Scientific profile:

Christian Neuwirth is dedicated to the DK-project “Simulating Spatial Dynamics of Water Resource Systems”, which belongs to the research cluster Time and Process.

He obtained his bachelor’s degree in Geography (2007) and his master’s degree in Applied Geoinformatics (2010) from the University of Salzburg. Between October 2009 and October 2011 he worked as a project collaborator at the Research Studio iSpace, where he was involved in the research projects CLISP (Climate Change Adaptation by Spatial Planning in the Alpine Space) and REBLAUS (Crossborder risk and natural hazard management based on regional lightning analyses).

As a consequence of his work experience he has gained a solid background in GIS and process modeling, with a preference of environmental disciplines such as hydrology and geomorphology. Moreover, due to the activities in the previously mentioned research projects, the application of risk management concepts plays a key role in his occupational history.

Research Cluster: Time and Process

PhD Thesis Topic: Simulating Spatial Dynamics of Water Resource Systems

Research Proposal:

Causal relationships in Water Resource Systems typically reach across domain boundaries. Consequently, there is a need for integrated models, which are able to consider coherent feedback cycles and interrelationships between domains (e.g. hydrological factors may be affected by the prevailing land use, which in turn is influenced by economic and hydrological factors as well). In addition, the respective processes may also operate on different time scales.

The presented PhD proposes the use of an approach called Spatial System Dynamics (SSD), which enables to logically link these cross-domain relationships based on causal assumptions. Thereby, System Dynamics (SD) software is coupled with a Geographic Information System (GIS). SD is a powerful approach for modeling dynamic behavior of complex systems by means of basic graphical building blocks. GIS, however, was initially designed for spatial analysis purposes. The coupling of the non-spatial, dynamic SD with a spatial but relatively static GIS produces synergy effects and enables sophisticated spatiotemporal modeling of water resource systems.

The application of SSD is focused on the three issues of flood, water scarcity and water pollution. Thereby, one major objective is to utilize the graphical building block structure of SD to create transferable modular components, which can be reused in different applications (e.g. flood modules can be utilized for the water scarcity model as well). This makes the modeling process much more efficient. In addition, the graphical approach facilitates the communication of the system structure and enables the synthesis of model conceptualization and implementation. 

Moreover, from a methodological point of view, a main objective is to evaluate the suitability of the SSD approach for the respective issues as well as the level of spatial complexity required for the appropriate system representation. Accordingly, the following methodological questions can be addressed:

• Which kinds of processes can be integrated in the SSD framework?
• Which levels of spatial complexity can be reached (Lumped Area Parameter Model or Spatial Process Model)?
• How to exchange and update data between the static GIS and the dynamic SD framework in order to explicitly consider feedback in time and space?