Baseflow Contribution to Streamflow and Aquatic Habitats Using Physical Habitat Simulations
Bibliographic record
Abstract
A scientific understanding of the baseflow contribution to streams and watershed processes is critical when dealing with water policy and management issues. However, most previous studies involving physical habitat simulation have been performed without considering the seepage of water from the underground into streams. Motivated by this, herein, we report an investigation of the impact of baseflow using physical habitat simulations for both dominant fish and benthic macroinvertebrate. The study area was located along the reach of the Ungcheon Stream, located 16.50 km downstream and 11.75 km upstream from the Boryeong Dam in the Republic of Korea. For the physical habitat simulation, Zacco platypus and Baetis fuscatus were selected as the target fish and benthic macroinvertebrate, respectively. The HydroGeoSphere (HGS) model (Aquanty Inc., Waterloo, ON, Canada) and the River2D model (Version 0.95a, University of Alberta, Edmonton, AB, Canada) were used for hydrologic and hydraulic simulations, respectively. The Habitat Suitability Index (HSI) model was used for the habitat simulations. Three habitat variables, flow depth, velocity, and substrate, were used. To assess the impact of baseflow, this study performed a physical habitat simulation using each representative discharge, with and without considering baseflow. It was found that the baseflow effects significantly increase the habitat suitability in the study reach. To restore the aquatic habitat, a scenario for modifying dam operations through natural flow patterns is presented using the Building Block Approach (BBA). In the study, the adjusted minimum flow allocation concept was used. It was revealed that the modified dam operations significantly increased the Weighted Usable Area (WUA) by about 48% for both target species. The results indicate that modifying the dam operations through restoration to natural flow regimes but also through inclusion of the baseflow are advantageous to aquatic fish habitats.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.001 |
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 teacher head, 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".