Under the background of the rapid economic transition from high-speed growth to high-quality development, urban sprawl, which is due to the land urbanization beyond population urbanization, is barely beneficial for high-quality and sustainable development. According to the data from 2001 to 2015 on the Yangtze River Economic Belt, the differential impact of industrial development on urban sprawl is examined. The results generally prove that：（1) on the first aspect of industrial structure, with the growing proportion of employment in the secondary industry, the degree of urban sprawl increases; nevertheless, with the advent of increasing proportion of employment in the tertiary industry, the pace of urban sprawl decreases;（2) on the second aspect of urban scale, it is the influence of the secondary industry on urban sprawl that plays a significant role in small and medium cities but not in large cities. The tertiary industry plays a prominent inhibitory role in large cities but not in small and medium cities, which mainly relates to the economic benefits of aggregation under different urban scales;(3) on the third aspect of the types of urban sprawl, it is the life service in the tertiary industry that promotes urban sprawl towards intensive development, while the secondary and the productive service industry promote the urban sprawl to excessive sprawling. All in all, in the Yangtze River Economic Belt, the secondary industry should be rationally laid out, the tertiary industry should be vigorously developed, the agglomeration effect of the industry should be improved, and the urban sprawl that is caused by unreasonable development and blind investment attraction should be avoided.

Informatization has become one of the important driving in regional modernization and comprehensive strength. Based on 719 study units in the Yangtze River Economic Belt at county scale, this paper builds an evaluation system with four key elements which contain 9 specific indicators to measure the level of regional informatization, and the four key elements are informatization development environment, the level of informatization infrastructure, informatization innovation capability and the level of networking information consumption. This paper aims to reveal differences in the spatial distribution characteristics of the counties and the factors influencing their development level, by means of using a comprehensive method of mean-variance weighting method, spatial interpolation, exploratory spatial data analysis and kernel density estimation. According to the research, four highlights are unveiled:（1) Overall the informationization level shows the significant regional differences, with the eastern coastal cities higher than those in the western interior at county scale in Yangtze River Economic Belt. Moreover, the high informationization level tends to be distributed in the Yangtze River Delta.（2) From the pattern of spatial auto-correlation, the level of informationization appears significant spatial agglomeration characteristics, that is means the number of the High-High regions（HH regions) and the Low-Low regions（LL regions) occupy most and the spatial agglomeration pattern is obvious. The significant HH areas are mainly distributed in Jinhua, Shaoxing, Wenzhou, Suzhou, Nantong, Changzhou, ect. The significant LL areas have mainly concentrated in Quanjiao, Hexian, Zongyang, ect.（3) From the result of kernel density estimation, the spatial level of informationization in the Yangtze River Delta becomes more obvious in the different search radius. The high density is centrally distributed in the Yangtze River Delta.（4) According to the spatial characteristics of informationization level, the mainly impact factors include geographic conditions, the level of economic development, the strategic policy, the personnel training and the innovation of science and technology.

Applying delphi approach, linear fitting prediction, kaya model and multi-factor spatial overlay analysis, this paper focus on measuring land development intensity and identifying restricting factors of construction land development in Jiangsu based on carrying capacity of resources and environment and suitability of development and construction. The results indicate:（1) Resources and environment factors have different restricting impact on construction land expansion in Jiangsu, and water resource carrying capacity precedes environment, while carbon emission lags behind former factors;（2) Unsuitable development area locates on lake, wetland and coastal zone in Jiangsu, while suitable development area is in the mode of aggregated distribution which covers Suzhou-Wuxi-Changzhou, Nanjing-Zhenjiang-Yangzhou-Yancheng and coastal area;（3) land development intensity of each municipality in Jiangsu presents regional, temporal and structural differences. Southern Jiangsu is mainly faced with restriction of environment and carbon emission, while median and northern Jiangsu area is restricted by water resource, environment and carbon emission alternately. Land development intensity prediction can provide theoretical and data base for making regional-different policies of land regulation and ecological protection.

