摘要
选取位于东北黑土区的拜泉县为研究区,以高精度的DEM(1∶1万比例尺)为基准,探讨低精度的DEM(1∶5万比例尺)提取地形因子的差异及其对土壤侵蚀评价的影响.结果表明:在拜泉县的西南平原和缓坡台地区、三河(双阳河、通肯河、润津河)沿岸低洼易涝区,1∶5万DEM提取的L因子分别高估11%和25%,提取的S因子则低估25%和31%.在西北和中部漫岗丘陵区、东南丘陵和台地区,L因子分别低估20%和7%,S因子分别低估16%和12%.地形因子的差异所带来的土壤侵蚀评价也有差异,其中在平原区差异较小(为10.67%),但在丘陵区差异较大(达23.14%).因此,在土壤侵蚀评价中,在高精度的DEM难以获取的情况下,平原区可用较低分辨率的DEM来代替;但在丘陵区则不能代替,或者须对其计算的LS因子进行必要的修订,从而在一定程度上保证土壤侵蚀评价的精度.
Baiquan county,located in the black soil region of Northeast China,was selected as the study area.Based on the high-precision DEM(1∶10000),the difference of topographic factors extracted by low-precision DEM(1∶50000)and its impacts on soil erosion assessment were compared.The main conclusions were as follows:in the southwestern plain and gentle slope area of Baiquan,and the low-lying and easy-lying areas along the Sanhe River(Shuangyang River,Tongken River and Runjin River),the L factor extracted by 1∶50000 DEM was overestimated by 11% and 25%,respectively.Besides,the S factor was underestimated by 25% and 31%,respectively.In the northwest and central rolling hills,southeast hills and platform,the L factor was underestimated by 20% and 7%,and the S factor was underestimated by 16% and 12%,respectively.Discrepancy existed in soil erosion assessments due to differences in topographic factors.The discrepancy at the plain area is small(10.67%),but at the hilly area was large(up to 23.14%).Therefore,in the soil erosion assessment,in the case where the high-precision DEM was difficult to obtain,the plain area could be replaced by a lower resolution DEM.However,it could not be replaced in the hilly area,necessary modifications must be made of the LS factor to ensure the accuracy of soil erosion evaluation to a certain extent.
作者
顾治家
李骜
GU Zhijia;LI Ao(School of Geographic Sciences/Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution,Xinyang Normal University,Xinyang 464000,China;Faculty of Geography,Beijing Normal University,Beijing 100875,China)
出处
《信阳师范学院学报(自然科学版)》
CAS
北大核心
2020年第3期398-404,共7页
Journal of Xinyang Normal University(Natural Science Edition)
基金
国家重点研发计划项目(2018YFC0507004)
信阳师范学院博士科研启动项目。