Assessment of Drought Impacts in the Ebro Basin Using Hydro-Economic Modeling and Copula-Based Water Availability Simulations
Bibliographic record
Abstract
Climate change will exacerbate drought events in arid and semiarid basins, with longer and more intense drought spells. This will further jeopardize the sustainability of water systems in these basins, augmenting the uncertainty of streamflows and the risks of large economic and environmental damages. Hydro-economic modeling has been used already in the literature for analyzing the impacts of reduced water availability from climate change. However, previous studies do not consider the change in the scale of drought duration and intensity. This study closes this gap by combining hydro-economic analysis with a procedure based on copulas, where the copula procedure generates future climate water stress conditions with longer and more intense droughts. In this work, the joint probability function of two consecutive monthly water inflows is fitted by a Clayton copula, an asymmetric copula that captures the lower tail dependence implicit in drought persistence. Then, the hydro-economic model is used to analyze the economic impacts of climate change in the Ebro Basin of Spain. The reliability, resilience, and vulnerability of the water system are evaluated in order to assess the sustainability of the Ebro basin. Results show that there are costs of maladaptation when changes in drought duration and intensity from climate change are ignored, where maladaptation costs ensue from erroneous drought planning. Measures for drought management would be flawed because of the inaccurate evaluation of climate change hazards, given that the temporal dependence of climate variables is overlooked.
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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".