Climate-induced drought has exerted obvious impacts on land systems in northern China.Although recent reports by the Intergovernmental Panel on Climate Change(IPCC) have suggested a high possibility of climate-induced drought in northern China,the potential impacts of such drying trends on land systems are still unclear.Land use models are powerful tools for assessing the impacts of future climate change.In this study,we first developed a land use scenario dynamic model(iLUSD) by integrating system dynamics and cellular automata.Then,we designed three drying trend scenarios(reversed drying trend,gradual drying trend,and acceleration of drying trend) for the next 25 years based on the IPCC emission scenarios and considering regional climatic predictions in northern China.Finally,the impacts of drying trend scenarios on the land system were simulated and compared.An accuracy assessment with historic data covering 2000 to 2005 indicated that the developed model is competent and reliable for understanding complex changes in the land use system.The results showed that water resources varied from 441.64 to 330.71 billion m3 among different drying trend scenarios,suggesting that future drying trends will have a significant influence on water resource and socioeconomic development.Under the pressures of climate change,water scarcity,and socioeconomic development,the ecotone(i.e.,transition zone between cropping area and nomadic area) in northern China will become increasingly vulnerable and hotspots for land-use change.Urban land and grassland would have the most prominent response to the drying trends.Urban land will expand around major metropolitan areas and the conflict between urban and cultivated land will become more severe.The results also show that previous ecological control measures adopted by the government in these areas will play an important role in rehabilitating the environment.In order to achieve a sustainable development in northern China,issues need to be addressed such as how to arrange land use struc
