Climate and Water

The Climate and Water section’s research is characterized by investigations on how existing cropping systems and peatlands can be transformed to meet the present challenges of climate change, environmental impact and loss of biodiversity. This work is done from micro-scale through field experiments to upscaling the impact of novel cropping systems and products from the agricultural land to understanding the underlying drivers supporting positive transformations.

Our data and statistics development and support create the foundation for modelling and upscaling efforts within and across the department. The section conducts modelling on multiple scales in relation to among other GHG, N leaching and pesticide losses. As such we aim at using mechanistic understanding, modelling, spatial variability and precision agriculture to optimize management of sustainable future cropping systems.

Through basic and applied research, we provide knowledge about

Novel use of crops and cropping systems for plant-based food and alternative use of biomasses for biorefining, building materials and energy
GHG, nitrogen and pesticide losses from cropping systems and rewetted lowland
Interactions driving productivity and emissions from plant to landscape scale
Meteorological and spatial data
Data-driven and process-based modelling at multiple scales of cropping systems under present and future climate scenarios
Management optimisation of agricultural systems

We carry out

Laboratory, greenhouse, and short and long-term field experiments
Plant trait investigations using mini-rhizotron tubes, multi/hyper-spectral cameras and scanning
Quantifications of GHG emissions and soil organic matter changes using automated chambers, eddy-co towers, analytical chemistry and isotopes
Analysis of aboveground plant and field status using remote sensing via drones and satelites (RGB, multi/hyper-spectral, thermal, LiDAR imageries) and Spatial analysis (GIS)
Analysis using field sensors belowground (TDR, DP sensors, suction cups, drain water and ground water wells)
Prediction and upscaling using machine learning, statistical and dynamic process-based modelling
Integration, management and analysis of environmental data across experiments, monitoring systems and landscapes using GIS and geospatial modelling
Development of digital systems and interactive platforms for spatial data collection, integration, visualization and advanced analytics
Database development and management, custom user interfaces, RESTful APIs, and integrated data solutions