There exists an extremely complex dynamic coupling relationship between urbanization and eco-environment, which indicates that urbanization has a strong coercing effect on eco-environment, and eco-environment has a lagged constraint force on urbanization. How to realize the coordinated development of urbanization and eco-environment has become a hot topic in recent years at home and aboard. This paper establishes the comprehensive evaluation index system on urbanization and eco-environment evaluation system, based on the data of nine provinces and two cities of the Yangtze river economic belt from 2000 to 2017. The results show that in terms of time series, the coordination between urbanization and ecological environment in the Yangtze river economic belt has been on a steady rise from 2000 to 2017, and the whole area is in a good coupling and coordination stage. At the beginning of the study, the comprehensive index of ecological environment was higher than the comprehensive index of urbanization. At the end of the study, the comprehensive index of urbanization was higher than the comprehensive index of ecological environment. In the spatial pattern, the coordinated development trend of the two has the spatial difference characteristic of decreasing from the eastern region to the central and western regions. There is an interactive stress relationship between urbanization and ecological environment in the Yangtze river economic belt. The spatial distribution of the dynamic coupling relationship between urbanization and ecological environment exists in all provinces and cities in the Yangtze river economic belt region. The urbanization level is higher in economically developed areas, while the ecological environment in economically less developed areas is at greater risk of deterioration.

The human-land linking system is an important innovation to promote the optimized allocation of labor force and land distribution between urban and rural areas, and plays an important role in solving the imbalance between population urbanization and land urbanization. Started from the analysis of the relationship between population urbanization and land urbanization under the framework of China’s special system and mechanism, this study constructed an index system based on the human-land linking urbanization coordinated development model, used the elastic coefficient method and gravity movement model to analyze the coordination of population urbanization and land urbanization in the upper stream of the Yangtze River Economic Zone from 2009 to 2016. The results showed that (1) in the study area population urbanization and land urbanization have achieved remarkable results, and the spatial clustering characteristics have been gradually manifested; (2)the western region had a faster development in population urbanization, while the eastern was opposite, urban agglomeration in central Guizhou is the hot spot of population urbanization and land urbanization, but land urbanization developed faster, which showed a trend of unbalanced urbanization development; (3)population urbanization and land urbanization were basically in a state of coordinated development, and the coordination has significantly improved. Therefore, in order to achieve coordinated development of population urbanization and land urbanization, the western should promote population urbanization in an orderly manner and strictly control land urbanization, meanwhile, the eastern, especially urban agglomeration in central Guizhou, should put an end to the ‘large-scale development’, raise the level of population urbanization by developing the industrial and promoting the urban charm.

The rapid development of high-speed rail has significantly improved intercity accessibility and connectivity, which has influenced spatial resource reallocations and changed regional economic development patterns. Taking 40 prefecture-level or above cities in the Yangtze River Delta (YRD) region as a case study, this paper employs urban strength index and intercity connection strength and compares the values before and after the operation of high-speed railway (2009 and 2018) to reveal the accessibility and connectivity changes in the YRD. It further analyzes the influences on economic development over the past decade by use of an improved production function model. The results show that: (1) The rapid high-speed rail development reduced the average shortest time accessibility of cities in the YRD by 0.257 h per year, and nearly doubled the network connectivity in the past decade, leading to much higher intercity accessibility and connectivity. (2) There were obvious regional differences across cities in the improvement of urban strength index and intercity connection strength in the past decade. The spatial accessibility for cities located in the peripheral YRD had higher increase, while the spatial connectivity for cities with higher level of development had the higher improvement. Central cities functioned as transport hubs had been enhanced from the development of HSR network, which created a significant Matthew effect of accumulated advantage. (3) The pattern of urban strength index was uneven distributed and the disparity had been increased significantly, which was mainly resulted from some transport hub cities’ much higher increase in urban strength values. (4) The evolution of high-speed rail network significantly influenced regional economic development pattern, particularly the tertiary industries, which led to a more polarized distribution of economic development in the YRD. This study offers some evidence to support high-speed rail-oriented development, regional planning and regional economic integration policies-making in the context of high-speed rail expansion in regional China.

