Araştırma Makalesi

Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025)

Cilt: 13 Sayı: 1 20 Ekim 2026
PDF İndir
EN TR

Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025)

Öz

Water availability in the Atatürk Dam basin, the largest reservoir of the Southeastern Anatolia Project (GAP) and a snow-fed Euphrates headwater, is sensitive to warming, yet its climatic drivers have not been ranked. Existing studies use trend tests, process models, or black-box machine learning. This study attributes and forecasts total runoff (a water-availability proxy) from basin-mean monthly ERA5-Land data (1950–2025), using XGBoost against linear and random-forest baselines under leakage-free cross-validation and exact TreeSHAP. The model reproduced the reanalysis runoff (R² ≈ 0.97, NSE ≈ 0.96), and SHAP ranked three-month accumulated snowmelt, deep-layer soil moisture, and water-year cumulative precipitation as the dominant drivers, with nonlinear thresholds; permutation and water-balance tests confirmed it is leakage-free. Antecedent snow-depth memory weakened over time while the snowmelt share was preserved, consistent with significant warming, snow decline, and rising evaporative demand (Mann–Kendall, Sen's slope); annual runoff showed no trend. From antecedent state, runoff was forecast about three months ahead (one-month R² ≈ 0.89). The framework can inform climate-resilient GAP reservoir operation; as it is reanalysis-based and unvalidated against gauges, future work should add gauge validation and gridded, scenario-based settings.

Anahtar Kelimeler

Explainable artificial intelligence, XGBoost, SHAP, Water availability, ERA5-Land

Destekleyen Kurum

Hakkari University

Proje Numarası

FM19BAP

Etik Beyan

During the preparation of this manuscript, the artificial intelligence tool "Gemini" developed by "Google" was used to a limited extent solely for linguistic refinement. The scientific content, analysis, and results are entirely the responsibility of the author(s).

Teşekkür

Acknowledges the Copernicus Climate Change Service (C3S) and the European Centre for Medium-Range Weather Forecasts (ECMWF) for the ERA5-Land reanalysis data, the HydroSHEDS/HydroBASINS project for the basin-delineation data, Natural Earth for the administrative boundary data, the OpenStreetMap contributors for the hydrographic data, Esri and its World Imagery contributors for the satellite basemap imagery, and the AWS Open Data Terrain Tiles (terrarium-encoded elevation) for the shaded-relief topography used in the study-area figure.

Kaynakça

  1. Ohara N, Kavvas ML, Anderson ML, Richard Chen ZQ, Yoon J. Water Balance Study for the Tigris-Euphrates River Basin. Journal of Hydrologic Engineering 2011;16:1071–82. https://doi.org/10.1061/(asce)he.1943-5584.0000209
  2. Bozkurt D, Sen OL. Climate change impacts in the Euphrates–Tigris Basin based on different model and scenario simulations. Journal of Hydrology 2013;480:149–61. https://doi.org/10.1016/j.jhydrol.2012.12.021
  3. Şorman AA, Uysal G, Şensoy A. Probabilistic Snow Cover and Ensemble Streamflow Estimations in the Upper Euphrates Basin. Journal of Hydrology and Hydromechanics 2019;67:82–92. https://doi.org/10.2478/johh-2018-0025
  4. Sen OL, Unal A, Bozkurt D, Kindap T. Temporal changes in the Euphrates and Tigris discharges and teleconnections. Environmental Research Letters 2011;6:024012. https://doi.org/10.1088/1748-9326/6/2/024012
  5. Şensoy A, Uysal G, Doğan YO, Civelek HS. The Future Snow Potential and Snowmelt Runoff of Mesopotamian Water Tower. Sustainability 2023;15:6646. https://doi.org/10.3390/su15086646
  6. Uysal G, Dogan YO, Civelek HS, Sorman AA, Sensoy A. Analyzing the Effects of Climate Change for the Water Tower of Mesopotamia, Türkiye. Proceedings of IAHS 2024;385:465–70. https://doi.org/10.5194/piahs-385-465-2024
  7. Imteaz MA, Mahmood W, Sagar KA, Yilmaz A. Climate change fingerprints in lower Euphrates basin: climate and flow data trend analysis. International Journal of Water 2017;11:279. https://doi.org/10.1504/ijw.2017.085888
  8. Yenigün K, Gümüş V, Bulut H. Trends in streamflow of the Euphrates basin, Turkey. Proceedings of the Institution of Civil Engineers - Water Management 2008;161:189–98. https://doi.org/10.1680/wama.2008.161.4.189
  9. Gumus V, Simsek O, Avsaroglu Y, Agun B. Spatio‐temporal trend analysis of drought in the GAP Region, Turkey. Natural Hazards 2021;109:1759–76. https://doi.org/10.1007/s11069-021-04897-1
  10. Zeray Öztürk E. Evaluation of Water Storage Changes in Southeastern Anatolia, Turkey, using GRACE and GLDAS. Meteorology Hydrology and Water Management 2022. https://doi.org/10.26491/mhwm/149849

Kaynak Göster

APA
Gül, E. (2026). Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025). Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, 13(1), 1-19. https://doi.org/10.54365/adyumbd.1984661
AMA
1.Gül E. Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025). Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2026;13(1):1-19. doi:10.54365/adyumbd.1984661
Chicago
Gül, Ertuğrul. 2026. “Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025)”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 13 (1): 1-19. https://doi.org/10.54365/adyumbd.1984661.
EndNote
Gül E (01 Ekim 2026) Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025). Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 13 1 1–19.
IEEE
[1]E. Gül, “Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025)”, Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, c. 13, sy 1, ss. 1–19, Eki. 2026, doi: 10.54365/adyumbd.1984661.
ISNAD
Gül, Ertuğrul. “Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025)”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 13/1 (01 Ekim 2026): 1-19. https://doi.org/10.54365/adyumbd.1984661.
JAMA
1.Gül E. Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025). Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2026;13:1–19.
MLA
Gül, Ertuğrul. “Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025)”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, c. 13, sy 1, Ekim 2026, ss. 1-19, doi:10.54365/adyumbd.1984661.
Vancouver
1.Ertuğrul Gül. Climatic Drivers of Water Availability in the Atatürk Dam Basin: An Explainable Machine-Learning (XGBoost–SHAP) Framework Using ERA5-Land (1950–2025). Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 01 Ekim 2026;13(1):1-19. doi:10.54365/adyumbd.1984661