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Journals / Coğrafya Dergisi / 2025 / Sayı: 50

An evaluation of the long-term changes in the shoreline of Lake Eğirdir in relation to climate and anthropogenic factors

Onur Yayla(MEHMET AKIF ERSOY UNIVERSITY, FACULTY OF ARTS AND SCIENCES, DEPARTMENT OF GEOGRAPHY)0000-0002-8710-3701
Hasan Akpınar(Süleyman Demirel University, Faculty of Humanities and Social Sciences, Department of Geography)0000-0002-8066-7459
Tuğçe Bilgin(Süleyman Demirel University, Faculty of Humanities and Social Sciences, Department of Geography)0000-0003-1883-3193
Yıldırım Atayeter(Süleyman Demirel University, Faculty of Humanities and Social Sciences, Department of Geography)0000-0002-7570-2993
Ogün Korkmaz(Süleyman Demirel University, Faculty of Humanities and Social Sciences, Department of Geography)0009-0007-9441-2944
Pages
65–78
Publication Date
2025-07-24
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Results indicated the highest EPR value of 61,06 m/yr at transect 2035, while the highest LRR value was 39,78 m/yr.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study quantifies shoreline changes in Lake Eğirdir between 1984 and 2024 by examining the direction, distance, and rate of change, along with climatic and anthropogenic influences.
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Key Findings & Data:Shoreline change rates were then calculated using the Digital Shoreline Analysis System (DSAS), employing metrics such as the End Point Rate (EPR), Linear Regression Rate (LRR), and Net Shoreline Movement (NSM).
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Conclusion & Impact:Results indicated the highest EPR value of 61,06 m/yr at transect 2035, while the highest LRR value was 39,78 m/yr.
🔬Design:Araştırma Makalesi
📍Scope:2024 Verileri
⚙️Variables:DSAS · Shoreline change · Eğirdir Lake

Abstract

This study quantifies shoreline changes in Lake Eğirdir between 1984 and 2024 by examining the direction, distance, and rate of change, along with climatic and anthropogenic influences. Landsat satellite images were used to delineate the lake's shoreline using the Modified Normalised Difference Water Index (MNDWI). Shoreline change rates were then calculated using the Digital Shoreline Analysis System (DSAS), employing metrics such as the End Point Rate (EPR), Linear Regression Rate (LRR), and Net Shoreline Movement (NSM). Results indicated the highest EPR value of 61,06 m/yr at transect 2035, while the highest LRR value was 39,78 m/yr. The NSM analysis revealed a maximum positive value of 2444,6 m, indicating significant recession in specific shoreline areas. The key factors driving these changes include climate change and agricultural irrigation practices. MannKendall trend analysis demonstrated a rising trend in maximum temperatures, although precipitation levels showed no significant variation. The expansion of fruit orchards around Lake Eğirdir has intensified water demand, resulting in a marked decline in water levels. This study highlights the combined impact of climatic shifts and human activities on shoreline dynamics, highlighting the need for sustainable water management strategies to mitigate further environmental degradation.

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Cite This Article

Yayla, O., Akpınar, H., Bilgin, T., Atayeter, Y., Korkmaz, O., *, H. A. (2025). An evaluation of the long-term changes in the shoreline of Lake Eğirdir in relation to climate and anthropogenic factors. Coğrafya Dergisi, Sayı: 50, 65–78. https://doi.org/10.26650/JGEOG2025-1620561

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References (56)