Postmodern tourism is a new concept in tourism, which was originated from the ideological trend of postmodernism. Through reviewing relevant domestic and oversea literature about postmodernism and postmodern tourism, this paper adopts the methods of field research and questionnaire survey, and takes Kaihui Town of Changsha County, Hunan Province, as an example for the empirical study. The results show:（1) Postmodern tourism is inherited from modern tourism. The demands of postmodern tourists are diverse, complex and even contradictory, which are difficult to identify.（2) In general, the development of postmodern tourism products should adhere to the concepts of green nature, emotional experience, individuality, health and fairness.（3) Although it is rich in rural tourism resource, the existing rural tourism products of Kaihui Town have several problems, such as low participation of tourists, low consumption level, unbalanced brand awareness, and inefficient new media marketing.（4) This paper has exploringly designed an index system which is composed of 13 factors.The factors are divided into three levels based on their importance to tourist. The weight of each factor is used as a reference for product development.（5) Four suggestions of developing postmodern rural tourism products are put forward, which are “earth art”, “family holiday”, “rural experience” and “outdoor leisure”. In the future, it is necessary to strengthen the research on rural tourism under the background of “postmodern” or “trans-modern” society.

The emerging and popularity of distributed hydrological models promote the development of hydrology sciences meanwhile massive model parameters are introduced, emphasizing the necessity of screening out sensitive parameters. Sensitivity analysis（SA) helps recognize sensitive parameters, reduce the number of model parameters to be analyzed and facilitates parametric optimization and uncertainty estimation. In this study the Xin’anjiang model was applied to Gaotan catchment located in the upstream of Han River basin and Nash-Sutcliffe efficiency（DC), water balance coefficient（WB) and their combination served as objective functions to evaluate the accuracy of daily streamflow simulation. A qualitative SA approach, Morris method was first used to screen out sensitive parameters and reduce the dimensionality of model parameters. The Sobol method was then adopted to quantify degrees of sensitivity of sensitive parameters quantitatively. Both methods are implemented for three different objective functions. The result showed that among 13 selected model parameters, runoff generation parameter KC, runoff separation parameters SM and KI/ KG, runoff routing parameters CI,CG and CS are identified as sensitive parameters, among which KC is most sensitive. Furthermore, the selection of objective functions to be evaluated has significant impact on the determination of sensitive parameters: water balance coefficient is most sensitive to KC while Nash-Sutcliffe efficiency more sensitive to other sensitive parameters, especially CS. Further investigation into sensitive parameters revealed that some parameters like SM have higher interaction sensitivities compared to first-order sensitivities, indicating that the interactions between model parameters should be regarded as an unnegligible factor of parameters sensitivity. The Morris method facilitates the reduction of dimensionalities of model parameters while the Sobol method precisely characterizes the features of parametric sensitivities and provides more information on the sensitivities. The integration of both methods is demonstrated to enhance the reliability and accuracy of sensitivity analysis.

Based on the data of water consumption in 16 cities of Anhui province from 2005 to 2016, the method of Social Network Analysis（SNA) is introduced to reveal the spatial correlation network structure of regional water use, and then the key areas of water management can be screened. The results show: the spatial linkages among regional water use are very close, there is no isolated urban node in the entire sample cities. During the investigated period, the network density declined slightly with a hierarchical network structure. The individual network characteristics show significant "polarization effect" and "Matthew effect". Hefei, Wuhu and Maanshan are located in the center of the network with high degree, betweenness centrality and closeness centrality, which dominate the water flow and overflow in the spatial network. At present, the regional water network in Anhui province is in the multi-core stage, which has evolved from the initial period with dual-core driving mode consists of Hefei and Maanshan-Wuhu-Tongling to the stable spatial pattern of three growth poles of Fuyang, Hefei and Maanshan-Wuhu-Tongling.

