701-1673-00L Environmental Measurement Laboratory
| Semester | Autumn Semester 2023 |
| Lecturers | P. U. Lehmann Grunder, A. Carminati |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Abstract | Measurements are the sole judge of scientific truth and provide access to unpredictable information, enabling the characterization and monitoring of complex terrestrial systems. Based on lectures and field- and laboratory training, the students learn to apply modern methods to determine forest inventory parameters and to measure subsurface properties and processes. | ||||||||||||||||||||||||||||||
| Learning objective | The students will be able to: - explain measurement principles that are used for characterization of landscapes and terrestrial systems - select appropriate measurement methods and sampling design to quantify key variables and processes above ground and in the subsurface - deploy sensors in the field - interpret collected laboratory and field data and report main conclusions deduced from measurements | ||||||||||||||||||||||||||||||
| Content | Week 1: Plant-Soil interactions – short introduction before sensor demonstration and installation in forest lab; Scholander pressure bomb (suction in leaves); LiCOR soil chamber Weeks 2 to 6 - Experimental Methods for Soil Health Assessment - - - - - - - - - - - - - - - - - - - - - - - - - - Week 2: Lecture on soil health and soil indicators; defining measurable soil health indicators for case studies for different soil threats and climate regions Week 3: Short lecture on sampling, sensors and data logging; preparing sensors and data loggers in the lab; measurements on water content and temperature in the lab Week 4: Short introduction on field installation; sensor installation at field site Hönggerberg Week 5: Lecture on geophysical methods on subsurface characterization: basic principles of ERT, GPR, and EM; planning of field experiment to assess soil health Week 6: Short introduction on data analysis; field sampling and conducting field experiment to assess soil health Week 7: Analysis of experimental data and soil health assessment; poster presentation and discussion - - - - - - - - - - - - - - - - - - - - - - - - - - Week 8: Lecture on plant soil relationship; connecting information below and above ground – data analysis Weeks 9 and 10: Forest characterization/ inventory: Principles of LiDAR; structures and features of the tree crowns, size/volume of the leaf area tree positions and diameters at breast height Weeks 11 and 12: Eddy covariance methods -Principles for field measurement of water vapor, carbon dioxide, and energy exchange between terrestrial surfaces and the atmosphere; Analysis of measured time series to determine evaporation rate and CO2-fluxes Week 13: Swiss Soil Monitoring networks – Monitoring of soil water content and potential; climate change and droughts Week 14: Global data – Global modeling and data interpretation; SoilGrids and OpenLandMap; exercises on Budyko analysis | ||||||||||||||||||||||||||||||
| Literature | Lecture material will be online for registered students using moodle | ||||||||||||||||||||||||||||||
| Prerequisites / Notice | The details of the schedule will be optimized based on the number of students; some blocks of the course will be offered as well to students of Environmental Engineering | ||||||||||||||||||||||||||||||
Competencies |
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