This paper looks at the Green for Grain Project in northern Shaanxi Province.Based on remote sensing monitoring data,this study analyzes the locations of arable land in northern Shaanxi in the years 2000,2010 and 2013 as well as spatio-temporal changes over that period,and then incorporates data on the distribution of terraced fields to improve the input parameters of a RUSLE model and simulate and generate raster data on soil erosion for northern Shaanxi at different stages with a accuracy verification.Finally,combined with the dataset of farmland change,compared and analyzed the characteristics of soil erosion change in the converted farmland to forest(grassland)and the unconverted farmland in northern Shaanxi,so as to determine the project’s impact on soil erosion over time across the region.The results show that between 2000 and 2010,the soil erosion modulus of repurposed farmland in northern Shaanxi decreased 22.7 t/ha,equivalent to 47.08%of the soil erosion modulus of repurposed farmland in 2000.In the same period,the soil erosion modulus of non-repurposed farmland fell 10.99 t/ha,equivalent to 28.6%of the soil erosion modulus of non-repurposed farmland in 2000.The soil erosion modulus for all types of land in northern Shaanxi decreased by an average of 14.51 t/ha between 2000 and 2010,equivalent to 41.87%of the soil erosion modulus for the entire region in 2000.This suggests that the Green for Grain Project effectively reduced the soil erosion modulus,thus helping to protect the soil.In particular,arable land that was turned into forest and grassland reduced erosion most noticeably and contributed most to soil conservation.Nevertheless,in the period 2010 to 2013,which was a period of consolidation of the Green for Grain Project,the soil erosion modulus and change in volume of soil erosion in northern Shaanxi were significantly lower than in the previous decade. 相似文献
Journal of Geographical Sciences - To understand the non-equilibrium morphological adjustment of a river in response to environmental changes, it is essential to (i) accurately identify how past... 相似文献
The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions. With advancement of remote sensing and better understanding of frozen soil dynamics, discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change. However, as an important data source of frozen soil processes, remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes. Although great progress has been made in remote sensing and frozen soil physics, yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies. In the present study, a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed. In order to reduce the uncertainty of the simulation, the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation. The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau. The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%. These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study. The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory. The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil. The average accuracy increased by about 5% after integrating remotely sensed information on the surface soil. The simulation accuracy was significantly improved, especially in transition periods between freezing and thawing of the surface soil. 相似文献
A model integrating geo-information and self-organizing map (SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals (As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows: (1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd. (2) As and Pb had a similar topo-logical distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements. (3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers, factories, and ore zones. (4) The variations of contamination index (CI) followed the trend of construction land (1.353) > forestland (1.267) > cropland (1.175) > grassland (1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.
Journal of Geographical Sciences - The terrestrial hydrological process is an essential but weak link in global/regional climate models. In this paper, the development status, research hotspots and... 相似文献