Kayseri ilinde deprem tehlikesinin, sezgisel ve istatistiksel modellerle karşılaştırmalı analizi

Öz

Türkiye genelinde, 6 Şubat 2023 Kahramanmaraş depremleri ile birlikte, depremin yıkıcılığı karşısında hem toplumsal hem de idari anlamda hassasiyet önemli ölçüde artmıştır. Olası afet tehlikeleri ve bunlara karşı kırılganlık-esneklik, zarar görme potansiyeli-dayanıklılık, yıkıcı etki-iyileşme, dönüşüm ve dirençlilik gibi kavramlar artık daha sık gündeme gelmektedir. Ancak bu konularda esas olarak dikkat edilmesi gereken, inşa, imar, kontrol ve değişim süreçlerinde söz sahibi olan kişi ve kuruluşlardır. Sağlıklı ve sürdürülebilir bir yapılaşma süreci için farkındalığın artırılması gerekmektedir. Bu çalışma, Kayseri ilindeki depremselliği ve olası etkilerini mekânsal boyutuyla ortaya koymakta ve analiz etmektedir. İldeki deprem tehlikesini belirlemek için bağımlı değişken olmaması nedeniyle, 10 bağımsız değişken kullanılarak sezgisel modellerden Analitik Hiyerarşi Prosesi (AHP) ve Fuzzy AHP (Bulanık AHP) uygulanmıştır. Bu iki modelden elde edilen sonuç haritalarında, %90 ve üzeri tehlikeye sahip alanlar bağımlı değişken olarak kullanılarak aynı bağımsız değişkenlerle (Episantr Yoğunluk, Fay Uzaklık, VS30, Litoloji, Yerleşme Gelişim, Bina Kat Sayısı, Zemin Sıvılaşma Duyarlılığı, Episantr Uzaklık, Eğim ve Yükselti) Rastgele Orman algoritması ile alternatif bir tehlike haritası üretilmiştir. Üç harita da birbirine yakın sonuçlar vermiş olmasına rağmen, Rastgele Orman modelinin mekânsal dağılım ve uyum açısından daha ayırt edici bir harita ürettiği tespit edilmiştir. İl genelinde Sarıoğlan-İncesu hattı boyunca uzanan depresyonlar en tehlikeli alanları oluşturmaktadır. Bu saha, aynı zamanda il genelindeki en yoğun nüfuslu kuşağa denk gelmektedir. Türkiye’de ortalama kat sayısının en fazla olduğu il olan Kayseri’de, özellikle il merkezindeki yüksek katlı binalar deprem tehlikesinin olası etkilerini arttırma potansiyeline sahiptir.

Anahtar Kelimeler

• Kayseri
• Deprem
• Afet
• AHP
• Fuzzy AHP
• Rastgele Orman

Comparative analysis of earthquake hazard in Kayseri province using intuitive and statistical models

Öz

Following the Kahramanmaraş earthquakes of 6 February 2023, sensitivity to the destructive effects of earthquakes has increased significantly throughout Turkey, both socially and administratively. Concepts such as potential disaster risk, vulnerability - resilience, damage potential - durability, destructive impact - recovery, transformation and sustainability are now being discussed more frequently. However, the primary focus should be on the individuals and organisations responsible for construction, planning, control and change processes. Raising awareness is essential for a healthy and sustainable building process. This study identifies and analyses the seismic activity and its potential impacts in Kayseri province from a spatial perspective. Analytic Hierarchy Process (AHP) and Fuzzy AHP were applied to determine the seismic hazard of the province using 10 independent variables, as no dependent variable was available. In the hazard maps derived from these two models, areas with a risk of 90% or more were used as the dependent variable, and an alternative hazard map was generated using the same independent variables with the Random Forest algorithm. Although all three maps produced similar results, the Random Forest model was found to produce a more distinctive map in terms of spatial distribution and orientation. The depressions along the Sarıoğlan-Incesu fault line were identified as the most vulnerable areas in the province. This area is also the most densely populated belt in the province. In Kayseri, which has the highest average number of storeys in buildings in Turkey, the high-rise buildings in the city centre are considered to have the potential to amplify the effects of earthquake hazards.

