Pilot Topobathymetric Terrain Model of the Kootenai River near Bonners Ferry, Idaho, 2009 - 2019
Bibliographic record
Abstract
The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) has started to initiate the development of pilot 3D National Topography Models to generate 3-dimensional surface elevation models that integrate river topographic bare-earth elevation surfaces with channel bed bathymetry. Detailed knowledge of integrated river system topography, bathymetry, and topobathymetry, is essential for habitat restoration, hydrologic modeling, and other key science applications such as flood mapping and identification of fluvial geomorphic features. An integrated 1-meter topobathymetric digital elevation model (TBDEM) for the Kootenai River near Bonners Ferry, Idaho, has been developed for this first pilot study. The Kootenai River is one of the upper most major tributaries of the Columbia River, flowing from British Columbia through Montana and the Idaho Panhandle then back into Canada, The Kootenai River TBDEM comprises the spatial integration of 10 different geospatial elevation sources including the USGS 3DEP topobathymetric lidar data, existing topographic lidar, and multi-beam acoustic surveys obtained from the U.S. Army Corps of Engineers , and the USGS Idaho Water Science Center. The TBDEM will provide a fundamental baseline for hydrographic and geomorphic applications to support restoration strategies for the white sturgeon habitat and enhanced 2D/3D hydrologic modeling . To develop the Kootenai River TBDEM, the USGS 3DEP acquired topobathymetric (green wavelength) lidar in 2017 for the Kootenai River near Bonners Ferry, Idaho that successfully captured primary deposition areas, secondary channels, and bank to bank (submerged topography) coverage of straight, meander, and shallow braided sections of the river. Topobathymetric lidar data were spatially integrated with topographic lidar and sonar data to create a seamless TBDEM void of gaps and with complete coverage for the Kootenai River pilot study area. The integration process includes a critical step where the topography, topobathymetry, and bathymetry data are sorted and prioritized based on survey date, accuracy, spatial distribution, and point density to develop a TBDEM based on the best available elevation data. Every input data source in the TBDEM has been horizontally referenced to UTM Zone 11, NAD83 2011 and vertically referenced to the North American Vertical Datum of 1988 (NAVD88) Geoid12b. The spatial resolution is 1-meter with general thalweg elevations ranging from 541 meters in the upstream segment to 521 meters in the downstream segment. The overall temporal range of the input topography, topobathymetry, and bathymetry is 2009 to 2019.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".