Water use efficiency（WUE) is an important index to measure the coupling degree of the carbon and water cycles. Based on MODIS data, land cover type data and meteorological data, the vegetation water use efficiency WUE of Anhui Province was estimated. The temporal and spatial patterns, changing trends and influencing factors of vegetation WUE in Anhui Province from 2000 to 2014 were explored by trend analysis and correlation analysis. The results showed that 1) Annual WUE of different vegetation types showed significant differences and average WUE of evergreen broad-leaved forest and evergreen coniferous forest was higher, which reached 1.66 gC?mm-1?m-2 and 1.69 gC?mm-1?m-2 respectively, while the annual average WUE of cultivated land was the lowest. The annual WUE of each vegetation type decreased following the order of that: evergreen coniferous forest＞evergreen broad-leaved forest＞shrub, sparse forest＞grassland＞deciduous broad-leaved forest＞coniferous broad-leaved mixed forest＞cultivated land. Annual average WUE of vegetation had a strong spatial variability in Anhui Province, where it was higher in the north and south of the province but lower in the middle part. The high value area of vegetation WUE was mainly distributed in Dabie mountain area and southern mountainous area in Anhui Province, and the distribution range was basically consistent with the distribution range of evergreen coniferous forest and evergreen broad-leaved forest. 2) Between 2000 and 2014, the variation of vegetation WUE showed an M-shaped “double-peak” trend of “increase-decrease-increase-decrease” with obviously seasonal variation, displayed the sequence of spring＞autumn＞summer＞winter. Besides, the average WUE of vegetation in each season accounted for 32.58%, 24.91%, 29.27% and 13.24% of the total vegetation WUE respectively. 3) The dynamic change of vegetation WUE in Anhui province resulting from non-climate factors made up 93.82% of the total area of vegetation in the province, followed by precipitation factor（3.88%) and temperature factor（2.19%), while the combination of precipitation and temperature had the smallest impact on WUE（0.11%). Besides, the temperature significantly affects the area within the cultivated land, while the precipitation significantly affects the area within the forrest land mainly. Due to the influence of human, non-climate factors had a greater impact on vegetation WUE changes.

Reasonable green space vegetation construction and management is an effective way to increase urban water storage capacity and reduce urban waterlog.Eight urban green space locations characterized by different vegetation types in the Wuhan city were selected to collect the surface soil samples. The effects of green space vegetation types on water infiltration rate and water retention capacity of surface soils were quantified by measuring the soil physiochemical properties and hydraulic parameters.Furthermore, the relationships between the physiochemical properties and hydraulic parameters were analyzed. The results showed that significant differences of soil water infiltration rate and retention capacity were observed among the eight urban green space locations.The highest infiltration rate was observed in the natural camphor forest, magnolia garden, osmanthusfragrans garden, and peony garden（179.70-441.69 cm/d), characterized by the highest saturated hydraulic conductivity（Ks), followed by the artificial grassland(31.53-126.60 cm/d), and the lowest in sakura garden, plum garden, and peaches mixed plums garden(22.40-57.99 cm/d). The highest soil water retention capacity was observed in the natural camphor forest,characterized by the highest field water capacity(0.315-0.336 cm³/cm³) and the maximum effective water content(0.170-0.177cm³/cm³), followed by themagnolia garden,osmanthusfragrans garden, peony garden, plum garden and peaches mixed plums garden(0.241-0.289 cm³/cm³,0.144-0.182cm³/cm³), and the lowest in the sakura garden and artificial grassland(0.209-0.254 cm³/cm³,0.139-0.165 cm³/cm³).Significantly positive correlations were observed between Ks and soil total porosity/non-capillary porosity, and a significantly negative correlation between Ks and soil bulk density. The soil water retention capacity was mainly affected by the bulk density, total porosity, sand content,and clay content.The practices of planting herbaceous under the wood plants, reduce trampling, and addition soil tillage could be applied for the urban green space construction, which could improve the effects of rainfall conservation and reduce urban waterlog by enhancing the water infiltration rate and water retention capacity of surface soil.

Accurate and efficient information of land use types is of great importance for monitoring and management of land resources. In order to improve the accuracy of land use classification in low mountain and hilly areas, the current study applied random forest with Sentinel-2 images and terrain indicators to classify land use types in Lishi town, Jiangjing, Chongqing. A total of 23 features involved three kind of variables, namely, traditional remote sensing indices, red-edge remote sensing indices and topographic indices were derived from the Sentinel-2 images and digital elevation model. Three models with different inputs were developed and compared. The accurate map of land use types and the relative importance of these indices to the classification were obtained by the best model. The results showed that the values of overall accuracy and Kappa coefficient were 86.54% and 0.800 9 for the model with traditional remote sensing indices, 87.17% and 0.810 2 for the model with traditional remote sensing indices and red-edge remote sensing indices, 88.61% and 0.831 4 for the model with traditional remote sensing indices, red-edge remote sensing indices, and terrain indicators, respectively. The top five importance variables was ranked in order of B2（Blue), B4（Red), B3（Green), Modified Normalized Difference Water Index（MNDWI), and B5（Vegetation Red Edge（1) The random forest with Sentinel-2 images and terrain indicators could be a suitable tool for producing accurate land use information over the study area. The results could provide valuable information for land use classification in the areas with complex topography.

