Assessing the Impact of Variations in Hydrologic, Hydraulic and Hydrometeorological Controls on Inundation in Urban Areas
Bibliographic record
Abstract
There is a great need for timely prediction of the extent and depth of flooding and related hazards in highly populated urban areas such as the Dallas-Fort Worth metroplex (DFW).The hydrologic, hydraulic and hydrometeorological processes involved and the large number of factors that control them are complex, interrelated and generally scale dependent, which makes real time prediction of flood inundation in urban areas particularly challenging.In addition, a large number of human created structures such as channels, pipes, culverts, buildings, parking lots and manholes add complexity.With continuing urbanization and climate change, it is critical that the dynamics of urban flooding be better understood to improve prediction and to mitigate water related hazards under changing conditions.In this work, we assess how different factors may impact urban flood inundation using the 1D-2D PCSWMM model through a series of controlled simulation experiments.The main study area is the 3.3 km 2 Forest Park-Berry catchment in Fort Worth in North Central Texas, which has a high density of underground storm drainage.Specifically, we assess the impact of variations in precipitation and impervious cover on simulated inundation maps.
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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 | 0.001 | 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 | 0.001 |
| 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 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".