  1. Aksoy, T., Sarı, S., & Çabuk, A. (2019). Sulak alanların yönetimi kapsamında su indeksinin uzaktan algılama ile tespiti, Göller Yöresi. GSI Journals Serie B: Advancements in Business and Economics, 2(1). google scholar
  2. Alevkayalı, Ç., Atayeter, Y., Yayla, O., Bilgin, T., & Akpınar, H. (2023). Burdur Gölü’nde uzun dönemli kıyı çizgisi değişimleri ve iklim ilişkisi: Zamansal-mekânsal eğilimler ve tahminler. Türk Coğrafya Dergisi, (82), 37-50. google scholar
  3. Aslan and Koc-San (2021). Investigation of the changes in lake surface temperatures and areas: Case study of Burdur and Egirdir Lakes, Turkey. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 299-304. google scholar
  4. Atayeter, Y. (2005). Aksu Çayı Havzası’nın Jeomorfolojisi. Fakülte Kitabevi. google scholar
  5. Atayeter, Y. (2011). Eğirdir Gölü Depresyonu ve Yakın Çevresinin Genel Fiziki Coğrafyası. Fakülte Kitabevi. google scholar
  6. Ayadi, K., Boutiba, M., Sabatier, F., & Guettouche, M. S. (2016). Detection and analysis of historical variations in the shoreline using digital aerial photos, satellite images, and topographic surveys DGPS: case of Bejaia Bay (East Algeria). Arabian Journal of Geosciences, 9, 1-12. google scholar
  7. Aydin, FA, & Dogu, AF (2018). Level changes in lakes and their causes: Van Lake example. Journal of Yuzuncu Yil University Social Sciences Institute, (41), pp. 183-208. google scholar
  8. Bahadır, M. (2013). Akşehir Gölü’nde Alansal Değişimlerin Uzaktan Algilama Teknikleri ile Belirlenmesi. Marmara Coğrafya Dergisi, (28), 246-275. google scholar
  9. Baig, M. H. A.; Zhang, L.; Shuai, T.; Tong, Q. (2020). Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance. Remote Sensing Letters, 11 (1), 66-75. https://doi.org/10.1080/2150704X.2020.1714329 google scholar
  10. Baş, N. (2023). An effective approach for analysis of shoreline change and determination of its future location using satellite imagery: A case study of Lake Burdur, Turkey. Gümüşhane Üniversitesi Fen Bilimleri Dergisi, 14(1), 61-72. google scholar
  11. Bozyiğit, R., and Tapur, T. (2009). Konya ovası ve çevresinde yeraltı sularının obruk oluşumlarına etkisi. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (21), 137-155. google scholar
  12. Cengiz, T. M., & Kâhya, E. (2011). Türkiye göl su seviyelerinin eğilim ve harmonik analizi. İTÜDERGİSİ/d, 5(3). google scholar
  13. Coşkun, S. (2024). Göller Yöresi’nde sıcaklık, yağış ve akım değerlerinde meydana gelen eğilimler (Akdeniz Bölgesi-Türkiye). Socıal Scıences Studıes Journal (SSSJournal), 6(66), 3142-3155. google scholar
  14. Çankal, G., & Alkın, R. C. (2024). İklim Değişikliği, Bilinçsiz Tarım ve Afet Yönetimi: Karapınar Obruklarına Bir Bakış. Afet ve Risk Dergisi, 7(2), 410-425. google scholar
  15. Demir, İ., Kılıç, G., Coşkun, M., & Sümer, U. M. (2008). Türkiye’de maksimum, minimum ve ortalama hava sıcaklıkları ile yağış dizilerinde gözlenen değişiklikler ve eğilimler. TMMOB İklim Değişimi Sempozyumu, Bildiriler Kitabı, 69, 84. google scholar
  16. Dereli, M. A., & Tercan, E. (2020). Assessing shoreline changes using historical satellite images and geospatial analysis along the Lake Salda in Turkey. Earth science informatics, 13(3), 709-718. google scholar
  17. Dereli, M. A., & Tercan, E. (2020). Assessment of shoreline changes using historical satellite images and geospatial analysis along the Lake Salda in Turkey. Earth Sci Inform. 2013; 13(3): 709-718. google scholar
  18. Dolan, R., Fenster, M. S., & Holme, S. J. (1991). Temporal analysis of shoreline recession and accretion. Journal of coastal research, 723-744. google scholar
