Cannabis and residential groundwater pumping impacts on streamflow and ecosystems in Northern California
Bibliographic record
Abstract
Abstract Cannabis is an emerging agricultural frontier, but due to its quasi-legal status its environmental impacts are poorly understood. Where cannabis is irrigated by groundwater, pumping can lead to streamflow depletion in surrounding streams which may impair other water users or aquatic ecosystems. Here, we investigate the impacts of groundwater pumping for cannabis irrigation at the scale of the watershed, the individual well, and the stream segment, and contextualize by comparing with residential groundwater use. Combining mapped cannabis cultivation and residential structure locations with grower reports of irrigation water sources, we develop distributed estimates of groundwater pumping and associated streamflow depletion caused by cannabis and residential users within the Navarro River Watershed in Northern California (USA). An estimated 73% of cannabis cultivation sites and 92% of residential structures in the watershed rely on groundwater, and groundwater abstraction leads to streamflow depletion during late summer when groundwater is a critical source of baseflow to ecologically important streams. However, streamflow depletion caused by cannabis cultivation is dwarfed by the impacts of residential use, which causes >5 times as much streamflow depletion and is concentrated close to ecologically important stream segments. Focusing on cannabis, a small number of wells (<25%) cause a disproportionate amount of depletion (>50%), and significant predictors for impacts of a well are the annual pumping rate, the distance to the closest stream, and the transmissivity between the well and the stream. Streamflow depletion increases nonlinearly when pumping occurs within 1.2 km of streams, and most cannabis and residential groundwater use is within this critical distance. Given the rapid increase in cannabis cultivation, these results indicate that potential streamflow depletion from groundwater irrigation of cannabis is a current and future concern, and will be superimposed on top of significant depletion already occurring due to residential use in the region studied.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".