Dissolved material transport—the flushing effect in surface and subsurface flow

1981 ◽  
Vol 6 (2) ◽  
pp. 173-178 ◽  
Author(s):  
M. Klein
Keyword(s):  
Subsurface Flow ◽  
Material Transport ◽  
Surface And Subsurface Flow

scholarly journals Surface and subsurface contributions to the build-up of forces on bed particles

2018 ◽  
Vol 851 ◽  
pp. 558-572 ◽  
Author(s):  
Alessandro Leonardi ◽  
D. Pokrajac ◽  
F. Roman ◽  
F. Zanello ◽  
V. Armenio
Keyword(s):  
Mutual Influence ◽  
Subsurface Flow ◽  
Porous Wall ◽  
Industrial Applications ◽  
Solid Particles ◽  
Free Flow ◽  
Spherical Particles ◽  
Large Eddy ◽  
Lift Forces ◽  
Surface And Subsurface Flow

In nature and in many industrial applications, the boundary of a channel flow is made of solid particles which form a porous wall, so that there is a mutual influence between the free flow and the subsurface flow developing inside the pores. While the influence of the porous wall on the free flow has been well studied, less well characterized is the subsurface flow, due to the practical difficulties in gathering information in the small spaces given by the pores. It is also not clear whether the subsurface flow can host turbulent events able to contribute significantly to the build-up of forces on the particles, potentially leading to their dislodgement. Through large eddy simulations, we investigate the interface between a free flow and a bed composed of spherical particles in a cubic arrangement. The communication between surface and subsurface flow is in this case enhanced, with relatively strong turbulent events happening also inside the pores. After comparing the simulation results with a previous experimental work from a similar setting, the forces experienced by the boundary particles are analysed. While it remains true that the lift forces are largely dependent on the structure of the free flow, turbulence inside the pores can also give a significant contribution. Pressure inside the pores is weakly correlated to the pressure in the free flow, and strong peaks above and below a particle can happen independently. Ignoring the porous layer below the particle from the computations leads then in this case to an underestimation of the lift forces.

A hybrid coupled model of surface and subsurface flow for surface irrigation

2013 ◽  
Vol 500 ◽  
pp. 62-74 ◽  
Author(s):  
Qinge Dong ◽  
Di Xu ◽  
Shaohui Zhang ◽  
Meijian Bai ◽  
Yinong Li
Keyword(s):  
Subsurface Flow ◽  
Coupled Model ◽  
Surface Irrigation ◽  
Surface And Subsurface Flow ◽  
Hybrid Coupled Model

scholarly journals Assessment of the Timing of Daily Peak Streamflow during the Melt Season in a Snow-Dominated Watershed

2016 ◽  
Vol 17 (8) ◽  
pp. 2225-2244 ◽  
Author(s):  
Xing Chen ◽  
Mukesh Kumar ◽  
Rui Wang ◽  
Adam Winstral ◽  
Danny Marks
Keyword(s):  
Water Flux ◽  
Subsurface Flow ◽  
Hydrologic Model ◽  
Daily Streamflow ◽  
Penn State ◽  
Integrated Hydrologic Model ◽  
Interseasonal Variability ◽  
Peak Streamflow ◽  
Surface And Subsurface Flow ◽  
Temporal Shifts

Abstract Previous studies have shown that gauge-observed daily streamflow peak times (DPTs) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes: 1) melt flux translation through the snowpack or percolation, 2) surface and subsurface flow of melt from the base of snowpacks to streams, and 3) translation of water flux in the streams to stream gauging stations. The goal of this study is to evaluate and quantify how these processes affect observed DPTs variations at the Reynolds Mountain East (RME) research catchment in southwest Idaho, United States. To accomplish this goal, DPTs were simulated for the RME catchment over a period of 25 water years using a modified snowmelt model, iSnobal, and a hydrology model, the Penn State Integrated Hydrologic Model (PIHM). The influence of each controlling process was then evaluated by simulating the DPT with and without the process under consideration. Both intra- and interseasonal variability in DPTs were evaluated. Results indicate that the magnitude of DPTs is dominantly influenced by subsurface flow, whereas the temporal shifts within a season are primarily controlled by percolation through snow. In addition to the three processes previously identified in the literature, processes governing the snowpack ripening time are identified as additionally influencing DPT variability. Results also indicate that the relative dominance of each control varies through the melt season and between wet and dry years. The results could be used for supporting DPTs prediction efforts and for prioritization of observables for DPT determination.

Sign in / Sign up

Export Citation Format

Share Document