Based on the daily precipitation data of 27 meteorological stations from 1960 to 2009 in the Huaihe River Basin, spatio-temporal trend and statistical distribution of extreme precipitation events in this area are analyzed. Annual maximum series (AM) and peak over threshold series (POT) are selected to simulate the probability distribution of extreme precipitation. The results show that positive trend of annual maximum precipitation is detected at most of used stations, only a small number of stations are found to depict a negative trend during the past five decades, and none of the positive or negative trend is significant. The maximum precipitation event almost occurred in the flooding period during the 1960s and 1970s. By the L-moments method, the parameters of three extreme distributions, i.e., Generalized extreme value distribution (GEV), Generalized Pareto distribution (GP) and Gamma distribution are estimated. From the results of goodness of fit test and Kolmogorov-Smirnov (K-S) test, AM series can be better fitted by GEV model and POT series can be better fitted by GP model. By the comparison of the precipitation amounts under different return levels, it can be found that the values obtained from POT series are a little larger than the values from AM series, and they can better simulate the observed values in the Huaihe River Basin.
Sensitivity analysis of hydrological model is the key for model uncertainty quantification. However, how to effectively validate model and identify the dominant parameters for distributed hydrological models is a bottle-neck to achieve parameters optimization. For this reason, a new approach was proposed in this paper, in which the support vector machine was used to construct the response surface at first. Then it integrates the SVM-based response surface with the Sobol’ method, i.e. the RSMSobol’ method, to quantify the parameter sensitivities. In this work, the distributed time-variant gain model (DTVGM) was applied to the Huaihe River Basin, which was used as a case to verify its validity and feasibility. We selected three objective functions (i.e. water balance coefficient WB, Nash-Sutcliffe efficiency coefficient NS, and correlation coefficient RC) to assess the model performance as the output responses for sensitivity analysis. The results show that the parameters g1 and g2 are most important for all the objective functions, and they are almost the same to that of the classical approach. Furthermore, the RSMSobol method can not only achieve the quantification of the sensitivity, and also reduce the computational cost, with good accuracy compared to the classical approach. And this approach will be effective and reliable in the global sensitivity analysis for a complex modelling system.
Using the daily temperature data of 95 meteorological stations from Sichuan- Chongqing Region and its surrounding areas, this paper adopted these methods (e.g., linear regression, trend coefficient, geographical statistics, gray relational analysis and spatial analysis functions of GIS) to analyze the relations of temperature variability with topography, latitude and longitude. Moreover, the rank of gray correlation between temperature variability and elevation, longitude, latitude, topographic position and surface roughness also was measured. These results indicated: (1) The elevation affected temperature variability most obviously, followed by latitude, and longitude. The slope of the linear regression between temperature change rate and elevation, latitude and longitude was 0.4142, 0.0293 and -0.3270, respectively. (2) The rank of gray correlation between temperature change rate and geographic factors was elevation > latitude > surface roughness > topographic position > longitude. The gray correlation degree between temperature change rate and elevation was 0.865, followed by latitude with 0.796, and longitude with 0.671. (3) The rate of temperature change enhanced with the increase of elevation. Especially, the warming trend was significant in the plateau and mountain areas of western Sichuan, and mountain and valley areas of southwestern Sichuan (with the warming rate of 0.74℃/10a during the 1990s). However, there was a weak warming trend in Sichuan Basin and its surrounding low mountain and hilly areas. (4) The effects of latitude on temperature change rate presented the specific regulation, which the warming rate of low-latitude areas was more significant than that of high-latitude areas. However, they were consistent with the regulation that the increasing of low temperature controlled most of the warming trend, due to the effects of terrain and elevation on annual mean temperature. (5) Basically, temperature variability along longitude direction resulted from the regular change of elevation along longitude. It was suggested that, in Sichuan-Chongqing Region, special features of temperature variability largely depended on the terrain complexity (e.g., undulations, mutations and roughness). The elevation level controlled only high or low annual mean temperature and the range of temperature change rate in the macro sense.
Based on China homogenized land surface air temperature and the National Centers for Environmental Prediction/Department of Energy (NCEP/DOE) Atmospheric Model Intercomparison Project (AMIP)-Ⅱ Reanalysis data (R-2), the main contributors to surface air temperature increase in Southeast China were investigated by comparing trends of urban and rural temperature series, as well as observed and R-2 data, covering two periods of 1954-2005 and 1979-2005. Results from urban-rural comparison indicate that urban heat island (UHI) effects on regional annual and autumn minimum temperature increases account for 10.5% and 12.0% since 1954, but with smaller warming attribution of 6.2% and 10.6% since 1979. The results by comparing observations with R-2 surface temperature data suggest that land use change accounts for 32.9% and 28.8% in regional annual and autumn minimum temperature increases since 1979. Accordingly, the influence of land use change on regional temperature increase in Southeast China is much more noticeable during the last 30 years. However, it indicates that UHI effect, overwhelmed by the warming change of background climate, does not play a significant role in regional warming over Southeast China during the last 50 years.