Rapid urban expansion is accompanied by a series of ecological problems while improving the level of social economy. How to reasonably coordinated the contradiction between urban expansion and ecological protection is an important task in China’s new urbanization construction. Scientifically identifying the conflict between urban expansion and ecological protection is the basis.In this paper, the Poyang Lake Ecological Economic Zone is used as a research area, and the spatial Bayesian method is used to identify potential compatible areas and conflict zones for urban expansion and ecological protection.The results show that: (1) the distribution of urban expansion suitability is relatively concentrated, the most suitable areas are mainly distributed in the surrounding counties of the main urban area, Yujiang County and Leping City, the suitable areas are mainly distributed in Xinjian District, Ruichang City, Gao’an City and Duchang County, the area is mainly distributed in Wuning County and the east bank of Poyang Lake, the unsuitable areas are mainly distributed in Shuyang County, Fuliang County and Wuning County; (2) the distribution of ecological protection suitability is relatively scattered, the most suitable areas are mainly distributed in Wuning County, Ruichang City, Shuyang County and Fuliang County, the suitable areas are mainly distributed in the northeast, southeast, Yujiang and Hukou counties of the main city, the main distribution of the less suitable areas is more scattered, and the districts (cities) and counties are distributed, the unsuitable areas are mainly distributed in the surrounding areas of Nanchang and the east bank of Poyang Lake; (3) the comprehensive analysis of urban expansion and ecological protection suitability evaluation results are mainly distributed in Ruichang City, Nanchang County and Xinjian District; the areas with high development suitability in the compatible areas are mainly distributed in the southeast of Nanchang City and Yongxiu County, Xingzi County and Yujiang County, the areas with high ecological protection suitability are mainly distributed in the east bank of Wuyang Lake and Wuning County; the areas with low urban expansion and ecological protection suitability are mainly distributed in Shuyang County, Yugan County and Duchang County.The research results could serve as a support for land use planning and ecological security protection.

The space-time characteristics of urban expansion and its driving factors help understand the laws of urbanization and provide a scheme for the formulation of urban spatial planning with regional characteristics. This study was a case of Nanchang City, where Multi-source data from Landsat (in 2000, 2008 and 2017) were used to obtain the space-time information of urban expansion and were analyzed using the expansion intensity index, landscape expansion index and center of gravity index. The influencing factors were then analyzed using the boosted regression tree model (BRT). The results show that：(1) From 2000-2017, the urban expansion area in Nanchang increased by 252.81 km². The intensity and speed of growth was comparatively greater during the first phase (2000-2008) than the second phase（2008-2017）. (2) In both the phases, the urban expansion pattern was dominated by edge expansion, some of them supplemented by infilling and outlying expansion, which was random and less intensive. (3) In the period of 2000-2017, the center of the city moved 2.19 km to the southwest. The shift in the first phase was 1.5 km west and 1.35 km southwest in the second phase. (4) Among the 16 directions, SW and SWW had comparatively larger urban expansion with NW, N, NNE, SE, and SSE directions expanding much smaller due to the natural barriers of the Meiling Mountains and the Junshan lakes. (5) BRT analysis of the neighborhood factors (distance from the city in 2000, rivers and road network), social factors (land use type, GDP and urban population) and natural factors (elevation, slope and aspect) showed that the urban expansion of Nanchang City has been mainly affected by the neighborhood factors. And among the social factors, only land-use types have a greater impact on urban expansion, while the influence of natural factors is relatively weak.
Key words：urban expansion; boosted regression tree; driving factor; Nanchang city

Population is an important social and economic resource, and the aging population is gradually becoming an unavoidable problem in the sustainable development of Guizhou’s economy and society. Studying the differences of ageing population in different counties across Guizhou province can provide a scientific reference for the solution of aging problems and the rational formulation of population policies. The age coefficient of Guizhou county during 1990-2010 was selected as the indicator of population aging. The method that we selected to explore the characteristics of population aging and environmental causes were The spatial auto-correlation and hot-spot analysis, geographical weighted regression and partial least squares method. The article draws the following conclusions: (1) During 1990-2010，the age coefficient of the county in Guizhou province generally decreased from northeast to southwest. After 2000, the internal organization of the space was obvious. The change of Guizhou’s ageing coefficient is roughly divided by Guiyang, the east old age coefficient increases rapidly, and the west slowly. (2) The spatial agglomeration of the elderly population in Guizhou province has been continuously enhanced，and the differences between regions have gradually expanded. The age coefficient of low-low area is significant growing, and there is obvious diffusion and transfer of cold hot-spot space.(3) There are spatial differences in the effects of environmental causes on population ageing. Precipitation in general is the main natural factor that promotes the gathering of the elderly population. Degree of terrain and temperature have negative effects on population aging. The influence of the improvement of rock desertification on population aging is becoming more and more stronger.

