Research Article
BibTex RIS Cite

Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri

Year 2023, , 137 - 156, 25.05.2023
https://doi.org/10.26650/JGEOG2023-1177718

Abstract

Taşkın tehlike ve risk çalışmalarında temel altlık veri olarak yüzey topografyasını temsil etmesi bakımından raster tabanlı Sayısal Yükseklik Modelleri (SYM) sıklıkla kullanılmaktadır. Bu çalışmanın amacı; küresel ve lokal ölçekte kullanılan ve birçok çalışmalara altlık oluşturan farklı kaynaklı ve farklı çözünürlükteki SYM’lerle taşkın tehlike analizleri gerçekleştirerek, Ulus yerleşmesi (Bartın) temelindeki tehlikenin değişkenliğini ortaya koymaktır. Bu amaç doğrultusunda atlık verileri, Ulus Çayı havzası ve Ulus yerleşmesi için elde edilen MERIT 90m, FABDEM 30m, TopoSYM 10m, SYM5m, LiDAR 1m ve İHA 0,1m çözünürlüklü SYM verileri, Ulus yerleşmesine akış gösteren Ulus üst kolu, Süleyman, Alpı ve Eldeş akarsularının SWAT yağış-akış modeliyle üretilmiş 500 yıllık akımları oluşturmaktadır. Bu veriler ile mekânsal çözünürlük değişkenliğini iyi ortaya koyabilmek için sabit Manning n değeri kullanılarak (n=0.035), 2 boyutlu LISFLOOD-FP hidrodinamik model temelinde taşkın tehlike analizleri gerçekleştirilmiştir. Sonuç olarak düşük çözünürlükten yüksek çözünürlüğe model zamanı ve ortalama hesaplama hataları artarken, suyun yayılışı, insan ve bina için üretilen tehlike sınıflarının alansal dağılışı azalış göstermiştir. Bölgesel yapılacak çalışmalarda FABDEM verisi daha avantajlı iken havza bazlı yapılacak çalışmalarda LiDAR verisi veya üzerindeki bina ve bitki örtüsü topluluklarına ait yüksekliklerin temizlenmesi koşuluyla SYM5 verisi kullanılabilir verilerdir.

Supporting Institution

Bursa Uludağ Üniversitesi Bilimsel Araştırma Projeleri Birimi, TÜBİTAK

Project Number

OUAP(F)-2019/13 ve 121Y578

Thanks

Yazarlar, çalışma alanının içine alacak şekilde LiDAR verisini sağlayan Delta LiDAR firması ve İbrahim Şimşek’e teşekkür eder.

