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Some essential water conservation areas in China have continuously suffered from various serious problems such as water pollution and water quality deterioration in recent decades and thus called for real-time water pollution monitoring system underwater resources management. On the basis of the remote sensing data and ground monitoring data, this study firstly constructed a more accurate retrieval model for total phosphorus (TP) concentration by comparing 12 machine learning algorithms, including support vector machine (SVM), artificial neural network (ANN), Bayesian ridge regression (BRR), lasso regression (Lasso), elastic net (EN), linear regression (LR), decision tree regressor (DTR), K neighbor regressor (KNR), random forest regressor (RFR), extra trees regressor (ETR), AdaBoost regressor (ABR) and gradient boosting regressor (GBR). Then, this study applied the constructed retrieval model to explore the spatial-temporal evolution of the Miyun Reservoir and finally assessed the water quality. The results showed that the model of TP concentration built by the ETR algorithm had the best accuracy, with the coefficient R2 reaching over 85% and the mean absolute error lower than 0.000433. The TP concentration in Miyun Reservoir was between 0.0380 and 0.1298 mg/L, and there was relatively significant spatial and temporal heterogeneity. It changed remarkably during the periods of the flood season, winter tillage, planting, and regreening, and it was lower in summer than in other seasons. Moreover, the TP in the southwest part of the reservoir was generally lower than in the northeast, as there was less human activities interference. According to the Environmental Quality Standard for the surface water environment, the water quality of Miyun Reservoir was overall safe, except only for an over-standard case occurrence in the spring and September. These conclusions can provide a significant scientific reference for water quality monitoring and management in Miyun Reservoir.

The increasing scale of urbanization and human activities has resulted in the fragmentation of natural habitats, leading to the reduction of ecological landscape connectivity and biodiversity. Taking Nanping as the study area, the core areas with good connectivity were extracted as ecological sources using a morphological spatial pattern analysis (MSPA) and landscape connectivity index. Then the ecosystem service functions of the ecological sources were evaluated based on the InVEST model. Finally, we extracted the potential ecological corridor based on the land type, elevation and ecosystem service functions. The results showed that the ecological source with higher landscape connectivity is distributed in the north and there are clear landscape connectivity faults in the northern and southern regions. Moreover, the areas with high habitat quality, soil retention and water production are mainly distributed in the northern ecological source areas. The 15 potential ecological corridors extracted were distributed unevenly. Among them, the important ecological corridors formed a triangle network, while the general ecological corridors were concentrated in the northwest. Therefore, it is suggested that the important core patches in the north be protected, and the effective connection between the north and south be improved. These results can provide a scientific basis for ecological construction and hierarchical management of the ecological networks.

In arid regions, land development and degradation (LDD) is sustained by the undesirable land development, human production and living, and climate change. Therefore, the understanding of LDD processes and their driving mechanism in the arid or semi-arid regions is significant to guarantee the sustainable development of ecological environment. This study explored the critical LDD processes in the Heihe River Basin (HRB) during 1990-2010 with the spatio-temporal evaluation of critical land use dynamics and its land quality changing trends. Then, the driving mechanism of cultivated land development process, grassland degradation process and water resource change process were analyzed by a simultaneous equations model which took the interaction of three processes into account. The results showed that the mutual transfers of cultivated land were primarily gathered in the middle reaches from 1990 to 2010. Its area grew by 13.5% and the average dynamic degree remained at 0.61%. The transfers between grassland and cultivated land, unused land were more remarkable, which led to the decline of grassland quality and even grassland degradation. Water area maintained a dynamic balance with almost unchanged area, but its dynamic trend was initially increasing and then decreasing. However, the average degradation of land quality in the whole study area is continuously alleviated. These changes were mainly due to the interaction of the LDD processes above, as well as socio-economic and climate change. Among them，agricultural research investments could restrain the unordered expansion of cultivated land resource for a relatively short period of time. Meanwhile, the variable of whether it is the main grain producing county is the main driver of grassland and water resource degradation in this region. These conclusions will provide scientific references for ecological land restoration and land quality improvement in the HRB.

Net primary productivity (NPP) lays the foundation for provision of various ecosystem services, and understanding the impacts of potential influencing factors on NPP is of great significance to formulating appropriate management measures to guarantee the sustainable provision of essential ecosystem services. This study analyzed the impacts of potential influencing factors on NPP in the lower Heihe River Basin, a typical arid and semi-arid region in China. First, NPP was estimated with the C-FIX model, and then the multilevel model was used to analyze the impacts of potential influencing factors on NPP during 2000-2008. Finally decomposition analysis was used to further analyze the contribution of influencing factors to NPP change during 2000-2008. The average NPP increased by approximately 9.07% during 2000-2008, and results of the multilevel model indicate that both the socioeconomic variables and demographic variables are useful in explaining NPP change. In particular, coefficients of rainfall and evapotranspiration which represent the water availability reached 0.0456 and 0.2956, respectively. Results of decomposition analysis suggested that the water availability played an important role in increasing NPP, with a contribution rate of 44.17%, and it is necessary to carry out some policies that can promote the water use efficiency to increase NPP under the background of climate change and intensified human activities. There are some uncertainties in the results of this study, but these results still can provide valuable reference information for the water resource management to increase the ecosystem service supply in the lower Heihe River Basin. (C) 2015 Elsevier Ltd. All rights reserved.