Taking Yubei District of Chongqing as an example, this paper uses the remote sensing data of Landsat TM and DEM data with the help of geographic information system and remote sensing methods, and uses the methods of landscape index analysis, terrain niche index and distribution index to analyze the characteristics of the changes of land use landscape pattern from 2010 to 2015. At the same time, it focuses on the changes of landscape types and the relationship between them under different terrain and gradient, so as to provide some reference for the selection of the best land use pattern in cities under similar conditions. The results show that:（1) The land resources of Yubei District are mainly made up of middle and high-level topography, and the land resources below 200 m above sea level and below 6° slope are scarce.（2).The main types of landscape in Yubei District are cultivated land and forest land, but the general trend of cultivated land landscape is decreasing, while the forest land is increasing and the land of construction is growing faster. Generally speaking, landscape fragmentation is increasing and landscape diversity is on the rise.（3) It is found that a large number of arable land is converted into construction land in the middle and low terrain location area during the research period, and the distribution trend of forest land and grassland landscape area expands with the increase of terrain location index, and its dominant terrain position mainly concentrates in the high terrain location area.

The historical data of drought and flood contain comprehensive and reliable environmental information, which records the frequent occurrence of natural disasters in China during the Little Ice Age. However, researches on the climatic and environmental conditions and their impacts on human activities in Guizhou region which use these data are few reported. This paper collated and analyzed the historical data of drought and flood in the area of Guizhou from 1470 to 1949, verifying by correlation analysis based on mutual information, exploring the humidity variation processes and cycles by sliding average method and wavelet analysis, , discussing its controlled mechanism and the influence on human activities compared with the high-resolution stalagmite δ18O sequence, ocean thermal condition and the relationship between central and local governments. Results showed that（1) the climatic condition in Guizhou was dry in the late 15th century, while in the 16th century it was wet. After the dry period in the early 17th century, Guizhou experienced a long and stable wet period which was from the mid-17th century to the early 20th century. These results correspond well with copious records.（2) The humidity variation had periods of about 128~155 years, 32~55 years and 11~20 years, reflecting that they are primarily controlled by solar radiation intensity and solar activity.（3)The humidity variation was affected by the intensity of the South Asian summer monsoon, ENSO and AMO as well as solar radiation, which also had profound impacts on political activities and other human activities during Ming and Qing Dynasty.

Based on the observed rainfall data, the accuracy of four remote sensing precipitation products, such as TRMM 3B42 V7, CMORPH CRT, PERSIANN and TRMM 3B42 RT, were evaluated in the Lancang River Basin. The evaluation was performed at multiple time scales, ranging from daily to yearly, for the years from 2001 to 2014, but only one spatial scale: grid spatial scale. On the ground of observations and the selected high-accuracy products, the SWAT model was applied in runoff simulation to further explore the applicability of remote sensing precipitation products in the Lancang River Basin. The results show that four products present low accuracy on daily time scale, and their correlation coefficients（R) with observed rainfall data are less than 0.5; as a whole, TRMM 3B42V7 is the most accurate dataset with R being 0.95, 0.90, from monthly to yearly time scale, respectively; the accuracy of CMORPH CRT is slightly lower than that of TRMM 3B42 V7, with R being 0.89, 0.77, from monthly to yearly time scale, respectively; TRMM 3B42 RT and PERSIANN have present poor accuracy, and their R in different time scales are relatively low, with R basically maintaining below 0.5. The runoff simulation results show that the skills of TRMM 3B42 V7 and CMORPH CRT are not as good as that of the observed rainfall data on simulating the daily and monthly runoff of the river basin outlet section, but all three can better reflect the variation trend of measured runoff in runoff simulation with the corresponding Nash-Sutcliffe coefficient（NS) of the three keeping within the range of 0.65-0.94. From the perspective of the NS, the value difference of the three is insignificant. From the perspective of relative error of water quantity（RE), all of them underestimate water quantity , but the RE value of CMORPH CRT（within the range of -10%—-20%) is larger than that of the other two（ within the range of -4%—-10%). Overall, the runoff simulation capability of TRMM 3B42 V7 is better than that of CMORPH CRT in the Lancang River Basin.