References

  • Abbaspour, K. C., Rouholahnejad, E., Vaghefi,, Srinivasan, R., Yang, H., & Kl0ve, B. (2015). A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a highresolution large-scale SWAT model. Journal of Hydrology, 524, 733-752. google scholar
  • Akbas, A., Freer, J., Ozdemir, H., Bates, P. D., & Turp, M. T. (2020). What about reservoirs? Questioning anthropogenic and climatic interferences on water availability. Hydrological Processes, 34(26), 5441-5455. google scholar
  • Akbaş, A., & Özdemir, H. (2021). Yağış-Akış Modellerinde ArcSwat Uygulaması: Bartın Çayı Havzası Örneği. In E. Akköprü, & M. F. Döker, Coğrafya Araştırmalarında Coğrafi Bilgi Sistemleri Uygulamaları (pp. 107-128). Ankara: Pegem Akademi. google scholar
  • Akbaş, A., & Özdemir, H. (2022). Tüm modeller yanlıştır, ancak bazıları faydalıdır: Akım Gözlem İstasyonu bulunmayan havzalarda düşük (kurak) ve yüksek (taşkın) akım davranışlarının belirlenmesi. Journal of Geography-Coğrafya Dergisi, (45), 33-46. google scholar
  • Akyürek, S. Z., Yildiz, S., & Aydın, A. (2018). 1/25 000 Ölçekli Standart Topoğrafik Haritalardan Elde Edilen Sayısal Yükseklik Modellerinin Doğruluk Analizi. google scholar
  • Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300(9), D05109. google scholar
  • Aliferi, L., Salamon, P., Bianchi, A., Neal, J., Bates, P. and Feyen, L. 2014. Advances in pan-European flood hazard mapping. Hydrol. Process. 28, 4067-4077. google scholar
  • Annis, A., Nardi, F., Petroselli, A., Apollonio, C., Arcangeletti, E., Tauro, F., ... & Grimaldi, S. (2020). UAV-DEMs for small-scale flood hazard mapping. Water, 12(6), 1717. google scholar
  • Apel, H., Aronica, G.T., Kreibich, H., Thieken, A.H., 2009. Flood risk analysesdhow detailed do we need to be? Nat. Hazards 49 (1), 79-98. google scholar
  • Apel, H., Thieken, A., Merz, B., Blöschl, G., 2006. A probabilistic modelling system for assessing flood risks. Nat. Hazards 38 (1-2), 79-100. google scholar
  • Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M. J., Srinivasan, R., ... & Kannan, N. (2012). SWAT: Model use, calibration, and validation. Transactions of the ASABE, 55(4), 14911508. google scholar
  • Arnold J.G., Srinivasan R, Muttiah, R.S., Williams, J.R. (1998). Large area hydrologic modelling and assessment- Part I: model development. Journal of American Water Resources Association 34 (1): 73-89. google scholar
  • ASPRS (2013). LAS Specification Version 1.4 - R13. USA. google scholar
  • Bates, P.D., and De Roo, A.P. J. (2000). A simple raster-based model for flood inundation simulation. Journal of Hydrology 236(1): 54-77. google scholar
  • Bates, P. D., Horritt, M. S., & Fewtrell, T. J. (2010). A simple inertial formulation of the shallow water equations for efficient twodimensional flood inundation modelling. Journal of Hydrology, 387, 33-45. google scholar Bayliss, A. C., & Jones, R. C. (1993). Peaks-over-threshold flood database. Institute of Hydrology. google scholar
  • Bhuiyan, M., Dutta, D., 2012. Analysis of flood vulnerability and assessment of the impacts in coastal zones of Bangladesh due to potential sea-level rise. Nat. Hazards 61 (2), 729-743. google scholar
  • Chone, G., Biron, P. M., Belanger, T. B., Mazgaranu, L., Neal, J. C., & Sampson, C. C. (2021). An assessment of large-scale flood modelling based on LiDAR data. Hydrological Processes, 35, 1-13. google scholar
  • Cobby, D.M., D.C. Mason, and I.J. Davenport. 2001. Image processing of airborne scanning laser altimetry data for improved river flood modelling. ISPRS Journal of Photogrammetry and Remote Sensing 56(2): 121-138. google scholar
  • Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. UK: Springer google scholar
  • CRED. 2022. 2021 Disasters in numbers. Brussels: CRED. https://cred.be/sites/default/files/2021_EMDAT_report.pdf google scholar
  • CRED-UNDRR. 2020. Human cost of disasters, an overview of the last 20 years (2019-2020). CRED Disaster Report, Belgium. google scholar
  • Çam, A., Fırat, O., & Yılmaz, A. (2013). Harita Genel Komutanlığında ortofoto ve sayısal yüzey modeli üretimi faaliyetleri. TMMOB Coğrafi Bilgi Sistemleri Kongresi, 11, 6. google scholar
  • de Almeida, G. A., Bates, P., Freer, J. E., & Souvignet, M. (2012). Improving the stability of a simple formulation of the shallow water equations for 2-D flood modeling. Water Resources Research 48, 1-14. google scholar
  • de Almeida, G. A., & Bates, P. (2013). Applicability of the local inertial approximation of the shallow water equations to flood modeling. Water Resour Res., 49, 4833-4844. google scholar
  • de Almeida, G. A., Bates, P., & Ozdemir, H. (2018). Modelling urban floods at submetre resolution: challenges or opportunities for flood risk management? Journal of Flood Risk Management, 11, S855-S865. google scholar
  • Dottori, F., Salamon, P., Bianchi, A., Alfieri, L., Hirpa, F.A. and Feyen, L. 2016. Development and evaluation of a framework for global flood hazard mapping. Advances in Water Resources 94, 87-102. google scholar DSİ. (2021). Devlet Su İşleri Veri Envanteri. www.dsi.gov.tr google scholar
  • DEFRA/Environmental Agency. (2003). Flood Risks to People Phase 1. R&D Tecnical Report FD2317. google scholar
  • DEFRA/Environmental Agency Flood and Coastal Defence R&D Programme. UK. DEFRA/Environmental Agency. (2006). Flood Risks to People Phase 2. google scholar
  • Defra/Environment Agency Flood and Coastal Defence R&D Programme. UK. google scholar
  • Dutta, D., Herath, S., Musiake, K., 2006. An application of a flood risk analysis system for impact analysis of a flood control plan in a river basin. Hydrol. Process. 20 (6), 1365e1384. google scholar
  • Dutta, D., Teng, J., Vaze, J., Lerat, J., Hughes, J., Marvanek, S., 2013. Storage-based approaches to build floodplain inundation modelling capability in river system models for water resources planning and accounting. J. Hydrol. 504 (0), 12-28. google scholar
  • Ercanoğlu, M. (2005). Landslide susceptibility assessment of SE Bartin (West Black Sea region, Turkey) by artificial neural networks. Natural Hazards and Earth System Sciences, 5, 979-992. google scholar
  • Elbaşı, E. (2022). Bölgesel Taşkın Analizleri ile Taşkın Tehlike Haritalarının Hazırlanması. İstanbul Üniversitesi, Sosyal Bilimler Enstitüsü, Coğrafya Anabilim Dalı (Yayınlanmamış Doktora Tezi), İstanbul. google scholar
  • Elbaşı, E. & Özdemir, H. (2019). Farklı Çözünürlükteki Sayısal Yükselti Modellerinin 2 Boyutlu Hidrodinamik Modeller Üzerindeki Etkisi. 1. İstanbul Uluslararası Coğrafya Kongresi. İstanbul. google scholar
  • Fuka, D.R., C.A. MacAllister, A.T. Degaetano, and Z.M. Easton. (2013). Using the Climate Forecast System Reanalysis dataset to improve weather input data for watershed models. Hydrol. Proc. DOI: 10.1002/hyp.10073. google scholar
  • Gallegos, H.A., Schubert, J.E., Sanders, B.F. 2009. Two-dimensional, high-resolution modeling of urban dam-break flooding: a case study of Baldwin Hills, California. Adv. Water Resour. 32 (8), 1323-1335. google scholar
  • Garrote, J. 2022. Free Global DEMs and Flood Modelling—A Comparison Analysis for the January 2015 Flooding Event in Mocuba City (Mozambique). Water 14, 176. https://doi.org/10.3390/ w14020176 google scholar
  • Guerriero, L., Ruzza, G., Guadagno, F. M., & Revellino, P. (2020). Flood hazard mapping incorporating multiple probability models. Journal of Hydrology, 587, 125020. google scholar
  • Hawker, L., P. Bates, J. Neal, and J. Rougier. 2018. Perspectives on Digital Elevation Model (DEM) simulation for flood modeling in the absence of a high-accuracy open access global DEM. Frontiers in Earth Science 6: Article 233. google scholar
  • Hawker, L., Neal, J., & Bates, P. (2019). Accuracy assessment of the TanDEM-X 90 Digital Elevation Model for selected floodplain sites. Remote Sensing of Environment, 232, 111319. google scholar
  • Hawker, L., Uhe, P., Paulo, L., Sosa, J., Savage, J., Sampson, C., & Neal, J. (2022). A 30 m global map of elevation with forests and buildings removed. Environmental Research Letters, 17(2), 024016. google scholar
  • Horton, P., Schaefli, B., & Kauzlaric, M. (2021). Why do we have so many different hydrological models? A review based on the case of Switzerland. google scholar
  • Hutchinson, M. F. 1988. Calculation of hydrologically sound digital elevation models. Paper presented at Third International Symposium on Spatial Data Handling at Sydney, Australia. google scholar