  19. Dönmez, S. (2018). Akşehir Gölü su seviyesinin çekilmesinin meteorolojik ve uydu verileri ile incelenmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 33(1). google scholar
  20. Dwyer, J. L., D. P. Roy, B. Sauer, C. B. Jenkerson, H. K. Zhang, and L. Lymburner (2018). Analysis of ready data: Enabling Landsat archive analysis. Remote Sensing, 10(9), 1363. https://doi.org/10.3390/rs10091405 google scholar
  21. Esper, J., Torbenson, M., & Büntgen, U. (2024). 2023 summer warmth unparalleled over the past 2,000 years. Nature, 1-2. google scholar
  22. European Centre for Medium-Range Weather Forecasts. (2024). Climate change services: Annual climate report 2024. Copernicus Climate Change Service. Retrieved from https://climate.copernicus.eu/annual-climate-report-2024. google scholar
  23. Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelate data. Journal of Hydrology, 204(1-4), 182-196. https://doi.org/10.1016/S0022-1694 (97)00125-X,)[https://doi.org/10.1016/S0022-1694(97)00125-X]; google scholar
  24. Himmelstoss, E. A., Henderson, R. E., Kratzmann, M. G., & Farris, A. S. (2021). Digital Shoreline Analysis System (DSAS), Version 5.1 User Guide (No. 2021-1053). U.S. Geological Survey. https://doi.org/10.3133/ofr20211053 google scholar
  25. Hwang, C. S., Choi, C. U., & Choi, J. S. (2014). Shoreline changes interpreted from multi-temporal aerial photographs and high resolution satellite images. A case study in Jinha beach. Korean Journal of Remote Sensing, 30(5), 607-616. google scholar
  26. Karmeshu, N. (2012). Trend detection in annual temperature & precipitation using the Mann-Kendall test-a case study to assess climate change on select States in the northeastern United States. Master of Environmental Studies Capstone Projects, 47, 1-33. google scholar
  27. Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons. google scholar
  28. Lu, D., & Weng, Q. (2007). A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing, 28(5), 823-870. google scholar
  29. Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13(3), 245-259. https://doi.org/10.2307/1907187 google scholar
  30. McFeeters, S. K. (1996). Use of the normalised difference water index (NDWI) for delineating open water features. International Journal of Remote Sensing, 17(7), 1425-1432. google scholar
  31. Mishra, R., Gupta, R. D., & Vishwakarma, A. K. (2019). Change detection analysis of coastlines using multi-temporal satellite images. Applied Geography, 102, 74-81. https://doi.Org/10.1016/i.apgeog.2018.11.010 google scholar
  32. Moore, L. J. (2000). Shoreline mapping techniques. Journal of Coastal Research, 16(1), 111-124. https://doi.org/10.1006/ecss.1999.0587 google scholar
  33. Moustafa, A. A., Elganainy, R. A., and Mansour, S. R. (2023). Insights into the UNSG announcement: The end of climate change and the arrival of the global boiling era, July 2023 confirmed as the hottest month recorded in the past 120,000 years. Catrina: The International Journal of Environmental Sciences, 28(1), 43-51. google scholar
  34. Nassar, K., Mahmod, W. E., Fath, H., Masria, A., Nadaoka, K., & Negm, A. (2019). Shoreline change detection using DSAS technique: Case of North Sinai coast, Egypt. Marine Georesources and Geotechnology, 37(1), 81-95. google scholar
  35. Onoz, B., and Bayazit, M. (2003). The power of statistical tests for trend detection. Turkish Journal of Engineering & Environmental Sciences, 27(4). google scholar
  36. Richards, J. A. (2013). Remote sensing digital image analysis: An introduction. Springer. google scholar
  37. Sabins, F. F. (1997). Remote sensing: Principles and interpretation. W. H. Freeman & Company. google scholar
