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This study analyzed the process of vegetation restoration in the eastern margin ecotone of Qinghai-Tibet Plateau (EMEQTP) from 2001 to 2019 under different restoration modes based on the vegetation net primary productivity (NPP) which was estimated by the Carnegie-Ames-Stanford approach (CASA) model. Then the potential NPP was calculated and the durations of NPP restoration were predicted based on the Autoregressive Integrated Moving Average (ARIMA) model. Finally, the relative importance of main parameters in the CASA model as well as global sensitivity and uncertainty were discussed. The results showed that the NPP under a natural restoration mode had the highest increase with 20.1%, and its spatial change showed an overall trend of restoration. The NPP under the comprehensive restoration mode achieved an increase of 11.5%, with the southwestern area experiencing an insignificant trend of degradation, whereas the northeastern area experiencing a significant restoration trend. As for the NPP under the artificial restoration mode, it experienced the lowest increase with 10.5%, and the northern part experiencing a significant restoration trend, whereas the southeastern part experiencing an insignificant degradation trend. In addition, the highest potential NPP of vegetation restoration would be appeared in the area under a comprehensive restoration mode. The area under an artificial restoration mode would have the lowest potential NPP of vegetation restoration, but the duration of restoration would be longest under this mode, reaching up to 64 years. Although the natural restoration mode achieved the best effect of vegetation restoration, considering the limited scope of the promotion of this mode, further attention should be placed on restoration measures and the effects of the artificial and comprehensive restoration modes. Finally, APAR, GST and PET were relatively important for the CASA model, and the parameters including Topt, GST, and PET were sensitive. Those results can offer scientific references for the management of ecological environment in the EMEQTP.

Guishui River Basin in northwestern Beijing has ecological significance and will be one of the venues of the upcoming Beijing Winter Olympic Games in 2022. However, accelerating climate change and human disturbance in recent decades has posed an increasing challenge to the sustainable use of water in the basin. This study simulated the runoff of the Guishui River Basin using the Soil and Water Assessment Tool (SWAT) model to reveal the spatio-temporal variations of runoff in the basin and the impacts of climate change and human activities on the runoff changes. The results showed that annual runoff from 2004 to 2018 was relatively small, with an uneven intra-annual runoff distribution. The seasonal trends in runoff showed a decreasing trend in spring and winter while an increasing trend in summer and autumn. There was a first increasing and then decreasing trend of average annual runoff depth from northwest to southeast in the study area. In addition, the contributions of climate change and human activities to changes in runoff of the Guishui River Basin were 60% and 40%, respectively, but with opposite effects. The results can contribute to the rational utilization of water resources in the Guishui River Basin.

This study applies the Dynamics of Land System (DLS) model to simulating the land cover under the designed scenarios and then analyzes the effects of land cover conversion on energy flux in the semiarid grassland area of China with the Weather Research and Forecasting (WRF) model. The results indicate that the grassland will show a steadily upgrowing trend under the coordinated environmental sustainability (CES) scenario. Compared to the CES scenario, the rate of increase in grassland cover is lower, while the rate of increase in urban land cover will be higher under the rapid economic growth (REG) scenario. Although the conversion from cropland to grassland will reduce the energy flux, the expansion of urban area and decreasing of forestry area will bring about more energy flux. As a whole, the energy flux of near surface will obviously not change under the CES scenario, and the climate therefore will not be possible to be influenced greatly by land cover change. The energy flux under the REG scenario is higher than that under the CES scenario. Those research conclusions can offer valuable information for the land use planning and climate change adaptation in the semiarid grassland area of China.

The land-use and land-cover change (LUCC) is the synthetic result of natural processes and human activities; it largely depends on the surface vegetation conditions, and the mutual conversion among land cover types can accelerate or alleviate the regional and global climate changes. Aiming at analyzing the regional climatic effects of the conversion from grassland to forestland, especially in the long term perspective, we carried out the comparison simulation using the Weather Research and Forecasting (WRF) Model in Fujian province, results indicated that this conversion had a significant influence on the regional climate; the annual average temperature decreased by 0.11°C and the annual average precipitation increased by 46 mm after 11.2% of the grassland was converted into the forestland in the study area from 2000 to 2008. In the future (form 2010 to 2050), the conversion from grassland to forestland is significant under two representative concentration pathways (RCPs) (RCP6 and RCP8.5); the spatial pattern of this conversion under the two scenarios is simulated by dynamic of land system (DLS); then, the regional climate effects of the conversion are simulated using WRF model.