  • Hutchinson, M.F., Xu, T. and Stein, J.A. 2011. Recent Progress in the ANUDEM Elevation Gridding Procedure. In: Geomorphometry 2011, edited by T. Hengel, I.S. Evans, J.P. Wilson and M. Gould, pp. 19-22. Redlands, California, USA. See: http://geomorphometry. org/HutchinsonXu2011. google scholar
  • Karamuz, E., Romanowicz, R. J., & Doroszkiewicz, J. (2020). The use of unmanned aerial vehicles in flood hazard assessment. Journal of Flood Risk Management, 13(4), e12622. google scholar
  • Kenward, T., D.P. Lettenmaier, E.F. Wood, and E. Fielding. 2000. Effects of Digital Elevation Model accuracy on hydrologic predictions. Remote Sensing of Environment 74(3): 432-444. google scholar
  • Krause, P., Boyle, D. P., Base, F. (2005). Comparison of different efficiency criteria for hydrological model assessment. Advances in geosciences, 5, 89-97. google scholar
  • Lim, N., and S. Brandt. 2019. Flood map boundary sensitivity due to combined effects of DEM resolution and roughness in relation to model performance. Geomatics, Natural Hazards and Risk 10(1): 1613-1647. google scholar
  • Matej Vojtek & Jana Vojtekovâ (2016) Flood hazard and flood risk assessment at the local spatial scale: a case study, Geomatics, Natural Hazards and Risk, 7:6, 1973-1992, D0I:10.1080/19475705 .2016.1166874. google scholar
  • Merz, B., Kreibich, H., Schwarze, R., Thieken, A., 2010. Review article ‘Assessment of economic flood damage’. Nat. Hazards Earth Syst. Sci. 10 (8), 1697-1724. google scholar
  • Muench, R., Cherrington, E., Griffin, R and Mamane, B. (2022). Assessment of Open Access Global Elevation Model Errors Impact on Flood Extents in Southern Niger. Front. Environ. Sci. 10:880840. doi: 10.3389/fenvs.2022.880840. google scholar
  • Muhadi, N. A., Abdullah, A. F., Bejo, S. K., Mahadi, M. R., & Mijic, A. (2020). The use of LiDAR-derived DEM in flood applications: A review. Remote Sensing, 12(14), 2308. google scholar
  • Monteith, J. L. (1965). Evaporation and environment. In Symposia of the society for experimental biology (Vol. 19, pp. 205-234). Cambridge: Cambridge University Press (CUP). google scholar
  • National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center. 2012. “Lidar 101: An Introduction to Lidar Technology, Data, and Applications.” Revised. Charleston, SC: NOAA Coastal Services Center. google scholar
  • Nash, J.E. Sutcliffe, J.V. (1970). River flow forecasting through conceptual models. Part I. A discussion of principles. Journal of Hydrology, 10, 282-290. doi:10.1016/0022-1694(70)90255-6 google scholar
  • Neal, J., Schumann, G., Fewtrell, T., Budimir, M., Bates, P., & Mason, D. (2011). Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 foods in Tewkesbury, UK. Journal of Flood Risk Management 4, 88-95. google scholar
  • Neal, J., Villanueva, I., Wright, N., Willis, T., Fewtrell, T., & Bates, P. (2012). How much physical complexity is needed to model flood inundation? Hydrol. Process., 26, 264-2282. google scholar
  • Neitsch, S. L., Arnold, J. G., Kiniry, J. R., & Williams, J. R. (2011). Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute. google scholar
  • OGM. (2011). Bartın, Ulus ve Safranbolu Orman İşletme Müdürlüklerine ait Orman Amenajman Harita ve Planları. Ankara. google scholar
  • Ozdemir, H. (2007). Determination of Flood Extent Using MultiTemporal & Multi-Resolution Satellite Images: A Case Study of Mahanadi River’s Floods in 2003 (Orissa-India). Journal of Geography-CoğrajyaDergisi, (15), 13-23. google scholar
  • Özdemir, H., Akbulak, C., & Özcan, H. (2011). Çokal Barajı (Çanakkale) çökme modeli ve taşkın risk analizi. Uluslararası İnsan Bilimleri Dergisi, 8(2), 659-698. google scholar
  • Ozdemir, H., & Elbaşı, E. (2015). Benchmarking land use change impacts on direct runoff in ungauged urban watersheds. Physics and Chemistry of the Earth, Parts A/B/C, 79, 100-107. google scholar
  • Ozdemir, H., Sampson, C. C., de Almeida, G. A., & Bates, P. D. (2013). Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data. Hydrology and Earth System Sciences, 17(10), 4015-4030. google scholar
  • Öztürk, M. Z., Çetinkaya, G., & Aydın, S. (2017). Köppen-Geiger İklim Sınıflandırmasına Göre Türkiye’nin İklim Tipleri. Coğrafya Dergisi - Journal of Geography, 35, 17-27. google scholar
  • Peker, İ. B., & Cüceloğlu, G. (2022). SWAT (Soil and Water Assessment Tool) Modeline Genel Bir Bakış ve Modelin Türkiye’deki Uygulamaları. Çevre İklim ve Sürdürülebilirlik, 1(1), 9-26. google scholar
  • Pistrika, A. K., & Jonkman, S. N. (2010). Damage to residential buildings due to flooding of New Orleans after hurricane Katrina. Natural Hazards, 54(2), 413-434. google scholar
  • Saha, S.,Moorthi, S., Pan, H. L., Wu, X., Wang, J., Nadiga, S., ... & Goldberg, M. (2010). The NCEP climate forecast system reanalysis. Bulletin of the American Meteorological Society, 91(8), 1015-1058 google scholar
  • Shaw, J., Kessewani, G., Neal, J., Bates, P. & Sharifian MK. 2021. LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs. Geosci. Model Dev., 14, 3577-3602 google scholar
  • Saksena, S. and Merwade, V. 2015. Incorporating the effect of DEM resolution and accuracy for improved flood inundation mapping. Journal of Hydrology 530: 180-194. google scholar
  • Salas, J. D., Anderson, M. L., Papalexiou, S. M., & Frances, F. (2020). PMP and climate variability and change: a review. Journal of Hydrologic Engineering, 25(12), 1-16. google scholar
  • Sampson, C. C., Fewtrell, T. J., Duncan, A., Shaad, K., Horritt, M. S., & Bates, P. D. (2012). Use of terrestrial laser scanning data to drive decimetric resolution urban inundation models. Advances in water resources, 41, 1-17. google scholar
  • Sampson, C. C., Smith, A. M., Bates, P. D., Neal, J. C., Alfieri, L., & Freer, J. E. (2015). A high-resolution global flood hazard model. Water resources research, 51(9), 7358-7381. google scholar
  • SCS, 1956, 1964, 1971, 1985, 1993. Hydrology, National Engineering Handbook, Supplement A, Section 4, Chapter 10. Soil Conservation Service, USDA, Washington, DC. google scholar
  • Shreve, R. (1966). Statistical Law of Stream Numbers, J. Geol., 74, 17-37 google scholar
  • Shustikova, I., Domeneghetti, A., Neal, J. C., Bates, P., & Castellarin, A. (2019). Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography. Hydrological Sciences Journal, 64:14, 1769-1782. google scholar
  • Şimşek, İ. 2020. Sel-Taşkın Modellerinde Hava Lidar Verilerinin Kullanımı: Ulus Çayı Örneği. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü, Coğrafya Anabilim Dalı. Yayınlanmamış Yüksek Lisans Tezi. İstanbul. google scholar
  • Su Yönetimi Genel Müdürlüğü. (2019). Batı Karadeniz Havzası Taşkın Yönetim Planı. Tarım ve Orman Bakanlığı Su Yönetimi Genel Müdürlüğü, Ankara. google scholar
  • Xu, K., Fang, J., Fang, Y., Sun, Q., Wu, C., & Liu, M. (2021). The Importance of Digital Elevation Model Selection in Flood Simulation and a Proposed Method to Reduce DEM Errors: A Case Study in Shanghai. International Journal of Disaster Risk Science, 12(6), 890-902. google scholar
  • Villarini, G., Smith, J. A., Baeck, M. L., Vitolo, R., Stephenson, D. B., & Krajewski, W. F. (2011). On the frequency of heavy rainfall for the Midwest of the United States. Journal of Hydrology, 400(1-2), 103-120. google scholar
  • Vojtek, M., & Vojtekovâ, J. (2016). Flood hazard and flood risk assessment at the local spatial scale: a case study. Geomatics, Natural Hazards and Risk, 7(6), 1973-1992. google scholar
  • Timur, E., Aksay, A. ve Çelik, B. 1997. Zonguldak F-28 paftası1/100 000 ölçekli jeoloji haritası, MTA Gn. Md., Jeoloji Etütleri Dairesi, Ankara. google scholar
  • Turoğlu, H., & Özdemir, H. (2005). Bartın’da Sel ve Taşkınlar. Çantay Kitapevi, İstanbul. google scholar
  • TÜİK. 2022. Adrese Dayalı Nüfus Kayıt Sistemi Sonuçları 2021. www. tuik.gov.tr google scholar
  • Utlu, M., & Özdemir, H. (2020). How much spatial resolution do we need to model a local flood event? Benchmark testing based on UAV data from Biga River (Turkey). Arabian Journal of Geosciences, 13(24), 1-14. google scholar
  • Yalcin, E. (2019). Two-dimensional hydrodynamic modelling for urban flood risk assessment using unmanned aerial vehicle imagery: A case study of Kirsehir, Turkey. Journal of flood risk management, 12, e12499. google scholar
  • Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O’Loughlin, F., Neal, J. C., ... & Bates, P. D. (2017). A high-accuracy map of global terrain elevations. Geophysical Research Letters, 44(11), 5844-5853. google scholar
  • Zhang W, Qi J, Wan P, Wang H, Xie D, Wang X, Yan G. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sensing. 2016; 8(6):501. google scholar

