Based on the collection and processing of the China national-wide monthly station observational precipitation data in 1900-2009, the data series for each station has been tested for their homogeneity with the Standard Normalized Homogeneity Test (SNHT) method and the inhomogeneous parts of the series are adjusted or corrected. Based on the data, the precipitation anomalies during 1900-2009 and the climatology normals during 1971-2000 have been transformed into the grid boxes at 5°×5° and 2°×2° resolutions respectively. And two grid form datasets are constructed by combining the normal and anomalies. After that, the missing values for the 5°×5° grid dataset are interpolated by Empirical Orthogonal Function (EOF) techniques. With the datasets of different resolutions, the precipitation change series during 1900-2009 over Mainland China are built, and the annual and seasonal precipitation trends for the recent 110 years are analyzed. The result indicates that the annual precipitation shows a slight dryer trend during the past 110 years, notwithstanding lack of statistical confidence. It is worth noting that after the interpolation of the missing values, the annual precipitation amounts in the early 1900s become less, which increases the changing trend of the annual precipitation in China for the whole 110 years slightly (from -7.48 mm/100a to -6.48 mm/100a).
Based on the field-survey prototype hydrology data in typical years, the effect during the running periods of different dispatch modes of the Three Gorges Reservoir on the water regimes in Dongting Lake area is comparatively analyzed. The results are shown as follows. (1) The influence periods are from 25 May to 10 June, from 1 July to 31 August, from 15 September to 31 October and from December to the next April, among which the influence of the water-supplement dispatch in the dry season is not very sensitive. (2) During the period under the pre-discharge dispatch, the runoff volume slightly increases as well as both the average water level and the highest water level rise in the usual year. While in the wet and dry years, the average increase in the runoff volume is 40.25×108 m3 and the average rises of the average water level and the highest water level are both 1.06 m. (3) As for the flood-storage dispatch, the flood volume increases slightly, in the dry and wet years, the flood volume, the average water level and the highest water level averagely reduce by 444.02×108 m3, 2.64 m and 1.42 m respectively. (4) Under the water-storage dispatch, the runoff volume slightly increases and the water level heightens in a sort in the usual year. And in the dry and wet years, the average decreases in the runoff volume, the average water level and the highest water levels are respectively 185.27×108 m3, 3.13 m and 2.14 m. (5) During the period under the water-supplement dispatch, the runoff volume, the average water level and the highest water levels averagely decline by 337.7×108 m3, 1.89 m and 2.39 m respectively in the usual and wet years. However, in the dry year, the runoff volume increases as well as the average and highest water levels slightly go up.
The concept of mass elevation effect (massenerhebungseffect, MEE) was introduced by A. de Quervain about 100 years ago to account for the observed tendency for temperature-related parameters such as tree line and snowline to occur at higher elevations in the central Alps than on their outer margins. It also has been widely observed in other areas of the world, but there have not been significant, let alone quantitative, researches on this phenomenon. Especially, it has been usually completely neglected in developing fitting models of timberline elevation, with only longitude or latitude considered as impacting factors. This paper tries to quantify the contribution of MEE to timberline elevation. Considering that the more extensive the land mass and especially the higher the mountain base in the interior of land mass, the greater the mass elevation effect, this paper takes mountain base elevation (MBE) as the magnitude of MEE. We collect 157 data points of timberline elevation, and use their latitude, longitude and MBE as independent variables to build a multiple linear regression equation for timberline elevation in the southeastern Eurasian continent. The results turn out that the contribution of latitude, longitude and MBE to timberline altitude reach 25.11%, 29.43%, and 45.46%, respectively. North of northern latitude 32°, the three factors’ contribution amount to 48.50%, 24.04%, and 27.46%, respectively; to the south, their contribution is 13.01%, 48.33%, and 38.66%, respectively. This means that MBE, serving as a proxy indicator of MEE, is a significant factor determining the elevation of alpine timberline. Compared with other factors, it is more stable and independent in affecting timberline elevation. Of course, the magnitude of the actual MEE is certainly determined by other factors, including mountain area and height, the distance to the edge of a land mass, the structures of the mountains nearby. These factors need to be included in the study of MEE quantification in the future. This paper could help build up a high-accuracy and multi-scale elevation model for alpine timberline and even other altitudinal belts.
The aim of this work is the determination of regional-scale rainfall thresholds for the triggering of landslides in the Tuscany Region (Italy). The critical rainfall events related to the occurrence of 593 past landslides were characterized in terms of duration (D) and intensity (I). I and D values were plotted in a log-log diagram and a lower boundary was clearly noticeable: it was interpreted as a threshold representing the rainfall conditions associated to landsliding. That was also confirmed by a comparison with many literature thresholds, but at the same time it was clear that a similar threshold would be affected by a too large approximation to be effectively used for a regional warning system. Therefore, further analyses were performed differentiating the events on the basis of seasonality, magnitude, location, land use and lithology. None of these criteria led to discriminate among all the events different groups to be characterized by a specific and more effective threshold. This outcome could be interpreted as the demonstration that at regional scale the best results are obtained by the simplest approach, in our case an empirical black box model which accounts only for two rainfall parameters (I and D). So a set of thresholds could be conveniently defined using a statistical approach: four thresholds corresponding to four severity levels were defined by means of the prediction interval technique and we developed a prototype warning system based on rainfall recordings or weather forecasts.
