Based on the application of the decoupling theory between environmental pressure and economic development and improved elastic analysis decoupling degree judgment standards, this paper attempted to make quantitative and comprehensive analysis of the features or rules of temporal-spatial evolution of decoupling degrees between resource environment and economic development of the Yangtze River Delta, with a time span from 2000 to 2009. The results show that: the relationship between resources-environment and economic growth of the Yangtze River was generally in the order of relative decoupling Ⅱ-relative decoupling Ⅲ-relative decoupling Ⅱ-relative decoupling Ⅰ, and the impact between economic growth and resources-environmental enhanced the impact during 2000-2005, then reduced during 2005-2009; the relationship between each index of resources-environment and economic development was generally in a state of relative decoupling, and decoupling degree of resource consumption and environmental pressure and comprehensive resource presented differences in time and indexes; in most of the time period, the Yangtze River Delta was in a relatively decoupling state, including 10 cities resources environment and economic growth on the decoupling relationship of "N" trend, and the pressure between economic development and resources-environment reached the highest in 2004 and 2005 in the Yangtze River Delta. Shanghai was wandering between absolute decoupling and relative decoupling Ⅰ, and Jiangsu and Zhejiang showed apparent internal differences.
A water resources supply and demand system dynamic model was built up based on the systematic analysis of characteristics and the inter-relationship of sub-systems of water resources supply and demand system in Dongting Lake District. In modeling, four scenarios, as traditional development model, economic development model, water saving model and concerted development model, were simulated to calculate the changing trends of the balance of water resources supply and demand in Dongting Lake District from 2010 to 2030. The simulation suggests that: 1) The problem of water resources supply and demand is becoming increasingly conspicuous with growing population and fast developed economy. 2) By 2030, the water resources demand will be reaching a total of 159.1×108 m3, the largest gap between supply and demand is 1.9×108 m3 in 2020, and the supply surplus of water resources is 3.6×108 m3 in 2030, water resources supply meets basically the growing demands for socio-economic development, and the greatest comprehensive benefits under concerted development model can be generated, hence it will be the best solution to the development and utilization of water resources in Dongting Lake District. 3) We should enhance our awareness of protection of water resources, strengthen the management on water conservation, optimize economic structure, increase our investment in water conservancy projects and environmental improvement, promote the utilization ratio and the support capabilities of water resources so as to realize the expected goal.
Climate change, causing transformation of climate resources, results in food security problem. The coupling of regional climate model with crop growth model can be used to quantitatively analyze crop yield variability under climate change, and to propose suitable field management for maintaining crop yield. Taking northwest plain of Shandong Province, which is one of the major food producing areas of China, as a research region, this study analyzed effect of climate change on winter wheat yield and its adaptation measurement under A1B climate change scenario, by means of coupling regional climate model with crop growth model. The results shows winter wheat yield will decrease under A1B climate change scenario. Taking the measures of cultivating new variety with a character of less sensible to vernalization, appropriate advancing sowing date and increasing the amount of overwintering irrigation can yield security and reduce annual variability.
In order to understand the vegetation phenological variation of Zhejiang Province and further improve the vegetation response to climate change mechanism, the vegetation phonological variation and relationship with the climate factors were deeply analyzed based on the reconstructed MODIS NDVI time-series using the improved Savitzky-Golay algorithm, the vegetation growth condition was retrieved, and the vegetation phenological metrics (the beginning data, the ending data and length of growing season) were extracted adopting the piecewise polynomial fitting and dynamic threshold method, the vegetation phenology interannual variation trend and its spatial pattern were analyzed, the relationship between the vegetation changes and the climate variations were discussed combined with the meteorological data. The results showed that the vegetation cover expressed slowly decreasing trend, while the length of growth season was slightly extended. The vegetation growing season was from late March to mid November, and the average length of growing season was about 222 days. In the past 10 years, the beginning time of growth season expressed the advance trend, but not significant, and the ending time was significantly delayed. The length of growing season was extended, about 7 days every 10 years. The spatial pattern of the begining time of growing season was delayed from north to south, the ending time was relatively concentrated in November, vegetation growing season of extended area was similar to the shortened area, about 32.40% and 31.88% of the effective pixel respectively. The correlation analysis of phenological metrics and climate factors indicated that heat supply in winter is the important factor for vegetation growth, and the increased cumulative temperature could prompt the start of vegetation growing season. The end of the growing season was positively related with mean temperature while precipitation and humid index were negatively correlated, but not significant, from the view of the month and seasonal scale, the humidity in autumn affected larger on the ending time of growing season.
