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Comparing random forest flood frequency analysis with regional flood frequency, Creager and SCS in Doab-Qazanchi, Kermanshah | ||
| Journal of Applied Research in Water and Wastewater | ||
| دوره 12، شماره 1 - شماره پیاپی 23، شهریور 2025، صفحه 86-95 اصل مقاله (1.31 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22126/arww.2025.11095.1349 | ||
| نویسندگان | ||
| Maryam Hafezparast* ؛ Sadaf Gord؛ Rasool Ghobadian | ||
| Water Engineering Department, Faculty of Agriculture, Razi University, Kermanshah, Iran. | ||
| چکیده | ||
| Due to climate change and rising global temperature, the occurrence of extreme floods and drought events has intensified. In this regard, in 2019, heavy rainfall occurred in Kermanshah province. The Gharasoo river runs through the city of Kermanshah in western Iran. The Doab-Qazanchi area is located on the Gharasoo River at the crossroads of the Razavar and mereg Rivers to the Gharasoo River and there is no hydrometric station in this area. In this research, floods with different return periods of 2, 5, 20, 50, 100, 200, 500 and 1000 years with Creager and regional flood frequency analysis (RFFA), and the random forest machine learning method using the physical and hydrological characteristics of the surrounding watersheds are predicted. The SCS method was implemented for the flood on 03/04/2019 and it showed that the occurred flood is equivalent to a 25-year flood in this region. The predicted values estimated a lower discharge than the soil conservation service (SCS) method. The random forest (RF) method, as a machine learning method compared to old statistical methods, has a good performance in predicting the flood discharge using the physical and hydrological indicators of the catchment area, and by determining the priority of different features, it predicts the flood discharge well. | ||
| کلیدواژه‌ها | ||
| Creager؛ Doab-Qazanchi؛ Flood؛ Regional flood frequency analysis (RFFA)؛ Random forest (RF)؛ Soil conservation service (SCS) | ||
| مراجع | ||
|
Allahbakhshian-Farsani P. et al. (2020) ‘Regional flood frequency analysis through some machine learning models in semi-arid regions’, Water Resources Management, 34, pp. 2887–2909. doi: https://doi.org/10.1007/s11269-020-02590-9
Al-Fawa’reh, M., et al. (2021) ‘Intelligent methods for flood forecasting in Wadi al Wala, Jordan’, Proceedings of the International Congress of Advanced Technology and Engineering (ICOTEN). Taiz, Yemen, 1–3 July. Piscataway, NJ: IEEE, pp. 1–9. doi: https://doi.org/10.1109/ICOTEN52080.2021.9493425
Bormann, H., Pinter, N. and Elfert, S. (2011) ‘Hydrological signatures of flood trends on German rivers: Flood frequencies, flood heights and specific stages’, Journal of Hydrology, 404(1–2), pp. 50–66. doi: https://doi.org/10.1016/j.jhydrol.2011.04.019
Chen R.C., et al. (2020) ‘Selecting critical features for data classification based on machine learning methods’, Journal of Big Data, 7, 52. doi: https://doi.org/10.1186/s40537-020-00327-4
Creager, W.P., Justin, J.D. and Hinds, J. (1945) Engineering for Dams, Vol. 1: General Design. New York: John Wiley.
Dogan E., et al. (2010) ‘Modelling of evaporation from the reservoir of Yuvacik dam using adaptive neuro-fuzzy inference systems’, Engineering Applications of Artificial Intelligence, 23(6), pp. 961–967. doi: https://doi.org/10.1016/j.engappai.2010.03.007
El Adlouni, S. and Bobée, B. (2015) Hydrological Frequency Analysis Using HYFRAN-PLUS Software. pp. 1–71. Available at: https://www.scribd.com/document/307191717/ (Accessed date: 5 June 2024.
Flynn, K.M., Kirby, W.H. and Hummel, P.R. (2006) User Manual for Program PeakFQ, Annual Flood-Frequency Analysis Using Bulletin 17B Guidelines (No. 4-B4). USGS. Available at: https://pubs.er.usgs.gov/publication/tm4B4 (Accessed date: 2 June 2024).