Ecological risk assessment is of great significance to promoting the rational management effectively for the oil-polluted areas. A comprehensive evaluation method of ecological risk, including probabilistic risk assessment and regional ecological risk assessment, is developed through employing the contaminant benzo[a]pyrene as an indicator to assess ecological risk of five oil mining plots, respectively in Yellow River Delta. In this study, firstly we evaluate the ecological risk probability of five oil mining plots using overlapping area of probabilistic curves, and the results show that local ecological risk varies between the maximum 0.4 and the minimum 0.01. Then we overlay boundaries of five administrative divisions in Yellow River Delta and the spatial distribution patterns of ecosystems to generate new risk receptor plaques, and calculate the integrated value of 30 specifically classified plaques for comprehensive evaluation of ecological risk. The results, fluctuating within the range of 0.00005 and 0.25, indicate that local government should be vigilant to ecological risk of benzo[a]pyrene to some extent, although the current situation is not severe in whole.

With the economic development and population growth, humans have changed ecosystems more rapidly and extensively to meet the rapidly growing demand for food, fresh water, timber, fiber and fuel. This has led to a substantial and largely irreversible loss of the biodiversity on earth. The ecosystem risk is created as a new concept to understand the environmental problems. Therefore, it is important to develop quantitative methods for regional ecosystem risk analysis. Yellow River Delta is the widest, most intact and youngest delta both in China and in the world; its ecosystem environment is much more vulnerable due to its special location and industrial structure. Therefore, it is very important to manage them wisely and strategically. Therefore, Yellow River Delta is selected as the case area to reveal the impacts of economic development on ecosystem risk in this study. This study selected the ecological quality index to show the potential ecosystem risk and estimated the impacts of economic development on ecosystem risk using the panel data model on the pixel level based on the GIS, RS technique. It's found that the economic development will have impacts on the ecological environment to a certain degree, however, these impacts can exchange to a greater degree with the development. Then more funds and advanced technologies can be used to promote the intensive development of land use, which may decrease the impacts of economic development on the environment. Therefore, we need to ensure the coordinated development of the economy and ecological environment. The research results provide meaningful decision-making information for the urbanization process and environmental protection in the Yellow River Delta.

Near surface energy budget changes have been proved to be induced by the land cover conversion through changing the surface physical properties, which can further impact the regional climate change. This study applies the DLS model to simulate the land cover under the business as usual (BAU) scenario and then analyses the seasonal and interannual variation of energy balance in the semiarid grassland area of China based on the simulated land cover with the Weather Research and Forecasting (WRF) model. The results indicate that the grassland will show a growing trend under the BAU scenario. Downward long wave radiation and downward short wave radiation will all have small-scale increase with time going by, while the surface net radiation will decrease from 2030 to 2050. However, there is obvious seasonal variation. Summer has the highest downward long wave radiation and downward short wave radiation, followed by spring and autumn. The lowest are in winter. As for the net surface radiation, there is obvious decrease in southeast of study area due to returning cropland to grassland. Those research conclusions can offer valuable information for the land use planning and relieving the effects of land cover change on climate change at the semiarid grassland area.

The purpose of this paper is to illustrate a modelling framework to simulate large-scale land use changes, and its effect on the structural and functional diversity of the ecosystem and social-economy based on the remotely sensed digital images. The improved DLS model is developed with three scenarios in China from 2001 to 2020. The projection results show that obvious land use changes will take place in the forestry area, grassland, cultivated land and unused land. Dramatic changes will appear in Cultivated area in Northeast China, Huang-Huai-Hai plain and Southwest China. The changes of forestry area are characterized by regional diversification. Grassland decreases mainly along the Great Wall of Inner Mongolia and on Tibets Plateau. The newly expanded urban land, comparably smaller, distributes mainly around the old towns or residential centers. There is no obvious change in water area. The unused area shrinks with the expansion of forest and grass area in Western China. Based on this study, the capability of improved DLS modelling framework in projecting the LUCC scenarios was tested successfully, and a conclusion was made that DLS model is an useful model in scenario construction.