Mountain landscape with houses

Investigating the processes in complex coupled human-environmental systems (Copyright: T. Exel)


The aim of this key research area is to achieve a better understanding of environmental processes on the surface of the planet. The goal is to improve the understanding, survey, and forecast of the dynamics of processes in complex coupled human-environmental systems. This key research tackles questions on the sustainable preservation of the basis of life.

Earth and atmosphere are subject to changes that have influenced the planet’s natural environment in the past and present, and will the future with a direct impact on society. Identification of environmental factors that have brought change, both natural and human-made, allows for the understanding of recent systems and provides a base for predicting future developments. This key research area aims to quantify the impact of social activity on the environment as well as characterize hazards and risks.

Process-oriented research in this area seeks to identify the interrelationships between humans, the atmosphere, biosphere, hydrosphere and the upper geosphere. Ecosystems and Society are to a large extent  influenced by such environmental processes. In order to understand these complex connections, we analyse, model and study components of these systems and their interactions. This key research area provides valuable insight into meteorological processes, the climate system and palaeo-climate reconstruction, as well as the socio-economic effects of global change on regional development including interactions with societal processes. It includes research on the usage of land and resources and ecosystem management, groundwater and surface water, environmental and emerging trace contaminants, natural hazard as well as risk research. These processes are investigated by means of comprehensive in-situ high-resolution measurements in space and time, cutting edge laboratory analysis, remote sensing, as well as modern, high-performance numerical modelling at various degrees of temporal and spatial resolution. The results obtained can then be structured in geo-databases and visualized dynamically.