Urban spatial expansion is the most significant feature of urbanization in space. It can not only measure the level of urbanization in cities, but also guide the sustainable development of cities. This paper takes Chengdu-Chongqing urban agglomeration (CCUA) as the study area, based on the nighttime lighting data, first of all, it analyzes the urban spatial expansion of CCUA and the distribution characteristics of urban hotspots. Secondly, based on the ecological space constraints of the CCUA, the minimum cumulative resistance surface was constructed, and the evolution trend of the urban hotspot pattern of CCUA was simulated. The main conclusions are as follows: (1) The cold-hot spots of urban expansion in CCUA reflect different characteristics in different periods. In the four time periods, CCUA urban expansion shows a weak trend of spatial natural correlation, and the global features of the distribution of cold-hot spots became randomized. Reflecting the diversity of urban space expansion, the cold-hot areas of the city spread pattern experienced a “spot expansion-point ring expansion-point axis expansion-axis radiation” transformation process.(2) In the different scales simulation of urban expansion, the evolution trend of cold-hot spots in CCUA is the hot spot area becoming increasing. When the urban space expands by 5%, there are only four hot-spot cities based in Chengdu, Mianyang, Dazhou, and Meishan. When the urban space expands by 20%, all cities (16 in total) have a spatial expansion intensity exceeding 10%, and has become hot spots for urban space expansion.

In order to clarify the composition of bacterioplankton communities and the environmental factors involved, we collected samples of bacterioplankton and monitored some main environmental indexes in February 2018 and July 2018 respectively in the Daye Lake. Basing on 16S rRNA high-throughput sequencing, we analyzed and compared the differences in composition and diversity of bacterial communities in the Daye Lake during the dry season and the wet season. We conducted the redundancy analysis (RDA) to explore the relationship between environment factors and composition and diversity of bacterial communities in the water. The results showed that the bacterioplankton had high microbial diversity in the Daye Lake. The Shannon indexes of dry season and wet season were 3.856±0.642 and 4.165±0.608, respectively. The main bacterial categories were Proteobacteria, Actinobacteria, Cyanobacteria, Bacteroidetes, Firmicutes, Planctomycetes, Verrucomicrobia, Chlorobi and Chloroflexi. In this case, the dominant bacteria was Betaproteobacteria (44.73%) in dry season. In wet season, however, the dominant bacteria were Cyanobacteria (31.39%) and Actinobacteria (31.37%). Redundancy analysis showed that nitrate (NO^-₃-N), temperature (T) and total nitrogen (TN) were the main environmental factors affecting the distribution of bacterial communities.

Considering the dynamic change of lake and land area, and the fact that land-use change has become the second largest greenhouse gas emission source after fossil energy combustion, this paper originally analyze the changes of the area of lake in a specific region and its indirect carbon effects. Based on the data obtained from remote sensing images in 2005, 2010 and 2015, the carbon emissions and carbon intensity changes from lake to four types of land in Wuhan city were assessed by the recognized model measuring carbon emission. The results show that: (1) From 2005 to 2015, the lake area in Wuhan decreased by more than 10  km2, and this trend accelerated after 2010. the reduction in 2010-2015 was about 2.04 times that in 2005-2010；(2)Although the conversion of some cultivated land, woodland and grassland into lakes leads to an increase in lake waters, the conversion of large areas of lakes into construction land directly results in significantly less water area;；(3)From the perspective of total carbon emission, the water conversion area was carbon source, and the carbon emission in the last five years was 1.46 times of that in the first five years. The carbon emission intensity was 0.03 t/km² from 2005-2010 and 0.04 t/km² from 2010-2015. The carbon emission intensity has increased obviously. In view of the situation of lake use in Wuhan, measures are put forward, such as “putting landscape, forestry, fields, lakes and grasses” into a unified management mechanism, standardizing the utilization of land resources, and restricting the excessive expansion of construction land.

In order to know the annual dynamics and migration characteristics of fish resources in the channel connecting Dongting Lake and the Yangtze River, A monthly surveys were conducted for larval, juvenile and adult fishes in the channel connecting Dongting Lake and the Yangtze River from May 2017 to June 2018. Larvae fishes were belonging to 19 species and 5 families. Hemiculter leucisculus (Basilewsky) accounted for 76.6% of the total, Rhinogobius giurinus (Rutter) accounted for 8,8% of the total, Pseudobrama simoni (Bleeker) accounted for 4.3% of the total. Larva appeared mainly in Apr to Sep, and the density was highest in June (848.8 Ind./1 000 m3). Also juvenile and adult fishes were belonging to 42 species and 9 families. Coilia brachygnathus (Kreyenberg et Pappenheim) accounted for 30.3% of the total, Hemiculter bleekeri (Warpachowsky) accounted for 15.3% of the total, and Hemiculter leucisculus (Basilewsky) accounted for 12.2% of the total. The abundance of juvenile and adult fishes was 729 each day also was the highest in Aug. The results showed that the abundance of larvae, juvenile and adult fishes showed strongly seasonal variation, both of them were higher in summer and lower in winter. From April to July, the movement index of the river-lake migratory fishes was between 0.1 and 0.7, showing a tendency of entering the lake. From August to march, the movement index was between -0.4and -0.1, showing a tendency of entering the river. The results also showed that juvenile and adult fish migrated mainly at night. And discharge were the main driving factors of fish.

