# Search result: Catalogue data in Autumn Semester 2020

Earth and Climate Sciences Bachelor | ||||||

Majors | ||||||

Major: Climate and Water Advisor of the BSc-major "Climate and Water" is Dr. Hanna Joos, Institute for climate and atmosphere (IAC). | ||||||

Electives The electives listed are recommended. Additional courses can be chosen from the complete offerings of the ETH Zurich and University of Zurich. | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|---|

401-0649-00L | Applied Statistical Regression | W | 5 credits | 2V + 1U | M. Dettling | |

Abstract | This course offers a practically oriented introduction into regression modeling methods. The basic concepts and some mathematical background are included, with the emphasis lying in learning "good practice" that can be applied in every student's own projects and daily work life. A special focus will be laid in the use of the statistical software package R for regression analysis. | |||||

Learning objective | The students acquire advanced practical skills in linear regression analysis and are also familiar with its extensions to generalized linear modeling. | |||||

Content | The course starts with the basics of linear modeling, and then proceeds to parameter estimation, tests, confidence intervals, residual analysis, model choice, and prediction. More rarely touched but practically relevant topics that will be covered include variable transformations, multicollinearity problems and model interpretation, as well as general modeling strategies. The last third of the course is dedicated to an introduction to generalized linear models: this includes the generalized additive model, logistic regression for binary response variables, binomial regression for grouped data and poisson regression for count data. | |||||

Lecture notes | A script will be available. | |||||

Literature | Faraway (2005): Linear Models with R Faraway (2006): Extending the Linear Model with R Draper & Smith (1998): Applied Regression Analysis Fox (2008): Applied Regression Analysis and GLMs Montgomery et al. (2006): Introduction to Linear Regression Analysis | |||||

Prerequisites / Notice | The exercises, but also the classes will be based on procedures from the freely available, open-source statistical software package R, for which an introduction will be held. In the Mathematics Bachelor and Master programmes, the two course units 401-0649-00L "Applied Statistical Regression" and 401-3622-00L "Statistical Modelling" are mutually exclusive. Registration for the examination of one of these two course units is only allowed if you have not registered for the examination of the other course unit. | |||||

701-0535-00L | Environmental Soil Physics/Vadose Zone Hydrology | W | 3 credits | 2G + 2U | P. U. Lehmann Grunder | |

Abstract | The course provides theoretical and practical foundations for understanding and characterizing physical and transport properties of soils/ near-surface earth materials, and quantifying hydrological processes and fluxes of mass and energy at multiple scales. | |||||

Learning objective | Students are able to - characterize porous media at different scales - parameterize structural, flow and transport properties of partially-saturated porous media - quantify driving forces and resulting fluxes of water, solute, and heat in soils - explain links between physical processes in the vadose-zone and major societal and environmental challenges | |||||

Content | Weeks 1 to 3: Physical Properties of Soils and Other Porous Media – Units and dimensions, definitions and basic mass-volume relationships between the solid, liquid and gaseous phases; soil texture; particle size distributions; surface area; soil structure. Soil colloids and clay behavior Soil Water Content and its Measurement - Definitions; measurement methods - gravimetric, neutron scattering, gamma attenuation; and time domain reflectometry; soil water storage and water balance. Weeks 4 to 5: Soil Water Retention and Potential (Hydrostatics) - The energy state of soil water; total water potential and its components; properties of water (molecular, surface tension, and capillary rise); modern aspects of capillarity in porous media; units and calculations and measurement of equilibrium soil water potential components; soil water characteristic curves definitions and measurements; parametric models; hysteresis. Modern aspects of capillarity Weeks 6 to 9: Water Flow in Soil - Hydrodynamics: Part 1 - Laminar flow in tubes (Poiseuille's Law); Darcy's Law, conditions and states of flow; saturated flow; hydraulic conductivity and its measurement. Part 2 - Unsaturated steady state flow; unsaturated hydraulic conductivity models and applications; non-steady flow and Richards equation; approximate solutions to infiltration (Green-Ampt, Philip); field methods for estimating soil hydraulic properties. Part 3 - Use of Hydrus model for simulation of unsaturated flow Week 10: Solute Transport in Soils; Transport mechanisms of solutes in porous media; breakthrough curves; convection-dispersion equation; solutions for pulse and step solute application; parameter estimation; salt balance. Week 11: Gas transport in soil and biological processes; gas diffusion as function of water content, Fickian law, biological activity and respiration; root water uptake; soil structure Week 12 to 13: Energy Balance and Land Atmosphere Interactions - Radiation and energy balance; evapotranspiration definitions and estimation; transpiration, plant development and transpirtation coefficients; small and large scale influences on hydrological cycle; surface evaporation. Week 14: Temperature and Heat Flow in Porous Media - Soil thermal properties; steady state heat flow; nonsteady heat flow; estimation of thermal properties; engineering applications. | |||||

Lecture notes | Classnotes: Vadose Zone Hydrology, by Or D., J.M. Wraith, and M. Tuller (available at the beginning of the semester) | |||||

