To Investigate the Impact of Land Use Change on the Potential Groundwater Recharge on Hillslope With Deep Loess Deposits
Bibliographic record
Abstract
ABSTRACT Accurately estimating groundwater recharge in hilly areas with limited water and thick vadose zones is challenging. This study investigated the impact of land use changes on groundwater recharge at a hillslope scale of Yuanzegou Watershed in China's Loess Plateau. Three adjacent hillslopes were selected for three different land uses: arbor (jujube, Ziziphus jujuba Mill.), subshrub (native grass, Artemisia gmelinii), and crop (millet, Setaria italica). Soil cores (as deep as 10–16/18 m) were collected at each of the three landscape positions on a hillslope. Reported tritium profiles in the watershed were used to estimate the net chloride input into vadose zone on hillslope associated with inverse chloride mass balance (CMB) method/chloride accumulation method (CAM). Soil water content and chloride profiles in the study were measured to determine recharge rates at each landscape position beneath different vegetation types. For the first time, we evaluated the actual chloride input into vadose zone on hillslopes as 540.2 ± 23.8 mg m−2 yr.−1, excluding the impact of runoff. Then, estimated recharge rates ranged from 42.7 ± 3.5 to 62.4 ± 4.7 mm yr.−1, consistent with nearby studies. Results showed that groundwater recharge does not change with landscape position except for higher value on upslope beneath subshrub hillslope. In contrast, groundwater recharge did significantly reduce by 12.9% ± 5.4% and 26.5% ± 4.5% after conversion from cropland to subshrub/arbor on the hillslope, respectively. Our findings contribute to understanding the ecohydrological effects of land use changes on groundwater recharge on hillslope and help to select suitable afforested vegetation for greening efforts in water‐limited hilly areas, with a priority on groundwater safety.
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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 | 0.000 | 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) | 0.001 | 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 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".