Anahtar Kelimeler

• Kayseri
• Earthquake
• Disaster
• AHP
• Fuzzy AHP
• Random Forest

Kaynakça

1. AFAD. (2024). Deprem Kataloğu. https://deprem.afad.gov.tr/event-catalog
2. AFAD. (2018). Türkiye’de Afet Yönetimi ve Doğa Kaynaklı Afet İstatistikleri. Afet ve Acil Durum Yönetimi Başkanlığı, Ankara. https://www.afad.gov.tr/kurumlar/afad.gov.tr/35429/xfiles/turkiye_de_afetler.pdf
3. AFAD. (2021). İl Risk Azaltma Planı, Kayseri (İRAP). Afet ve Acil Durum Yönetimi Başkanlığı, Kayseri. https://kayseri.afad.gov.tr/kurumlar/kayseri.afad/Egitim/Kayseri_IRAP_Baski.pdf
4. Akgül, A. (2023). Kayseri il merkezi için Vs30 kayma dalgası hızı haritalarının hazırlanması (Tez Yayın No: 801843) [Yüksek Lisans Tezi, Nevşehir Hacı Bektaş Veli Üniversitesi]. YÖK Tez Merkezi.
5. Allen, T. I., Wald, D. J. (2007). Topographic slope as a proxy for seismic site-conditions (VS30) and amplification around the globe. Geological Survey (US), No. 2007-1357, https://pubs.usgs.gov/of/2007/1357/
6. Anwar, G. A., Dong, Y. (2020). Seismic resilience of retrofitted RC buildings. Earthquake Engineering and Engineering Vibration. 19(3), 561-571. https://doi.org/10.1007/s11803-020-0580-z
7. Boğaziçi Üniversitesi Kandilli Rasathanesi ve Deprem Araştırma Enstitüsü. (2023). Regional Earthquake-Tsunami Monitoring and Evaluation Center - Earthquake Catalog. http://www.koeri.boun.edu.tr/sismo/zeqdb/
8. Borcherdt, R. D. (2012, September 24-28). VS30–A site-characterization parameter for use in building Codes, simplified earthquake resistant design, GMPEs and ShakeMaps [Conference presentation]. In the 15th world conference on earthquake engineering. Lisbon, Portugal. https://pubs.usgs.gov/publication/70041709 Breiman, L. (2001). Random forests. Machine learning, 45, 5-32. https://link.springer.com/article/10.1023/a:1010933404324

9. Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649-655. https://doi.org/10.1016/0377-2217(95)00300-2
10. Emre, Ö., Duman, T.Y., Özalp, S., Elmacı H., Olgun, Ş. (2011). 1:250.000 Ölçekli Türkiye Diri Fay Haritası Serisi. Seri No: 32, Maden Tetkik ve Arama Genel Müdürlüğü, Ankara, https://mta.gov.tr/v3.0/hizmetler/diri-fay-haritalari
11. Erdem, F., Derinpınar, M. A., Nasırzadehdızajı, R. , Oy, S. , Şeker, D. Z. Bayram, B. (2018). Rastgele orman yöntemi kullanılarak kıyı çizgisi çıkarımı İstanbul örneği. Geomatik, 3(2), 100-107. https://doi.org/10.29128/geomatik.362179
12. ESRI, Environmental Systems Research Institute. (2023). Sentinel-2 10m Land Use/Land Cover Time Series.
13. ESRI. https://www.arcgis.com/home/item.html?id=d3da5dd386d140cf93fc9ecbf8da5e31
14. Field, E. H. (2000). Accounting for site effects in probabilistic seismic hazard analyses of Southern California: overview of the SCEC Phase III report. Bulletin of the Seismological Society of America, 90(6B), 1-31. https://doi.org/10.1785/0120000512
15. Gilbert, S. W. (2016). Disaster resilience: A guide to the literature. CreateSpace Independent Publishing Platrorm.
16. Gutenberg, B., Richter, C. F. (1944). Frequency of earthquakes in California. Bulletin of the Seismological society of America, 34(4), 185-188. https://doi.org/10.1785/BSSA0340040185
17. Harff, J., Meschede, M., Petersen, S., Thiede, J. (Eds.). (2016). Encyclopedia of marine geosciences. Springer Science Business Media. https://doi.org/10.1007/978-94-007-6644-0
18. Heath, D. C., Wald, D. J., Worden, C. B., Thompson, E. M., Smoczyk, G. M. (2020). A global hybrid VS30 map with a topographic slope-based default and regional map insets. Earthquake Spectra, 36(3), 1570–1584. https://earthquake.usgs.gov/data/vs30/
19. Hu, J., Chen, J., Chen, Z., Cao, J., Wang, Q., Zhao, L., Zhang, H., Xu, B., Chen, G. (2018). Risk assessment of seismic hazards in hydraulic fracturing areas based on fuzzy comprehensive evaluation and AHP method (FAHP): A case analysis of Shangluo area in Yibin City, Sichuan Province, China. Journal of Petroleum Science and Engineering, 170, 797-812. https://doi.org/10.1016/j.petrol.2018.06.066
20. Jennings, P. C. (2003). An introduction to the earthquake response of structures. International Geophysics, 81, 1097-1125. https://doi.org/10.1016/S0074-6142(03)80181-X
21. Kant Sharma, L., Kanga, S., Singh Nathawat, M., Sinha, S. and Chandra Pandey, P. (2012), Fuzzy AHP for forest fire risk modeling. Disaster Prevention and Management, 21(2), 160-171. https://doi.org/10.1108/09653561211219964
22. Koks, E. E., Jongman, B., Husby, T. G., Botzen, W. J. (2015). Combining hazard, exposure and social vulnerability to provide lessons for flood risk management. Environmental Science Policy, 47, 42-52. https://doi.org/10.1016/j.envsci.2014.10.013
23. Koks, E. E., Rozenberg, J., Zorn, C., Tariverdi, M., Vousdoukas, M., Fraser, S. A. (2019). A global multi-hazard risk analysis of road and railway infrastructure assets. Nature Communications, 10(1), 1-11. https://doi.org/10.5281/zenodo.2583746
24. Kramer, S. L. (1996). Geotechnical earthquake engineering. Pearson Education India. Lee, C.; Schaaf, T. (2006, 19-21 June). The Future of Drylands [Conference presentation]. International Scientific Conference on Desertification and Drylands Research. Tunis, Tunisia. https://doi.org/10.1007/978-1-4020-6970-3
25. Marconcini, M., Metz-Marconcini, A., Üreyen, S., Palacios-Lopez, D., Hanke, W., Bachofer, F. (2020). World Settlement Footprint (WSF) 2015. Dataset. https://doi.org/10.6084/m9.figshare.10048412.v1
26. McGuire R (2004). Seismic hazard and risk analysis: earthquake engineering research institute. Monograph. https://faeng.ufms.br/files/2019/06/PGA_Seismic-Hazard-And-Risk-Analysis_McGuire_2004.pdf
27. MICROSOFT. (2023). Microsoft Building Footprints, Türkiye. MICROSOFT, https://github.com/Microsoft/USBuildingFootprints
28. Mokarram, M., Negahban, S. Abdeldjalil, B. (2021). GIS-based fuzzy-analytic network process (FAHP), fuzzy-analytic hierarchy process (FANP) methods and feature selection algorithm (FSA) to determine earthquake-prone areas in Kermanshah Province. Environ Earth Sci, 80(633), 1-16. https://doi.org/10.1007/s12665-021-09934-7
29. Morell, K. D., Styron, R., Stirling, M., Griffin, J., Archuleta, R., Onur, T. (2020). Seismic hazard analyses from geologic and geomorphic data: Current and future challenges. Tectonics, 39(10), 1-47. https://doi.org/10.1029/2018TC005365
30. MTA (2024). Kayseri Jeoloji Haritası. Maden Tetkik ve Arama Genel Müdürlüğü, https://eticaret.mta.gov.tr/index.php?route=product/productpath=2_46product_id=36727