Vegetation plays an important role in land use and land cover. Vegetation classification has a great reference value for watershed ecology research. Jianghe river basin in western Hubei is an important water source for the Middle Route of the South-to-North Water Transfer Project. Because of its large altitude range, complicated terrain, a large number of complex shadows exist in remote sensing images. It is difficult to classify the vegetation types in the shadow. This paper constructed a stratified analysis for vegetation classification. The stratified classification is a method based on the idea of division of layers step by step and different criteria and methods in each layer. The criteria included the vegetation indices, water index and shadow index, which were calculated from Landsat OLI image of 2017 and DEM.The vegetation indices included NDVI (Normalized Difference Vegetation Index) and RVI (Ratio Vegetation Index).The study selected Modified Normalized Difference Water Index (NMDWI) to indicate water. The topographic shadow was calculated from the hill-shade module based on ArcGIS. The input parameters of hill-shade model consisted of solar azimuth angle, solar zenith angle and ASTER GDEM. The results showed that: (1)Using the intelligent decision tree algorithm, the overall accuracy of the classification reached 92.93%, with a Kappa coefficient of 0.912; (2) For the same vegetation, there were higher NDVI and RVI in exposed halves of hills than that in shaded halves. It was consistent with the phenomenon of same object with different spectra. The value of RVI from high to low was: deciduous shrub, thedeciduous shrub and evergreen coniferous mixed forest and evergreen coniferous forest. (3) Because of different solar azimuth angle and solar zenith angle changing the distribution of shadow, each remote sensing image had a certain shadow shape. The accuracy of vegetation classification is largely reduced. Overall, this vegetation classification method combined the decision tree and hill-shade model to categorize the Jianghe river basin into six classes. As an intelligent decision tree classification algorithm, the method has the advantages of identifying vegetation categories in shaded halves and is of high application value, especially in low mountains and hills. There is still space to improve the classification accuracy, i.e., an optimized vegetation index, the increasing of vegetation samples in high altitude and large slope regions, and the use of higher spatial and temporal resolution images.

Litchi fruit from a typical subtropical evergreen fruit tree, is known as the "king of fruits" and plays important roles in the fruit market at home and abroad. To provide a scientific basis for L. chinens’ expand production its potential planting area was simulated in China by using MaxEnt model under the current conditions based on 132 known coordinates and 22 environmental factors, and then the main influencing factors and threshold were also detected. The accuracy of Maxent model is excellent in predicting its potential planting area, with an AUC value of 0.986 and 0.976 for model training and testing. The main influencing factors were precipitation of driest quarter, annual mean temperature, min temperature of coldest month, temperature seasonality and mean temperature of warmest quarter with thresholds of 60-110 mm、21-24℃、7.5-14℃、31-37℃ and 28-30℃ respectively. The most suitable distribution area for L. chinens was in southeast Sichuan, southwest Chongqing, central and southern Guangxi, coastal areas of Guangdong and Fujian, northern Hainan, northwestern Taiwan, northwestern and southwestern Guizhou, etc. The medium area is the outward expansion of these high distribution areas. Meanwhile, medium distribution area is also found in the south-central region of Yunnan, the Linzhi region of Tibet near the Indian and the scattered areas of Hubei, Hunan, Jiangxi and Anhui Provinces. The suitable areas of different Provinces are as follows: Guangxi > Guangdong > Chongqing > Sichuan > Fujian > Hainan > Taiwan > Yunnan > Guizhou. The moderate suitable areas were Yunnan > Guangxi > Sichuan > Guangdong > Guizhou > Fujian > Chongqing > Hainan > Taiwan. The above information reflects the potential geographical distribution of L. chinens in China. Besides the traditional areas of Guangxi, Sichuan, Guangdong, Fujian, Hainan, Taiwan and Yunnan, suitable and moderate suitable areas such as Guizhou and Chongqing are also expanding planting areas.

