Representing responses to climate change in spatial land system models

Research output: Contribution to JournalArticleAcademicpeer-review

14 Downloads (Pure)

Abstract

Modeling future change to land-use and land cover is done as part of many local and global scenario environmental assessments. Nevertheless, there are still considerable challenges related to simulating land-use responses to climate change. Mostly, climate change is considered by changing the temperature and precipitation, affecting the spatial distribution and productivity of future land-use and land cover as result of differential changes in growing conditions. Other climate change effects, such as changes in the water resources needed to support future cropland expansion and intensification are often neglected. In this study, we demonstrate how including different types of responses to climate change influences the simulation of future changes to land-use and land cover, and land management. We study the influence of including different climate change effects in land system modeling step by step. The results show that land system models need to include numerous simultaneous climate change effects, particularly when looking at adaptation options such as implementing irrigation. Otherwise, there is a risk of biased impact estimates leading either to under or overestimation of the consequences of land-use change, including land degradation. Spatial land system models therefore need to be developed accounting for a multitude of climate change impacts, uncertainties related to climate data, and an assessment of the sensitivity of the outcomes towards the decisions of modelers on representing climate change impacts.
Original languageEnglish
JournalLand Degradation & Development
DOIs
Publication statusE-pub ahead of print - 7 Sep 2021

Keywords

  • climate change
  • cropland intensification
  • irrigation
  • abandonment
  • water resources
  • spatial allocation

Fingerprint

Dive into the research topics of 'Representing responses to climate change in spatial land system models'. Together they form a unique fingerprint.

Cite this