Based on energy consumption data of each region in China from 1997 to 2009 and using ArcGIS9.3 and GeoDA9.5 as technical support, this paper made a preliminary study on the changing trend of spatial pattern at regional level of carbon emissions from energy consumption, spatial autocorrelation analysis of carbon emissions, spatial regression analysis between carbon emissions and their influencing factors. The analyzed results are shown as follows. (1) Carbon emissions from energy consumption increased more than 148% from 1997 to 2009 but the spatial pattern of high and low emission regions did not change greatly. (2) The global spatial autocorrelation of carbon emissions from energy consumption increased from 1997 to 2009, the spatial autocorrelation analysis showed that there exists a “polarization” phenomenon, the centre of “High-High” agglomeration did not change greatly but expanded currently, the centre of “Low-Low” agglomeration also did not change greatly but narrowed currently. (3) The spatial regression analysis showed that carbon emissions from energy consumption has a close relationship with GDP and population, R-squared rate of the spatial regression between carbon emissions and GDP is higher than that between carbon emissions and population. The contribution of population to carbon emissions increased but the contribution of GDP decreased from 1997 to 2009. The carbon emissions spillover effect was aggravated from 1997 to 2009 due to both the increase of GDP and population, so GDP and population were the two main factors which had strengthened the spatial autocorrelation of carbon emissions.
The agricultural and land policies in China are always focused on protecting its food supply and security because of the country’s large population and improved diets. The crop production guide ‘Take Grain as the Key Link’ prompted peasants to plant grain on most of the agricultural land, leading to the majority of fertilizer being used in grain crops for many years in China. This situation has changed dramatically in recent years. Based on data pertaining to provincial crops sown area and fertilizer use per unit area in 1998 and 2008, the temporal and spatial variations of China’s fertilizer consumption by crops were analyzed at the provincial level, and the results are presented here. (1) Fertilizer consumption in China grew strongly in the last decade, while the growth was mainly attributable to the increase of fertilizer consumption by horticultural crops. The fertilizer consumption of grain crops dropped from 71.0% in 1998 to 57.8% in 2008. Thus, it is concluded that the emphasis of fertilizer consumption is shifting toward horticultural crops. (2) There were marked differences in the growth rates of fertilizer consumption from the regional point of view. The national average growth rate of fertilizer consumption was 31.9% during 1998-2008. The western and northeastern parts of the country came close to the national average, while the eastern part was lower, with an average of 13.0%, and central China was much higher (50.8%). The increase of fertilizer consumption in central and west China was higher than the other zones, which already accounted for 77.9% of the national total. Thus, it is concluded that the consumption emphasis of chemical fertilizer shifts toward the central and western regions. (3) The decline of fertilizer consumption by grain crops was largely due to the decrease in sown area compared with the increase by vegetable crops attributable to the enlarging sown area; the increase by orchard crops was affected by both expanding the sown area and fertilizer use per unit area.
Rice cropping systems not only characterize comprehensive utilization intensity of agricultural resources but also serve as the basis to enhance the provision services of agro-ecosystems. Yet, it is always affected by external factors, like agricultural policies. Since 2004, seven consecutive No.1 Central Documents issued by the Central Government have focused on agricultural development in China. So far, few studies have investigated the effects of these policies on the rice cropping systems. In this study, based upon the long-term field survey information on paddy rice fields, we proposed a method to discriminate the rice cropping systems with Landsat data and quantified the spatial variations of rice cropping systems in the Poyang Lake Region (PLR), China. The results revealed that: (1) from 2004 to 2010, the decrement of paddy rice field was 46.76 km2 due to the land use change. (2) The temporal dynamics of NDVI derived from Landsat historical images could well characterize the temporal development of paddy rice fields. NDVI curves of single cropping rice fields showed one peak, while NDVI curves of double cropping rice fields displayed two peaks annually. NDVI of fallow field fluctuated between 0.15 and 0.40. NDVI of the flooded field during the transplanting period was relatively low, about 0.20?0.05, while NDVI during the period of panicle initiation to heading reached the highest level (above 0.80). Then, several temporal windows were determined based upon the NDVI variations of different rice cropping systems. (3) With the spatial pattern of paddy rice field and the NDVI threshold within optimum temporal windows, the spatial variation of rice cropping systems was very obvious, with an increased multiple cropping index of rice about 20.2% from 2004 to 2010. The result indicates that agricultural policies have greatly enhanced the food provision services in the PLR, China.