Co-farming technology of rice and crayfish could contribute to good economic, ecological and social effects. whereas farmers’ adoption confronted with multiple constraints because of inadequate sources of effective technology diffusion and high technical risk and economic risk. Based on a field survey dataset of farmers in Hubei Province and Jiangsu Province, this paper analyzes the influence of neighborhood effect and agricultural technology diffusion on farmers’ adoption of co-farming technology of rice and crayfish. After that, we analyzes the complementary and substitution effect of neighbourhood effect and agricultural technology diffusion on farmers’ adoption of co-farming technnology of rice and crayfish. The main findings are as follows: 1）Neighbourhood observation learning and communicating experience are both significantly positive to promote farmers’ adoption of co-farming technnology of rice and crayfish. 2)The diffusion of agricultural technology in agricultural enterprises has a significant positive impact on farmers’ adoption of co-farming technnology of rice and crayfish. 3)About the influence on the adoption of co-farming technnology of rice and crayfish in farmers, there are some substitution effects of Neighbourhood observational learning and agricultural technology diffusion, and so does the social norms; Some substitution and complementary effect of communicating experience and agricultural technology diffusion; Based on the above conclusions, this paper puts forward some policy suggestions to improve the operation efficiency and practical influence of each agricultural technology diffusion agent by combining the complementary and substitution effects of neighborhood effect, so as to improve the normality and efficiency of farmers’ adoption behaviors.

Land resources are the material basis for human survival and development, but the extensive land management mode brings a series of serious challenges: land resources are limited, non-point source pollution aggravated, the quality of agricultural land deteriorated, agricultural carbon emissions increased sharply, agricultural land conversion, etc. This development model at the expense of resources and environment has seriously restricted the sustainable development of agricultural economy. It is of great theoretical and practical significance to scientifically analyze the spatial-temporal differences and impact mechanism of agricultural land ecological efficiency for realizing the coordinated development of agricultural land use, resources and environment, and formulating sustainable agricultural development policies. In this paper, Jiangxi Province was taken as a typical case study area. First, inventory analysis and carbon emission coefficient method were used to calculate the pollution and carbon emissions of agricultural surface sources，and then it was incorporated into the SBM-Undesirable model of undesirable output. Secondly, the ecological efficiency of agricultural land was quantitatively measured and the spatial-temporal pattern of the study area was revealed in Jiangxi Province and its districts and cities from 1990 to 2017. Finally, it used the Tobit regression model to discuss the influence mechanism of relevant factors. The results showed that: (1) From 1990 to 2016, the ecological efficiency of agricultural land in Jiangxi Province showed a “first decreased and then increased” trend, with an average value of 0.749, showing an overall upward trend;(2) The spatial pattern of eco-efficiency of agricultural land in Jiangxi Province was characterized by a flat “V” feature that decreased first and then increased. The high efficiency regions changed from “serial” distribution to “spot” distribution and then to “serial” distribution, and the spatial pattern tended to be unbalanced; (3) The per capita disposable income of rural residents, multiple cropping index, cultural proportion of rural labor force above senior high school and per capita sowing area had significant positive effects on the ecological efficiency of agricultural land in Jiangxi Province, while the income gap between urban and rural areas had significant negative effects. Finally, the paper putting forward some suggestions to improve the ecological efficiency of agricultural land from the aspects of optimizing the allocation of resources, strengthening the innovation and application of agricultural science and technology, perfecting the rural land circulation system, abandoning the extensive development model of excessive dependence on resources and factors input and environmental pollution, taking the “intensive cultivation” and sustainable development of agricultural ecological civilization. Meanwhile, there are still some somewhat limitations in this study: (1) In the aspect of unexpected output, the loss of agricultural land ecological efficiency caused by unexpected output, such as rural domestic sewage or rural industrial wastewater discharge pollution, has not been considered; （2) The differences of initial land quality and soil fertility among different regions have not been included in the evaluation system of agricultural land ecological efficiency; （3) In the analysis of impact mechanism, the micro-factors such as farmers’ willingness to adopt agricultural science and technology, pollution prevention and control are not included in the analysis. The spatial and temporal differences of agricultural land ecological efficiency and its influencing mechanism are the result of many factors, which provide an important direction for further research in the future.

