Challenges to the Use of a Base of Fresh Water in Groundwater Management: Total Dissolved Solids vs. Depth Across California
Bibliographic record
Abstract
According to the California Sustainable Groundwater Management Act, the bottom of a basin, and subsequently the depth to which groundwater is managed, can be defined through physical or geochemical qualities of the aquifer. Total dissolved solids (TDS) concentrations are most frequently used to define the basin bottom. However, upper limits in TDS concentrations for “fresh” and “useable” groundwater can range from 1,000 to 10,000 mg/L. To evaluate the applicability of using TDS concentrations to delineate depths subject to sustainable groundwater management, we analyze 216,754 TDS measurements throughout the state of California. We find major challenges to reasonably estimating the BFW with our dataset in 73% of California due to data insufficiencies or complexity introduced by non-montonic TDS-depth relationships. We estimate the BFW in 22% of the Central Valley, a key agricultural region with large groundwater demands and many critically overdrafted groundwater subbasins. Using a TDS limit of 3,000 mg/L, where possible, we estimate the shallowest BFW in the Central Valley to be 155 m below ground surface and the deepest BFW to be 589 m below ground surface. We find that the base of brackish water (TDS < 10,000 mg/L) can extend more than 500 m deeper than the BFW in 78% of the Central Valley where we are able to estimate the BFW, which corresponds to 2% of California. There is a need to evaluate alternative strategies for defining groundwater subject to sustainable management, which likely involves additional measurements and analysis to better characterize groundwater quality with depth throughout California.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".