The Effects of Spatial Resolution Variability of Digital Elevation Models on Flood Hazard Analysis

Year 2023, , 137 - 156, 25.05.2023
https://doi.org/10.26650/JGEOG2023-1177718

Abstract

Raster-based Digital Elevation Models (DEMs) represent the surface topography as the primary input in flood hazard and risk studies. The study aims to reveal the variability of the hazard at the base of the Ulus settlement by performing flood hazard analyses with different source and resolution DEMs, which are used on a global and local scale and form a primary input for many studies. For this purpose, DEMs data, such as MERIT 90m, FABDEM 30m, TopoDEM 10m, DEM5m, LiDAR 1m, and UAV 0.1m, for the Ulus River basin and settlement and the 500-year flood produced for the river tributaries using the SWAT rainfall-runoff model were used. To examine spatial resolution variability, flood hazard analyses were performed based on the two-dimensional LISFLOODFP hydrodynamic model, using a fixed Manning n value (n=0.035). As a result, although there is an increase in cost, time, and model instabilities from low resolution to high resolution, it is essential to choose the most appropriate DEM according to the required detail and scale of the hazard analysis to be able to obtain more accurate results. While the model time and average computational errors from low resolution to high resolution increased, the water extent and the spatial distribution of the hazard classes produced for people and buildings decreased. The FABDEM data is more advantageous in regional studies than others, whereas the LiDAR data can be used in basin-scaled studies. In addition, the DEM5 data also can be used in basin-scaled studies after clearing the heights of the buildings and vegetation groups.

