Successful implementation of ASR in basalt-hosted aquifers in the Pacific Northwest of the United States
Bibliographic record
Abstract
Despite the Pacific Northwest’s reputation for being “wet,” many cities west and east of the Cascade Range in the United States of America find it increasingly difficult to meet peak water supply demand during the dry summer months. Aquifers in the east side of Oregon and Washington are the primary water supply sources for a vast agriculture industry, and they have experienced significant declines prompting regulatory restrictions. For these reasons, municipalities west and east of the Cascade Range, as well as agricultural interests have opted to implement aquifer storage and recovery (ASR) projects as a unique water management technique to help meet peak summer water demands. Unique to the Pacific Northwest are the Miocene-age continental flood-basalt flows of the Columbia River Basalt Group (CRBG), which consists of a thick, areally extensive series of extraordinarily huge lava flows. The CRBG plays host to an extensive regional aquifer system in eastern Washington, eastern Oregon, and western Oregon. The two ASR projects discussed in this paper, the City of Beaverton and Madison Farms, use CRBG aquifers to host their ASR projects. Since 1999, the City of Beaverton (City), Oregon, population 85,500, has installed three ASR wells hosted in the CRBG aquifer. Currently, the City stores approximately 1,703,000 cubic meters of treated drinking water annually with its ASR wells. The three wells can provide up to about 22,700 cubic meters per day of peaking capacity, which is equivalent to 35 percent of the City’s summer peak day demand. Favorable hydrogeologic response and significant economic savings have made the City’s ASR system immensely successful. Since 2006, Madison Farms, a 71-square-kilometer farm near Echo, Oregon, has been using ASR to increase summer pumping capacity from the CRBG. Unlike the City of Beaverton, which uses treated river water to recharge the CRBG aquifer, Madison Farms uses untreated shallow alluvial groundwater to recharge the CRBG aquifer. Nitrate is the only constituent of concern for the Madison Farms ASR system and is monitored continuously to ensure recharge water does not have nitrate concentrations greater than the project-specific regulatory threshold of 7 milligrams per liter (mg/L). A nitrate analyzer is connected to the downhole control valve in the injection well that stops injection when the 7 mg/L threshold is met. The economics of Madison Farms’ ASR system also are very favorable compared to the alternative of piping surface water from the Columbia River more than 22 kilometers to meet irrigation demands. Key lessons learned at each ASR project include: storage in basalt is highly successful; understanding well and aquifer hydraulics in CRBG aquifers, however, is challenging because of their unique geologic characteristics (e.g., tabular interflows and compartmentalization); aquifer clogging by air entrainment is a concern, but can be managed with the installation of a downhole control valve; recharge well design is important; radon dissolves quickly into stored water; natural filtration of shallow groundwater shows that it can be used to recharge deeper aquifers; surface water and shallow groundwater have proven to be geochemically compatible with native CRBG groundwater; continuous monitoring of recharge linked to a downhole control valve has proven to be successful; and ASR has proven to be a cost-effective peak water management technique.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".