Research On Soil Erosion Characteristics Of Chengde City Based On RUSLE Model

A serious threat to agricultural output,water conservation infrastructure,and the natural environment,soil erosion will result in a number of issues,including land degradation,soil loss,and water and water quality issues.Higher standards for soil erosion prevention and management have been proposed as a result of the multi-scale characteristics of soil erosion and the complexity of its influencing elements.Spatial and temporal distribution characteristics of soil erosion as well as its contributing variables can be studied to establish a scientific basis for the crucial problem of minimizing water and soil loss.The north rocky mountainous region includes Chengde city,which is close to the Beijing-Tianjin Region.It is one of the typical areas of water erosion in China and its soil erosion is serious.It is very important to ensure the ecological environment quality of Chengde city to build the ecological barrier of Beijing-Tianjin region.Taking Chengde city as the study area,this paper employs remote sensing images,vector elevation,hydrometeorology and other multi-source data,and uses remote sensing technology and RUSLE model quantitatively examines the characteristics of soil erosion intensity and soil erosion sensitivity in Chengde city,and reveals the temporal and spatial changes in these qualities.In addition to providing a scientific foundation for the work of water and soil conservation in Chengde city and addressing the issue of sediment deposition in river sections,the study can deepen understanding of the characteristics of soil erosion in Chengde city.The main results are as follows:（1）From 2003 to 2018,the temporal and spatial changes of rainfall erosivity R and vegetation cover and management C in Chengde city were obvious,while the annual changes of soil erodibility K,slope length and steepness LS and conservation practice factor P were not obvious.The R factor generally shows an increasing trend,and the interannual variation fluctuates greatly,ranging from 963.05 to 3160.97 MJ·mm·hm^-2·h^-1·a^-1.The R value demonstrates the characteristics of small distribution from south to north.With significant regional variability,the coefficient of spatial variation of R value reaches 0.72 in 2018.C factor value in the research region is small as a whole,vegetation coverage is good,and vegetation coverage in some areas is poor in 2012.（2）In 2018,the micro erosion area of Chengde city was 28860.71 km²,accounting for about 73.03%of the total area,which is generally at the level of micro erosion.During the study period,the soil erosion modulus of Chengde city showed an upward trend and then a downward trend,ranging from 69.17 to 209.16 t·km^-2·a^-1,reaching the maximum in 2012.The crucial value of slope was 15°,and as slope climbed,the rate of soil erosion increased initially before decreasing;The primary locations for high intensity soil erosion are grassland and cultivated land.R,C factor are the primary influencing factors of changes in soil erosion modulus,while R factor is the primary influencing factor of changes in regional differences in soil erosion.（3）The sum of the areas of the soil erosion insensitive area and the lightly sensitive area in Chengde city accounts for about 81.47%of the total area,which is generally at the lightly sensitive level.The overall sensitivity has improved since 2009,and the situation in partial areas such as Pianqiaozi town and Xinglong county has deteriorated.Soil erodibility sensitivity is related to soil mechanical composition.The lower soil clay content is,the higher soil erodibility sensitivity is.The main factor influencing the total area of highly sensitive and extremely sensitive areas in the study area between 2003 and 2009 was factor C,and factor R was the main factor after 2009.Land use change in the study area is likely to increase soil erosion sensitivity,and the positive correlation between them is more significant.The soil erosion modulus is strongly influenced by changes in the total area of the very sensitive area and the extremely sensitive area,and there is a strong linear positive correlation between these two variables.