31. Nyimbili, P.H., Erden, T. & Karaman, H. (2018). Integration of https://eticaret.mta.gov.tr/index.php?route=product/productpath=2_46product_id=36727
32. Nyimbili, P.H., Erden, T. & Karaman, H. (2018). Integration of GIS, AHP and TOPSIS for earthquake hazard analysis. Nat Hazards, 92, 1523-1546. https://doi.org/10.1007/s11069-018-3262-7
33. Ochoa, L. H., Niño, L. F., Vargas, C. A. (2018). Fast estimation of earthquake epicenter distance using a single seismological station with machine learning techniques. Dyna, 85(204), 161-168. https://doi.org/10.15446/dyna.v85n204.68408
34. Öncü, S. (2021). CBS yöntemiyle Bursa’nın bütünleşik doğal tehlike analizi (Tez Yayın No: 696829) [Yüksek Lisans Tezi, Bursa Uludağ Üniversitesi]. YÖK Tez Merkezi.
35. Özmen, M. (2023). Evaluating earthquake vulnerability of 2023 Kayseri, Türkiye via BWM-ABAC method. Sādhanā, 48(3), 1-20. https://doi.org/10.1007/s12046-023-02216-x
36. Pesaresi, M., Politis, P. (2023). GHS-BUILT-H R2023A - GHS building height, derived from AW3D30, SRTM30, and Sentinel2 composite. European Commission, Joint Research Centre. http://data.europa.eu/89h/85005901-3a49-48dd-9d19-6261354f56fe
37. Rashed, T., & Weeks, J. (2003). Assessing vulnerability to earthquake hazards through spatial multicriteria analysis of urban areas. International Journal of Geographical Information Science, 17(6), 547-576. https://doi.org/10.1080/1365881031000114071
38. Rusydi, H., Effendi, R., Rahmawati, R. (2017). Vulnerability zoning of earthquake disaster of Palu. Universitas Sebelas Maret, International Journal of GEOMATE, 1(2), 137-143. https://doi.org/10.20961/ijsascs.v1i2.5138 Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. McGraw-Hill International.
39. Sagara, J., Saito, K. (2013). Risk assessment and hazard mapping. World Bank, https://openknowledge.worldbank.org/handle/10986/16146
40. Sianko, I., Ozdemir, Z., Khoshkholghi, S., Garcia, R., Hajirasouliha, I., Yazgan, U., & Pilakoutas, K. (2020). A practical probabilistic earthquake hazard analysis tool: case study Marmara region. Bulletin of Earthquake Engineering, 18(6), 2523-2555. https://doi.org/10.1007/s10518-020-00793-4
41. SRTM, The Shuttle Radar Topography Mission. (2014). USGS SRTM DEM. NASA. https://doi.org/10.5066/F7PR7TFT Stein, S., Geller, R. J., Liu, M. (2012). Why earthquake hazard maps often fail and what to do about it. Tectonophysics, 562, 1-25. https://doi.org/10.1016/j.tecto.2012.06.047
42. Taş, N. (2003). Yerleşim alanlarında olası deprem zararlarının azaltılması. Uludağ Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 8(1), 225-231. https://acikerisim.uludag.edu.tr/items/bfd7c3ae-aa12-4511-a538-af9bc97985ce
43. TÜİK. (1997). 1997 Köy Envanter Etüdü Kayseri. T.C. Başbakanlık Devlet İstatistik Enstitüsü. https://kutuphane.tuik.gov.tr/pdf/0014605.pdf
44. TÜİK. (2022). Bina İstatistikleri. Türkiye İstatistik Kurumu. https://data.tuik.gov.tr/Bulten/Index?p=Survey-on-Building-and-Dwelling-Characteristics-2021-45870
45. TÜİK. (2024). Adrese Dayalı Nüfus Kayıt Sistemi Sonuçları. Türkiye İstatistik Kurumu. https://biruni.tuik.gov.tr
46. UNISDR, UN Office for Disaster Risk Reduction. (2009). 2009 UNISDR terminology on disaster risk reduction. UNISDR, Geneva. http://www.unisdr.org/we/inform/publicaitons/7817
47. WorldPop, (2020)a. Global Population Density. University of Southampton. https://dx.doi.org/10.5258/SOTON/WP00674
48. WorldPop, (2020)b. Global 100m Age/Sex Structures. University of Southampton. https://dx.doi.org/10.5258/SOTON/WP00646
49. Yanis, M., Furumoto, Y. (2019). Lithological identification of devastated area by Pidie Jaya earthquake through Poisson’s ratio analysis. GEOMATE, 17(63), 210-216. https://doi.org/10.21660/2019.63.77489
50. Yariyan, P., Zabihi, H., Wolf, I. D., Karami, M., Amiriyan, S. (2020). Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran. International Journal of Disaster Risk Reduction, 50, 1-17. https://doi.org/10.1016/j.ijdrr.2020.101705
51. Zadeh L.A. (1965). Fuzzy sets. Information and Control, 8, 338-353. https://pdf.sciencedirectassets.com/273276/1-s2.0-S0019995800X00952/1-s2.0-S001999586590241X/main.pdf?X-
52. Zhou, J., Huang, S., Wang, M., Qiu, Y. (2022). Performance evaluation of hybrid GA–SVM and GWO–SVM models to predict earthquake-induced liquefaction potential of soil: a multi-dataset investigation. Engineering with Computers, 38, 4197–4215. https://doi.org/10.1007/s00366-021-01418-3
53. Zhu, Z., Zhang, Y. (2022). Flood disaster risk assessment based on random forest algorithm. Neural Computing and Applications, 34, 3443–3455. https://doi.org/10.1007/s00521-021-05757-6