Jianghan Plain is an important commodity grain base in China, the acquisition of high-precision rice planting area is of great significance to the country’s agricultural development and planning. However, there are many cloud and rain weathers in southern China affected by climate, and the optical remote sensing images are seriously missing. At the same time, due to the satellite revisiting cycle, the available data is less, which affects the accuracy of rice planting area extraction. Obtaining high spatial-temporal resolution remote sensing images is the key to extracting rice growing areas in southern China. In order to solve the problem of high spatial-temporal resolution image loss, the fusion of Landsat 8 OLI and MODIS data based on Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) is used to obtain Landsat Normalized Difference Vegetation Index(NDVI) time series data with high spatial and temporal resolution. The ESTARFM model could improves the accuracy of heterogeneous landscape extraction for more heterogeneous and fragmented areas with high precision. In the existing crop area information extraction research, the classification relies on a single NDVI data, and the phenological feature information in the process of crop growth has not been fully utilized in the remote sensing classification structure. In this article, we use time NDVI series data to analyze the phenological characteristics of rice and combining key phenological parameters, so that a variety of machine learning methods could be used to extract rice planting areas, in this article, machine learning classification methods including Support Vector Machine(SVM), random forest and neural network were used to extract rice planting area and evaluate which method works best. The results show that this method can extract the rice planting area in the study area well, and the SVM method has the best classification effect. In the meanwhile, the overall classification accuracy of rice planting area extraction is 93.31%, and the Kappa coefficient is 0.920 2. This study provides an effective technical means for the extraction of rice planting area in the southern region, and providing technical support for regional land use planning and food policy.

The construction of high-standard basic farmland is an important grasp to consolidate the agricultural foundation and ensure national food security. Taking Nan’an District of Chongqing as the research object, this paper selects 12 indicators from three aspects of basic geo-power, utilization conditions and location conditions, constructs a comprehensive evaluation system of high-standard basic farmland construction, introduces the method of entropy weight and obstacle degree model to measure the construction potential and difficulty coefficient of each evaluation unit, and finally uses the administrative village as the evaluation unit to couple the two evaluation results, and puts forward the Nan’an District High standard time sequence of basic farmland construction. The results showed that the area of cultivated land with high standard basic farmland conditions in Nan’an area was about 76.6 hm², accounting for 11% of the total permanent basic farmland. The remaining 624.19 hm² cultivated land could be gradually built into high standard basic farmland through land renovation. Spatially, the regions with high construction potential are mainly concentrated in Guangyang Town in the northeast of China, and the construction difficulty level shows the distribution law of “high in the South and low in the north”. According to the construction principle of “easy in the first place” and “difficult in the second place”, the construction time sequence also needs to follow the rule of “from north to south” to carry out the renovation project in turn. The research results can provide reference for the implementation of high standard basic farmland planning in Nan’an area.

In order to explore the environmental magnetic properties and their spatial distribution in “urban-to-rural”, this study choose Xuhui, Minhang and Fengxian districts in Shanghai to systematic magnetic analysis. The results show that the soil magnetic enhancement is obvious and is caused by human activities. Soil magnetic properties are mainly controlled by ferrimagnetic minerals with low coercivity and soft magnetic properties. Magnetic mineral particles are relatively coarser, mainly multi-domain (MD) and stable single domain (SSD). χlf, SIRM, χarm, and HIRM showed the similar spatial variation characteristics, the high value area is located in the north of Xuhui District, southeast and southwest of Minhang District, and north and south of Fengxian District. The magnetically enhanced high value points are located in the industrial area. The distribution of the magnetic susceptibility is basically consistent with the layout of the enterprise, and the pollution-type enterprises are used as the source to spread the pollution.

The land-water ecotone is under the influence by the combinatory of natural and human factors, and the adaptability development of its landscape system urgently needs scientific and rational assessment tool. This paper explored the holistic adaptation assessment method of the land-water ecotone in southern Chongming island, based on the landscape physical characteristics analysis from baseline evaluation, and the characteristic zoning from the Landscape Character Assessment tool (LCA). The study formed the adaptation assessment system from three sub-target levels: the importance status of natural resources protection, the suitable situation of land resources utilization and the significant characteristics of environmental security pressures. The assessment system was constructed by 12 selecting indicators, and the adaptation assessment analysis at the factors level and target level was carried out. Six type of adaptation zonings were formed and the promotion strategies for the holistic adaptation of landscape resources were put forward. The research provides the evaluation method and decision support path for the integrated development of land-water Ecotone Landscape system.

In recent years, the sewage emission in China has increased gradually and the water pollution incident happened frequently, causing serious damage to the ecological environment and residents’ health. To reverse the situation, governments at different levels have introduced various environmental protection policies. We collected weekly provincial panel data from 2013 to 2016, and three water pollution indicators including permanganate (COD_Mn), dissolved oxygen (DO) and ammonia nitrogen (NH₃) are selected. Then, differential treatment charge policy about the sewage water in Jiangsu Province were evaluated basing on the synthetic control method(SCM), and a comprehensive indicator was constructed using the entropy weight method to evaluate the comprehensive policy effect. The main findings are: the policy has obviously improved the overall surface water quality; dissolved oxygen (DO) indicator has been improved, indicating that the self-purification ability of the surface water has been improved; however, it made eutrophication increasingly serious which was measured by permanganate(COD_Mn) and ammonia nitrogen (NH₃)indicator owing to supervising difficulty. For achieving effective regulation, policy decision and its dynamic adjustment must comply with constraints of “Incentive Compatibility”.