Project Number

OUAP(F)-2019/13 ve 121Y578

References

  • Abbaspour, K. C., Rouholahnejad, E., Vaghefi,, Srinivasan, R., Yang, H., & Kl0ve, B. (2015). A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a highresolution large-scale SWAT model. Journal of Hydrology, 524, 733-752. google scholar
  • Akbas, A., Freer, J., Ozdemir, H., Bates, P. D., & Turp, M. T. (2020). What about reservoirs? Questioning anthropogenic and climatic interferences on water availability. Hydrological Processes, 34(26), 5441-5455. google scholar
  • Akbaş, A., & Özdemir, H. (2021). Yağış-Akış Modellerinde ArcSwat Uygulaması: Bartın Çayı Havzası Örneği. In E. Akköprü, & M. F. Döker, Coğrafya Araştırmalarında Coğrafi Bilgi Sistemleri Uygulamaları (pp. 107-128). Ankara: Pegem Akademi. google scholar
  • Akbaş, A., & Özdemir, H. (2022). Tüm modeller yanlıştır, ancak bazıları faydalıdır: Akım Gözlem İstasyonu bulunmayan havzalarda düşük (kurak) ve yüksek (taşkın) akım davranışlarının belirlenmesi. Journal of Geography-Coğrafya Dergisi, (45), 33-46. google scholar
  • Akyürek, S. Z., Yildiz, S., & Aydın, A. (2018). 1/25 000 Ölçekli Standart Topoğrafik Haritalardan Elde Edilen Sayısal Yükseklik Modellerinin Doğruluk Analizi. google scholar
  • Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300(9), D05109. google scholar
  • Aliferi, L., Salamon, P., Bianchi, A., Neal, J., Bates, P. and Feyen, L. 2014. Advances in pan-European flood hazard mapping. Hydrol. Process. 28, 4067-4077. google scholar
  • Annis, A., Nardi, F., Petroselli, A., Apollonio, C., Arcangeletti, E., Tauro, F., ... & Grimaldi, S. (2020). UAV-DEMs for small-scale flood hazard mapping. Water, 12(6), 1717. google scholar
  • Apel, H., Aronica, G.T., Kreibich, H., Thieken, A.H., 2009. Flood risk analysesdhow detailed do we need to be? Nat. Hazards 49 (1), 79-98. google scholar
  • Apel, H., Thieken, A., Merz, B., Blöschl, G., 2006. A probabilistic modelling system for assessing flood risks. Nat. Hazards 38 (1-2), 79-100. google scholar
  • Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M. J., Srinivasan, R., ... & Kannan, N. (2012). SWAT: Model use, calibration, and validation. Transactions of the ASABE, 55(4), 14911508. google scholar
  • Arnold J.G., Srinivasan R, Muttiah, R.S., Williams, J.R. (1998). Large area hydrologic modelling and assessment- Part I: model development. Journal of American Water Resources Association 34 (1): 73-89. google scholar
  • ASPRS (2013). LAS Specification Version 1.4 - R13. USA. google scholar
  • Bates, P.D., and De Roo, A.P. J. (2000). A simple raster-based model for flood inundation simulation. Journal of Hydrology 236(1): 54-77. google scholar
  • Bates, P. D., Horritt, M. S., & Fewtrell, T. J. (2010). A simple inertial formulation of the shallow water equations for efficient twodimensional flood inundation modelling. Journal of Hydrology, 387, 33-45. google scholar Bayliss, A. C., & Jones, R. C. (1993). Peaks-over-threshold flood database. Institute of Hydrology. google scholar
  • Bhuiyan, M., Dutta, D., 2012. Analysis of flood vulnerability and assessment of the impacts in coastal zones of Bangladesh due to potential sea-level rise. Nat. Hazards 61 (2), 729-743. google scholar
  • Chone, G., Biron, P. M., Belanger, T. B., Mazgaranu, L., Neal, J. C., & Sampson, C. C. (2021). An assessment of large-scale flood modelling based on LiDAR data. Hydrological Processes, 35, 1-13. google scholar
  • Cobby, D.M., D.C. Mason, and I.J. Davenport. 2001. Image processing of airborne scanning laser altimetry data for improved river flood modelling. ISPRS Journal of Photogrammetry and Remote Sensing 56(2): 121-138. google scholar
  • Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. UK: Springer google scholar
  • CRED. 2022. 2021 Disasters in numbers. Brussels: CRED. https://cred.be/sites/default/files/2021_EMDAT_report.pdf google scholar
  • CRED-UNDRR. 2020. Human cost of disasters, an overview of the last 20 years (2019-2020). CRED Disaster Report, Belgium. google scholar
  • Çam, A., Fırat, O., & Yılmaz, A. (2013). Harita Genel Komutanlığında ortofoto ve sayısal yüzey modeli üretimi faaliyetleri. TMMOB Coğrafi Bilgi Sistemleri Kongresi, 11, 6. google scholar
  • de Almeida, G. A., Bates, P., Freer, J. E., & Souvignet, M. (2012). Improving the stability of a simple formulation of the shallow water equations for 2-D flood modeling. Water Resources Research 48, 1-14. google scholar
  • de Almeida, G. A., & Bates, P. (2013). Applicability of the local inertial approximation of the shallow water equations to flood modeling. Water Resour Res., 49, 4833-4844. google scholar
  • de Almeida, G. A., Bates, P., & Ozdemir, H. (2018). Modelling urban floods at submetre resolution: challenges or opportunities for flood risk management? Journal of Flood Risk Management, 11, S855-S865. google scholar
  • Dottori, F., Salamon, P., Bianchi, A., Alfieri, L., Hirpa, F.A. and Feyen, L. 2016. Development and evaluation of a framework for global flood hazard mapping. Advances in Water Resources 94, 87-102. google scholar DSİ. (2021). Devlet Su İşleri Veri Envanteri. www.dsi.gov.tr google scholar
  • DEFRA/Environmental Agency. (2003). Flood Risks to People Phase 1. R&D Tecnical Report FD2317. google scholar
  • DEFRA/Environmental Agency Flood and Coastal Defence R&D Programme. UK. DEFRA/Environmental Agency. (2006). Flood Risks to People Phase 2. google scholar
  • Defra/Environment Agency Flood and Coastal Defence R&D Programme. UK. google scholar
  • Dutta, D., Herath, S., Musiake, K., 2006. An application of a flood risk analysis system for impact analysis of a flood control plan in a river basin. Hydrol. Process. 20 (6), 1365e1384. google scholar
