Soil Erosion Of Small Watershed Study By GIS Technology

Water and soil loss, the root of many disasters, is extremely unfavorable for humanenvironment. Millions of hectares of arable land disappeared in the world annually, whileChina is the one of the countries which is confronting with the severe water and soil loss. Theintensive soil erosion, that is the key factor of water and soil loss which makes the LoessPlateau emerge the criss-cross ravines and gullies. It is high time to utilize high-tech to studythe regular pattern on soil erosion, in order to effectively control water and soil loss. Smallwatershed is the basic unit running through the process as emerge and exacerbation of soilerosion in the Loess Plateau. So, the fundamental studies such as soil erosion, water and soilloss control, basing on the small watershed as unit, is in accordance with natural andeconomic laws, and conducive to radically control water and soil loss at root, so as torationally use and conserve of soil and water resources.We collected a large number of geographic information data from small watershednamed Nanxiaohegou in Qingyang City, Gansu Province, detailed analyzed the variousfactors affecting soil erosion , adopted Universal Soil Loss Equation(USLE) model aftercomprehensive compared and assessed several international model for calculating soil erosion,and combined with GIS and remote sensing technology to quantitative study on soil erosionoriented small watershed.On this thesis, we selected the six factors affecting soil erosion as soil parent materials,vegetation cover, terrain slope, slope length,rainfall,and soil and water conservation,obtained vegetation and land use information and extracted the vegetational cover andartificial measures factors for the model by processing remote sensing data, collected rainfalland soil data to respectively calculate the rainfall erosivity and soil erodibility factors, createdDEM and calculated LS factor by using Topographic map data, drafted the factor grid map,calculated the soil erosion modulus of each pixel in the entire study area according toprediction model, classify the soil erosion intensity, generated the area of each soil erosion intensity class by utilizing GIS spatial statistical functions, multiplied the area by thecorresponding soil erosion modulus, summed up the results of all class, got the amount of soilerosion, Finally drew the conclusion of variation characteristics of soil erosion by analyzingthe result.