A RIVERBANK FILTRATION DEMONSTRATION PROJECT ON THE KALI RIVER, DANDELI, KARNATAKA, INDIA
Bibliographic record
Abstract
A small scale RBF system was installed in a village near the Kali River in the state of Karnataka to evaluate the performance of riverbank filtration (RBF) under the hydrogeological and climatological conditions of southern India. A series of hydraulic and tracer tests were carried out along with periodic biological and geochemical monitoring of various water sources in the study area. Hydrogen and oxygen isotopes highlight the impact of evaporation and irrigation at nearby rice paddies on the RBF production well. Dissolved silica data used to determine the relative contributions of surface and groundwater indicate that this RBF system derives approximately 28% of its water from the river. Even with nearly ¾ of the RBF water coming from groundwater, bacteria and metals data indicate that groundwater dilution does not appear to play a major role in pollutant reduction. Instead, other RBF removal processes, such as biodegradation and redox chemistry, are at work in the system. Bacteria levels demonstrate at least 88% to >99% removal over currently used source waters. Despite this, Indian drinking water standards for E. coli are not consistently met and total coliform standards are never met in the RBF system. Bacteria levels are higher during the three month monsoon season. Average dissolved metal levels meet Indian standards for all metals analyzed. A community survey carried out before and after RBF installation shows significantly improved health indicators amongst RBF water users. In summary, this pilot-scale project demonstrates an RBF system that is welcomed by the host community and provides water of higher quality than other water sources in this study area.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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; both teacher heads agree on what is shown here.
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".