Spatially-explicit estimation of aboveground biomass (AGB) plays an important role to generate action policies focused in climate change mitigation, since carbon (C) retained in the biomass is vital for regulating Earth’s temperature. This work estimates AGB using both chlorophyll (red, near infrared) and moisture (middle infrared) based normalized vegetation indices constructed with MCD43A4 MODerate-resolution Imaging Spectroradiometer (MODIS) and MOD44B vegetation continuous fields (VCF) data. The study area is located in San Luis Potosí, Mexico, a region that comprises a part of the upper limit of the intertropical zone. AGB estimations were made using both individual tree data from the National Forest Inventory of Mexico and allometric equations reported in scientific literature. Linear and nonlinear (exponential) models were fitted to find their predictive potential when using satellite spectral data as explanatory variables. Highly-significant correlations (p=0.01) were found between all the explaining variables tested. NDVI62, linked to chlorophyll content and moisture stress, showed the highest correlation. The best model (nonlinear) showed an index of fit (Pseudo-r2) equal to 0.77 and a root mean square error equal to 26.00 Mg/ha using NDVI62 and VCF as explanatory variables. Validation correlation coefficients were similar for both models: linear (r=0.87**) and nonlinear (r=0.86**).
Landform classification is commonly done using topographic altitude only. However, practice indicates that locations at a same altitude may have distinctly different landforms, depending on characteristics of soils underneath those locations. The objectives of this study were to: 1) develop a landform classification approach that is based on both altitude and soil characteristic; and 2) use this approach to determine landforms within a watershed located in northern Ordos Plateau of China. Using data collected at 134 out of 200 sampling sites, this study determined that D10 (the diameter of soil particles 10% finer by weight) and long-term average soil moisture acquired in 2010, which can be estimated at reasonable accuracy from remote sensing imagery, can be used to represent soil characteristics of the study watershed. Also, the sampling data revealed that this watershed consists of nine classes of landforms, namely mobile dune (MD), mobile semi-mobile dune (SMD), rolling fixed semi-fixed dune (RFD), flat sandy land (FD), grassy sandy land (GS), bedrock (BR), flat sandy bedrock (FSB), valley agricultural land (VA), and swamp and salt lake (SW). A set of logistic regression equations were derived using data collected at the 134 sampling sites and verified using data at the remaining 66 sites. The verification indicated that these equations have moderate classification accuracy (Kappa coefficients K>43%). The results revealed that the dominant classes in the study watershed are FD (36.3%), BR (27.0%), and MD (23.5%), while the other six types of landforms (i.e., SMD, RFD, GS, FSB, VA, and SW) in combination account for 13.2%. Further, the landforms determined in this study were compared with the classes presented by a geologically-based classification map. The comparison indicated that the geologically-based classification could not identify multiple landforms within a class that are dependent upon soil characteristics.
Using ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) infrared remote sensing data we inversed the parameters of urban surface heat fluxes applying the PCACA model and theoretical position algorithm, and then we analyzed the influence of different land use types on the surface heat fluxes and energy balance. In this study, Kumagaya, a city in Saitama Prefecture, Japan, was selected as the experimental area. The result shows that the PCACA model is feasible for the surface heat fluxes estimation in urban areas because this model requires less parameters in the procedure of heat fluxes estimation in urban areas with complicated surface structure and can decrease the uncertainty. And we found that different land-use types have indicated the height heterogeneity on the surface heat fluxes significantly. The magnitudes of Bowen ratio in descending order are industrial, residential, transportation, institutional, dry farmland, green space, and water body. Under the same meteorological condition, there are distinct characteristics and regional differences in Bowen ratios among different surface covers, indicating higher sensible heat flux and lower latent heat flux in the urban construction land, while lower sensible heat flux and higher latent heat flux in the vegetation-covered area, the outskirt of the urban area. The increase of urban impervious surface area caused by the urban sprawl can enlarge the sensible heat flux and the Bowen ratio, so that it causes the increasing of urban surface temperature and air temperature, which is the mechanism of the so-called heat island effect.
