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Journals / Disaster Science and Engineering / 2020 / Cilt: 6 Sayı: 2

Comparison of flood discharge calculated by different statistical distribution functions and software

Tülay Ekemen Keskin(KARABÜK ÜNİVERSİTESİ)
Emrah Doğan(SAKARYA ÜNİVERSİTESİ)
Osman Sönmez(SAKARYA ÜNİVERSİTESİ)
Hatice Betül Umarusman(KARABÜK ÜNİVERSİTESİ)
Pinar Spor(BÜLENT ECEVİT ÜNİVERSİTESİ)
Meisam Badfar(SAKARYA ÜNİVERSİTESİ)
Halil İbrahim Çetiner(NETCAD)
Packialakshmi S(Sathyabama Institute of Science and Technology)
Pages
1–7
Publication Date
2020-12-15
DOI
—
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AI Summary & Key Takeaways

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

By comparing the results obtained from models, it was found that the values obtained by Pearson distribution from Model 1 and the values obtained by DSI Synthetic Method from Model 2 were correlated well with each other.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Flood discharges can be calculated by using the flow observation station data and the precipitation observation station data.
📊
Key Findings & Data:Firstly (Model 1), based on flow data of Kocaırmak (Bartın) River, the possible flood discharges were calculated by using different statistical distribution functions.
💡
Conclusion & Impact:By comparing the results obtained from models, it was found that the values obtained by Pearson distribution from Model 1 and the values obtained by DSI Synthetic Method from Model 2 were correlated well with each other.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Flood Analysis · Statistical Distribution Functions · Mockus and DSI Synthetic Methods

Abstract

Flood discharges can be calculated by using the flow observation station data and the precipitation observation station data. In this study, both of the data set were evaluated and the results were correlated each other. Firstly (Model 1), based on flow data of Kocaırmak (Bartın) River, the possible flood discharges were calculated by using different statistical distribution functions. Secondly (Model 2), calculations were made with the help of different maps and different methods based on the data of precipitation observation stations using software. In Model 1, as a result of calculations made with Normal, Log Normal, Gumbel and Pearson distributions functions, the flood discharges according to 50 year return period were determined as 926, 1579, 1128, and 1024 m3/sec, respectively. The calculations made with the help of DSI and Mockus methods using the 1/25000 scaled digitized topographic maps and Aster-GDEM images with 30x30 m resolution in Model 2, the flood discharges were calculated as 999, 1305, and 1033, 1332 m3/sec, respectively. By comparing the results obtained from models, it was found that the values obtained by Pearson distribution from Model 1 and the values obtained by DSI Synthetic Method from Model 2 were correlated well with each other.

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Cite This Article

Keskin, T. E., Doğan, E., Sönmez, O., Umarusman, H. B., Spor, P., Badfar, M., Çetiner, H. İ., S, P. (2020). Comparison of flood discharge calculated by different statistical distribution functions and software. Disaster Science and Engineering, Cilt: 6 Sayı: 2, 1–7. https://ajindex.com/articles/1583474

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References (28)

