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.

There is evidence that warming leads to greater evapotranspiration and surface drying, thus contributing to increasing intensity and duration of drought and implying that mitigation would reduce water stresses. However, understanding the overall impact of climate change mitigation on water resources requires accounting for the second part of the equation, i.e., the impact of mitigationinduced changes in water demands from human activities. By using integrated, high-resolution models of human and natural system processes to understand potential synergies and/or constraints within the climate-energy-water nexus, we show that in the United States, over the course of the 21st century and under one set of consistent socioeconomics, the reductions in water stress from slower rates of climate change resulting from emission mitigation are overwhelmed by the increased water stress from the emissions mitigation itself. The finding that the human dimension outpaces the benefits from mitigating climate change is contradictory to the general perception that climate change mitigation improves water conditions. This research shows the potential for unintended and negative consequences of climate change mitigation.climate change | mitigation | water deficit | Earth system model | integrated assessment E arlier work addressing the impact of emissions mitigation on water supply and demand has produced conflicting results (1-5). The reasons are complex. Earth system models (ESMs) and climate models are generally in agreement that a lack of climate change mitigation would lead to greater warming and intensification of the global water cycle (6), increasing precipitation intensity (7), changes in runoff that amplify the existing wet/dry patterns (8), and increasing flood risk (9) as well as aridity (10). However, changes in seasonal patterns and the increasing probability of extreme events may complicate the general patterns of wet/dry trends (11). Additionally, changes in water demands caused by socioeconomic drivers alone may surpass the effects of climate change on water availability (12). Several studies (1-5) have assessed the consequences of mitigation on some measure of water deficit. Each study used its own integrated assessment and global hydrologic models, generally with varying underlying socioeconomic and technological assumptions, climate inputs, measures of water deficit, and a wide range of spatial and temporal resolutions. A key distinction of the study presented here is its coupling of regional ESMs and human systems models using finer spatial and/or temporal resolutions than previous efforts.Extending the work of Hejazi et al. (4) and Voisin et al. (13), integrated regional models of human and natural systems with enhanced capabilities are used at high temporal and spatial resolution while maintaining consistency with regional and global climate and economic modeling. In this modeling framework, a regional integrated assessment model (IAM) simulates water demand for both irrigation and nonirrigation sectors (a resu...

Abstract. Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5∘) sectoral water withdrawal dataset for the period 1971–2010, which distinguishes six water use sectors, i.e., irrigation, domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971–2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. The reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.

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.

The Shared Socioeconomic Pathways (SSPs) were developed without explicit assumptions for the future of the water sector; therefore, projections of future water demands based on the SSPs often lack a treatment of water technology assumptions that is consistent with the SSP storylines. This study has developed a set of qualitative and quantitative assumptions for future water sector technological advancements in the agricultural, electricity, manufacturing, and municipal sectors within the SSPs and then applied the resulting scenarios to an integrated assessment model to permit analysis of future water demand in a water‐constrained world. These scenarios are then compared to another set that excludes the adoption of water‐efficient technologies. Water demand impacts of individual SSP assumption categories are analyzed to determine scenario‐by‐scenario changes. By 2100, global annual water demands range from 3,560 to 6,600 km3. The results show that (1) technological change in the water sector can act to reduce water demand in a water limited world by up to 32% in 2100 in the SSP scenarios, (2) the most sustainable scenario produces end‐of‐century water withdrawals lower than 2010 values, (3) low‐income regions will likely be one of the largest drivers of future water demands and exhibit the greatest sensitivity to highly‐efficient water technologies, and (4) nonwater sector SSP assumptions have significant and differing impacts on demands across SSP scenarios that act to alter global water demands.