A typical case with chlorobenzene contamination in a chemical factory relocation site in Shaoxing city Zhejiang Province, was selected, and some nested well groups (1~5, 5~9 and 10~14m) was set up to investigate the concentration of chlorobenzene in groundwater in three-dimensional space.On the basis of statistical analysis of the survey results, the 3D spatial interpolation calculation of chlorobenzene concentration in groundwater was performed by ordinary Kriging interpolation method (OK), inverse distance weight interpolation method (IDW), improved inverse distance weight interpolation method (IDWN) and nearest neighbor interpolation method (NN), respectively. The optimal interpolation method was selected to study the three-dimensional spatial distribution of chlorobenzene, after the comparison of the prediction accuracy of different interpolation models and parameters, and the comparison of the amount of groundwater above certain management target value and the concentration characteristics of chlorobenzene obtained by different calculation methods. The results showed that the spatial distribution of chlorobenzene content in groundwater varied greatly at different depths, and that the concentration of chlorobenzene in groundwater decreased gradually with the increase of depth. The maximum detection concentration was 8050 μg/L, and that the average concentrations were 484.45 μg/L, 230.43 μg/L and 23.08 μg/L, at three different depths. The results also showed that there existed a certain positive global spatial autocorrelation relationship in the concentration of chlorobenzene in groundwater, and the accuracy of IDWN prediction was the higher than other methods, and the interpolation accuracy was the highest when the vertical anisotropy ratio coefficient was 3 and the weight function was 6. The amount of contaminated groundwater above the third level of groundwater quality standard in china and the average concentration of chlorobenzene were suitable, estimated by this interpolation method, which can better reflected the spatial distribution characteristics of pollutants.

Using mean daily discharge data from 1980 to 2015, effects of the Three Gorges Dam on hydrological situation of the Three Outlets were measured based on indicators of hydrologic alteration. Except for a slight increase in Xinjiangkou station and Mituoshi station from January to March, mean monthly flow showed a significant downward trend in the five hydrological stations of Three Outlets, and decreased more in flood season. The maximum daily flow showed an significant downward trend for all hydrological stations in the past decades, but the trend was relatively stable after 2003. Number of days for Shadaoguan station and Guanjiapu station draught-up increased significantly, and the rate of flow change was obviously reduced for all hydrological stations. Hydrologic regime change for the Three Outlets was influenced by its own channel evolution, runoff reduction and runoff process change of the Yangtze River, had some negative effects on the Four Major Chinese Carp populations and the Carex meadow development of Dongting Lake.

Soil pH value is the major property influencing the cultivated land quality. It is important to measure and to understand the spatial distribution of soil pH value. In this research, Shiyan city was chosen as an example in the mountainous area of northwest Hubei province and a total of 701 soil samples of cultivated land were collected in Shiyan city for measurement of soil pH value. Furthermore, spatial variability of soil pH value in this region was analyzed by using the geo-statistics and GIS (Geographic Information System), and its dominating factors was analyzed by means of variance analysis and regression analysis. The result shows that the soil pH value of the region varies in the range of 6.46±0.84, with a variation coefficient being 13.00%, both indicate the soil belongs a moderate level. The overall trend of the spatial distribution of pH is that the lowest value appears in the middle and southwest of the study area and the highest value appears in the north and southeast. There is a decreasing trend of soil pH value from the northeast to the southwest. Regression analysis indicates that parent material of the soil was the dominating factor, which alone could explain 13.6% of the soil pH value spatial variability of the region. The second import factor is the altitude, which could explain 6.30% of the soil pH value spatial variability of the region. Land use pattern could only explain 1.4% of the soil pH value spatial variability of the region.and slope of cultivated land has almost no impact on soil pH. According to these research results, the most influenced factor on the soil pH variation is structural factors. Land use patterns and farming methods will be the important driving forces of soil pH value in the study region in the future.

