Two Dimensional Modeling to Simulate Stormwater Flows at Photovoltaic Solar Energy Sites
Bibliographic record
Abstract
Solar farms (sometimes known as solar parks or solar fields) are the large scale use of photovoltaic (PV) solar panels to generate green, clean electricity at scale, usually to feed into the grid.Solar farms can cover anything between 1 acre (0.40 ha) and several hundred acres (120+ ha), and are usually developed in rural areas.Solar farms consist of arrays of ground mounted rectangular panels that are sloped toward the sun at either fixed or adjustable angles.Amec Foster Wheeler assessed several candidate solar farm sites in Texas for stormwater flooding hazard and designed the stormwater management system for a site in Georgia using two-dimensional (2D) hydrologic and hydraulic (H&H) models to simulate the infiltration and overland flow.The FLO-2D software package was used to develop a rectangular grid for runoff calculation.The Soil Conservation Service (SCS) method and the shallow water equations were used to route stormwater runoff across FLO-2D grids.Results were exported to ArcGIS for the creation of maps that displayed maximum velocities and flow depths for different storm events.Input data required for the development of the models was obtained from publicly available sources including U.S. Geological Survey (USGS) 1/3 arc-second digital elevation models (DEM), National Land Cover Database (NLCD), U.S. Department of Agriculture (USDA) soil data and National Hydrography Dataset (NHD) data.These data inputs were supplemented with site field survey data.ESRI ArcGIS software and other tools were used to process the data for the assignment of curve numbers (CN) and ground roughness coefficients (Manning's n value) to the model grid cells.HEC-HMS modeling software was used to develop runoff hydrographs from offsite drainage areas which were then added to the FLO-2D model as an inflow boundary condition.Models were created to identify the flooding risks on a conceptual level, to evaluate the final grading design, and to develop a stormwater permitting plan.Model results were also used to estimate the scour potential at the piles that supported the panels.This work demonstrates the use of spatially varied 2D H&H models in assessing potential sites and in designing stormwater control measures for solar farms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".