As a result of global climate change, Earth and its systems are undergoing rapid alterations. To adapt to changes happening at unprecedented rates, we must study how the interrelated multi-disciplinary fields (e.g., geosphere, atmosphere, hydrosphere, and biosphere) interact with each other.

Furthermore, the effectiveness of emergency response depends on the quick provision of detailed, precise, and up-to-date information. Not only the natural environment has to be monitored, but also the state of traffic, hospitals, civil infrastructures such as electricity, water supplies, the location, status, and number of injured people must be provided on time. To that end, the availability of information infrastructure may decrease in the case of a disaster. Also, legal issues are complicating or even blocking the access to information. Then, the state of relevant objects is changing extremely quickly. For instance, hospitals might close down operations abruptly due to electricity shortcuts, while emergency medical-care points start operations at unpredictable points in time once the set-up is completed. This motivates the need for simulating both the natural phenomena and the reactions of people or organizations. Ultimately, the prediction of possible scenarios and searching for secure, reliable information channels becomes possible.

The main aim of my research is to develop a unified framework in the form of a simulation-based Environmental DisastEr predictioN system (i.e., sim-EDEN). It should comprise many different perspectives as given below.

An interdisciplinary approach including software, control engineering, environmental, and social science can contribute to the environmental resources management, environmental disaster prediction, and their analysis. The natural resources (e.g., water, air, and earth systems) can be regarded as networks consisting of their different representations. These elements create phenomena that must be described, analyzed, and managed by mathematical and physical models using different computation techniques.

The target is to develop a set of methods dealing with physical phenomena that are described by mathematical and physical models and are evaluated using different computation techniques. Then, the heterogeneous nature of the models should be analyzed and evaluated using a common framework.

This would be an interdisciplinary contribution to a number of communities (e.g., related to Geographic Information Systems (GIS)), where the analysis of different behavioral models stimulated with heterogeneous data plays a significant role.