Climate Change-Driven Shoreline Dynamics and Sustainable Fisheries: Future Projections from the Lake Van Case (Türkiye)


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Akkuş M.

Sustainability, cilt.18, sa.3, ss.1-12, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 18 Sayı: 3
  • Basım Tarihi: 2026
  • Doi Numarası: 10.3390/su18031611
  • Dergi Adı: Sustainability
  • Derginin Tarandığı İndeksler: Scopus, Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.1-12
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

Shoreline variations in closed-basin lakes are closely linked to hydrological fluctuations and long-term changes in water balance, making them important indicators of environmental change. This study analyzes historical shoreline dynamics in Lake Van (Türkiye), the world’s largest soda lake, and provides scenario-based shoreline projections for 2032 and 2042 to support hydrological assessment and water-related management. Multi-temporal Landsat satellite images from 1982, 1992, 2002, 2012, and 2022 were processed using the Digital Shoreline Analysis System (DSAS 5.0) to quantify shoreline retreat and accretion, while future shoreline positions were estimated using the Kalman filter model. The results show pronounced spatial variability, with the most significant shoreline retreat observed in the Çelebiba˘g and Karahan regions, where sediment supplied by major inflowing streams contributes to shoreline instability through reworking and redistribution rather than stable accretion. Net shoreline movement values reached −2580.1 m for erosion and up to 1700 m for accretion. Model projections indicate an increasing trend of shoreline retreat by 2032 and 2042, accompanied by localized accretion zones. These hydrological-driven shoreline changes have potential implications for littoral habitats, water–land interactions, and human use of the shoreline, including fisheries infrastructure. The study demonstrates the value of integrating remote sensing and statistical forecasting for monitoring shoreline dynamics in closed-basin lake systems.