Siehe TUMonline

The course will provide to the students both the theoretical as well the practical knowledge to use modeling methods to explore water-food nexus under land and water management issues. Upon completion of the module, students are able to: • gain advanced hydrological modeling skills; • acquire knowledge about water-food nexus; • apply modeling approaches to simulate land and management scenarios; • predict water availability and crop yield according to specific land and water management conditions.

• Advanced modeling skill with SWAT/SWAT+; • Knowledge of water-food nexus modeling processes of multiple advanced modules (crop yield, land management and water management) in SWAT/SWAT+; • Application of SWAT/SWAT+ model for land management and water management modeling practices; • Evaluation of the impacts of management scenarios on water and crop yield; • Development of the case study; • Presenting a case study.

• Basics of programming in Python. • Basics of GIS. • Adequate knowledge of hydrology and hydrological modelling (relevant course records). • Adequate knowledge of SWAT/SWAT+ model (relevant course records). • Knowledge of Remote Sensing is an asset.

The module will be organized in an interactive manner as a lecture with integrated computational hand-on exercises. The lectures’ contents are presented by the lecturer using the digital slides and programming tutorials. During the exercises, the students independently solve practical examples and learn modeling skills. The students work in groups (max 3 persons per group) on one assignment, which tests the achievement of the study goals and competences based on more extensive case studies. A report by each group is required to be presented at the end.

The exam consists of the development of a project to be presented during an oral examination. The exam will verify i) how the students understand concepts of water-food nexus; ii) how the students master the modeling processes and skills; iii) how the students are able to apply those theoretical and technical knowledge for the solution of realistic case studies.

• Neitsch, S.L., Arnold, J.G., Kiniry, J.R. and Williams, J.R., 2011. Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute. • Arnold, J.G., Kiniry, J.R., Srinivasan, R., Williams, J.R., Haney, E.B. and Neitsch, S.L. Soil and water assessment tool input/output file documentation version 2012. Texas Water Resources Institute. • White, M., Gambone, M., Yen, H., Daggupati, P., Bieger, K., Deb, D. and Arnold, J., 2016. Development of a cropland management dataset to support US SWAT assessments. JAWRA Journal of the American Water Resources Association, 52(1), pp.269-274. • Volk, M., Bosch, D., Nangia, V. and Narasimhan, B., 2016. SWAT: Agricultural water and nonpoint source pollution management at a watershed scale. Agricultural Water Management, 175, pp.1-3. • Papers from the following journals: Water Resources Research, Journal of Hydrology, HESS etc.