Öz et al. (2026) Deciphering Reservoir Storage Variability: A Multi-Reservoir Assessment of Hydroclimatic Drought Responses in Northwestern Türkiye

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Identification

• Journal: Atmosphere
• Year: 2026
• Date: 2026-09-21
• Authors: Fatma Yaman Öz, Esra Eren, Emre Özelkan, Hasan Tatlı, Muhittin Karaman
• DOI: 10.3390/atmos17090910

Research Groups

Not specified in the provided text.

Short Summary

This study evaluates the response of 12 reservoirs in northwestern Türkiye to hydroclimatic drought using various statistical models and drought indices. The results indicate that 6–12 month drought indices are the primary predictors of reservoir storage, with Random Forest generally providing the highest predictive performance.

Objective

• To evaluate reservoir storage responses to hydroclimatic drought and identify the most effective drought indices and predictive models across 12 reservoirs in northwestern Türkiye.

Study Configuration

• Spatial Scale: 12 reservoirs located within the Marmara, Susurluk, Meriç–Ergene, and Northern Aegean basins of northwestern Türkiye.
• Temporal Scale: 2013–2022.

Methodology and Data

• Models used: Random Forest (RF), Linear Models (LMs), Generalized Additive Models (GAMs), and Leave-one-year-out cross-validation (LOYO-CV).
• Data sources: Meteorological data from 27 stations (used to calculate SPI, SPEI, and RDI at 1, 3, 6, 9, and 12-month scales), agricultural-area NDVI, and reservoir characteristics.

Main Results

• Drought indices at 6–12 month scales were the dominant predictors for 11 of the 12 reservoirs.
• Random Forest (RF) was the best-performing model in 20 of 48 reservoir–season combinations, compared to 16 for LMs and 12 for GAMs.
• A strong correlation (mean r = 0.88) was found between basin mean and local drought series.
• Local hydroclimatic heterogeneity was highlighted by changes in dominant predictors across eight of the reservoirs.
• Agricultural NDVI showed significant spatial and temporal variability but did not serve as a direct measure of reservoir-specific withdrawals.

Contributions

• The study provides an integrated cross-validation and spatial sensitivity framework that enhances the assessment of reservoir drought sensitivity, accounting for cumulative hydroclimatic conditions and reservoir-specific variability to support adaptive water resource management.

Funding

Not specified in the provided text.

Citation

@article{Öz2026Deciphering,
  author = {Öz, Fatma Yaman and Eren, Esra and Özelkan, Emre and Tatlı, Hasan and Karaman, Muhittin},
  title = {Deciphering Reservoir Storage Variability: A Multi-Reservoir Assessment of Hydroclimatic Drought Responses in Northwestern Türkiye},
  journal = {Atmosphere},
  year = {2026},
  doi = {10.3390/atmos17090910},
  url = {https://doi.org/10.3390/atmos17090910}
}