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Working groups

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Contribution to ZALF research

Today, model building is a well-established tool in many disciplines and the number and complexity of available models is steadily increasing. The complexity of landscape processes is one of the reasons for the multitude of modelling approaches that must be combined into newly developed modelling platforms to support integrated landscape research. Beyond model building, the use of models also results in new challenges that require scientific attention: methods of model calibration and validation, data assimilation techniques, data-driven modelling approaches and the behaviour of models and model ensembles at the boundaries of their application range are commonly not studied by researchers interested in landscapes. However, particularly models which operate at the landscape level and integrate processes of different entities to describe interactions at the interface of nature, economy and society are not yet fully explored. Applied model solutions which represent agricultural landscapes as the arena of land use and governance decisions are also rare. The Research Platform “Models & Simulation” closes these gaps and provides a framework for the integration of different disciplines and modelling approaches aiming for an improved understanding of agricultural landscape functioning.

The Research Platform “Models & Simulation” will consist of working groups which conduct cutting-edge research on modelling and simulation methods. Depending on their focus they will work on

  • the scale dependency of both model parameters and the availability of inputs,
  • the limited prediction horizon of nonlinear systems, and
  • the stochastics of system inputs.


Working groups


Ecosystem Modelling

Image of the WG Ecosystem Modelling 

The working group deals with point- and grid-based simulations with respect to topics like food security, climate protection and resource management. A focus lies on the numerous process interactions between soil and plants in managed agricultural systems and the effects their representation in models has on simulations. The working group builds on existing process-based agroecosystem, forest ecosystem and hydrological models, which form the core of future model development. Model improvement will focus on the reduction of uncertainties associated with model structure and parameters as well as on the expansion of the represented processes. To this end, the working group cooperates with different national and international networks and projects, such as e.g. MACSUR and AgMIP.

Contact: Dr. Claas Nendel


Integrated Landscape Modelling

Image of the WG Integrated Landscape Modelling

This newly established working group develops the framework for the coupling of fundamentally different modelling approaches into an integrate landscape simulation. Initially, the working group will concentrate on a concept for the integration of process-based simulation models for cropland, grassland and forest ecosystems into a single modelling framework, with a special focus on transition zones between these ecosystems and the observed abiotic processes in these transition zones. In addition, remote sensing data is to be used to parameterise, initialise and drive one-dimensional process-based and other types of two- to three-dimensional models at the landscape scale. This includes models for socioeconomic processes.

Contact: Dr. Claas Nendel


Simulation Methods and Data-driven Models

Image of the WG Simulation Methods

This methodologically oriented working group deals with the analysis of the data-model-data loop in agricultural landscape research. The overarching task is to test the suitability of established methods from neighbouring disciplines and sectors for the simulation of interrelations and patterns in landscapes and the deduction of new insights from their application. To this end, the working group uses methods such as machine learning, deep learning, cluster computing, fuzzy models as well as Bayesian modelling.

Contact: Dr. Ralf Wieland


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