Economic Potential for Rainfed Agrivoltaics in Groundwater-Stressed Regions
Bibliographic record
Abstract
Agrivoltaics co-locate crops with solar photovoltaics (PV) to provide sustainability benefits across land, energy, and water systems. Policies supporting a switch from irrigated farming to rainfed, grid-connected agrivoltaics in regions experiencing groundwater stress can mitigate both groundwater depletion and CO 2 from electricity generation. Here, hydrology, crop, PV, and financial models are integrated to assess the economic potential for rainfed agrivoltaics in groundwater-stressed regions. The analysis reveals 11.2–37.6 PWh/yr of power generation potential, equivalent to 40%–135% of the global electricity supply in 2018. Almost 90% of groundwater depletion in 2010 (∼150 km 3 ) occurred where the levelized cost for grid-connected rainfed agrivoltaic generation is 50–100 USD/MWh. Potential revenue losses following the switch from irrigated to rainfed crops represent 0%–34% of the levelized generation cost. Future cost–benefit analysis must value the avoided groundwater stress from the perspective of long-term freshwater availability.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".