By decomposing and reconstructing the runoff information from 1965 to 2007 of the hydrologic stations of Tuotuo River and Zhimenda in the source region of the Yangtze River, and Jimai and Tangnaihai in the source region of the Yellow River with db3 wavelet, runoff of different hydrologic stations tends to be declining in the seasons of spring flood, summer flood and dry ones except for that in Tuotuo River. The declining flood/dry seasons series was summer > spring > dry; while runoff of Tuotuo River was always increasing in different stages from 1965 to 2007 with a higher increase rate in summer flood seasons than that in spring ones. Complex Morlet wavelet was selected to detect runoff periodicity of the four hydrologic stations mentioned above. Over all seasons the periodicity was 11-12 years in the source region of the Yellow River. For the source region of the Yangtze River the periodicity was 4-6 years in the spring flood seasons and 13-14 years in the summer flood seasons. The differences of variations of flow periodicity between the upper catchment areas of the Yellow River and the Yangtze River and between seasons were considered in relation to glacial melt and annual snowfall and rainfall as providers of water for runoff.
Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satellite precipitation analysis (TMPA; 3B43 V.6) product during the period 1998 to 2009 is an alternative precipitation data source with good accuracy. By using the standard precipitation index (SPI), at the grid point (0.25°×0.25°) and sub-basin spatial scales, this work assessed the effectiveness of TMPA in drought monitoring during the period 1998 to 2009 at the 1-month scale and 3-months scale; validated the monitoring accuracy of TMPA for two severe droughts happened in 2006 and 2009, respectively. Some conclusions are drawn as follows. (1) At the grid point spatial scale, in comparison with the monitoring results between rain gauges (SPI1g) and TMPA grid (SPI1s), both agreed well at the 1-month scale for most of the grid points and those grid points with the lowest critical success index (CSI) are distributed in the middle stream of the Lancang River Basin. (2) The same as SPI1s, the consistency between SPI3s and SPI3g is good for most of the grid points at the 3-months scale, those grid points with the lowest were concentrated in the middle stream and downstream of the Lancang River Basin. (3) At the 1-month scale and 3-months scale, CSI ranged from 50% to 76% for most of the grid points, which demonstrated high accuracy of TMPA in drought monitoring. (4) At the 3-months scale, based on TMPA basin-wide precipitation estimates, though we tended to overestimate (underestimate) the peaks of dry or wet events, SPI3s detected successfully the occurrence of them over the five sub-basins at the most time and captured the occurrence and development of the two severe droughts happened in 2006 and 2009. This analysis shows that TMPA has the potential for drought monitoring in data-sparse regions.
Ecological compensation is a hot subject in academic studies, and the determination of the spatial allocation of compensation payments is a key point in the research of ecological compensation. There are two kinds of thoughts in the determination of regional spatial allocation at present: “evaluation of ecological construction cost” and “evaluation of ecosystem services value”. This paper analyzes the relationships between social ecological compensation and regional socio-economic development, and establishes two econometric models with the data of 2007 from various provinces in China. Through these models, the impacts of geographical endowments on the regional socio-economic development in various provinces are analyzed from the social justice viewpoint and the concept of “equivalent value of geographical endowments” (EGE for short) is proposed. This paper analyzes the application prospect of EGE in the policy making of regional ecological compensation. The results showed that: (1) the implementation of social ecological compensation is not only an effective guarantee for each region to obtain the equal rights of survival, development and decent environment, but also an essential assurance to the coordinated, balanced and sustainable development among various regions; (2) the regional difference in geographical endowments is an important factor affecting the regional spatial variation of socio-economic development. Therefore, geographical endowments are important bases for the determination of the spatial allocation of compensation payments in social ecological compensation; (3) based on the EGE, the government can determine the spatial allocation of social ecological compensation scientifically, and avoid the “sweeping approach” phenomenon in the policy making process of ecological compensation.