Many studies on land use change (LUC), using different approaches and models, have yielded good results. Applications of these methods have revealed both advantages and limitations. However, LUC is a complex problem due to influences of many factors, and variations in policy and natural conditions. Hence, the characteristics and regional suitability of different methods require further research, and comparison of typical approaches is required. Since the late 1980s, CA has been used to simulate urban growth, urban sprawl and land use evolution successfully. Nowadays it is very popular in resolving the LUC estimating problem. Case-based reasoning (CBR), as an artificial intelligence technology, has also been employed to study LUC by some researchers since the 2000s. More and more researchers used the CBR method in the study of LUC. The CA approach is a mathematical system constructed from many typical simple components, which together are capable of simulating complex behavior, while CBR is a problem-oriented analysis method to solve geographic problems, particularly when the driving mechanisms of geographic processes are not yet understood fully. These two methods were completely different in the LUC research. Thus, in this paper, based on the enhanced CBR model, which is proposed in our previous research (Du et al. 2009), a comparison between the CBR and CA approaches to assessing LUC is presented. LUC in Dongguan coastal region, China is investigated. Applications of the improved CBR and the cellular automata (CA) to the study area, produce results demonstrating a similarity estimation accuracy of 89% from the improved CBR, and 70.7% accuracy from the CA. From the results, we can see that the accuracies of the CA and CBR approaches are both >70%. Although CA method has the distinct advantage in predicting the urban type, CBR method has the obvious tendency in predicting non-urban type. Considering the entire analytical process, the preprocessing workload in CBR is less than that of the CA approach. As such, it could be concluded that the CBR approach is more flexible and practically useful than the CA approach for estimating land use change.
Soil loss tolerance (T) is the maximum rate of annual soil erosion that is tolerated and still allows a high level of crop productivity to be sustained economically and indefinitely. In the black soil region of Northeast China, an empirically determined, default T value of 200 (t/km2·a) is used for designing land restoration strategies for different types of soils. The objective of this study was to provide a methodology to calculate a quantitative T for different black soil species. A field investigation was conducted to determine the typical soil profiles of 21 black soil species in the study area and a quantitative methodology based on a modified soil productivity index model was established to calculate the T values. These values, which varied from 68 t/km2·a to 358 t/km2·a, yielded an average T value of 141 t/km2·a for the 21 soil species. This is 29.5% lower than the current national standard T value. Two significant factors that influenced the T value were soil thickness and vulnerability to erosion. An acceptable reduction rate of soil productivity over a planned time period of 1% is recommended as necessary for maintaining long-term sustainable soil productivity. Compared with the currently used of regional unified standard T value, the proposed method, which determines T using specific soil profile indices, has more practical implications for effective, sustainable management of soil and water conservation.
High accuracy surface modeling (HASM) is a method which can be applied to soil property interpolation. In this paper, we present a method of HASM combined geographic information for soil property interpolation (HASM-SP) to improve the accuracy. Based on soil types, land use types and parent rocks, HASM-SP was applied to interpolate soil available P, Li, pH, alkali-hydrolyzable N, total K and Cr in a typical red soil hilly region. To evaluate the performance of HASM-SP, we compared its performance with that of ordinary kriging (OK), ordinary kriging combined geographic information (OK-Geo) and stratified kriging (SK). The results showed that the methods combined with geographic information including HASM-SP and OK-Geo obtained a lower estimation bias. HASM-SP also showed less MAEs and RMSEs when it was compared with the other three methods (OK-Geo, OK and SK). Much more details were presented in the HASM-SP maps for soil properties due to the combination of different types of geographic information which gave abrupt boundary for the spatial variation of soil properties. Therefore, HASM-SP can not only reduce prediction errors but also can be accordant with the distribution of geographic information, which make the spatial simulation of soil property more reasonable. HASM-SP has not only enriched the theory of high accuracy surface modeling of soil property, but also provided a scientific method for the application in resource management and environment planning.
The Bohai Rim region is one the most important bases for commodity grain production in China. With the rapid pace of agricultural industrialization, nitrogenous fertilizer has been used at an ever increasing rate, which resulted in the trace of accumulative nitrogen in the soil and caused serious environmental problems. In this study we made use of the farmland nitrogen balance model to assess the spatial difference of farmland nitrogen nutrient budget in the Bohai Rim region in 2008 with the assistance of GIS. Our results indicated that: 1) Farmland in this region has a nitrogen surplus totaling 5.0822 million tons, or an average of 288.54 kg/ha. 2) In the Bohai Rim region, farmland nitrogen input and farmland nitrogen budget both show a spatial differentiation. Major grain-producing areas have a higher nitrogen input than that of the grazing-farming areas. The main sources of nitrogen input include chemical fertilizer, organic fertilizer, deposition from atmospheric drying and wetting, and biological fixation, which account for 79.47%, 9.53%, 4.62%, and 3.58% of the total input, respectively. Therefore, chemical fertilizer is the predominant source of nitrogen input to farmland. 3) A total of 3.3398 million tons of nitrogen were output from the farmland via harvested crops and it accounts for 52.36% of the total nitrogen output from farmland in this region. On average, the amount of nitrogen output from unit farmland is equal to 176.65kg/ha. This study has shed light on farmland nitrogen budget and its spatial variation in the study area, may provide scientific evidences for rationalizing the use of chemical fertilizer and managing agricultural operation on the regional scale and is also valuable for improving the economic and ecological efficiency of fertilizer use at the regional scale.