This paper investigated the effects of crop planting structure on agricultural output value and non-point source pollution by analysising the relation of crop diversity, agricultural output value, and released pollutants. The panel data of 30 provinces in China from 1990 to 2016 were included. The results showed that crop diversity had an inverted u-shape effect on agricultural output value and there were greatly diversified crop categories for non-dominant crops (relatively weak comparative advantage) currently, which had an inhibitory effect on agricultural output value and had a positive effect on agricultural non-point source pollution. Holding all other things constant, a 1 increase of the crop diversity will lead to a decrease in agricultural output value of 1.5% and an increase in agricultural non-point source pollution of 1.3%, respectively. The increase of regional dominant crop diversity had a greater inhibitory effect on agricultural non-point source pollution, when the crop diversity rises 1, agricultural non-point source pollution decreases 1.5 percent. Besides, the crop diversity had a negative effect on comprehensive indicators of output value and pollution. With the outflowing of agricultural labor, reducing crop diversity benefits agricultural output value; the increase of crop diversity is beneficial to the growth of agricultural output value when natural ecosystems are fragile. In order to improve agricultural income and enhance ecological environment, the crop varieties and planting areas should be reduced for those weaker comparative crops, meanwhile developing agricultural products, local agricultural products, and building agricultural brands will substantially help. For other factors we discussed, agricultural infrastructure, farmers’ awareness of disaster prevention are significantly affecting the agricultural outputs and need be addressed properly.

Rural residential land is one of the major landscapes for rural settlement. Spatially, the newly-construction or reconstruction for rural residential land depends on its interaction of competitive control and coverage with interior and exterior environment. Under the background of accelerating urbanization in China, rural residential land has been increasing rather than decreasing. At the same time, the impact of its spatial layout and expansion on the natural ecological environment and feedback has not been considered enough. Based on the relevant theories and methods of landscape ecological pattern, this paper uses the minimum cumulative resistance model, and takes Dujiangyan as an example to evaluate and analyze the ecological suitability of rural residential land sites. The results showed that: (1) For the past ten years, the spatial distribution of ecological suitability zoning in the study area was relatively concentrated, with shrink in divisions of relative high and highest levels of ecological suitability, while evident expansion in divisions that of relative low and lowest levels. These great contrasts indicated that the impact of human activities on the local landscape pattern was increasing. (2) The dynamic changes of ecological suitability varied within different time periods, in lowest level of ecological suitability area, the quantities and areas of rural residential land kept increasing, while in that of moderate and above levels, the quantities and areas showed increase firstly and then decline. (3) The ecological suitability of residential land was changing continuously, with 559.39 hm2 from 2005 to 2010 and 781.11 hm2 from 2010 to 2015 respectively. The results have extensive practical value in strengthening protection of local significant ecological landscape unions, coordinating the contradiction between human and land, and human and nature, improving the utilization efficiency of rural land resource, making plans of rural constructive development.

Climate engineering, as a fast and effective means of cooling the earth, has become one of the focuses of discussion in the international negotiations on climate change. To diagnose whether different stages of climate engineering have an impact on rainfall structure in China under the current GeoMIP model. According to the daily rainfall intensity classification standard of the Central Meteorological Observatory of China Meteorological Administration, 0.5°×0.5°spatial resolution daily precipitation data of the solar radiation management climate engineering G4 experiment and RCP 4.5 scenario based on the BNU-ESM model , the spatial differences of rainfall amounts and rainfall days contribution rate of different grades in China during the three different periods of implementation of climate engineering, namely, 2010-2099, 2020-2069 and 2070-2099, are compared and analyzed. The results show that: Firstly, in the climatic state, there is a good consistency between the climatic state of different grades rainfall in China in three periods under the two scenarios. Climate engineering has not changed the spatial characteristics of rainfall structure in China. Secondly, in the differences between climate engineering and non-climate engineering, different stages of implementation of climate engineering can indeed have an impact on rainfall structure in different regions of China, and the differences are different in different periods. Thirdly, in the difference before and after the implementation of climate engineering, the implementation of climate engineering promote moderate rainfall, heavy rainfall and total rainstorm events, but restrained light rainfall events. Under the current GeoMIP model, the implementation of climate engineering will have different impacts on rainfall structure in China.

