Spatio-temporal Change Of The Soil Erosion In Hunan Province

Soil erosion may destroy surface vegetation,cause loss of soil nutrients,reduce land productivity,lead to destruction of land resources,pollution of water quality in river basins,accumulation of sediment in reservoirs,and endanger ecological safety and flood control safety.And it is one of the global ecological and environmental problems.The vigorous development of the USLE and RUSLE models is widely used in soil erosion research,mostly on the slope and small watershed scale.At present,there are few studies on the spatial and temporal changes of soil erosion in the long time at the provincial scope.Hunan Province is located in the southern region of China.The rainfall frequency is high and the rainfall intensity is heavy.The rainfall is concentrated,and it is easy to produce large-flow surface runoff.The erosion capacity is often greater than the surface erosion resistance,which has a greater risk of soil erosion.The research is supported by the Hunan Water Conservancy Science and Technology Project.Factors of influencing soil erosion including R Value,K Value,LS Value,B Value,E Value,T Value in 1995,2000,2005,2010 and 2015 were calculated respectively with daily rainfall data of precipitation stations from 1961 to2018 years,multi-period land-use data,DEM data and RS image using the methods of spatial interpolation et al.CSLE model was used to assess the spatial variations of soil erosion intensity and determine the distribution of soil erosion grade from 1995 to2015 with the obtained five annual soil erosion impact factor maps for Hunan Province.The annual mean of R value was between 4948 and 7260MJ·mm/(hm~2·h·yr)in Hunan Province with high spatial heterogeneity,the average K value was 0.004245t·hm~2·h/(hm~2·MJ·mm),the average L value was 2.21,the average S value was 3.26,the average LS value was 8.83,90%of the province’s regional LS values are below 30,the B value was between 0.3143 and 0.3175,the E value was between 0.8079 and0.8117,and the T value was between 0.8051 and 0.8093.The average soil erosion modulus were 1520,1086,1058,1631 and 1534t/(km~2·a)respectively in 1995,2000,2005,2010 and 2015.During the study period,erosive rainfall change aggravated the soil erosion.The average erosion modulus of this 5 years is 1366t/(km~2·a),which belongs to the slight erosion level.The modulus of soil erosion changed with elevation and the soil erosion of different land types was listed as rainfed cropland,Shrubland,sparse woodland,forest land and paddle field from high to low.During the study period,the change of erosive rainfall is the main driving factor of the spatio-temporal change of Hunan Province in the past 20 years.The assessment soil loss value is valuable for reference.Counties in the hilly region of the central and western Hunan Province,such as Sangzhi County,Baojing County,Yongshun County,Wulinyuan County,Guzhang County,Longshan County,Yongding County,Jishou County,Yuanlin County,Cili County,Shimen County,Anhua County,Huayuan County,Xupu County,Mayang County,Luxi County,Xinhua County,Fenghuang County,and Shuangpai County,were the key areas of soil and water conservation in the future.The calculated results of erosion in the control range of hydrometric station were much larger than the measured sediment during the study period.The erosion calculation result is far greater than the measured sediment transport.The sediment and the sediment transport ratio showing fluctuations year by year.High-coverage forests and grasses in the watershed,soil and water conservation projects participate in the process of intercepting sediment,causing most of the sediment to deposit locally or along the way,and ultimately failing to reach the sediment outlets of various hydrological stations,making the sediment delivery ratio much smaller.Compared with existing research,This article uses 58 years of daily rainfall data from 97 rainfall stations across the province.The rainfall data covers a long time,wide range and the R value calculation relative accuracy is high.Try to combined with the historical sediment observation data to compare the simulated erosion at the provincial scale.