  • Dutta, D., Teng, J., Vaze, J., Lerat, J., Hughes, J., Marvanek, S., 2013. Storage-based approaches to build floodplain inundation modelling capability in river system models for water resources planning and accounting. J. Hydrol. 504 (0), 12-28. google scholar
  • Ercanoğlu, M. (2005). Landslide susceptibility assessment of SE Bartin (West Black Sea region, Turkey) by artificial neural networks. Natural Hazards and Earth System Sciences, 5, 979-992. google scholar
  • Elbaşı, E. (2022). Bölgesel Taşkın Analizleri ile Taşkın Tehlike Haritalarının Hazırlanması. İstanbul Üniversitesi, Sosyal Bilimler Enstitüsü, Coğrafya Anabilim Dalı (Yayınlanmamış Doktora Tezi), İstanbul. google scholar
  • Elbaşı, E. & Özdemir, H. (2019). Farklı Çözünürlükteki Sayısal Yükselti Modellerinin 2 Boyutlu Hidrodinamik Modeller Üzerindeki Etkisi. 1. İstanbul Uluslararası Coğrafya Kongresi. İstanbul. google scholar
  • Fuka, D.R., C.A. MacAllister, A.T. Degaetano, and Z.M. Easton. (2013). Using the Climate Forecast System Reanalysis dataset to improve weather input data for watershed models. Hydrol. Proc. DOI: 10.1002/hyp.10073. google scholar
  • Gallegos, H.A., Schubert, J.E., Sanders, B.F. 2009. Two-dimensional, high-resolution modeling of urban dam-break flooding: a case study of Baldwin Hills, California. Adv. Water Resour. 32 (8), 1323-1335. google scholar
  • Garrote, J. 2022. Free Global DEMs and Flood Modelling—A Comparison Analysis for the January 2015 Flooding Event in Mocuba City (Mozambique). Water 14, 176. https://doi.org/10.3390/ w14020176 google scholar
  • Guerriero, L., Ruzza, G., Guadagno, F. M., & Revellino, P. (2020). Flood hazard mapping incorporating multiple probability models. Journal of Hydrology, 587, 125020. google scholar
  • Hawker, L., P. Bates, J. Neal, and J. Rougier. 2018. Perspectives on Digital Elevation Model (DEM) simulation for flood modeling in the absence of a high-accuracy open access global DEM. Frontiers in Earth Science 6: Article 233. google scholar
  • Hawker, L., Neal, J., & Bates, P. (2019). Accuracy assessment of the TanDEM-X 90 Digital Elevation Model for selected floodplain sites. Remote Sensing of Environment, 232, 111319. google scholar
  • Hawker, L., Uhe, P., Paulo, L., Sosa, J., Savage, J., Sampson, C., & Neal, J. (2022). A 30 m global map of elevation with forests and buildings removed. Environmental Research Letters, 17(2), 024016. google scholar
  • Horton, P., Schaefli, B., & Kauzlaric, M. (2021). Why do we have so many different hydrological models? A review based on the case of Switzerland. google scholar
  • Hutchinson, M. F. 1988. Calculation of hydrologically sound digital elevation models. Paper presented at Third International Symposium on Spatial Data Handling at Sydney, Australia. google scholar
  • Hutchinson, M.F., Xu, T. and Stein, J.A. 2011. Recent Progress in the ANUDEM Elevation Gridding Procedure. In: Geomorphometry 2011, edited by T. Hengel, I.S. Evans, J.P. Wilson and M. Gould, pp. 19-22. Redlands, California, USA. See: http://geomorphometry. org/HutchinsonXu2011. google scholar
  • Karamuz, E., Romanowicz, R. J., & Doroszkiewicz, J. (2020). The use of unmanned aerial vehicles in flood hazard assessment. Journal of Flood Risk Management, 13(4), e12622. google scholar
  • Kenward, T., D.P. Lettenmaier, E.F. Wood, and E. Fielding. 2000. Effects of Digital Elevation Model accuracy on hydrologic predictions. Remote Sensing of Environment 74(3): 432-444. google scholar
  • Krause, P., Boyle, D. P., Base, F. (2005). Comparison of different efficiency criteria for hydrological model assessment. Advances in geosciences, 5, 89-97. google scholar
  • Lim, N., and S. Brandt. 2019. Flood map boundary sensitivity due to combined effects of DEM resolution and roughness in relation to model performance. Geomatics, Natural Hazards and Risk 10(1): 1613-1647. google scholar
  • Matej Vojtek & Jana Vojtekovâ (2016) Flood hazard and flood risk assessment at the local spatial scale: a case study, Geomatics, Natural Hazards and Risk, 7:6, 1973-1992, D0I:10.1080/19475705 .2016.1166874. google scholar
  • Merz, B., Kreibich, H., Schwarze, R., Thieken, A., 2010. Review article ‘Assessment of economic flood damage’. Nat. Hazards Earth Syst. Sci. 10 (8), 1697-1724. google scholar
  • Muench, R., Cherrington, E., Griffin, R and Mamane, B. (2022). Assessment of Open Access Global Elevation Model Errors Impact on Flood Extents in Southern Niger. Front. Environ. Sci. 10:880840. doi: 10.3389/fenvs.2022.880840. google scholar
  • Muhadi, N. A., Abdullah, A. F., Bejo, S. K., Mahadi, M. R., & Mijic, A. (2020). The use of LiDAR-derived DEM in flood applications: A review. Remote Sensing, 12(14), 2308. google scholar
  • Monteith, J. L. (1965). Evaporation and environment. In Symposia of the society for experimental biology (Vol. 19, pp. 205-234). Cambridge: Cambridge University Press (CUP). google scholar
  • National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center. 2012. “Lidar 101: An Introduction to Lidar Technology, Data, and Applications.” Revised. Charleston, SC: NOAA Coastal Services Center. google scholar
  • Nash, J.E. Sutcliffe, J.V. (1970). River flow forecasting through conceptual models. Part I. A discussion of principles. Journal of Hydrology, 10, 282-290. doi:10.1016/0022-1694(70)90255-6 google scholar
  • Neal, J., Schumann, G., Fewtrell, T., Budimir, M., Bates, P., & Mason, D. (2011). Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 foods in Tewkesbury, UK. Journal of Flood Risk Management 4, 88-95. google scholar
  • Neal, J., Villanueva, I., Wright, N., Willis, T., Fewtrell, T., & Bates, P. (2012). How much physical complexity is needed to model flood inundation? Hydrol. Process., 26, 264-2282. google scholar
