Modelling of groundwater flow in Indira Sagar canal command at central India
Bibliographic record
Abstract
This study focused on managing the Indira Sagar Canal Command Area (ISCCA) by simulating groundwater flow using Visual MODFLOW version 4.2. The model examined hydraulic head changes under transient pumping conditions from 2001 to 2010, with calibration based on six years of data and validation using the remaining years. Data from 48 observation wells supported this analysis. Convergence was achieved with a maximum of 50 outer iterations and 100 inner iterations, with a residual threshold set to 0.01. Sensitivity analysis identified groundwater recharge as the most critical parameter, followed by aquifer hydraulic conductivity. Specific storage and yield parameters showed less sensitivity. The consistency between observed and computed groundwater head contours validated the model’s accuracy in replicating groundwater dynamics. The groundwater balance calculated from the model closely matched actual field conditions, confirming the model’s reliability. Additionally, the study highlighted the impact of topography and base flow on groundwater flow within the canal command area. Key findings include the successful development of a reliable Groundwater Model (GWM) for the ISCCA, which accurately simulates aquifer behaviour, recharge, and withdrawal patterns. The calibration and validation process demonstrated the model’s potential for future integration with climate models to enhance groundwater predictions and support sustainable water management.
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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 | 0.000 | 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".