What about reservoirs? Questioning anthropogenic and climatic interferences on water availability
Bibliographic record
Abstract
Abstract Water resources in semi‐arid regions like the Mediterranean Basin are highly vulnerable because of the high variability of weather systems. Additionally, climate change is altering the timing and pattern of water availability in a region where growing populations are placing extra demands on water supplies. Importantly, how reservoirs and dams have an influence on the amount of water resources available is poorly quantified. Therefore, we examine the impact of reservoirs on water resources together with the impact of climate change in a semi‐arid Mediterranean catchment. We simulated the Susurluk basin (23.779‐km 2 ) using the Soil and Water Assessment Tool (SWAT) model. We generate results for with (RSV) and without reservoirs (WRSV) scenarios. We run simulations for current and future conditions using dynamically downscaled outputs of the MPI‐ESM‐MR general circulation model under two greenhouse gas relative concentration pathways (RCPs) in order to reveal the coupled effect of reservoir and climate impacts. Water resources were then converted to their usages – blue water (water in aquifers and rivers), green water storage (water in the soil) and green water flow (water losses by evaporation and transpiration). The results demonstrate that all water resources except green water flow are projected to decrease under all RCPs compared to the reference period, both long‐term and at seasonal scales. However, while water scarcity is expected in the future, reservoir storage is shown to be adequate to overcome this problem. Nevertheless, reservoirs reduce the availability of water, particularly in soil moisture stores, which increases the potential for drought by reducing streamflow. Furthermore, reservoirs cause water losses through evaporation from their open surfaces. We conclude that pressures to protect society from economic damage by building reservoirs have a strong impact on the fluxes of watersheds. This is additional to the effect of climate change on water resources.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".