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[1]ZHAO Guangxu,WANG Quanjiu,YANG Ting,et al.Study on Estimation Method of Depression Storage of Slope Surface[J].Research of Soil and Water Conservation,2015,22(06):89-94.

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Study on Estimation Method of Depression Storage of Slope Surface

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 22 Number of periods: 2015 06 Page number: 89-94 Column: Public date: 2015-12-28

Title:: Study on Estimation Method of Depression Storage of Slope Surface

Author(s):: ZHAO Guangxu¹, WANG Quanjiu^1,2, YANG Ting¹, SU Lijun³; 1. College of Water Conservancy and Hydropower, State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Xi’an University of Technology, Xi’an 710048, China;
2. State Key Laboratory of Soil Erosion and Dryland Farming on the Losses Plateau, Institute of Soil and Water Conservation, Northwest A & F University, Yangling, Shaanxi 712100, China;
3. School of Science, Xi’an University of Technology, Xi’an 710048, China

Keywords:: depression storage; surface roughness; micro topography; generalization

CLC:: S157.2

DOI:: -

Abstract:: Surface depression storage is one of the most important parameters in the hydrological process analysis, which is closely related to surface roughness. In order to obtain the method of calculating surface depression storage, based on the generalization model of different micro topography shapes, we achieved the calculating formula of surface depression storage under different surface depression storages, and checked the theoretical formula using experimental data, obtained the corresponding real depression storage. The results showed that, with the increase of slope, the theoretical depression storage and real depression storage both decrease; the unit length of depression storage had no obvious change with slope length. With the increase of flow rate, depression storage showed the increase trend, and met a linear growth relationship. Depression storage is closely related with surface roughness, it increased with the increase of surface roughness, and can be described by the power function.

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