Study on Determination Method of Surface Roughness

ZHANG Nana; WANG Bing; ZHANG Baoqi and LI Yongning

doi:10.13870/j.cnki.stbcxb.2020.01.020

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Study on Determination Method of Surface Roughness

更新时间：2025-03-12

- Study on Determination Method of Surface Roughness
- Vol. 34, Issue 1, Pages: 135-140(2020)
- 作者机构：
  
  1. 西北农林科技大学黄土高原土壤侵蚀与旱地农业国家重点实验室, 陕西杨凌,712100
  2. 中国科学院水利部水土保持研究所, 陕西杨凌,712100
- 作者简介：
- 基金信息：
- DOI：10.13870/j.cnki.stbcxb.2020.01.020
  CLC： P208;S157
- Published：2020
- 稿件说明：
移动端阅览
ZHANG Nana, WANG Bing, ZHANG Baoqi and LI Yongning. Study on Determination Method of Surface Roughness[J]. 2020, 34(1): 135-140.
DOI：

ZHANG Nana, WANG Bing, ZHANG Baoqi and LI Yongning. Study on Determination Method of Surface Roughness[J]. 2020, 34(1): 135-140. DOI： 10.13870/j.cnki.stbcxb.2020.01.020.

摘要

地表微地形测量是地表粗糙度定量化的基础，对地表形态动态监测和土壤侵蚀过程相关研究具有重要意义。采用链条法、照相机法和无人机法，选取常规人工降雨土槽和野外径流小区，设置裸地和植物根系2个处理，分别测定其地表糙度。结果表明：（1）链条法、照相机法和无人机法测定的平均弯曲性指数分别为0.257，0.219，0.248，与标件实际平均弯曲性指数0.242偏差小于<10%；其中链条法测定的弯曲性指数整体偏大（6.2%），照相机法测定的弯曲性指数整体偏小（-9.5%），无人机法测定的弯曲性指数略有偏大，但误差仅为2.5%。（2）裸地土槽细沟较深，链条法和照相机法测定结果与实际不符，无人机法测定结果与实际较为-致，链条法和照相机法相对无人机法均偏小了50.0%和40.3%；有根系土槽链条法测定结果与实际不符，照相机法和无人机法测定结果与实际较为-致，链条法相对于照相机法和无人机法均偏小了48.2%和57.8%。（3）受地形因素限制，照相机法无法测定径流小区地表糙度；对于裸地和有根系小区，无人机法测定结果与实际较为相符，而链条法测定结果与地表起伏不-致，链条法相对于无人机法测定的地表弯曲性指数分别偏大了28.6%和24.8%。总体而言，立体摄影测量能有效地反映地表糙度，但受拍摄高度和地形因素的限制，照相机法测定结果会存在低估或使用受限，无人机法测定结果相对稳定；受人为操作和本身测定过程误差的影响，链条法测定结果偏差相对较大，但对于立体摄影测量无法测定的立地环境，链条法仍可作为地表糙度测量的有效方法。

Abstract

Surface microtopography measurement is the basis of surface roughness quantification

which is of great significance to the dynamic monitoring of surface morphology and the study of soil erosion process. This research adopted the chain method

cameras and unmanned aerial vehicle (uav) method

selected the conventional artificial rainfall soil bin and field runoff plots

set up the bare land and two processing plant roots respectively

to determine the surface roughness. The results showed that:(1) The average curvature indexes determined by the chain method

cameras and uav method were 0.257

0.219 and 0.248

respectively

with the average actual bending index deviation was less than 0.242 < 10%. Among them

the bending index measured by the chain method was relatively large as a whole (6.2%)

the bending index measured by the camera method was relatively small as a whole (-9.5%)

and the bending index measured by the uav method was slightly large

but the error was only 2.5%. (2) The groove of bare soil was deep

and the measured results of chain method and camera method were inconsistent with the reality. The measured results of uav method were relatively consistent with the reality

and the chain method and camera method were slightly smaller than uav method by 50.0% and 40.3% respectively. The results of the chain method with root soil groove were not consistent with the actual conditions

and the results of the camera method and the uav method were relatively consistent with the actual conditions. The chain method was 48.2% and 57.8% respectively smaller than the camera method and the uav method. (3) Limited by the topographic factors

the camera method could not determine the surface roughness of runoff plot. For bare land and rooted plots

the measured results of uav were relatively consistent with the actual situation

while the measured results of chain method were inconsistent with the ups and downs of the surface. The surface bending index measured by chain method was slightly higher than that by uav method by 28.6% and 24.8%

respectively. In general

stereoscopic photogrammetry could effectively reflect surface roughness. However

due to the limitations of shooting height and terrain factors

the measurement results of camera method might be underestimated or limited

and the measurement results of uav method were relatively stable. Due to the influence of human operation and the error of the measurement process

the error of the measurement results of the chain method was relatively large.

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