Based on the data of 16 cities in Hubei Province from 2005 to 2017, the spatial scale model was applied to study the impact on urbanization and industrialization level of the content of SO2, NO2 and PM10 in air. The results show that the per-capita GDP has significant negative effect on the content of SO2 in air and significant positive effect on NO2, the quantity of civil car and highway mileage have significant positive effect on SO2, NO2 and PM10 in urban air, the industrialization level has significant negative effect on SO2 and NO2 in air and significant positive effect on PM10, besides, the per-capita green space area has significant negative effect on SO2 in air and whose effect on NO2 and PM10 is not significant in the urbanization level. Therefore, it is necessary to accelerate the transformation and upgrading of industry and the development plan of it, strengthen the detection of exhaust emission of civil car in urbanization and garden construction of urban matching, establish a city green development linkage mechanism and regional inspection supervision.

Based on the daily precipitation data collected from 131 meteorological stations in the Yangtze River Basin during 1963-2016, precipitation-concentration degree (PCD) and precipitation-concentration period (PCP) of annual precipitation and heavy precipitation (extreme precipitation and rainstorm) were calculated, respectively. Meanwhile, the M-K nonparametric trend test and correlation analysis methods were used to analyze the inhomogeneity and the variation trend of precipitation in this area. The aims of this study are to characterize the inhomogeneity of different types of precipitation in this basin, and enhance our understanding of spatial and temporal distribution for heavy precipitation. The results showed that multi-year mean annual PCDDP and PCPDP increased from the lower to upper reaches. The variation trend of PCDDP was not significant. For PCPDP, its spatial variation trend was obviously different, an increasing trend occurred in the middle and lower reaches, while a decreasing trend appeared in the upper reaches. There was a significant positive correlation between annual precipitation and PCDDP, which mainly distributed in Sichuan Basin. The multi-year mean annual PCDEP and PCPEP and their variation trends were similar to that of PCDDP and PCPDP. The multi-year mean annual rainstorm precipitation (daily precipitation≥50 mm) decreased from the lower to upper reaches, while it was higher for Sichuan Basin than that in the surrounding area. The variation trend of rainstorm increased in the east of the Yangtze River Basin and decreased in Sichuan Basin. The multi-year mean annual PCDRP and PCPRP decreased from southeast to northwest of the Yangtze River Basin. However, PCDRP increased in Hubei, Guizhou and eastern Sichuan, and decreased in southeastern of the basin. An increasing trend (but not significant) for PCPRP was found in Jiangsu and Zhejiang, Anhui, Hunan and Guizhou, while a decreasing trend was observed in Sichuan and Yunnan. 

This study presents the spatio-temporal differentiation of ozone concentration and its driving factors in the Yangtze River Delta urban agglomeration from 2015 to 2017 via Kriging interpolation, spatial auto-correlation, hot and cool spot analysis, and geographical detection. The results show that: 1) the concentration of ozone rises during this period with 90th percentile of maximum daily 8-h average ozone concentration rising from 149 μg/m3 to 166 μg/m3, the percentage of days which exceed standard (GB 3095-2012) going up from 9.3% to 12.1%, and the proportion of days with ozone as primary pollutant to total polluted days increasing from 32.3% to 46.4%; 2) impacted by the large inter-annual fluctuations of temperature and precipitation, the curves of monthly ozone concentration differ slightly in different years; the days with over-limit ozone concentration mainly occurred from April to September, which account for 88.3%, 98.2% and 97.0% of the year 2015, 2016 and 2017, respectively; 3) due to the rapid increase of ozone concentration in Anhui province, the spatial distribution pattern of ozone concentration evolves from high in East and low in West to high in North and low in South, but the concentration is more homogenized than before; 4) with the rise of ozone concentration, the hot spots expand from Taihu Lake area to Nanjing metropolitan area, while the cool spots shrink evidently in Anhui Province; 5) the analysis of geographical detector shows that socioeconomic factors such as economic scale, urbanization and emission source have a significantly positive impact on the spatial distribution of ozone concentration, while precipitation and wind have a negative impact on the spatial distribution of ozone concentration since the precipitation scavenges ozone and wind promotes the dispersion of ozone.