Gavrilović, L., Milanović Pešić, A. and Urošev, M. (2012) ‘A hydrological analysis of the greatest floods in Serbia in the 1960–2010 period’, Carpathian Journal of Earth and Environmental Sciences, 7(2), pp. 107–116. Available at: https://www.cjees.ro/viewTopic.php?topicId=274 (Accessed date: 6 June 2024).
Ghanbarpour M.R., et al. (2011) ‘Calibration of river hydraulic model combined with GIS analysis using ground-based observation data’, Research Journal of Applied Sciences, Engineering and Technology, 3(5), pp. 456–463. Available at: https://portal.research.lu.se/en/publications/calibration-of-river-hydraulic-model-combined-with-gis-analysis-u#:~:text=Abstract,used%20for%20many%20practical%20applications (Accessed date: 2 June 2024).
Gilleland, E., Ribatet, M. and Stephenson, A.G. (2013) ‘Software review for extreme value analysis’, Extremes, 16(1), pp. 103–119. doi: https://doi.org/10.1007/s10687-012-0155-0
Gizaw, M.S. and Gan, T.Y. (2016) ‘Regional flood frequency analysis using support vector regression under historical and future climate’, Journal of Hydrology, 538, pp. 387–398. doi: https://doi.org/10.1016/j.jhydrol.2016.04.041
Hailegeorgis, T.T. and Alfredsen, K. (2017) ‘Regional flood frequency analysis and prediction in ungauged basins including estimation of major uncertainties for mid-Norway’, Journal of Hydrology: Regional Studies, 9, pp. 104–126. doi: https://doi.org/10.1016/j.ejrh.2016.12.084
Hafezparast Mavadat, M., and Marabi, S. (2021). 'Prediction of SAR and TDS parameters using LSTM- RNN model: A case study on Aran station, Iran', Journal of Applied Research in Water and Wastewater, 8(2), pp. 88-97. doi: https://doi.org/10.22126/arww.2021.5708.1188
Hamaamin D., et al. (2022). 'The simulation of flood hydrograph under uncertain conditions of rainfall extreme values in different return periods: A case study on Gharesoo basin', Journal of Applied Research in Water and Wastewater, 9(1), pp. 91-99. doi: https://doi.org/10.22126/arww.2022.7902.1251
Hurst, H.E. (1951) ‘Long-term storage capacity of reservoirs’, Transactions of the American Society of Civil Engineers, 116(1), pp. 770–799. doi: https://doi.org/10.1061/TACEAT.0006518
Jabbari, I., Ghobadian, R. and Ahmadi Melaverdi, M. (2017) ‘The relationship between the LFH index and the flood zones with different return periods (Case study: Gharasoo River)’, Journal of Geographic Space, 17(58), pp. 191–207. Available at: http://geographical-space.iau-ahar.ac.ir/article-1-447-fa.html (Accessed date: 10 June 2024).
Jahandideh, K., et al. (2011) ‘Evaluation and calibration model WMS/HEC-HMS in the drainage basin of Gharesoo’, 1st National Conference on Coastal Water Resources Management. Sari Agricultural Sciences and Natural Resources University, Iran, 9-10 December. Civilica, NCCLWRM01_025. Available at: https://civilica.com/doc/105739/(Accessed date: 1 January 2024).
Karkouti A. et al. (2010). 'Determination of Maximum Flood Flow by use of Sampling (observe) Creager and SCS Method (Case study: Gharasoo river, Kermanshah, Iran)', Journal of Environmental Studies, 36(55), pp. 99-110. dor: https://dor.org/20.1001.1.10258620.1389.36.55.10.7
Kendall, M.G. (1975) Rank correlation methods. 4th ed. London: Charles Griffin.
Kozanis S. et al. (2010) ‘Hydrognomon – opensource software for the analysis of hydrological data’, Proceedings of the European Geosciences Union General Assembly, Vienna, Austria, 2-7 May, EGU General Assembly, p. 12419. doi: https://doi.org/10.13140/RG.2.2.21350.83527
Kundzewicz, Z.W. (Ed.). (2012). Changes in flood risk in Europe . Boca Raton: CRC Press.
