NIGK17003U Hydrogeology: Data Collection and Processing
MSc Programme in Geology-Geoscience.
The course prepares attendants for MSc thesis work in the field of hydrogeology or other environmental sciences/fields. The course will focus on the planning of research/investigation activities, in concordance with scientific theory, methodologies of data collection, dealing with uncertainties, data processing, and data presentation. The aim of the course is for the attandants to:
- Acquire experience in the planning of research/investigation activities: For example, to decide, for a field study, the number of wells and where to place them.
- Acquire hands-on experience on data collection: For example, installation of wells and piezometers, head measurements, and sampling for water chemistry or stable isotopes of water.
- Learn how to systematically organize collected data in structured data formats.
- Learn how to process data in order to present high-quality graphs and illustrations.
The attendants will combine th euse of MS EXCEL with the free open source codes Phyton and QGIS as tools for data processing and presentation.
The course is a field course, but competences, skills, and knowledge gained are broadly applicable to laboratory or computerbased data collection as well.
Attendants are expected to possess some experience in hydrological/environmental data interpretation from other courses. Accordingly, it is outside the primary scope of the course to specifically address how to jointly interpret hydrological, geological and water chemical data, although discussions on data interpretation are still welcomed and encouraged, as interpretation is an integral part of selecting the most informative and illustrative means of data processing and presentation.
- Proper stucturing of an 'EXCEL database'.
- Phyton (free, open-source programming language).
- QGIS (free, open-source GIS coupled to Phyton).
- Uncertainty evaluation in hydrology, water chemistry, and geology.
- To organize and conduct field data collection.
- To assess experimental design aspects of planned research/investigation activities.
- To evaluate the data types/entities needed in a database.
- To create clear tables, graphs and illustrations addressing specific relations from which conclusions can be drawn.
- To propagate data point uncertainty to uncertainty in a derived parameter.
- To design a reasoned data collection strategy for investigating a working hypothesis related to hydrogeological and solute transport problems.
- To develop structured databases enabling fast, solid and advanced data processing.
- To evaluate suitable ways of presenting data/results in order to illustrate relationships which are informative and conclusive for the hypothesis.
Please see Absalon.
Second half of the course: field trip, followed by data presentation and interpretation, initiating the writing the individual Assignment. This will be followed by group presentations at a seminar, to be held about a week before the deadline for handing in the Assignment. The last week will be devoted to finishing up the Assignment.
- Field Work
- Project work
- Theory exercises
Continuous oral individual and colletive feedback from teachers during the course. Oral peer- and teacherfeedback at group presentations given at the seminar near the end of the course. Written feedback, supplementing the mark, will be given to the final Assignment.
- 7,5 ECTS
- Type of assessment
- Written assignment, Ongoing preparation throughout the courseThe written assignment is prepared during the course and must be handed in during the exam week.
- Exam registration requirements
Approved participation in the fieldwork. If the student does not take part in the fieldwork, the student cannot take part in the exam or re-exam and will have to re-take the course on next occasion.
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners.
Resubmission of written assignment. The written assignment must be handed in during the reexamination week.
Criteria for exam assesment
See learning outcome.