Literature | Supplemental textbook (not mandatory) -Environmental Soil Physics, by: D. Hillel | |||||

401-0624-00L | Mathematics IV: Statistics | W | 4 credits | 2V + 1U | J. Ernest | |

Abstract | Introduction to basic methods and fundamental concepts of statistics and probability theory for practicioners in natural sciences. The concepts will be illustrated with some real data examples. The lecture will be held in German. | |||||

Learning objective | Capacity to learn from data; good practice when dealing with data and recognizing possible fraud in statistics; basic knowledge about the laws of randomness and stochastic thinking (thinking in probabilities); apply simple methods in inferential statistics (e.g., several hypothesis tests will be introduced). The lecture will be held in German. | |||||

Content | Beschreibende Statistik (einschliesslich graphischer Methoden). Einführung in die Wahrscheinlichkeitsrechnung (Grundregeln, Zufallsvariable, diskrete und stetige Verteilungen, Ausblick auf Grenzwertsätze). Methoden der Analytischen Statistik: Schätzungen, Tests (einschliesslich Binomialtest, t-Test, Vorzeichentest, F-Test, Wilcoxon-Test), Vertrauensintervalle, Prognoseintervalle, Korrelation, einfache und multiple lineare Regression. | |||||

Lecture notes | Skript zur Vorlesung ist erhältlich. | |||||

Literature | Stahel, W.: Statistische Datenanalyse. Vieweg 1995, 3. Auflage 2000 (als ergänzende Lektüre) | |||||

Prerequisites / Notice | Die Übungen (ca. die Hälfte der Kontaktstunden; einschliesslich Computerübungen) sind ein wichtiger Bestandteil der Lehrveranstaltung. Voraussetzungen: Mathematik I, II | |||||

» Choice of courses from the complete offerings of ETH. | ||||||

701-0479-00L | Environmental Fluid Dynamics | W | 3 credits | 2G | H. Wernli, M. Röthlisberger | |

Abstract | This course covers the basic physical concepts and mathematical equations used to describe environmental fluid systems on the rotating Earth. Fundamental concepts (e.g. vorticity dynamics and waves) are formally introduced, applied quantitatively and illustrated using examples. Exercises help to deepen knowledge of the material. | |||||

Learning objective | Students are able - to name the bases, concepts and methods of environmental fluid dynamics. - to understand and discuss the components of the basic physical equations in fluid dynamics - to apply basic mathematical equations to simple problems of environmental fluid dynamics | |||||

Content | Basic physial terminology and mathematical laws: Continuum hypothesis, forces, constitutive laws, state equations and basic principles of thermodynamics, kinematics, laws of mass and momentum on rotating earth. Concepts and illustrative flow sytems: vorticity dynamics, boundary layers, instability, turbulence - with respect to environmental fluid systems. Scale analysis: dimensionles variables and dynamical similarity, simplification of the fluid system, e.g. shallow water assumption, geostrophic flow. Waves in environmental fluid systems. | |||||

Lecture notes | In english language | |||||

Literature | Will be presnted in class. See also: web-site. | |||||

401-6215-00L | Using R for Data Analysis and Graphics (Part I) | W | 1.5 credits | 1G | M. Mächler | |

Abstract | The course provides the first part an introduction to the statistical software R (https://www.r-project.org/) for scientists. Topics covered are data generation and selection, graphical and basic statistical functions, creating simple functions, basic types of objects. | |||||

Learning objective | The students will be able to use the software R for simple data analysis and graphics. | |||||

Content | The course provides the first part of an introduction to the statistical software R for scientists. R is free software that contains a huge collection of functions with focus on statistics and graphics. If one wants to use R one has to learn the programming language R - on very rudimentary level. The course aims to facilitate this by providing a basic introduction to R. Part I of the course covers the following topics: - What is R? - R Basics: reading and writing data from/to files, creating vectors & matrices, selecting elements of dataframes, vectors and matrices, arithmetics; - Types of data: numeric, character, logical and categorical data, missing values; - Simple (statistical) functions: summary, mean, var, etc., simple statistical tests; - Writing simple functions; - Introduction to graphics: scatter-, boxplots and other high-level plotting functions, embellishing plots by title, axis labels, etc., adding elements (lines, points) to existing plots. The course focuses on practical work at the computer. We will make use of the graphical user interface RStudio: www.rstudio.org Note: Part I of UsingR is complemented and extended by Part II, which is offered during the second part of the semester and which can be taken independently from Part I. | |||||

Lecture notes | An Introduction to R. http://stat.ethz.ch/CRAN/doc/contrib/Lam-IntroductionToR_LHL.pdf | |||||

Prerequisites / Notice | The course resources will be provided via the Moodle web learning platform. Subscribing via Mystudies should *automatically* make you a student participant of the Moodle course of this lecture, which is at https://moodle-app2.let.ethz.ch/course/view.php?id=13499 ALL material is available on this moodle page. |

- Page 1 of 1