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Lecturer(s)
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Borovec Jakub, RNDr. Ph.D.
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Course content
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Content of lectures: Introduction: The goal of the lecture, a review of lectures and basic terminology. Example of solution of an environmental problem. Data obtained by manual sampling and by automatic monitoring. Quantitative and qualitative data. Collecting and storing data. Sources of data. Computer databases and their utilization. Use of spreadsheets. Systems analysis of environmental problems: Steps of systems analysis. Definition of system and its elements, system relations. Methods for analysis of exact and uncertain data. Analysis of time dependent data and time series analysis. Mathematical models: types and use, formulation of mathematical models. Empirical (statistical) and theoretical (dynamic, simulation) models. Empirical models: Application of statistical approaches, in particular regressions for environmental analysis. Possibilities and pitfalls of different regression types: linear regression, transformation of axes, polynomial regression, periodic regression, and polynomial regression. Basic types of nonlinear relations and nonlinear regression. Static and dynamic empirical models. Theoretical mathematical models. Principles of systems dynamics. Difference and differential equations and their numerical solution. Formulation of environmental models. Systems simulation. Review of application models for solution of selected environmental problems, how to use them. Derivation of conclusions for environmental problems: Approaches to derive conclusions for decisions. Formulation of indexes of environmental quality based on both quantitative and qualitative data. Optimization and management of environmental systems. Data elaboration as a system: Mutual relations between the goals of data collection, precision of determination of individual variables, sampling frequency and derived conclusions. Review of the state of environmental pollution: Situation in the Czech Republic, in Europe and in the world. Sources of information. Content of practices: Use of spreadsheets and databases. Regressions. Examples of formulating calculation and statistical models. Nonlinear parameter estimates for functional relations among variables. Training with a dynamic ecological model. Sample elaboration of collected data.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Practical training
- Class attendance
- 36 hours per semester
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Learning outcomes
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The goal of the lectures and exercises is to learn students basic approaches to elaboration of environmental data and evaluation of such data for decisions concerning the environment. The lecture is directed to both data obtained by classical methods (with low frequency of sampling) and by automatic monitoring. Data elaboration is performed by classical methods as well as by systems analysis approaches and the use of dynamic mathematical models.
Critical view of data from monitoring and experimental data. Their evaluation, treatment (finding errors) and interpretation. Understanding the factual link between the dynamics of monitored processes and data collection and processing.
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Prerequisites
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Prerequisites and co-requisites The subject assumes knowledge of mathematics at the level of the second level of elementary school, knowledge of biostatistics and work on PC in MS Office.
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Assessment methods and criteria
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Written examination, Interview
Active participation in the practical session.
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Recommended literature
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Bossel H. (1994) Modelling and Simulation, Verlag Vieweg, Germany.
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Hardisty J., Taylor D. M., Metcalfe S. E. (1993) Computerized environmental modelling. A practical introduction using Excel. Wiley, Chichester.
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Jorgensen S. E. (1983) Application of environmental modelling in environmental management, Elsevier.
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Straškraba M. (1983) Teorie systémů a systémová analýza pro ochranu životního prostředí, Skripta Přírodovědecká fakulta UK, Praha.
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