Effects of vegetation density, arrangement, and morphology on flow structure under ice-covered condition
Bibliographic record
Abstract
Aquatic vegetation appears very often in rivers and floodplains, which significantly affects the flow structure. On the other hand, a common feature of cold regions is the presence of river ice on water surfaces. Ice cover imposes an additional boundary layer on water surface which leads to significant change in flow structure and bed deformation. It also causes a decreasing trend of velocity profile near the cover. Because of vegetation’s positive impacts on water quality, habitat, and channel stability, researchers now advocate replanting and restoring projects in rivers, especially in agricultural waterways, floodways, and emergency spillways. The expansion of vegetation in fluvial systems may worsen the flood impact since highly dense vegetation in a channel reduces its flow capacity due to the increase in flow resistance and decrease in the channel width. Therefore, an accurate and critical assessment of the vegetation density and distribution pattern through reduction of bulk velocity is crucial in sustainable restoration projects. To the author's knowledge, no studies have been conducted to investigate the impacts of both ice cover and vegetation on flow resistance and channel bed deformation. It is thus necessary to examine the connection between vegetation and ice covers thoroughly in order to guarantee successful restoration projects. Most of research projects on submerged vegetation have been done in small-scale laboratory flume and specifically under the open channel flow condition. Besides, most of reported research uses uniform sediment which is not an appropriate representative of natural river systems. In the present study, deflected and non-bending model vegetation elements arranged in both square and staggered configurations with different density in the channel bed with three different non-uniform sands under different cover conditions of water surface including open channel flow and ice-covered flow conditions were used. In order to simulate the ice cover condition, smooth and rough ice covers made of Styrofoam panels were created to investigate the impacts of ice cover roughness on channel bed deformation. To represent non-uniform sediment condition, three different bed materials with median particle size (D50) of 0.50 mm, 0.60 mm, 0.98 mm were used. Results showed that the most significant variable influencing the depth of scour holes under ice-covered flow conditions is the ratio of the ice cover roughness to the bed roughness and in open channel flow conditions, the flow Froude number is determining. In the conducted experiments, it was consistently observed that the maximum scour depths occurred at the upstream, front face of the vegetation elements. It was found that the scour holes were deeper and longer under ice-covered flow. In the presence of vegetation in the bed under ice-covered flow conditions, the velocity profiles exhibit a distinct pattern characterized by two peak values. The study revealed an inverse relationship between canopy density and the dimensions of the wake zone. As the spacing distance between deflected vegetation elements decreases, the streamwise velocity experiences significant retardation slightly below the inflection point. With a sparser vegetation canopy, the inflectional region tends to diminish or disappear. Furthermore, the study observed that the inflection point was not observed in non-bending vegetation. Additionally, velocity profiles showed more pronounced inflection points in the case of a staggered arrangement of vegetation elements compared to a square arrangement. Results of this study will provide vital information for river management, channel restoration, and rehabilitation of fluvial environments through understanding the effect of various vegetation densities, arrangement patterns and morphology, as well as the revitalization of cold-weather river ecosystems.,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".