Base on GIS, self-organizing map (SOM), back trajectory model and geostatistical method, this study investigates the spatiotemporal distribution of air pollution and its impacted factors in Nanchang City. For this purpose, the data of air quality index (AQI) and the main air pollutants in different time scales from 2014 to 2017 is selected, as well as the meteorological factors. Results show that the air quality of Nanchang City is not significantly improved in recent years. 51≤AQI≤100 is the main level of AQI with the ratios between 57% and 61%. But the primary pollutants are greatly changed, e.g. the number of polluted days of PM2.5 decrease, while the counterpart of NO2 and O3 increase. For seasonal variation, the air quality in Nanchang City is poor in winter and spring, with PM10 and PM2.5 as the primary pollutants. In comparison, the counterpart is good in summer, with O3 as the primary pollutant. The air quality is relatively bad on Monday and the weekends, and relatively good on Wednesdays and Thursday. It reveals that travel habit of people is not the only influence factor for the air quality in Nanchang City. The diurnal variation of air quality in Nanchang City shows a bimodal distribution peaked at 9:00-11:00 and 20:00-22:00, which is primarily related to the traffic exhaust during the rush hours. For spatial distribution, the air quality in Nanchang City is poor in the downtown area compared with that in the suburban area. Specifically, the concentrations of PM10, PM2.5, SO2, NO2, CO are higher in the downtown area. In contrary, O3 shows the higher concentration in the suburban area. Because there is more amount of NOx emission in the downtown area and O3 is easily consumed by rapid reaction with them. Back trajectories and cluster analysis suggest that the prevailing air masses were from the nearby area in Nanchang and PM10, PM2.5, NO2 and O3 pollution may mainly originate from these areas. Principal component analysis (PCA) demonstrates that the relative humidity and temperature is the main impact corresponding to the high concentration of PM2.5, PM10 and NO2 and the concentration of O3, respectively.

Response of vegetation NPP to climate change is one of the key issues in the study of global change and terrestrial ecosystem carbon cycle. In this paper, vegetation NPP was estimated by CASA model in Jianghan Plain from 2000 to 2015, and the spatial-temporal variation characteristics of vegetation NPP and its relativities with climatic factors were quantitatively studied by linear regression and pixel correlation analysis. Results are summarized as follows: (1) Total annual NPP ranged from 25.43 to 29.76 TgC in Jianghan Plain from 2000 to 2015, and showing an increasing trend of fluctuation. (2) The spatial distribution pattern of NPP in Jianghan Plain is obviously uneven, forming a series of high value and low value centers, which was consistent with the attenuation trend of “hills-plain-river-city”. (3) The correlation coefficients between NPP and annual precipitation, and annual mean temperature were 0.183 7 and 0.498 5, respectively; and the significant test of correlation coefficient indicated that the yield of NPP in Jianghan Plain has a weak correlation with annual precipitation, but a positive correlation with annual mean temperature. (4) The area with positive correlation between NPP and annual precipitation and annual mean temperature accounted for 69.19% and 83.41% of the total area, respectively, mainly distributed in the agricultural region in the abdomen of Jianghan Plain, which indicated that the yield of NPP in the agricultural region of Jianghan Plain was strongly dependent on the annual precipitation and annual mean temperature.

In this paper the daily precipitation data from five global climate models (GCMs), which are all from CMIP5 and also the input in the Inter-Sectoral Impact Model Inter-comparison Project (ISIMIP), under RCP2.6 and RCP8.5 scenarios respectively in the Hanjiang River Basin is used to project the drought changes in the area through Standard Precipitation Index (SPI) at different time scales. Based on the observed data from 22 meteorological stations in Hanjiang River Basin in 1960-2004, and the GCM data in 2020-2059, three characters related to the drought events in these two durations, including drought severity, frequency and duration are compared and analyzed. Results show that in the drought severity the light or moderate drought events will happened less while the severe drought events can arise more often. As to the frequency and duration it is difficult to draw an identical conclusion from different GCMs. Anyway there is a general tendency in less frequency and shorter duration in the future. Through the comparison between the historical observed data and GCM generated data, HadGEM2-ES shows better performance in the rainfall simulation while GFDL-ESM2M and IPSL-CM5A-LR have better results in the less-rainfall namely drought analysis.