Soil conservation function is one of the important means of measuring the effectieness of ecological rehabilitation of rocky desertification in karst areas. Based on InVEST model, “3S” technology was used for interpreting rocky desertification in Guanling-Zhenfeng Huajiang Demonstration Area in 2005, 2010 and 2015, and the response mechanism between rocky desertification and soil conservation was studied. The results showed that, from 2005 to 2015, (1) Degree of rocky desertification in the Huajiang demonstration area presented an overall downward trend, and areas of rocky desertification was reducing from 3 773.56 to 3 474.23 hm². Moreover, the overall soil conservation quantities presented an upward trend, rising from 279 900 to 348 100 t. the increasing quantities of soil conservation per unit area, from 2005 to 2010, was concentrated in 6-30 t·hm^-2·a^-1, and in the last five years it slowed within 0-6 t·hm^-2·a^-1. (2) although differences in land-use type, slopes, and soil thickness, soil conservation functions did not show a simple decline at all, but rather: intensity > moderate, mild > potential, non-karst > no rock desertification. Among them, the difference between light and potential is biggest difference up to 5.53 t·hm^-2·a^-1, which indicated that potential rocky desertification is the harness priority in the future. (3) In 2005-2010, the increasing quantities of restoring-type soil conservation of rocky desertification was 10.27 t·hm^-2·a^-1, which was reduced to 3.01 t·hm^-2·a^-1 in 2010-2015 due to the change of land-use type and harness effectiveness. The change of the increasing quantities of stable type soil conservation of rocky desertification maintain the most stable; soil conservation function rises rapidly in intensity-rocky desertification slowdown areas, while mild-rocky desertification area is smoothest, which indicated that the harness period is long and needs to be gradual. Therefore, in the process of harness, it is necessary to consider the soil conservation function of different degree of rocky desertification and the effectiveness of its restoration.

Based on the daily average temperature data from 2010 to 2099 in geoengineering (G4 experiment) and non-geoengineering (RCP4.5) scenarios of BNU-ESM model, this research diagnosed the influence of geoengineering implementation on temperature change in different regions of China by using various mathematical statistics methods. The results showed that: Firstly, under the two scenarios from 2010 to 2099, the annual mean temperature in different regions of China showed an increasing trend. Geoengineering effectively reduced the increasing trend of annual average temperature in different regions of China from 2020 to 2069. Secondly, the annual average temperature in most areas of China dropped by more than 1.0℃ from 2020 to 2069, which played an active role in promoting the realization of the 1.5℃ temperature control target set by the Paris Agreement. And there was no retaliatory rebound in temperature in different regions of China from 2070 to 2099 after the implementation of geoengineering. Thirdly, the average annual temperature in different regions of China under two scenarios had changed from 2010 to 2099. The implementation of geoengineering had delayed the abrupt change of temperature in most areas of China for 11-19 years. Fourthly, high energy spectral oscillations of annual mean temperature series in different regions of China based on cross wavelet transform showed that the high frequency annual mean temperature in the two scenarios had inverse correlation on the scale of 1-4 years, indicating that geoengineering had changed the direction of temperature change in a short time. Low energy spectral oscillations of annual mean temperature series in different regions of China based on wavelet coherence showed that geoengineering had not fundamentally changed the long term trend of temperature change.

The Holocene profile with palaeoflood slackwater deposit was found in the SJGT reach downstream of the Wuding River basin after a thorough investigation. The palaeoflood SWD is 30 cm thick and contains thin parallel bedding, which directly covers the Eastern Han culture layer. The grain size of palaeoflood SWD is mainly silt with good sorting and low magnetic susceptibility. The mode (Md) and mean (Mz) of palaeoflood SWD are 31.88 and 35.71 μm respectively, which belong to coarse silt. The mode (Md) and mean (Mz) of 2012 flood SWD are similar to those of palaeoflood, and both belong to coarse silt. The sorting coefficients of paleofloods SWD and 2012 floods SWD are smaller, 0.79 and 0.65 respectively, which indicates that they are better sorting in the process of sediment transport. Palaeoflood SWD has sedimentary characteristics similar to those of the 2012 floods and is a Holocene flood geological record. OSL dating of the Eastern culture layer indicates that the palaeoflood occurred between 1 900 and 1 700 a B.P., which is the result of regional response to global climate change. The stage of palaeoflood is 765.86 m by using SWD thickness and sediment concentration method, and the discharge is 15 460 m3/s by using HEC-RAS model method. At the same time, the same method and hydrological parameters (such as roughness coefficient and gradient) are used to simulate the error between the peak discharge of flood and the measured value of hydrological station in 2012, which shows that the selection of parameters and the restoration of peak discharge are reasonable and accurate. The hydrological data of paleoflood are added to the measured flood and historical flood series to establish the relationship between flood peak discharge and frequency at the scale of ten thousand years. The once-in-a-century and once-in-a-thousand floods are transformed from extension to interpolation, which improves the accuracy of flood frequency analysis. Flood peak discharge of once-in-a-century, once-in-a-thousand and once-in-a ten thousand floods in Wuding River Basin are 7 070, 10 820 and 15 710 m³/s, respectively. The results provide important hydrological data for design floods of water conservancy and traffic engineering in the Wuding River Basin.