Literature DB >> 29361651

Effect of Heterogeneous Sediment Distributions on Hyporheic Flow in Physical and Numerical Models.

Susa H Stonedahl, Audrey H Sawyer1, Forrest Stonedahl2, Caleb Reiter3, Caleb Gibson3.   

Abstract

Variations in permeability have been found to significantly affect the flow of water though hyporheic systems, especially in regions with discontinuous transitions between distinct streambed lithologies. In this study, we probabilistically arranged two sediments (sand and sandy gravel) in a grid framework and imposed a single hyporheic flow cell across the grid to investigate how discontinuous permeability fields influence volumetric flow and residence time distributions. We used both a physical system and computer simulations to model flow through this sediment grid. A solution of blue dye and salt was pumped into the system and used to detect flow. We recorded the dye location using time-lapse photography and measured the electrolytic conductivity levels as the water exited the system as a proxy for salt concentration. We also used a computer simulation to calculate dye-fronts, residence times, and exiting salt concentrations for the modeled system. Comparison between simulations and physical measurements yielded strong agreement. In further simulations with 300 different grids, we found a strong correlation between volumetric flow rate and the placement of high permeability grid cells in regions of high hydraulic head gradients. One implication is that small anomalies in streambed permeability have a disproportionately large influence on hyporheic flows when located near steep head gradients such as steps. We also used moving averages with varying window sizes to investigate the effect of the abruptness of transitions between sediment types. We found that smoother permeability fields increased the volumetric flow rate and decreased the median residence times.
© 2018, National Ground Water Association.

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Year:  2018        PMID: 29361651     DOI: 10.1111/gwat.12632

Source DB:  PubMed          Journal:  Ground Water        ISSN: 0017-467X            Impact factor:   2.671


  1 in total

1.  Machine Learning Analysis of Hydrologic Exchange Flows and Transit Time Distributions in a Large Regulated River.

Authors:  Huiying Ren; Xuehang Song; Yilin Fang; Z Jason Hou; Timothy D Scheibe
Journal:  Front Artif Intell       Date:  2021-04-15
  1 in total

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