Based on SWAT model and quantitatively analyses, the impact of different land use types and climatic factors on watershed runoff in different scenarios were studied to reveal the influence of LUCC and climate change on watershed runoff variation. Combined with RCP4.5 and RCP8.5 climate scenarios, the upcoming runoff change of the Lixian River Basin was predicted. Results were as follows: (1) SWAT model performs well in simulating Lixian River basin runoff. The model parameters R2 and Ens were 0.74 and 0.73 respectively in parameter calibration period, and 0.63 and 0.63 respectively in model verification period. (2) The single land use scenario shows that the conversion of farmland into woodland or grassland will decrease watershed runoff, however, the conversion of forest to pasture will increase watershed runoff. The three types of land contributed to the rise of runoff in the order from the largest to the smallest, followed by cultivated land, grassland and forest land. (3) the average monthly runoff increase caused by LUCC was lower than the average monthly runoff reduction caused by climate change in the Lixian River Basin during 2006-2015. (4) Under the RCP4.5 and RCP8.5 climatic scenarios, the runoff in the Lixian River basin shows a decreasing trend during the period of 2021 to 2050, with decreasing rates of 3.6 ×108 m³/10a and 2.15 ×108 m³/10a respectively. This is consistent with the trend of deceleration of the measured runoff of 6.7×108 m3/10a in the Lixian River basin between 1971 and 2015. However, under these two scenarios, the trend of runoff reduction has been some extent decreased, reaching 53.7% and 32.1% respectively for the 1971-2015 deceleration.

High-risk periods and priority control areas refer to the main periods and areas of soil erosion, respectively. Identification of high-risk periods and priority control areas of soil erosion on monthly scale has important practical significance for the protection of soil and water resources. Based on the USLE model, the temporal and spatial distribution characteristics of soil erosion in each month in the middle and lower reaches of the Hanjiang River Basin were analyzed quantitatively. By using the cooperation analysis of high-risk periods and priority control areas, the high-risk periods of soil erosion were identified quantitatively based on the erosion-period curve, and then the priority control areas in high-risk periods were identified based on the erosion-area curve. The results showed that the soil erosion in the middle and lower reaches of the Hanjiang River Basin in 2010 has the characteristic of concentrated distribution. The severe erosion areas were mainly distributed in the northwest and southeast of the basin, accounting for 11.70% of the basin area. The areas with mild and slight erosion were mainly distributed in the east and south of the basin with lower slopes, accounting for 88.30% of the basin area. The high-risk periods of soil erosion in the basin were months 4 and 7, and the amount of soil erosion accounted for 69.12% of the year. And the amount of soil erosion in July was the highest, accounting for 41.83% of the whole year, followed by April, accounting for 27.29% of the year. In the high-risk periods of soil erosion in the middle and lower reaches of the Hanjiang River Basin, the priority control areas accounted for 12.22% of the basin area, and the amount of the erosion reached 82.01% of the basin. The priority control areas were mainly distributed in the north, west and southeast of the basin. The control efficiency of soil erosion can be greatly improved by controlling priority control areas in high-risk periods.

Fast and accurate prediction of flood damage is the basis for emergency management of flood disasters, and forecasting techniques and methods are the core and key to flood disaster loss prediction. This paper constructs a flood disaster assessment index system from the aspects of disaster risk component and data accessibility, and selects 13 loss assessment input indicators from disaster-causing factors, affected environment, disaster-bearing object and emergency response capability. A prediction method of flood damage loss based on Gaussian process regression model is proposed, which is applied to the prediction of the flood damage loss in Chongqing of affected number of people, crop affected area and direct economic losses. The example shows that the residual square sum of the three loss cases mentioned above is 0.99, 0.1 and 12.67 respectively, and the fitting precision is 99.85%, 99.97% and 96.1% respectively. Compared with the multi-layer perceptron neural network and support vector machine, the Gauss process regression method is more superior.