Relationship between soil surface roughness and hydraulic roughness coefficient on sloping farmland

The soil surface roughness and hydraulic roughness coefficient are important hydraulic resistance characteristic parameters. Precisely estimating the hydraulic roughness coefficient is important to understanding mechanisms of overland flow. Four tillage practices, including cropland raking, artificial hoeing, artificial digging, and straight slopes, were considered based on the local agricultural conditions to simulate different values of soil surface roughness in the Loess Plateau. The objective of this study was to investigate the relationship between the soil surface roughness and hydraulic roughness coefficient on sloping farmland using artificial rainfall simulation. On a slope with a gradient of 10°, a significant logarithmic function was developed between the soil surface roughness and Manning＇s roughness coefficient, and an exponential function was derived to describe the relationship between the soil surface roughness and Reynolds number. On the slope with a gradient of 15°, a significant power function was developed to reflect the relationship between the soil surface roughness and Manning＇s roughness coefficient, and a linear function was derived to relate the soil surface roughness to the Reynolds number. These findings can provide alternative ways to estimate the hydraulic roughness coefficient for different types of soil surface roughness.

Roughness evaluation in shotcrete-lined water tunnels with invert concrete based on cases from Nepal

Most of the existing roughness estimation methods for water tunnels are related to either unlined or concrete/steel-lined tunnels. With the improvement in shotcrete technology, advancement in tunneling equipment and cost and time effectiveness, future water tunnels built for hydropower projects will consist of rock support with the extensive use of shotcrete lining in combination with systematic bolting and concrete lining in the tunnel invert. However, very little research has been performed to find out tunnel surface roughness for shotcrete-lined tunnels with invert concrete, which is important in calculating overall head loss along the waterway system to achieve an optimum and economic hydropower plant design. Hence, the main aim of this article is to review prevailing methods available to calculate tunnel wall roughness, and to use existing methods of head loss calculation to back-calculate roughness of the shotcrete-lined tunnels with invert concrete by exploiting measured head loss and actual cross-sectional profiles of two headrace tunnels from Nepal. Furthermore, the article aims to establish a link between the Manning coefficient and the physical roughness of the shotcrete-lined tunnel with invert concrete and to establish a link between over-break thickness and physical roughness. Attempts are also made to find a correlation between over-break thickness and rock mass quality described by Q-system and discussions are conducted on the potential cost savings that can be made if concrete lining is replaced by shotcrete lining with invert concrete.

Characterization of Flow Structures Induced by Highly Rough Surface Using Particle Image Velocimetry, Proper Orthogonal Decomposition and Velocity Correlations

High Reynolds number flow inside a channel of rectangular cross section is examined using Particle Image Velocimetry. One wall of the channel has been replaced with a surface of a roughness representative to that of real hydropower tunnels, i.e. a random terrain with roughness dimensions typically in the range of ≈10% - 20% of the channels hydraulic radius. The rest of the channel walls can be considered smooth. The rough surface was captured from an existing blasted rock tunnel using high resolution laser scanning and scaled to 1:10. For quantification of the size of the largest flow structures, integral length scales are derived from the auto-correlation functions of the temporally averaged velocity. Additionally, Proper Orthogonal Decomposition (POD) and higher-order statistics are applied to the instantaneous snapshots of the velocity fluctuations. The results show a high spatial heterogeneity of the velocity and other flow characteristics in vicinity of the rough surface, putting outer similarity treatment into jeopardy. Roughness effects are not confined to the vicinity of the rough surface but can be seen in the outer flow throughout the channel, indicating a different behavior than postulated by Townsend’s similarity hypothesis. The effects on the flow structures vary depending on the shape and size of the roughness elements leading to a high spatial dependence of the flow above the rough surface. Hence, any spatial averaging, e.g. assuming a characteristic sand grain roughness factor, for determining local flow parameters becomes less applicable in this case.