Growing water scarcity is one of the central challenges for sustainability in China, given its burgeoning industry and huge population, especially in the arid and semi-arid inland river basin where precipitation is very limited. Industrial transformation is an important engine of economic growth, which is required to be implemented by governments at all levels in China. Economic models have generally been applied to evaluate the effects of economic policy change (e.g., industrial transformation or adjustment of price) on the allocation of production factors. The computable general equilibrium (CGE) model is an effective tool to reallocate the primary factors across sectors for different industrial transformation scenarios. In this research, we first briefly introduced the principles and structure of the CGE model, which embeds water resources as a primary factor of production. Then we chose Zhangye as an example to evaluate the impacts of industrial transformation on water consumption under three designed scenarios with the water-embedded CGE model. Simulation results showed that there will be considerable water saving benefit from industrial transformation when the output value of secondary industry and tertiary industry increases and the contribution of the planting sector to the total output value decreases. Finally, we put forward a scheme that can improve water utilization efficiency in policy options.

Ecosystem services are the benefit human populations derive directly and indirectly from the natural environment. They suffer from both the human intervention, like land use zoning change, and natural intervention, like the climate change. Under the background of climate change, regulation services of ecosystem could be strengthened under proper land use zoning policy to mitigate the climate change. In this paper, a case study was conducted in the middle reaches of the Heihe River Basin to assess the ecosystem services conservation zoning under the change of land use associated with climate variations. The research results show the spatial impact of land use zoning on ecosystem services in the study area which are significant reference for the spatial optimization of land use zoning in preserving the key ecosystem services to mitigate the climate change. The research contributes to the growing literature in finely characterizing the ecosystem services zones altered by land use change to alleviate the impact of climate change, as there is no such systematic ecosystem zoning method before.

Scenario analysis and dynamic prediction of land use structure which involve many driving factors are helpful to investigate the mechanism of land use changes and even to optimize land use allocation for sustainable development. In this study, land use structure changes during 1988–2010 in North China Plain were discerned and the effects of various natural and socioeconomic driving factors on land use structure changes were quantitatively analyzed based on an econometric model. The key drivers of land use structure changes in the model are county-level net returns of land resource. In this research, we modified the net returns of each land use type for three scenarios, including business as usual (BAU) scenario, rapid economic growth (REG) scenario, and coordinated environmental sustainability (CES) scenario. The simulation results showed that, under different scenarios, future land use structures were different due to the competition among various land use types. The land use structure changes in North China Plain in the 40-year future will experience a transfer from cultivated land to built-up area, an increase of forestry, and decrease of grassland. The research will provide some significant references for land use management and planning in the study area.

The land use simulation model is an important tool to analyze the land use/land cover change (LUCC), which plays a key role in influencing the global warming. However, there have been very few global LUCC simulation models, especially the models that can be used to analyze the interaction among the socioeconomic development, climate change, and LUCC. The Global Change Assessment Model (GCAM) and the GTAP-AEZ model are two models that take account of the influence of social economy and climate change at the global scale, but they may have some parameter errors due to the rough parameter setting. This study aims to compare the simulation results obtained with the GCAM model and GTAP-AEZ model and optimize their parameters according to the specific conditions of China. First, we simulated the land use structure in China in 2010 with the two models and compared the simulation results with the real one. Second, we calibrated these parameters of models according to the China’s national conditions and implemented the simulation again. The result indicates that the calibrated GCAM can provide more accurate simulation result of land use, which can provide significant reference information for the land use planning and policy formulation to mitigate the climate change in China.