  • Neitsch, S. L., Arnold, J. G., Kiniry, J. R., & Williams, J. R. (2011). Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute. google scholar
  • OGM. (2011). Bartın, Ulus ve Safranbolu Orman İşletme Müdürlüklerine ait Orman Amenajman Harita ve Planları. Ankara. google scholar
  • Ozdemir, H. (2007). Determination of Flood Extent Using MultiTemporal & Multi-Resolution Satellite Images: A Case Study of Mahanadi River’s Floods in 2003 (Orissa-India). Journal of Geography-CoğrajyaDergisi, (15), 13-23. google scholar
  • Özdemir, H., Akbulak, C., & Özcan, H. (2011). Çokal Barajı (Çanakkale) çökme modeli ve taşkın risk analizi. Uluslararası İnsan Bilimleri Dergisi, 8(2), 659-698. google scholar
  • Ozdemir, H., & Elbaşı, E. (2015). Benchmarking land use change impacts on direct runoff in ungauged urban watersheds. Physics and Chemistry of the Earth, Parts A/B/C, 79, 100-107. google scholar
  • Ozdemir, H., Sampson, C. C., de Almeida, G. A., & Bates, P. D. (2013). Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data. Hydrology and Earth System Sciences, 17(10), 4015-4030. google scholar
  • Öztürk, M. Z., Çetinkaya, G., & Aydın, S. (2017). Köppen-Geiger İklim Sınıflandırmasına Göre Türkiye’nin İklim Tipleri. Coğrafya Dergisi - Journal of Geography, 35, 17-27. google scholar
  • Peker, İ. B., & Cüceloğlu, G. (2022). SWAT (Soil and Water Assessment Tool) Modeline Genel Bir Bakış ve Modelin Türkiye’deki Uygulamaları. Çevre İklim ve Sürdürülebilirlik, 1(1), 9-26. google scholar
  • Pistrika, A. K., & Jonkman, S. N. (2010). Damage to residential buildings due to flooding of New Orleans after hurricane Katrina. Natural Hazards, 54(2), 413-434. google scholar
  • Saha, S.,Moorthi, S., Pan, H. L., Wu, X., Wang, J., Nadiga, S., ... & Goldberg, M. (2010). The NCEP climate forecast system reanalysis. Bulletin of the American Meteorological Society, 91(8), 1015-1058 google scholar
  • Shaw, J., Kessewani, G., Neal, J., Bates, P. & Sharifian MK. 2021. LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs. Geosci. Model Dev., 14, 3577-3602 google scholar
  • Saksena, S. and Merwade, V. 2015. Incorporating the effect of DEM resolution and accuracy for improved flood inundation mapping. Journal of Hydrology 530: 180-194. google scholar
  • Salas, J. D., Anderson, M. L., Papalexiou, S. M., & Frances, F. (2020). PMP and climate variability and change: a review. Journal of Hydrologic Engineering, 25(12), 1-16. google scholar
  • Sampson, C. C., Fewtrell, T. J., Duncan, A., Shaad, K., Horritt, M. S., & Bates, P. D. (2012). Use of terrestrial laser scanning data to drive decimetric resolution urban inundation models. Advances in water resources, 41, 1-17. google scholar
  • Sampson, C. C., Smith, A. M., Bates, P. D., Neal, J. C., Alfieri, L., & Freer, J. E. (2015). A high-resolution global flood hazard model. Water resources research, 51(9), 7358-7381. google scholar
  • SCS, 1956, 1964, 1971, 1985, 1993. Hydrology, National Engineering Handbook, Supplement A, Section 4, Chapter 10. Soil Conservation Service, USDA, Washington, DC. google scholar
  • Shreve, R. (1966). Statistical Law of Stream Numbers, J. Geol., 74, 17-37 google scholar
  • Shustikova, I., Domeneghetti, A., Neal, J. C., Bates, P., & Castellarin, A. (2019). Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography. Hydrological Sciences Journal, 64:14, 1769-1782. google scholar
  • Şimşek, İ. 2020. Sel-Taşkın Modellerinde Hava Lidar Verilerinin Kullanımı: Ulus Çayı Örneği. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü, Coğrafya Anabilim Dalı. Yayınlanmamış Yüksek Lisans Tezi. İstanbul. google scholar
  • Su Yönetimi Genel Müdürlüğü. (2019). Batı Karadeniz Havzası Taşkın Yönetim Planı. Tarım ve Orman Bakanlığı Su Yönetimi Genel Müdürlüğü, Ankara. google scholar
  • Xu, K., Fang, J., Fang, Y., Sun, Q., Wu, C., & Liu, M. (2021). The Importance of Digital Elevation Model Selection in Flood Simulation and a Proposed Method to Reduce DEM Errors: A Case Study in Shanghai. International Journal of Disaster Risk Science, 12(6), 890-902. google scholar
  • Villarini, G., Smith, J. A., Baeck, M. L., Vitolo, R., Stephenson, D. B., & Krajewski, W. F. (2011). On the frequency of heavy rainfall for the Midwest of the United States. Journal of Hydrology, 400(1-2), 103-120. google scholar
  • Vojtek, M., & Vojtekovâ, J. (2016). Flood hazard and flood risk assessment at the local spatial scale: a case study. Geomatics, Natural Hazards and Risk, 7(6), 1973-1992. google scholar
  • Timur, E., Aksay, A. ve Çelik, B. 1997. Zonguldak F-28 paftası1/100 000 ölçekli jeoloji haritası, MTA Gn. Md., Jeoloji Etütleri Dairesi, Ankara. google scholar
  • Turoğlu, H., & Özdemir, H. (2005). Bartın’da Sel ve Taşkınlar. Çantay Kitapevi, İstanbul. google scholar
  • TÜİK. 2022. Adrese Dayalı Nüfus Kayıt Sistemi Sonuçları 2021. www. tuik.gov.tr google scholar
  • Utlu, M., & Özdemir, H. (2020). How much spatial resolution do we need to model a local flood event? Benchmark testing based on UAV data from Biga River (Turkey). Arabian Journal of Geosciences, 13(24), 1-14. google scholar
  • Yalcin, E. (2019). Two-dimensional hydrodynamic modelling for urban flood risk assessment using unmanned aerial vehicle imagery: A case study of Kirsehir, Turkey. Journal of flood risk management, 12, e12499. google scholar
  • Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O’Loughlin, F., Neal, J. C., ... & Bates, P. D. (2017). A high-accuracy map of global terrain elevations. Geophysical Research Letters, 44(11), 5844-5853. google scholar
  • Zhang W, Qi J, Wan P, Wang H, Xie D, Wang X, Yan G. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sensing. 2016; 8(6):501. google scholar
There are 87 citations in total.

