Assessment of Surface Water Resources in the Big Sunflower River Watershed Using Coupled SWAT–MODFLOW Model
Why this work is in the frame
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Bibliographic record
Abstract
The groundwater level in the Big Sunflower River Watershed (BSRW) in the U.S. has declined significantly in the past 30 years. Therefore, it is imperative to assess surface water resources (SWR) availability in BSRW to mitigate groundwater use for irrigation. This research applied the coupled Soil and Water Assessment Tool–Modular Groundwater Flow model (SWAT–MODFLOW) to assess SWR in BSRW. This study aimed at: (1) Assessing the reliability of SWAT–MODFLOW in BSRW, (2) analyzing temporal and spatial variations of SWR, and (3) assessing the potential availability of SWR in BSRW. Calibration and validation results showed that SWAT–MODFLOW can well simulate streamflow and groundwater levels in BSRW. Our results showed that BSRW had lower average monthly total stream resources (MSR = 8.8 × 107 m3) in growing seasons than in non-growing seasons (MSR = 11.0 × 107 m3), and monthly pond resources (MPR from 30,418 to 30,494 m3) varied less than stream resources. The proportion of sub-basins in BSRW with stream water resources greater than 700 mm was 21% in dry years (229 to 994 mm), while this increased to 35% in normal years (296 to 1141 mm) and 57% in wet years (554 to 991 mm). The Water Stress Index (WSI) ranged from 0.4 to 2.1, revealing that most of the sub-basins in BSRW have net SWR available for irrigation. Our results suggested that surface water resources might be supplementary irrigation sources to mitigate the water resources scarcity in this region.
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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 | 0.001 | 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) | 0.001 | 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 it