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Note: This course is for Master students.

1. At the end of the module, the students are able to understand the principles of remote sensing, and how the satellite products for various hydrological components are generated. 2. Students will be able to process various satellite products in the different data formats using ArcGIS, QGIS and some programming software Matlab and Python. 3. Students will be able to evaluate the satellite products, to identify different influencing factors on the satellite data quality, and how to and how to integrate satellite products to hydrological modelling to solve practical problems.

Contents for lectures: In first two theoretical lectures, the fundamentals of hydrology and remote sensing will be explained. Then in the following theoretical lectures, remote sensing methods for different hydrological components and the applications in case studies will be explained and presented: • Precipitation • Vegetation • Evaporation • Soil moisture • Water level and water volume • Groundwater • Snow and ice The application of remote sensing in other environmental studies such as land use and land cover classification, soil erosion and water quality will also be briefly discussed. Contents for exercises in the computer lab The methods for processing various remote sensing products in different formats will be taught based on a practical example in the computer lab: • Visualization of satellite data (Landsat, MODIS, Sentinel etc.) and projection in ArcGIS • Processing satellite precipitation TRMM data and comparison with measurements from WMO stations • Processing vegetation index products from different satellites • Processing satellite ET products and surface temperature products • Processing satellite soil moisture products • Analysis of satellite altimetry data for water level in lakes and reservoirs • Analysis of groundwater variation from GRACE satellites • Analysis of MODIS satellite snow cover products

Basics of hydrology, hydrological modelling and GIS. Basics of GIS software ArcGIS or QGIS. Basics of programming in Matlab and/or Python. Ability to literature review and critical thinking of scientific journal papers.

Lecture (talk, presentation, group work): The lecture provides the fundamentals of hydrology and remote sensing, mathematical remote sensing calculation methods and data formats for various hydrological components (e.g. precipitation, evaporation, water level), and applications of remote sensing in practical hydrological studies. Exercises (talk, presentation, individual and group work, case study): Hands-on exercises will be given in the computer lab. A detailed investigation of single hydrological components as it is done in the lecture will be achieved through the practical processing of the satellite products. The application of software and programing and the data evaluation will be taught in more details. During the exercises the students learn the satellite data processing in a more practical hands-on manner. The students are expected to learn how to download and process the satellite data. The processing procedures in ArcGIS and some programming in Matlab and Python will also be taught during the exercises. Students will receive support by student tutors and the lecturing tutor. During the exercise, some small exercises will be assigned but they will be voluntary and used only for students’ self-assessment. In the end, a voluntary report can be also handed in: students can form a group with 2 or maximum 4 members to select a topic (e.g. precipitation, water level) to write a report with an approx. 20 pages. The lectures and exercises in computer lab will be closely linked to achieve the study goals.

The examination is done via a 90 minute written exam. The exam consists of 2/3 theoretical questions and 1/3 calculations. Allowed tool is a non-programmable calculator. Based on theoretical questions, the students have to show that they understand the principles of remote sensing in hydrology and can evaluate the different satellite products in terms of quality and can understand how to integrate remote sensing data in hydrological modelling to solve the practical limitations of point-based ground measurements. Based on short calculations the students demonstrate that they can understand various mathematical procedures for estimating key hydrological components by the means of remote sensing data.

Schultz, G. A., & Engman, E. T. (Eds.). (2000). Remote sensing in hydrology and water management. Springer Science & Business Media. Campbell, J. B. (2002). Introduction to remote sensing. CRC Press. Davie, T. (2008). Fundamentals of hydrology. Taylor & Francis. Gebremichael, M., & Hossain, F. (2010). Satellite rainfall applications for surface hydrology. New York: Springer. Papers from the following journals: Remote Sensing of Environment, Water Resources Research, Journal of Hydrology, International Journal of Remote Sensing etc. User manuals for specific satellite products. The manuals will be specified during lectures.