Shortage of water resources and extreme drought limited crop production in Heihe River Basin in Northwest China. The concerned areas are also affected by serious wind erosion, and intensive tillage of conventional agriculture has worsened the situation. Therefore, conventional tillage (CT) and four conservation tillage were studied to analyze the effects of different tillage on soil water storage dynamics, soil moisture profile of the key growth period, grain yield and water use efficiency (WUE) through field experiment implemented in Zhangye from 2003 to 2005. The aim of the research is to identify a suitable conservation agriculture practice for this area. The results showed that conservation tillage increased the soil water storage compared with that of the conventional tillage. At the end of fallow stage, soil water storage of no tillage with 40 cm pressed stubble (NPS40), no tillage with 40 cm standing stubble (NS40), no tillage with 20 cm standing stubble (NS20) and no tillage with 20 cm pressed stubble (NPS20) in 0-30 cm soil layer was increased by 30.22%, 27.29%, 20.92% and 13.64% in 2003, and 48.32%, 38.90%, 29.85% and 23.28% in 2004, compared with that of CT. Soil water content in 0-5 cm soil layer of NPS40, NS40, NPS20 and NS20 was increased by 37.29%, 37.10%, 21.49% and 41.90% in 2004, and 33.99%, 40.17%, 8.90% and 38.44% in 2005 compared to the conventional tillage at sowing time. Conversation tillage changed the soil water supplying characteristics that could supply more water for crop growth and development under the conditions of water shortage, while saving more for coming stage when soil water was sufficient. Conservation tillage increased grain yield and WUE which was increased by 53.08% and 5.85% in 2004 and 52.04% and 7.30% in 2005 in NPS20 compared to the conventional tillage.
In order to study influence of quantitative degree of climate factors and human activities (environmental changes) on the surface runoff, clustering analysis was applied to determine the benchmark period of the Luanhe River Basin runoff variation and influence period of human activities, and HBV model was used to restore the natural runoff, identify the quantitative analysis influence degree of climate change and human activities for the Luanhe River Basin. The results showed the period before 1979 was the benchmark period of the runoff series, HBV model has a good simulation effect on the Luanhe River Basin runoff, human activities have an intensified influence on the runoff. After 1980, natural runoff and measured runoff separated. The change of human activities affected period (1980-2007) was compared with the benchmark period (1960-1979). The influence of climate factors and human activities on runoff amount accounted for 55% and 45% of the total reduced runoff. At different levels, human activities have different effects on runoff, but the analysis found that with the intensification of human activities, the impact of climatic factors in the Luanhe River Basin is gradually weakened, the impact of human activities is increased in the basin.
The balance of grain supply and demand accurately reflects the condition of grain supply and demand. It is of great significance to ensure grain security. Existing studies usually focus on single factor of grain supply and demand, however, the spatial-temporal changes of the relationship between grain supply and demand, especially how urbanization influences them are rarely involved. Basing on the statistic data concerning grain production and population of Guangdong Province from 1994 to 2009, and taking Guangdong Province as the research object, the space differentiation is analyzed through constructing space cluster-diffusion and contribution index and the relationship between urbanization level and the balance of grain supply and demand is analyzed with Granger causality test. Since 1994, the balance of grain supply and demand of Guangdong Province appears rise and diffusion and grain shortages change to common phenomenon. The balance of grain supply and demand of the 21 cities tends to slow down growth and the difference among them appears smaller. The spatial distribution characteristic of cities leading grain needs is cluster→diffusion→cluster, and for cities with high contribution rate is diffusion. The balance of grain supply and demand has significant spatial differences. All the 21 cities can be divided into four types as high growth index with high contribution rate, high growth index with low contribution rate, low growth index with high contribution rate and low growth index with low contribution rate. Granger causality test indicates the improvement of urbanization level can enlarge the per capita share of the balance of grain supply and demand in low urbanization regions.
