Cluster A - Projects


Structural controls of soil hydraulic properties

Dr. Sara Bauke
University of Bonn  |  +49-228-73 2965  |  [Email protection active, please enable JavaScript.]

Prof. Dr. Wulf Amelung
University of Bonn  |   +49-228-73 2780  |  [Email protection active, please enable JavaScript.]


The hydraulic conductivity function of soils is a key property, controlling the partitioning of water into soil infiltration and surface runoff as well as the flow of water within the soil profile. Structure is an important factor for hydraulic conductivity in the wet range of soil moisture. However, this is currently not well implemented into land surface models, which typically produces incorrect representations of hydraulic conductivity at and near saturation, erroneous estimates of water partitioning at the soil surface especially in extreme events and thereby a misrepresentation of soil and surface water fluxes in the global water cycle. In this project we will therefore assess the effect of soil structure on soil hydraulic conductivity for different climatic, soil and land use setting across Europe. The results will then be incorporated into continental-scale modelling of water and energy cycles.


Estimation of root zone soil moisture from gamma radiation measurements

Prof. Dr. J.A. (Sander) Huisman
Forschungszentrum Jülich  |  +49-2461-618607  |  [Email protection active, please enable JavaScript.]


Root zone soil moisture is an essential variable in land surface models, but there is still a lack of sensing information that adequately represents this zone. In this project, we want to explore whether a root zone soil moisture product for Europe can be derived from existing gamma radiation data available from the European radiological data exchange platform (EURDEP). For this, it is important to understand how infiltration, evaporation, transpiration, and secondary cosmic radiation affect measured gamma radiation.


Parameterization of evapotranspiration partitioning function in land-surface models using water stable isotopes

Prof. Dr. Youri Rothfuss
Forschungszentrum Jülich  |  +49-2461-96925  |  [Email protection active, please enable JavaScript.]

Prof. Dr. Nicolas Brüggemann
Forschungszentrum Jülich  |  +49-2461-8643  |  [Email protection active, please enable JavaScript.]


In this sub-project, we would like to answer the question whether CLM5.0 simulations for specific ecosystems (or for major ecosystem/climate combinations) can be improved by a better representation of the ration of transpiration to evapotranspiration (T/ET). We aim to combine high frequency and non-destructive measurements of the stable isotopic compositions of soil and plant water as well as of ambient air humidity exemplary at selected experimental sites, i.e., one arable land, one grassland, and one coniferous forest in the temperate climate zone (part of the TERENO Rur catchment observatory, Germany), and one Mediterranean tree-grass system (MANIP experiment, Majadas del Tietar, Spain). These sites were chosen to cover the major plant functional types (PFT) represented in CLM5.0. The isotopic data will be used to parameterize the isotope-enabled soil-vegetation-atmosphere transfer model SiSPAT-Isotope for field-scale simulations of T/ET for different PFT and climatic conditions. The project will contribute to the CRC’s key objectives in that it will provide essential information for improving the PFT-specific parametrization of T/ET ratios implemented in CLM5.0.


Precipitation processes

PD. Dr. Silke Trömel
University of Bonn  |  +49-228-73779  |  [Email protection active, please enable JavaScript.]


Atmospheric models still do not adequately represent precipitation generating processes, which is partly responsible for their deficiency in reproducing observed regional trends in total water storage (TWS). We will quantify these deficiencies in the Integrated Monitoring System (IMS) by exploiting especially polarimetric radar observations with inherent information on precipitation generating processes aloft. The use of polarimetric microphysical retrievals and the evaluation of climate model runs in radar observation space enable us to compare the observed and simulated impact of greenhouse gas forcing and regional anthropogenic interventions on precipitation generation.


Representation of adaptation: the on-farm perspective

Prof. Dr. Silke Hüttel
University of Göttingen  |  +49 551 39-24846  |  [Email protection active, please enable JavaScript.]

Prof. Dr. Michael Leyer
University of Marburg  |  +49 6421 28-23382  |  [Email protection active, please enable JavaScript.]

Dr. Stefan Seifert
University of Göttingen  |  +49 551 39-24841  |  [Email protection active, please enable JavaScript.]


In A05, we aim at an improved representation of how farmers adapt to climate change, altering weather (extremes), production risk and efficiency, and ultimately expectations on farming returns. Yet to date, farms seem reluctant to adapt their farming structure. Based on the real options approach, we hypothesize that this reluctance can be explained by farms’ investment behaviour under risk and various sources of inefficiency. We test this hypothesis using observational data. To understand underlying cognitive decision processes under extreme hydrometeorological events, we test the impact of such perceived instances on farm adaptation decisions using an experimental approach.


Processes and determinants of climate-relevant landscape configurations

Prof. Dr. Jan Börner
University of Bonn  |  +49 228 73-3548  |  [Email protection active, please enable JavaScript.]

Prof. Dr. Thomas Heckelei
University of Bonn  |  +49 228 73-2331  |  [Email protection active, please enable JavaScript.]

Prof. Dr. Silke Hüttel
University of Göttingen  |  +49 551 39-24846  |  [Email protection active, please enable JavaScript.]


This project seeks to advance the understanding of the determinants of spatiotemporal dynamics in landscape configuration and composition, including crops, forests, and grasslands. Considering the broad range of theories of land system change, we explore relevance of and interaction between economic trends, agricultural market dynamics, infrastructure investments, and related risks and policies at various administrative scales. In close collaboration with natural sciences, we generate metrics of landscape dynamics and analyze related drivers and their interaction/interrelation using multivariate econometric methods combined with machine learning techniques.

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