Land Use/Land Cover change (LUCC) is a key aspect of global environmental change, which has a significant impact on climate change. In the background of increasing global warming resulting from greenhouse effect, to understand the impact of land use change on climate change is necessary and meaningful. In this study, we choose China as the study area and explore the possible land use change trends based on the AgLU module and ERB module of global change assessment model (GCAM model and Global Change Assessment Model). We design three scenarios based on socioeconomic development and simulated the corresponding structure change of land use according to the three scenarios with different parameters. Then we simulate the different emission of CO2under different scenarios based on the simulation results of structure change of land use. At last, we choose the most suitable scenario that could control the emission of CO2best and obtain the relatively better land use structure change for adaption of climate change. Through this research we can provide a theoretical basis for the future land use planning to adapt to climate change.

Food safety and its related influencing factors in China are the hot research topics currently, and cultivated land conversion is one of the significant factors influencing food safety in China. Taking the North China Plain as the study area, this paper examines the changes of cultivated land area using satellite images, estimates land productivity from 1985 to 2005 using the model of Estimation System for Land Productivity (ESLP), and analyzes the impact of cultivated land conversion on the land production. Compared with the grain yield data from statistical yearbooks, the results indicate that ESLP model is an effective tool for estimating land productivity. Land productivity in the North China Plain showed a slight decreasing trend from 1985 to 2005, spatially, increased from the north to the south gradu- ally, and the net changes varied in different areas. Cultivated land area recorded a marginal decrease of 8.0 × 10 5 ha, mainly converted to other land uses. Cultivated land conversion had more significant negative impacts on land produc- tion than land productivity did. Land production decreased by about 6.48 × 10 6 t caused by cultivated land conversion between 1985 and 2005, accounting for 91.9% of the total land production reduction. Although the land productivity increased in Anhui and Jiangsu provinces, it can not offset the overall adverse effects caused by cultivated land con- version. Therefore, there are significant meanings to control the cultivated land conversion and improve the land pro- ductivity for ensuring the land production in the North China Plain.

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.

There is plenty of forests in Northeast China which contributes a lot to the conservation of water and land resources, produces timber products, and provides habitats for a huge number of wild animals and plants. With changes of socio-economic factors as well as the geophysical conditions, there are dramatic changes on the spatial patterns of forest area. In this sense, it is of great significance to shed light on the dynamics of forest area changes to find the underlining reasons for shaping the changing patterns of forest area in Northeast China. To explore the dynamics of forest area change in Northeast China, an econometric model is developed which is composed of three equations identifying forestry production, conversion from open forest to closed forest and conversion from other land uses to closed forest so as to explore the impacts on the forest area changes from demographic, social, economic, location and geophysical factors. On this basis, we employ the Dynamics of Land System (DLS) model to simulate land-use conversions between forest area and non-forest cover and the land-use conversions within the sub-classes of forest area for the period 2000-2020 under business as usual scenario, environmental protection scenario and economic growth scenario. The simulation results show that forest area will expand continuously and there exist various kinds of changing patterns for the sub-classes of forest area, for example, closed forest will expand continuously and open forest and shrub will decrease a little bit, while area of other forest will keep intact. The research results provide meaningful decision-making information for conserving and exploiting the forest resources and making out the planning for forestry production in the Northeast China region.

Based on field survey and statistical analysis, the immediate impacts of the Wenchuan Earthquake happened on May 12, 2008, are evaluated from two aspects, i.e., the influence on the prices and yields of grain and pork products in the local region and that on China. Wenchuan Earthquake, undoubtedly, has some negative effects on the local agricultural yields in Sichuan Province. It has caused immediate impacts on the grain and livestock breeding industry in the earthquake worst-hit counties. For example, due to the earthquake, the grain yields in Sichuan Province will decreased more than 0.4% and the pork productions decrease 5% at least. Thus, prices of grain and pork products are likely to rise in local mountainous areas over a short term. Our studying results that the disaster rate, the hazard rate and the complete loss rate of grain productions are 18%, 10% and 6% respectively in the earthquake worst-hit counties, while the disaster rate in the eastern plain areas even reach to 30%-49%. Even so, the results of model analysis for sample survey indicates that Wenchuan Earthquake has caused only marginal impacts on agricultural production, does not heavily hurt the stability of the prices and yields of grain and pork products at the national level. In other words,Wenchuan Earthquake had not affected the overall situation of national agricultural production. It is estimated that the reduction rate of national grain yield is as low as 0.006%, and the price changes of grain and pork products are no more than 0.5% and 2.2% respectively.

This chapter focuses on the climate effect of ecological restoration programs in China. The fourth assessment report of Intergovernmental Panel on Climate Change (IPCC AR4) indicated that the human activities are a significant influencing factor of climate change. Deforestation, grassland degradation, and desertification, which are mainly induced by human activities, have been greatly intensified due to the irrational exploitation of the natural resources, rapid population growth, and the expansion of road network in the past decades. Some ecological restoration programs have been recently carried out, e.g., Green for Grain Project, which can affect the climate through not only the carbon sink but also the thermal properties of the land surface.

In climate modeling, land use data is applied as underlying surfaces and definitively determines the simulation results of regional climate. Researches show that Land Use and Cover Change (LUCC) not only affects the terrestrial ecosystem biodiversity, energy balance, water cycle, but also exerts influence on climate and social economy (Berg et al. 2010; Liu and Diamond 2005). Besides, LUCC is a significant performance of material and energy interactions between human and global environment.

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.