沂蒙山区不同抽样密度对土壤侵蚀因子估算精度的影响

齐斐; 苏新宇; 黎家作; 胡续礼; 刘霞; 张春强; 邢先双; 丁鸣鸣

doi:10.13961/j.cnki.stbctb.2019.02.029

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沂蒙山区不同抽样密度对土壤侵蚀因子估算精度的影响

试验研究

- 沂蒙山区不同抽样密度对土壤侵蚀因子估算精度的影响
- Effects of Sampling Densities on Estimation Precision of Soil Erosion Factors in Yimeng Mountain Area
- 水土保持通报 2019年39卷第2期页码：179-183
- 作者机构：
  
  1. 江苏省水土保持与生态修复重点实验室/南方现代林业协同创新中心/南京林业大学林学院,江苏,南京,210037
  2. 淮河水利委员会淮河流域水土保持监测中心站,安徽,蚌埠,233001
  3. 水利部淮河水利委员会水土保持处,安徽,蚌埠,233001
  4. 山东省水文局,山东,济南,250012
  5. 南京市水务局,江苏,南京,210036
- 作者简介：
- 基金信息：
  
  全国水土流失动态监测与公告项目“淮河流域国家级重点防治区水土流失动态监测”（HWSBJ201302），“山东省省级重点治理区水土流失动态监测项目”（SWJ201601）;国家自然科学基金项目（31070627）;江苏省高校优势学科建设工程项目
- DOI：10.13961/j.cnki.stbctb.2019.02.029
  中图分类号： S157
- 纸质出版：2019
- 稿件说明：
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齐斐, 苏新宇, 黎家作, 等. 沂蒙山区不同抽样密度对土壤侵蚀因子估算精度的影响[J]. 水土保持通报, 2019,39(2):179-183.

Qi Fei, Su Xinyu, Li Jiazuo, et al. Effects of Sampling Densities on Estimation Precision of Soil Erosion Factors in Yimeng Mountain Area[J]. Bulletin of Soiland Water Conservation, 2019, 39(2): 179-183.
齐斐, 苏新宇, 黎家作, 等. 沂蒙山区不同抽样密度对土壤侵蚀因子估算精度的影响[J]. 水土保持通报, 2019,39(2):179-183. DOI： 10.13961/j.cnki.stbctb.2019.02.029.

Qi Fei, Su Xinyu, Li Jiazuo, et al. Effects of Sampling Densities on Estimation Precision of Soil Erosion Factors in Yimeng Mountain Area[J]. Bulletin of Soiland Water Conservation, 2019, 39(2): 179-183. DOI： 10.13961/j.cnki.stbctb.2019.02.029.

摘要

[目的]探讨分层系统抽样方法下不同抽样密度对土壤侵蚀因子估算精度的影响，为区域水土流失动态监测抽样方法和抽样密度的选取提供数据支撑。[方法]以沂蒙山泰山国家级重点治理区蒙阴县为对象，基于2013年SPOT5遥感影像和1：1万地形图，采用人机交互解译、野外调查、统计分析等方法，以全县土壤侵蚀因子为基准值，对1%和4%密度土壤侵蚀因子进行精度评价。[结果]①1%抽样密度下，S，E，K因子相对误差较大，分别为33.48%，23.46%，20.64%，主要受坡度、土地利用和土壤类型影响；L，B，T相对误差均小于11%；六者平均14.44%。②4%抽样密度下，E，K，B相对误差较大，分别为15.07%，13.94%和10.69%，主要受土地利用和土壤类型影响；L，S，T相对误差均小于10%；6者平均7.89%。③以栅格计算法结果为基准值，采用单元插值外推法推算全县水土流失面积，1%密度下水土流失面积比偏高19.73%，4%密度下水土流失面积比偏高11.77%。[结论]蒙阴县1%和4%密度各因子均有不同程度的精度损失，并对水土流失估算结果造成一定影响，在区域水土流失动态监测过程中可根据需求选取合适的抽样密度。

Abstract

[Objective] In order to provide data support for sampling method and sampling density selection in regional dynamic monitoring of soil erosion

the influence of sampling densities on estimation precision of soil erosion factors was studied.[Methods] The paper took Mengyin County

in the Yimeng and Tai Mountains national key control areas

as the research object to calculate the precision loss of soil erosion factors estimation under 1% and 4% sampling densities. The precision loss of soil erosion factors estimation under 1% and 4% sampling densities

compared to the soil erosion factors of the county was evaluated by human-computer interaction interpretation

field investigation and statistical analysis

based on the SPOT5 remote sensing images in 2013 and 1:10 000 topographic maps.[Results] ① Under the 1% sampling density

the relative errors of S

E and K factors were 33.48%

23.46% and 20.64% respectively

which are mainly influenced by slope

land use and soil types

while the relative errors of L

B and T factors were less than 11%. The average relative error of soil erosion factors was 14.44% in the field investigation units. ② Under the 4% sampling density

the relative errors of E

K and B factors were 15.07%

13.94% and 10.69% respectively

which were mainly affected by land use and soil types

while the relative errors of L

S and T factors were less than 10%. The average relative error of soil erosion factors in the field survey units was 7.89%. ③ The results calculated by the element interpolation extrapolation method under the two sampling densities were higher than that of the grid calculation method. The area of soil erosion under the 1% sampling density was 19.73% higher than that of the grid calculation method

and under the 4% sampling density

it was 11.77% higher.[Conclusion] The 1% and 4% density factors of Mengyin County had different degree of precision loss

which had a certain influence on the results of soil erosion estimation. In the process of dynamic monitoring of regional soil erosion

the appropriate sampling density can be selected according to the demand.

关键词

Keywords

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