Details

Primary Language Turkish
Subjects Human Geography (Other)
Journal Section Research Article
Authors

Hasan Özdemir 0000-0001-8885-9298

Abdullah Akbaş 0000-0003-2024-0565

Project Number OUAP(F)-2019/13 ve 121Y578
Publication Date May 25, 2023
Submission Date September 28, 2022
Published in Issue Year 2023

Cite

APA Özdemir, H., & Akbaş, A. (2023). Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri. Journal of Geography(46), 137-156. https://doi.org/10.26650/JGEOG2023-1177718
AMA Özdemir H, Akbaş A. Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri. Journal of Geography. May 2023;(46):137-156. doi:10.26650/JGEOG2023-1177718
Chicago Özdemir, Hasan, and Abdullah Akbaş. “Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri”. Journal of Geography, no. 46 (May 2023): 137-56. https://doi.org/10.26650/JGEOG2023-1177718.
EndNote Özdemir H, Akbaş A (May 1, 2023) Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri. Journal of Geography 46 137–156.
IEEE H. Özdemir and A. Akbaş, “Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri”, Journal of Geography, no. 46, pp. 137–156, May 2023, doi: 10.26650/JGEOG2023-1177718.
ISNAD Özdemir, Hasan - Akbaş, Abdullah. “Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri”. Journal of Geography 46 (May 2023), 137-156. https://doi.org/10.26650/JGEOG2023-1177718.
JAMA Özdemir H, Akbaş A. Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri. Journal of Geography. 2023;:137–156.
MLA Özdemir, Hasan and Abdullah Akbaş. “Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri”. Journal of Geography, no. 46, 2023, pp. 137-56, doi:10.26650/JGEOG2023-1177718.
Vancouver Özdemir H, Akbaş A. Sayısal Yükseklik Modellerindeki Mekânsal Çözünürlük Değişkenliğinin Taşkın Tehlike Analizine Etkileri. Journal of Geography. 2023(46):137-56.