Global future land use (LU) is an important input for Earth system models for projecting Earth system dynamics and is critical for many modeling studies on future global change. Here we generated a new global gridded LU dataset using the Global Change Analysis Model (GCAM) and a land use spatial downscaling model, named Demeter, under the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios. Compared to existing similar datasets, the presented dataset has a higher spatial resolution (0.05° × 0.05°) and spreads under a more comprehensive set of SSP-RCP scenarios (in total 15 scenarios), and considers uncertainties from the forcing climates. We compared our dataset with the Land Use Harmonization version 2 (LUH2) dataset and found our results are in general spatially consistent with LUH2. The presented dataset will be useful for global Earth system modeling studies, especially for the analysis of the impacts of land use and land cover change and socioeconomics, as well as the characterizing the uncertainties associated with these impacts.
Future changes in climate and socioeconomic systems will drive both the availability and use of water resources, leading to evolutions in scarcity. The contributions of both systems can be quantified individually to understand the impacts around the world, but also combined to explore how the coevolution of energy-water-land systems affects not only the driver behind water scarcity changes, but how human and climate systems interact in tandem to alter water scarcity. Here we investigate the relative contributions of climate and socioeconomic systems on water scarcity under the Shared Socioeconomic Pathways-Representative Concentration Pathways framework. While human systems dominate changes in water scarcity independent of socioeconomic or climate future, the sign of these changes depend particularly on the socioeconomic scenario. Under specific socioeconomic futures, human-driven water scarcity reductions occur in up to 44% of the global land area by the end of the century.
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