Progress in Geography, Volume. 39, Issue 4, 651(2020)

Experimental study on determining Manning roughness coefficient during slope runoff process

Yashan CHENG1,1,2,2, Zhonggen WANG1,1、*, Jun LI3,3, Zhen HUANG1,1,2,2, Xiangyu YE1,1,2,2, and Yin TANG1,1
Author Affiliations
  • 1Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 1中国科学院地理科学与资源研究所,陆地水循环及地表过程重点实验室,北京 100101
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 2中国科学院大学,北京 100049
  • 3Institute of Mountain Hazards and Environment, CAS, Chengdu 610041, China
  • 3中国科学院、水利部成都山地灾害与环境研究所,成都 610041
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    Manning roughness coefficient is the key parameter of flow velocity calculation. Overland flow is significantly different from open channel flow. In this study, we focused on the application of Manning formula in calculating the velocity of overland flow. Compared with open channel flow, the depth of overland flow is very shallow, sometimes only a few millimeters. Thus, vegetation, soil, surface roughness, and other factors have more obvious impact on overland flow. Therefore, the existing open channel flow Manning roughness coefficient cannot be directly used in overland flow. In order to determine the Manning roughness coefficient of overland flow, in this study we developed an indoor experimental system with variable roughness on slope, which includes a water supply system, an experimental tank, and an observation and data recording system. In this system, we used uniform river sand on the flat plate to simulate different roughness of the underlying surface, and placed it in a water tank. The stability and accuracy of the water supply system were verified by 87 pre-experiments. The results show that when the water supply was stable, the discharge was consistent with the data displayed by the electronic flow meter. The 87 groups of weighing data are relatively stable and consistent with normal distribution, and the data are within the 95% confidence interval. Then we designed 166 experiment scenes through a combination of different slopes, surface roughness, and water supply flow to explore the relationship between experimental conditions and Manning roughness coefficient. Among the 166 experiment scenes, a total of six kinds of roughness were designed. The water supply flow ranged from 1 to 25 m 3/h. The slope was between 4°-25°. We used the volume method to calculate the average diameter of the river sand and the chain method to calculate the surface roughness. The experiment data were processed for Support Vector Machine (SVM) training and forecasting, which used root mean square error (RMSE) and coefficient of determination (R2) as the evaluation indices, considered slope, measured flow, measured depth, average diameter of the river sand, and surface roughness as the independent variables, and Manning roughness coefficient as the dependent variable. The results show that no matter how many kinds of factors were considered, it was difficult to predict the Manning roughness coefficient of laminar flow and transitional flow by the training results of turbulent flow, which indicates a different influence mechanism in different flow patterns. In order to predict the Manning roughness coefficient accurately, we need three factors at least, and measured water depth must be included. When considering four or more factors at the same time, the Manning roughness coefficient could be accurately predicted in turbulent flow.

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    Yashan CHENG, Zhonggen WANG, Jun LI, Zhen HUANG, Xiangyu YE, Yin TANG. Experimental study on determining Manning roughness coefficient during slope runoff process[J]. Progress in Geography, 2020, 39(4): 651

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    Paper Information

    Received: Nov. 4, 2019

    Accepted: --

    Published Online: Oct. 16, 2020

    The Author Email: WANG Zhonggen (wangzg@igsnrr.ac.cn)

    DOI:10.18306/dlkxjz.2020.04.012

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