have even more choice. You choose between in-depth or free electives, a multi- or interdisciplinary project in the Netherlands or abroad, and cross-over modules. This prepares you to make a well-informed decision for a master’s thesis research topic."@en . . "2"@en . "FALSE" . . "Master"@en . "Thesis" . "2314.00" . "Euro"@en . "20560.00" . "Recommended" . "Graduates of Applied Earth Sciences find jobs in industry, governmental organisations, knowledge institutes, and universities worldwide that centre around the programmes disciplines (Weather and Climate, Earth Observation, Geo-Energy and Geo-Resources) as well as in engineering jobs outside these disciplines. They are hired within the engineering industry, construction firms, energy, resource and water companies, IT companies, and consultancy firms advising these industries. They are employed by a range of governmental organisations, knowledge and space institutes, NGOs, and our students continue their academic career at leading universities within the Netherlands and abroad."@en . "4"^^ . "FALSE" . "Downstream"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "Faculty Of Civil Engineering and Geosciences"@en . .