Lee, J., et al. (2020) ‘Estimating design floods at ungauged watersheds in South Korea using machine learning models’, Water, 12(11), 3022. doi: https://doi.org/10.3390/w12113022
Mann, H.B. (1945) ‘Non-parametric test against trend’, Econometrica, 13, pp. 245-259. doi; http://dx.doi.org/10.2307/1907187
Morlot, M., Brilly, M. and Šraj, M. (2019) ‘Characterisation of the floods in the Danube River basin through flood frequency and seasonality analysis’, Acta Hydrotechnica, 32(56), pp. 73–89. doi: https://doi.org/10.15292/acta.hydro.2019.06
Mosavi, A., Ozturk, P. and Chau, K.W. (2018) ‘Flood prediction using machine learning models: Literature review’, Water, 10(11), 1536. doi: https://doi.org/10.3390/w10111536
Mustamin, M.R., Maricar, F. and Karamma, R. (2021) ‘Hydrological analysis in selecting flood discharge method in watershed of Kelara River’, INTEK: Jurnal Penelitian, 8(2), pp. 141–150. doi: https://doi.org/10.31963/intek.v8i2.2874
Nash, J.E. and Sutcliffe, J.V. (1970) ‘River flow forecasting through conceptual models part I — A discussion of principles’, Journal of Hydrology, 10(3), pp. 282–290. doi: https://doi.org/10.1016/0022-1694(70)90255-6
National Research Council. (1999). Improving American river flood frequency analyses. Washington, DC: The National Academies Press.
Oosterbaan, R.J. (1994) 'Frequency and regression analysis of hydrologic data', in Ritzema, H.P. (ed.) Drainage principles and applications. 2nd edn. Wageningen, The Netherlands.
Raes, D., Mallants, D. and Song, Z. (1996) 'RAINBOW: a software package for analysing hydrologic data', in Proceedings of the 6th International Conference on Hydraulic Engineering Software (HYDROSOFT 96), George Town, Malaysia, 1 September. Edited by Blain, W.R. Southampton: Computational Mechanics Publications, pp. 525-534. Available at: https://kuleuven.limo.libis.be/discovery/fulldisplay?docid=lirias4049382&context=SearchWebhook&vid=32KUL_KUL:Lirias&lang=en&search_scope=lirias_profile&adaptor=SearchWebhook&tab=LIRIAS&query=any,contains,LIRIAS4049382&offset=0 (Accessed date:12 September 2024 )
Rutkowska, A. et al. (2017) ‘Regional L-moment-based flood frequency analysis in the upper Vistula River basin, Poland’, Pure and Applied Geophysics, 174(2), pp. 701–721. doi: https://doi.org/10.1007/s00024-016-1428-3
Salami, W.A. et al. (2017) ‘Runoff hydrographs using Snyder and SCS synthetic unit hydrograph: A case study of selected rivers in south west Nigeria’, Journal of Ecological Engineering, 18(1), pp. 25–34. doi: https://doi.org/10.12911/22998993/66258
Schittkowski, K. (1980) Nonlinear programming codes: Information, tests, performance. lecture notes in economics and mathematical systems. 1st edn. Berlin: Springer. Available at: https://www.amazon.com/Nonlinear-Programming-Codes-Information-Mathematical/dp/3540102477 (Accessed date: 20 September 2024)
Shahabi, S., and Hessami Kermani, M. R. (2015) 'Flood frequency analysis using density function of wavelet (Case study: Polroud River)', Journal of Applied Research in Water and Wastewater, 2(1), pp. 122-130. doi: https://doi.org/10.22126/arww.2015.122
Sharifi Garmdareh, E., Vafakhah, M. and Eslamian, S.S. (2018) 'Regional flood frequency analysis using support vector regression', Journal of Hydrology, 565, pp. 14-24. https://doi.org/10.1016/j.jhydrol.2018.07.072
Topaloğlu, F. (2005) 'Regional flood frequency analysis of the basins of the East Mediterranean region', Turkish Journal of Agriculture and Forestry, 29(4), pp. 281-288. doi: https://doi.org/10.3906/tar-0409-8 | ||
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