Interactions of Tides, Storm Surge, and River Flow in the Microtidal Neretva River Estuary
Bibliographic record
Abstract
Estuaries and tidal rivers are highly dynamic transitional zones where marine and riverine processes interact, creating complex hydrodynamic environments. These regions are influenced by natural phenomena such as tidal oscillations, storm surges, and river flow, as well as human activities like water management, hydropower operations, flood protection, and navigation. Effective management of these environments relies on understanding and predicting their hydrodynamic behavior, particularly under extreme conditions such as flooding or abrupt water level changes.This study examines the microtidal Neretva River estuary in Croatia to investigate the interactions between tides, storm surges, and river discharge, and their impacts on water level variability. A modified non-stationary harmonic analysis, based on the NS_Tide model, was developed specifically for microtidal conditions. This model incorporates storm surge and river discharge, improving the predictive accuracy of water levels along the estuary, from tide-dominated downstream sections to discharge-influenced upstream areas. The new version of NS_Tide also allows for a more detailed decomposition of total water levels and tide-surge-river interactions.The results reveal that river discharge is the primary factor influencing water levels at most stations, while the impact of storm surge decreases upstream. Tide-river interactions were observed throughout the study area, whereas tide-surge interactions had minimal effects. The analysis showed that high-frequency discharge fluctuations caused by hydropower operations amplify the S1 tidal constituent in upstream river sections. These fluctuations also modulate the amplitudes of other tidal constituents in estuarine and tidal river regions, highlighting the complex influence of human activities on tidal dynamics.The proposed non-stationary harmonic model proved highly effective for the microtidal Neretva River, capturing the complex interactions between tidal and non-tidal forces under various conditions. Its adaptability to local conditions suggests it could also be applied to mesotidal and macrotidal systems, offering a practical tool for managing estuaries and tidal rivers across diverse environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".