The decision tree and the threshold methods have been adopted to delineate boundaries and features of water bodies from LANDSAT images. After a spatial overlay analysis and using a remote sensing technique and the wetland inventory data in Beijing, the water bodies were visually classified into different types of urban wetlands, and data on the urban wetlands of Beijing in 1986, 1991, 1996, 2000, 2002, 2004 and 2007 were obtained. Thirteen driving factors that affect wetland change were selected, and gray correlation analysis was employed to calculate the correlation between each driving factor and the total area of urban wetlands. Then, six major driving factors were selected based on the correlation coefficient, and the contribution rates of these six driving factors to the area change of various urban wetlands were calculated based on canonical correlation analysis. After that, this research analyzed the relationship and mechanism between the main driving factors and various types of wetlands. Five conclusions can be drawn. (1) The total area of surface water bodies in Beijing increased from 1986 to 1996, and gradually decreased from 1996 to 2007. (2) The areas of the river wetlands, water storage areas and pool and culture areas gradually decreased, and its variation tendency is consistent with that of the total area of wetlands. The area of the mining water areas and wastewater treatment plants slightly increased. (3) The six factors of driving forces are the annual rainfall, the evaporation, the quantity of inflow water, the volume of groundwater available, the urbanization rate and the daily average discharge of wastewater are the main factors affecting changes in the wetland areas, and they correlate well with the total area of wetlands. (4) The hydrologic indicators of water resources such as the quantity of inflow water and the volume of groundwater are the most important and direct driving forces that affect the change of the wetland area. These factors have a combined contribution rate of 43.94%. (5) Climate factors such as rainfall and evaporation are external factors that affect the changes in wetland area, and they have a contribution rate of 36.54%. (6) Human activities such as the urbanization rate and the daily average quantity of wastewater are major artificial driving factors. They have an influence rate of 19.52%.
Cultivation is one of the most important human activities affecting the grassland ecosystem besides grazing, but its impacts on soil total organic carbon (C), especially on the liable organic C fractions have not been fully understood yet. In this paper, the role of cropping in soil organic C pool of different fractions was investigated in a meadow steppe region in Inner Mongolia of China, and the relationships between different C fractions were also discussed. The results indicated that the concentrations of different C fractions at steppe and cultivated land all decreased progressively with soil depth. After the conversion from steppe to spring wheat field for 36 years, total organic carbon (TOC) concentration at the 0 to 100 cm soil depth has decreased by 12.3% to 28.2%, and TOC of the surface soil horizon, especially those of 0-30 cm decreased more significantly (p<0.01). The dissolved organic carbon (DOC) and microbial biomass carbon (MBC) at the depth of 0-40 cm were found to have decreased by 66.7% to 77.1% and 36.5% to 42.4%, respectively. In the S.baicalensis steppe, the ratios of soil DOC to TOC varied between 0.52% and 0.60%, and those in the spring wheat field were only in the range of 0.18%-0.20%. The microbial quotients (qMBs) in the spring wheat field, varying from 1.11% to 1.40%, were also lower than those in the S. baicalensis steppe, which were in the range of 1.50%-1.63%. The change of DOC was much more sensitive to cultivation disturbance. Soil TOC, DOC, and MBC were significantly positive correlated with each other in the S. baicalensis steppe, but in the spring wheat field, the correlativity between DOC and TOC and that between DOC and MBC did not reach the significance level of 0.05.
Karamay City is a typical mining city, relying on oilfield exploration and development. After 60 years of construction and development, Karamay has become the first large oilfield and an important base of the national petroleum and petrochemical industry in China. Based on spatial analysis, and Geographic Information Systems (GIS) grid computing and overlay techniques, whilst considering the effect of oilfield development and aimed at the ecological problems of Karamay City in the Xinjiang Uygur Autonomous Region of China, we conducted research on the spatial characteristics of the comprehensive ecological sensitivity of Karamay. The ecological problems of natural environment evolution include soil erosion, land desertification, soil salinization, and biodiversity reduction. The most significant disturbance factor from the activities of humans in this area is oilfield exploitation. This study carries out an analysis of single factor ecological problem sensitivity and integrated ecological sensitivity. The results of the research are as follows: (1) Soil erosion is relatively sensitive, especially in Karamay district, Dushanzi district, north of Urho district and west of Baijiantan district, which is mainly a result of the vertical dropping slopes, serious rainfall erosion and the distribution of scattered woodland. (2) The main types of land desertification are represented by high and moderate grade sensitivities, and high and extremely high sensitive areas are distributed in the intersection of Karamay and Baijiantan districts. This is due to evaporation exceeding rainfall in these areas, and the soil mainly consists of sand and is seldom covered by vegetation. (3) The soil salinizatiion sensitivity grades are mainly moderate, high and extremely high. The highly sensitive areas are mainly distributed in southeast of Baijiantan district, north and east of Karamay district and east of Urho district. The primary causes are evaporation exceeding rainfall and extreme human activities. (4) The main types of biodiversity sensitivity are light and moderate grade. Highly sensitive areas are located in the east and south of Karamay district, north of the Baiyang River basin and parts of the wetland areas. (5) Oil fields development areas are highly ecologically sensitive, which are located in the northern oilfields of Urho district, western oilfields of Baijiantan district, northwestern oilfields of Karamay district and central oilfields of Dushanzi district. (6) The main types of integrated ecological sensitivity are high and moderate. The high and extremely highly sensitive areas are located in the central and northern parts of Karamay district, and southwest of Baijiantan district. The evaluation results will provide guidance for the future planning and development, the protection of the ecological environment and the realization of harmonious social, economic, and ecological development in Karamay City.