Climate change has exerted increasing impacts on glaciers, not only on rainfall and snowfall, but also on landscape pattern. Analysis of the glacier patch dynamics, based on RS and GIS data, in the middle Qilian Mountains showed that the glacier patch area was reduced by 15.39%, small patches with an area less than 1 hm2 was reduced by more than 50%, patch shape index was declined in general, and the dominance of the largest patch was reduced too from 2001 to 2009. It thus made the mean Euclidean Distance between patches increased by 16.56 m. The patch connectivity had scale dependent effect and was higher in 2009 than that in 2001 when the threshold value was set less than 7000 m; when the threshold value was set more than 7000 m, the connectivity was changed reversely. In terms of patch types, the ablation patches played an important role in glacier degradation, and the ablation area was 744.30 hm2, about 16.53% of the glacier area at the beginning. Simultaneously, the generated patches were produced but increased only by 1.15% of the glacier area at the beginning. There was a positive correlation between the ablation and generated glacier patch areas in the period from 2001 to 2009.
The cultivated land quality can influence crop yield and agricultural sustainable development obviously. Taking Guangrao County in Shandong Province as a case study, this paper explored the cultivated land quality evaluation based on GIS. Evaluation factors are chosen by Delphi approach and cluster analysis with their weights determined by AHP method, the grades of cultivated land quality are evaluated by fuzzy discrimination method based on 50 m×50 m raster data in 1979 and 2007. Also, the changing situation of cultivated land quality from 1979 to 2007 is analyzed with GIS. The result shows that, the changing situation of evaluation factors of cultivated land is different, the physiognomy and soil physical character change slowly, but the soil nutrient changes greatly, especially the organic matter and available nitrogen. Cultivated land quality grade in 1979 has an obvious decreasing distribution from south to north, the cultivated land with high grades was distributed in the southwestern part and which with low grades was in the northeastern. The area of the cultivated land in 1979 with the first grade and the second grade accounts for 12.84% of the total area, while the third and the fourth grade is 63.61% of the total area, and the fifth and the sixth grade is 23.55% of the total area. Generally speaking, the cultivated land quality in 1979 was mostly with moderate grades. And the area of the cultivated land in 2007 with the first grade and the second grade is 62.89% of the total area, while the third and the fourth grade is 36.37% of the total area, and the fifth and the sixth grade is only 0.73% of the total area. Obviously, the cultivated land quality in 2007 was mostly with high grades. Cultivated land quality grades have an obvious decreasing distribution from southwestern inland to northeastern coastal area both in 1979 and 2007. The cultivated land quality improved obviously form 1979 to 2007 because of perfection of basic facilities and improvement of soil nutrition, especially in the southern part of Guangrao County.
Based on meteorological data from 48 monitoring stations during 1961-2009, the spatial distribution and temporal trends of meteorological elements on the Loess Plateau were analyzed with Inverse Distance Weighted Interpolation and Mann-Kendall methods. Results show that the meteorological elements on the Loess Plateau spatially distributed with an obvious gradients. Precipitation and mean temperature decreased while mean wind speed and sunshine hours increased from southeast to northwest, relative humidity decreased while reference evapotranspiration increased from south to north. Monotonic trends were detected on most stations for each meteorological element; however, the numbers of stations with significant trends were different. About 98% of stations had significant upward trends in mean temperature, 60% of stations had significant downward trends in sunshine hours and wind speed and upward trends in reference evapotranspiration, 40% of stations had significant downward trends in relative humidity, and 30% of stations had significant downward trends in precipitation. Interdecadal variation existed in each meteorological element. Relative humidity decreased significantly since 2004; precipitation decreased, mean temperature and reference evapotranspiration increased significantly since the 1990s; the significant decrease in sunshine hours and wind speed was from the 1980s. Some new changing trends in climate were detected on the Loess Plateau, which might cause some uncertainties for the sustainable development of this region; therefore, more attention should be paid to this issue.
