Evaluating the impacts of climate change and crop land use change on streamflow, nitrates and phosphorus: A modeling study in Bavaria
Bibliographic record
Abstract
Study region Bavaria, Germany. Study focus The Altmühl River is prone to nutrient inputs from agricultural activities. Quantifying nitrate nitrogen (NO 3 − -N) and total phosphorus (TP) concentrations due to potential future changes in the watershed is necessary for managing water quality and adhering to water policy directives. The Soil and Water Assessment Tool (SWAT) was used to provide stakeholders with support in determining the impacts of climate change (CC) in combination with crop land use change (LUC) scenarios on streamflow, NO 3 − -N and TP to the 2050 time horizon. The CC simulations stemmed from RCMs and the LUC scenarios were developed with stakeholders. New hydrological insights for the region When CC was combined with LUC, mean annual NO 3 − -N loads increased 3-fold, and TP loads 8-fold, compared to the CC simulations alone. Nutrient loads were higher in several months due to the future increased annual precipitation plus the additional fertilizer input in the land use scenarios. The maize areas above the Altmühl Lake contributed greatly to TP loads, while winter wheat areas mainly contributed to NO 3 − -N loads. When CC was combined with LUC, the in-stream nutrient concentrations exceeded ministerial guidelines of 11 mg TP/L and 0.05 mgNO 3 − -N/L every month at the outlet. CC simulations combined with LUC scenarios demonstrated non-linear dynamics whereby the direction and the magnitude of impacts were not predictable from the individual changes alone.
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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 | 0.001 | 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) | 0.000 | 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".