Relationship between vegetation and environmental factors has always been a major topic in ecology, but it has also been an important way to reveal vegetation’s dynamic response to and feedback effects on climate change. For the special geographical location and climatic characteristics of the Qaidam Basin, with the support of traditional and remote sensing data, in this paper a vegetation coverage model was established. The quantitative prediction of vegetation coverage by five environmental factors was initially realized through multiple stepwise regression (MSR) models. However, there is significant multicollinearity among these five environmental factors, which reduces the performance of the MSR model. Then through the introduction of the Moran Index, an indicator that reflects the spatial autocorrelation of vegetation distribution, only two variables of average annual rainfall and local Moran Index were used in the final establishment of the vegetation coverage model. The results show that there is significant spatial autocorrelation in the distribution of vegetation. The role of spatial autocorrelation in the establishment of vegetation coverage model has not only improved the model fitting R2 from 0.608 to 0.656, but also removed the multicollinearity among independents.
To understand historical human-induced land cover change and its climatic effects, it is necessary to create historical land use datasets with explicit spatial information. Using the taxes-cropland area and number of families compiled from historical documents, we estimated the real cropland area and populations within each Lu (a province-level political region in the Northern Song Dynasty) in the mid-Northern Song Dynasty (AD1004-1085). The estimations were accomplished through analyzing the contemporary policies of tax, population and agricultural development. Then, we converted the political region-based cropland area to geographically explicit grid cell-based fractional cropland at the cell size of 60 km by 60 km. The conversion was based on calculating cultivation suitability of each grid cell using the topographic slope, altitude and population density as the independent variables. As a result, the total area of cropland within the Northern Song territory in the 1070s was estimated to be about 720 million mu (Chinese area unit, 1 mu = 666.7 m2), of which 40.1% and 59.9% occurred in the north and south respectively. The population was estimated to be about 87.2 million, of which 38.7% and 61.3% were in the north and south respectively, and per capita cropland area was about 8.2 mu. The national mean reclamation ratio (i.e. ratio of cropland area to total land area; RRA hereafter for short) was bout 16.6%. The plain areas, such as the North China Plain, the middle and lower reaches of the Yangtze River, Guanzhong Plain, plains surrounding the Dongting Lake and Poyang Lake and Sichuan Basin, had a higher RRA, being mostly over 40%; while the hilly and mountainous areas, such as south of Nanling Mountains, the southwest regions (excluding the Chengdu Plain), Loess Plateau and southeast coastal regions, had a lower RRA, being less than 20%. Moreover, RRA varied with topographic slope and altitude. In the areas of low altitude (≤250 m), middle altitude (250-100 m) and high altitude (1000-3500 m), there were 443 million, 215 million and 64 million mu of cropland respectively and their regional mean RRAs were 27.5%, 12.6% and 7.2% respectively. In the areas of flat slope, gentle slope, medium slope and steep slope, there were 116 million, 456 million, 144 million and 2 million mu of cropland respectively and their regional mean RRAs were 34.6%, 20.7%, 8.5% and 2.3% respectively.
The agricultural reclamations in the Xiliao River Valley since the Holocene have led to a huge landscape change from grassland to farmland. In this paper we reconsider the man-land relationship in the Xiliao River Valley by analyzing three major agricultural reclamations in prehistory, the Liao-Jin Dynasty and the period since the Qing Dynasty. We argue that when the demographic pressure appears in this area, especially during the last reclamation, the intraregional migration (second migration) is the major response to relieve such pressure, which also distinguishes two different settlement locations: “the initial area” and “the secondary area”. Due to the environmental differences between these two areas, the cultivation on the latter one has caused more serious disturbance to the local environment. Thus the secondary area has become the key region which needs environmental management seriously.
As products of urbanization, cities are focal points for social and economic interaction. Though China is an ancient civilization, only recently has the urban population surpassed that in rural areas. During the last three decades, unprecedented urbanization has reshaped China’s geographical, social, economic and cultural landscapes. Among the social-economic transformations having occurred in China in recent history, urbanization is probably the most impressive and dynamic process; it has changed daily life of Chinese population and profoundly impacted the regional and global economy.
The IGU Regional Conference (UGI 2011) was held on November 14-18, 2011 in Santiago, Chile. It was organized by the Military Geographic Institute (IGM). Nearly 1000 geographers across the world participated in this event. The Geographical Society of China (GSC) sent a delegation consisting of more than 40 members to attend the conference.