  1. Aron, G., White, EL (2007) Fitting a gamma distribution over a synthetic unit hydrograph. J Am Water Resource Assoc., 18/1, 95–8
  2. Bayazıt, M (2003) Hidroloji. Birsen Publishing House 260, Ankara
  3. Bedient, PB., Huber, WC (1998) Hydrology and Floodplain Analysis. Addison-Wesley
  4. Bhadra, A., Panigrahy, N., Singh, R., Raghuwanshi, NS., Mal, BC., Tripathi, MP (2008) 9. Development of a geomorphological instantaneous unit hydrograph model for scantily gauged watersheds. J. Environ. Model Softw. 23, 1013–1025
  5. Bhunya, PK., Panda, SN., Goel, MK (2011) Synthetic Unit Hydrograph Methods: A Critical Review. The Open Hydrology Journal, 5, 1–8
  6. Boughton, W., Droop, O (2003) Continuous simulation for design flood estimation – A Review. Environ. Modell. Softw., 18, 4, 309-318
  7. Chow, VT (1964) Handbook of Applied Hydrology. McGraw-Hill Book C., New York, USA
  8. Chow, VT., Maidment, DR., Mays, LW (1988) Applied Hydrology. McGraw-Hill, New York, USA
  9. Dastorani, MT., Talebi, A., Dastorani, M (2010) Using neural networks to predict run off from ungauged catchments. Asian J Appl Sci, 3/6, 399–410
  10. DMI., T.C. (2018) General Directore of Meteorology, Ankara (https://mgm.gov.tr)
  11. Islam, M., Sado, K (2000) Satellite remote sensing data analysis for flood damaged zoning with GIS for flood management”. Ann J Hydraul Eng JSCE, 44, 301
  12. Jarosiska, E., Pierzga, K (2015) Estimating flood quantiles on the basis of multi-event rainfall simulation – case study. Acta Geophysica, 63, 6, 1639–1663
  13. Keskin, TE (2011) Bartın ve Çevresinin Hidrojeoloji İncelemesi. Cumhuriyet Üniversitesi Bilimsel Araştırma Projeleri Komisyon Başkanlığı (CÜBAP), Proje No: M-504, Sivas
  14. Keskin, TE (2013) Mineral-water interaction and hydrogeochemistry of groundwater around Bartın coal mine, Turkey. Fresenius Environmental Bulletin 22(9a), 2750–2762
  15. Linsley, RK., Kohler, MD., Paulhus, JIH (1988) Hydrology for Engineers. McGraw-Hill, New York, USA
  16. Lopez, V., Napolitano, F., Russo, F (2005) Calibration of a rainfall runoff model using radar and rain gauge data”. J. Adv. Geosci. 2, 41–46
  17. McCuen, RH (2005) Hydrologic Design and Analysis. Prentive Hall
  18. Mishra, SK., Singh, VP (2003) Soil Conservation Service Curve Number (SCS-CN) Methodology. Water Science and Technology Library, 42, Kluwer Academic Publishers, Dordrecht, 519
  19. Ogunlela, AO., Kasali, MY (2002) Evaluation of four methods of storm hydrograph development for an ungauged watershed. Nigerian J. Technol. Develop, 2, 25–34
  20. Özcan, O (2017) Taşkın tespitinin farklı yöntemlerle değerlendirilmesi: Ayamama Deresi örneği. Artvin Çoruh Üniversitesi Doğal Afetler Uygulama ve Araştırma Merkezi Doğal Afetler ve Çevre Dergisi, 3, 9–27
  21. Patrick, LG., Donald, HB., Juraj, MCA (2002) Comparison of index flood estimation procedure’s for ungauged catchments. Can. J. Civ. Eng. 29/5, 734–741
  22. SCS. (1972) Estimation of direct runoff from storm rainfall. National Engineering Handbook, Section 4
  23. SCS. (1989) Rufoff curve number coputation. Hydrology Training Series, Module 104
  24. Salami, AW., Bilewu, SO., Ayanshola, AM., Oritola, SF (2009) Evaluation of synthetic unit hydrograph methods for the development of design storm hydrographs for Rivers in South-West, Nigeria. J. Am. Sci. 5/4, 23–32
  25. Singh, N., Singh, KK (2017) Geomorphological analysis and prioritization of sub-watersheds using Snyder’s synthetic unit hydrograph method. Appl. Water Sci, 7, 275–283
  26. Singh, VP (2018) Hydrologic modeling: progress and future directions. Geosci. Lett. 5, 15, doi.org/10.1186/s40562-018-0113-z
  27. Taş, E., İçağa, Y., Zorluer, İ (2016) Taşkın yayılım haritalarının oluşturulması ve taşkın zarar analizi: Akarçay Afyon Alt Havzası Örneği. AKÜ FEMÜBİD, 16, 711–721
  28. Yonatan, B., Tamir, G., Judith, L., Efrat, M (2009) Rainfall-runoff modeling in a small hyper-arid catchment. J. Hydrol. 373, 204–217