Sürdürülebilir Kalkınma Amaçları

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Yazarlar

• Afsin, Mustafa(1)
• Aksever, Fatma(1)
• Aktug, Bahadir(1)
• Aladogan, Kayhan(1)
• Biswas, A(1)
• Cakansimsek Unlukaya, Ece Bengunaz(1)
• Davraz, Aysen(1)
• Demirelli, Ertugrul(1)
• Dönmez, Ergin(1)
• Eyübagil, Eda Esma(1)
• Gezgin, Cemil(1)
• Gülal, Vahap Engin(1)
• Maden, Nafiz(1)
• Sahiner, Furkan(1)
• Sharma, SP(1)
• Solak, Halil Ibrahim(1)
• Tiryakioglu, Ibrahim(1)
• Yalvaç, Sefa(1)
• Yigit, Cemal Ozer(1)
• Yildirim, Muhiddin Can(1)

• MakaleAçık Erişim2026Scopus SJRQ1/r/gumushane/10585
  Modeling Long-Term Postseismic Deformation Following the 2020 Mw 7.0 Samos Earthquake Using Campaign and Continuous GNSS Observations

  Solak, Halil Ibrahim; Tiryakioglu, Ibrahim; Gezgin, Cemil; Aladogan, Kayhan; Yalvaç, Sefa; Aktug, Bahadir; Yigit, Cemal Ozer; Dönmez, Ergin; Demirelli, Ertugrul; Eyübagil, Eda Esma

  Highlights What are the main findings? What are the implications of the main findings?Highlights What are the main findings? What are the implications of the main findings?Abstract Postseismic deformation provides fundamental insights into earthquake-cycle processes, lithospheric rheology, and stress redistribution following large earthquakes. Although the 2020 Mw 7.0 Samos earthquake has been extensively investigated in terms of coseismic deformation and early postseismic behavior, the long-term evolution of deformation following the event remains poorly constrained. This study characterizes the long-term spatiotemporal evolution of postseismic deformation associated with the 2020 Mw 7.0 Samos earthquake using combined campaign and continuous GNSS observations. A total of 18 GNSS stations were analyzed over an approximately 4.5-year period following the earthquake. Pre-earthquake GNSS velocities were incorporated as prior constraints, while postseismic deformation was modeled using linear, logarithmic, exponential, and combined logarithmic-exponential functions. The preferred model for each station component was identified using the corrected Akaike Information Criterion (AICc), and model-selection robustness was evaluated through 1000 Monte Carlo observation-perturbation simulations. The results reveal a spatially heterogeneous postseismic deformation field with station-dependent temporal behavior. Among the nonlinear solutions passing the Monte Carlo and goodness-of-fit criteria, the seven single-process LOG and EXP solutions yielded characteristic relaxation times ranging from 182.6 to 730.5 days, with a median of 438.3 days. The two LOGEXP solutions additionally contained a logarithmic timescale of 109.6 days and exponential timescales of 292.2-438.3 days. These findings demonstrate that campaign GNSS observations, when integrated with continuous GNSS data and an objective statistical framework, can provide meaningful constraints on the long-term evolution of postseismic deformation despite sparse temporal sampling. More broadly, the results emphasize the strongly time-dependent nature of postseismic deformation and the critical role of observation timing in capturing its spatiotemporal evolution.

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• Kitap BölümüYalnız künye2020/r/gumushane/16269
  Geothermal Potential and Circulation Depth of Hudai Thermal Springs (Sandikli-Afyonkarahisar, Turkiye) Using Magnetic, Geothermometry and Heat Flow Data

  Maden, Nafiz; Afsin, Mustafa; Aksever, Fatma; Davraz, Aysen; Biswas, A; Sharma, SP

  The Hudai-Sandikli geothermal basin having 23 thermal productivity wells is a significant geothermal energy source field. The analysis of power spectrum, conventional heat flow and silica heat flow methods were implemented to identify the geothermal waters circulation depth, depth to Curie point and surface heat flow rate in the Hudai-Sandikli geothermal field. Hydrogeochemical facies of geothermal immature ancient waters having deep circulation in lower hydraulic conductive aquifers are Na-Ca-HCO3-SO4 and Na-Ca-SO4-HCO3, which is represented very high ion content because of extensive contact with rocks. The heat conduction law is employed to specify the rate of heat flow using the geothermal gradient value. The numerical results determined from silica geothermometer method, the mean heat flow density and Curie temperature depth are obtained as 103.69 mWm(-2) and 11.81 km, respectively. The study region was represented by a mean geothermal gradient of 49.18 degrees C km(-1) yielding average reservoir depths of 0.90 km. The estimated Curie temperature, heat flow, reservoir temperature values demonstrated that the region indicates significant geothermal energy potential because of the partial melting of lithospheric crust.

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  AtıfWoS1·OpenAlex3

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