Based on meteorological and forage observation data from 21 meteorological stations in typical steppe, Inner Mongolia, together with potential evapotranspiration model and improved crop coefficient, crop coefficient and actual evapotranspiration were studied. This study analyzed spatial and temporal distribution characteristics using GIS, which were tested based on the NDVI variation trend. The result shows the maximum of Kcx rose from 0.6 to 1.4 from May to August, while the mean value was 0.28, 0.36, 0.40 and 0.38 respectively. The Kcx value region from 0.2 to 0.6 accounts for more than 55% of the total Kcx value region. The spatial and temporal distribution of actual evapotranspiration was consistent with Kcx value. Low-value region area decreased gradually over the four-month period, while the high-value region area went up. The evapotranspiration value region ranged from 30 to 90 mm, constituting the main part during the entire growing season. The correlation coefficient of forage actual evapotranspiration and NDVI value is 0.446 (P<0.01). It is practicable to use this research method in analyzing the evapotranspiration in steppe area.
Drought analysis through multivariate joint distributions can determine the evolution rules of drought. Three drought variables, i.e., drought duration, drought severity and drought peak, were selected from long sequence of monthly rainfall data for Urumqi and Shihezi weather stations in Xinjiang, China. Two-dimension and three-dimension joint distributions of drought variables were analyzed based on four kinds of symmetric Archimedean Copulas functions. And three-dimension joint distributions of drought variables were analyzed using five kinds of asymmetric Archimedean Copulas functions. Furthermore their return periods were determined. Test of goodness of fit showed that, Frank Copula function was the best when it was applied to two-dimension joint distribution for drought duration-drought severity, and drought duration-drought peak.Clayton Copula function was the best when it was applied to two-dimension joint distributions of drought severity-drought peak and three-dimension joint distribution of the three drought variables. The return period of single variable ranged between return periods of the two-dimension, three-dimension and co-occurrence. This study showed that Copulas function can describe multivariate joint distributions of drought variables well.
Record length of rainfall datasets is an important element which should be taken into account in the process of computing the mean annual rainfall erosivity. Based on the monthly rainfall datasets for the period 1980-2009, the annual rainfall erosivity for 601 weather stations of China was calculated using a simplified method originally proposed by Wischmeier and Smith. According to the theory of statistics, by drawing simple random samples of 30 years, 20 years, 10 years and 5 years of the datasets, the confidence coefficients of the mean annual rainfall erosivity were calculated based on the percent sampling errors of 10% and 25%. The results suggest that: 1) record length of datasets does have an effect on the confidence level for the mean annual rainfall erosivity; 2) the confidence coefficients for the mean annual rainfall erosivity vary greatly across China, and higher confidence level lies in south of the Yangtze River, eastern Tibetan Plateau and the mountainous area in southern part of Hexi Corridor; 3) when modeling soil erosion with limited rainfall data, it’s necessary to analyze the confidence level of sampling error by setting the allowable errors of the mean annual rainfall erosivity according to the research goal and predefined accuracy.
Considering the difficulty in the estimation of sustainable development due to the complex ecological pressure influencing factors, this paper proposed the radial basis function neural network model for predicting urban ecological system pressure and analyzed the primary influencing factors on urban ecological system pressure. The model was studied on the basis of Fushun’s data during 1995-2009, the accuracy of the radial basis function neural network prediction model is validated and then the situation of urban ecological system pressure was predicted from 2010 to 2015. The results of the study showed that the energy consumption indicator was the primary influencing factor for urban ecological system pressure; the fitting and simulation precision for training and testing samples were 97.91% and 94.16% by using radial basis function neural network model, respectively; the ecological footprint, the ecological carrying capacity and the ecological deficit would be 7.013, 0.523 and 6.49 hm2/cap for Fushun in 2015, respectively.
