Real‐Time Water Levels Using GNSS‐IR: A Potential Tool for Flood Monitoring
Bibliographic record
Abstract
Abstract Global Navigation Satellite System Interferometric Reflectometry (GNSS‐IR) using low‐cost antennas is a practical solution for monitoring water levels from rivers, lakes and seas that does not require submerging any instruments in water. Here we present a novel method for obtaining real‐time water levels using multiple low‐cost antennas that we validate by comparing with measurements from a co‐located pressure gauge at two sites with variable tides. Additionally, we use survey measurements to show that there is a site‐dependant mean bias in GNSS‐IR measurements up to a few centimeters, but this mean bias can be effectively removed by using a correction for the effect of tropospheric delay. We conclude that GNSS‐IR water level sensors could be a powerful tool for real‐time applications such as flood or storm surge monitoring and water resource management, as well as for improving the spatial coverage of sensors in remote regions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".