  38. Sarp, G., & Özcelik, M. (2017). Water body extraction and change detection using time series data: A case study of Lake Burdur, Turkey. Journal of Taibah University for Science, 11(3), 381-391. google scholar
  39. Selçuk Biricik, A. S. (2014). Türkiye Sular Atlası. Oray Basım Yayın ve Matbaacılık. google scholar
  40. Sipahi, M. H. (1987). Aksu Çayı Havzası’nın (Antalya) Karst’ı ve Hidrojeolojisi. [Doktora tezi, İstanbul Üniversitesi]. google scholar
  41. Şen, C. (2013). Isparta İlinde Sıcaklık ve Yağış Verilerinin Trend Analizi, [Yüksek lisans tezi, Süleyman Demirel Üniversitesi]. YÖK Tez Merkezi. google scholar
  42. Taberi, H., Marofi, S., Aeini, A., Talaee, P.H., Mohammadi, K., 2011. Trend Analysis of Reference Evapotranspiration in the Western half of Iran. Agricultural and Forest Meteorology 151, 128-136. google scholar
  43. Tapur, T., & Bozyiğit, R. (2015). Konya Ilinde Güncel Obruk Oluşumlari. Marmara Coğrafya Dergisi, (31), 415-446. google scholar
  44. Thieler, E. R., Himmelstoss, E. A., Zichichi, J. L., and Miller, T. L. (2005). Digital shoreline analysis system (DSAS) version 3.0. An ArcGIS© extension for calculating shoreline change: US Geological Survey Open-File Report, 1304. google scholar
  45. Thieler, E. R., Mart’in, D., & Ergul, A. (2003). Digital Shoreline Analysis System (DSAS) version 2.0: An ArcView extension for calculating shoreline change (No. 2003-76). US Geological Survey. google scholar
  46. Thieler, E. R., J. F. O’Connell, and C. A. (2009). The Digital Shoreline Analysis System (DSAS) version 4.0-An ArcGIS extension for calculating shoreline change (No. 2008-1278). U.S. Geological Survey. https://doi.org/10.3133/ofr20081078 google scholar
  47. Turoğlu, H. (2017). Deniz ve Göllerde Kıyı. (Editörler: H. Turoğlu ve H. Yiğitbaşıoğlu), and Yasal ve Bilimsel Boyutlarıyla KIYI. Jeomorfoloji Derneği Yayınları, (1), 1-32, google scholar
  48. Uzun, M. (2024). Analysis of Manyas Lake Surface Area and Shoreline Changes over Various Periods with DSAS Tool. Turkish Journal of Remote Sensing, 6 (1), 35-56 google scholar
  49. Woodcock, C. E., Allen, R. G., & Anderson, M. C. (2008). Landsat 5 TM and Landsat 7 ETM+ data for land surface monitoring. Remote Sensing of Environment, 112(1), 215-219. https://doi.Org/10.1016/i.rse.2008.03.010 google scholar
  50. World Meteorological Organisation. (2024). United in Science 2024: A multi-organisation high-level compilation of the latest weather, climate, water, and related environmental and social sciences for the future. World Meteorological Organisation. https://library.wmo.int/idurl/4/69018 google scholar
  51. Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open-water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14), pp. 3025-3033. google scholar
  52. Yarar, A., & Onüçyıldız, M. (2009). Yapay sinir ağları ile Beyşehir Gölü su seviyesi değişimlerinin belirlenmesi. Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 24(2), 21-30. google scholar
  53. Yılmaz, M. (2010). Karapınar çevresinde yeraltı suyu seviye değişimlerinin yaratmış olduğu çevre sorunları. Ankara Üniversitesi Çevrebilimleri Dergisi, 2(2), 145-163. google scholar
  54. Yigit, A. Y., Senol, H. I., & Kaya, Y. (2022). Çok zamanlı multispektral uydu verilerinin Marmara Gölü kıyı değişimi analizinde kullanılması. Geomatik, 7(3), 253-260. google scholar
  55. Yue, S., Pilon, P., & Cavadias, G. (2002). Power of the Mann-Kendall and Spearman's rho tests for detecting monotonic trends in hydrological series. Journal of hydrology, 259(1-4), 254-271. google scholar
  56. Zheng, F., Hu, S., Ma, J., Wang, L., Li, K., Wu B, et al. & Zhu, J. (2024). The world will encounter the warmest winter in 2023. google scholar