Spatial data, like land-use data, have a tendency to be dependent (spatial autocorrelation), which means that when using spatial models, a part of the variance may be explained by neighboring values. Through incorporating components describing the spatial autocorrelation into a classic logistic model, this study sets up a regression model (Autologistic model), and uses the model to simulate and analyze the spatial land use patterns in Ganzhou District of Zhangye City. Then the scenario simulation of the land use/cover change in 2020 in the study area was modeled by CLUE-S (The Conversion of Land Use and its Effects at Small Region Extent) model. The results show that: (1) Through comparison with the classic logistic model without considering the spatial autocorrelation, the Autologistic model showed better goodness of fitting and higher accuracy of fitting. The distribution of land use types of cultivated land, forestland, water area and unused land yielded areas under the ROC curves (AUC) were improved to 0.924, 0.892, 0.766, 0.716 and 0.835 respectively when using autologistic model. (2) The land use type spatial pattern of 2009 was simulated based on the LUCC data of 2005. The Kappa index based on Autologistic model and logistic model is 0.9354 and 0.8880, respectively,which means the accuracy of CLUE-S model was increased by Autologistic model. (3) This paper simulates the land use pattern of 2020 based on the five scenarios indicated that there existed an obvious spatial difference during different scenarios of LUCC model. 1) Under natural growth scenario, the increase of arable land is important for food security, and the expansion of construction land area will promote the economic development, but the woodland and grassland conversion to unused land will exacerbate land degradation and ecological environmental degradation. 2) Under three water resource restriction scenarios, the water resources serve as very important restriction factors for land use/cover change, and improvement of the utilization of water resources is an important measure to improve the ecological environment in arid areas. 3) Under the land use structure optimization scenario, the land use was more rational because of taking into account the needs of food security, ecological protection and economic development in the study area. 4) Under the scenario of economic development, the construction land was rapidly expanded, and food security would be threatened due to occupation of lots of high quality cultivated land and grassland. 5)Under the ecological protection scenario, the regional eco-environmental quality could be improved to a large extent in woodland, grassland and water area.
By defining the concepts of carbon harvest and carbon harvest table and then using the second orthogonal rotation design to set standards plots of Cunninghamia lanceolata plantation in Fujian Province and by investigating and then measuring the carbon contents in different parts of a sampling tree and carbon stocks in different forest stands in the representative Cunninghamia lanceolata plantation, carbon harvest model of individual tree based on the relative growth equation with the independent variables of DBH, tree height and wood volume and stand carbon harvest table of variable density with the independent variables of average DBH, average tree height, density index and stand volume were respectively established in Cunninghamia lanceolata plantation in order to reveal the relationships between forest carbon harvest and forest stand of plantation especially Cunninghamia lanceolata plantation in Fujian Province from the point of view of yield prediction. The estimating accuracies of the carbon harvest models and the stand carbon harvest tables in Cunninghamia lanceolata plantation were high, both of which were more than 95% upon testing. In addition, the influences of single wood volume and stand forest stock volume on carbon harvest were fully considered by the models and tables. There are good application values in forest carbon sink estimation as the models and tables have excellent compatibility and strong operability. When the established carbon harvest models and tables of Cunninghamia lanceolata plantation were applied to estimate carbon harvest of a single wood or a forest stand in a reality Cunninghamia lanceolata plantation, the results were perfect with high accuracy. Especially, the proportional error was only 4.70% in the carbon harvest model of a single wood which indicated that the carbon harvest models and stand carbon harvest tables established in the paper could be used to estimate carbon storage or stock of a single tree and a forest stand in a Cunninghamia lanceolata plantation in Fujian Province, which would enrich the content of dynamic prediction of forest resources, provide reference for the monitoring of forest resources in the province and accumulate basic data for other relevant researches.
