Representing climate change in spatial land system models: an ensemble of climate and land system change models
Suggested elective courses (optional)
- Q4: Land cover change modeling
- Spatial analyses of ecosystem services: nature's benefits to people
About 75% of the Earth’s land surface has been altered and land use change has affected more than 30% of global land areas in the past six decades. Understanding the land cover and land use change hence is essential in developing mitigation strategies and interventions for societal challenges such as food security, climate change, and environmental degradation. However, on the other hand, climate change is a forceful driving factor for land use changes. For example, the temperature and precipitation change can determine the distribution of agricultural land and yield, the increasing frequency of climate extremes will significantly reduce crop yield in the future. Different climate projections also come with various degree of uncertainties. Yet there is considerable challenge for how climate change is represented and how associated uncertainty is counted when modelling land use changes.
The MSc will compare different ways to represent climate change and its impacts to land use simulation results. The MSc will utilize climate projections and identify the relevant climate variables for land use change, and process the climate variables in CLUMondo, a spatial-explicit land system optimization model. The MSc will use southern Europe[or another chosen site] as a case study accounting for the climate variability in the region. The project will employ an ensemble modeling approach, to quantify the uncertainty embedded in various ways of using climate data in land system modeling. The output can be used to provide more comprehensive and unbiased estimation of future changes.
Malek, Ž., & Verburg, P. H. (2021). Representing responses to climate change in spatial land system models. Land Degradation and Development, 32(17), 4954–4973. https://doi.org/10.1002/ldr.4083
Different ways to use climate change will bring variation in future land system projections. For agricultural intensification and urban expansion, how climate change data is used will affect spatial governance on optimizing water stress significantly.