برآورد سیلاب طرح حوضه آبخیز با به‌کارگیری تئوری فرکتال و مدل بارش- رواناب HEC-HMS (مطالعه موردی: حوضه آبخیز رودخانه خرم‌آباد)

نوع مقاله : مقالات پژوهشی

نویسندگان

• حمیدرضا باباعلی ¹
• زهره رامک ²
• رضا سپهوند ³

¹ دانشگاه آزاد اسلامی واحد خرم آباد

² دانشگاه آزاد اسلامی واحد خرم اباد

³ دانشگاه صنعتی اصفهان

https://doi.org/10.22067/jsw.v32i6.71723

چکیده

برآورد سیلاب طرح حوضه آبخیز جهت طراحی سازه­های هیدرولیکی، تثبیت سواحل رودخانه، پروژه­های آبخیزداری و پهنه­بندی سیل یکی از مهم‌ترین مسائل هیدرولیکی و هیدرولوژیکی به­شمار می­آید. منحنی­های شدت- مدت- فراوانی (IDF) بارش یکی از ابزارهای هیدرولوژیکی جهت محاسبه سیلاب طرح و طراحی سازه­های هیدرولیکی می­باشند. حوضه آبخیز رودخانه خرم­آباد یکی از زیرحوضه­های حوضه کرخه همواره در معرض وقوع سیلاب­های مخرب و خسارت­های ناشی از آن بوده است. در این تحقیق، ابتدا منحنی­های شدت- مدت- فراوانی حوضه آبخیز به کمک تئوری فرکتال برآورد گردید و پس از آن، بارش طرح حوضه در دوره­های بازگشت­ مختلف به­دست آمد. در مرحله بعد مدل بارش- رواناب HEC-HMS برای حوضه مورد نظر واسنجی و در نهایت سیلاب طرح حوضه در دوره­های بازگشت­ مختلف تخمین زده شد. نتایج تحقیق، کارآیی بالای مدل فرکتال و نیز مدل هیدرولوژیکی HEC-HMS را در این حوضه نشان داد. همچنین نتیجه تحقیق توزیع احتمالاتی گامبل را با آزمون کای­اسکور، اندرسون دارلینگ و نیز کولموگروف-اسمیرنوف با سطح معنا داری 5 درصد برای داده­های حداکثر بارش سالانه با تداوم روزانه این حوضه مناسب دانست.

کلیدواژه‌ها

• بارش طرح ، تئوری فرکتال
• سیلاب طرح
• مدل HEC-HMS
• منحنی های IDF

20.1001.1.20084757.1397.32.6.5.9

عنوان مقاله [English]

Estimation of Design Flood using Fractal Theory and HEC-HMS Model (Case Study: Khorramabad River Basin)

نویسندگان [English]

• Hamidreza Babaali ¹
• Zohreh Ramak ²
• Reza Sepahvand ³

¹ Islamic Azad University

² Islamic azad university

³ Isfahan University of Technology

چکیده [English]

Introduction: Estimating the design flood of the basin for the design of hydraulic structures, stabilization of river banks, watersheds and flood zoning projects are the most important in hydraulic and hydrological issues and projects. The flood used to design structures and influenced by hydrological events is called design flood which depends on   structure safety, cost, life expectancy, and possible damage. Intensity- duration- frequency (IDF) curves of rainfall is a hydrological tool for the estimation of the design flood and design of hydraulic structures. These curves are constructed for a region from rainfall data which are recorded at various continuations. Usually, in some countries such as Iran which has a large extent, there is not enough rain-gage station; or the length of the statistical period is low, so it is impossible to calculate the IDF curves. But since it is not usually possible to access daily rainfall data, the fractal theory can be used to estimate the precipitation data in different consistency and the IDF curve with a very good accuracy.
Materials and Methods: Korramabad river basin, one of sub-basin of Karkhe basin, often has been exposed to destructive floods and damages caused by it. In this research, the intensity-duration-frequency curves of the catchment area are estimated using fractal theory at first, and then the design precipitations are obtained in different return periods. In the next step we calibrated HEC-HMS rainfall- runoff model and finally the design floods are estimated in different return periods. The HEC-HMS model is an extension of the HEC-1 model under Windows, with all its capabilities. Hydrographs calculated by this model are used directly or in combination with other software for various purposes such as water supply, urban drainage, flood and flow forecasting, land use change, flood control studies and exploitation of reservoir systems.
In this research, SCS curve number method and recession method are used to calculate the losses and base flow. Also for estimation of runoff, SCS curve number, Snyder unit hydrograph and Clark unit hydrograph are used in three methods and after comparing the results of the three methods in the calibration stage of the model, the Clarke unit hydrograph method is identified as the best method for estimating runoff. Also the Maskingham method has also been used for flood routing. The data needed for this study include rain gage data, hydrometric data, physiographic data of the basin, and also amounts of CN or curve number of the basin. Rain gage and hydrometric station used in this research are Chamanjir station.
In this research, due to the importance of peak discharge for designing hydraulic structures, the optimization of the parameters has been done using the peak-weighted RMS Error criterion. In the calibration step, Comparison between hydrographs shows that there is a good agreement between computational and observational hydrographs, in such a way that the difference between the simulated and the actual peak discharge are 0.6, 0.2 percent for the selected floods. After calibration of the HEC-HMS rainfall runoff model for the studied area, this model is used to estimate the design flood. In the process of conversion precipitation to runoff, it is necessary to determine the pattern for temporal distribution of rainfall at the stations and in the area. To do so, the non-dimensional rainfall data are plotted for some storms with different time durations. For making data for each storm non-dimensional, the accumulated depth of precipitation to the desired time step was divided by the total depth of storm’s rainfall. The same procedure was carried out to make the time axis non-dimensional. By analyzing the precipitation data of the recorder station at the basin, it was found that in the majority of the precipitations, 20% of rainfall occurs in the first quarter, 20% in the second quarter, 40% in the third quarter and 20% in the fourth quarter.
Results and Discussion: The results of this research show that:

Daily precipitation data have a fractal characteristic in the ranging from 1 to 8 days, and during this time interval, rainfall data can be converted from a continuity to another continuity.
Due to the lack of recorded rainfall statistics in different continuations, using fractal method can be a useful way to prepare IDF curves in this basin and these curves are obtained based on the daily rainfall data available.
There is high efficiency of fractal model and HEC-HMS model in this catchment and the Gambel probabilistic distribution is appropriated for the maximum daily rainfall data of this basin.

کلیدواژه‌ها [English]

• Design precipitation
• Design flood
• IDF Curves
• Fractal theory
• HEC-HMS model

مراجع

1. Azari M., Sadeghi H.M., Talvari A. 2008. Determine the participation of sub-basins of Jaghrgh in peak discharge and runoff volume to prioritize flood control. Geography and Development, 12: 199-212. (in Persian with English abstract)

2. Bara M. 2008. Analysis of short-term rainfall intensities the simple scaling approaches. Proceedings of the 20th Conference of young hydrologists, SHMI, Bratislava,CD,10 p.

3. Bara M. 2009. Scaling properties of extreme rainfall in Slovakia. Proceedings of the 11th international science conference of PhD Students, Juniorstav, VUT Brno, CD, 6 p.

4. Burlando P., and Rosso R. 1996. Scaling and multiscaling models of depth – duration – frequency curves for storm precipitation. Journal of Hydrology, 187: 45-65.

5. Cheng K.S., Hueter I., Hsu E.C., and Yeh H.C. 2001. A Scaling Gauss-Markov for Design Storm Hyetographs. Journal of the American Water Resources Association, 37(3): 723-736.

6. Danandehmehr A., Majdzadeh Tabatabai M.R. 2010. Prediction of Daily Discharge Trend of River Flow Based on Genetic Programmin. Journal of Water and Soil, 24: 325-333. (In Persian with English abstract)

7. Deidda R. 2000. Rainfall downscaling in Space – time multifractal framework. Water Resource Research, 36: 1779-1794.

8. Fazaeeli H. 2010. Using Genetic Planning Method in Rainfall Modeling. M.S thesis, Water Engineering Department, Tabriz University.

9. Hajizadeh M., Noorani V. 2011. Presenting a Geomorphological Runoff-Runoff Model Based on the Concept of Nonlinear Cascading Tanks. 6th National Congress of Civil Engineering, Semnan University, p. 1-8. (in Persian)

10. Haghizadeh A., Mohammadloo M., Noori F.2015. Simulation of Runoff Rainfall Process Using Artificial Neural Network and Fuzzy Neuro-Comparative System and Multivariate Regression (Case Study : Khorramabad Watershed). Journal of ecohydrology, 2: 233-243. (in Persian)

11. Kamali M., Solaimani K., Shahedi K., Gord- Noshahri A., Gomrokchi A. 2015. Determining the Flooding Points and Prioritizing Subcatchments of Barajin Catchment of Qazvin Using Hec-HMS and GIS. Iran-Watershed Management Science & Engineering, 9(27-34): 27-34. (in Persian with English abstract)

12. Malamud B. D., and Turcotte D.L. 2006. The applicability of power law frequency statistics of floods. Journal of hydrology, 322:168-180.

13. Molnar P., and Burlando P. 2005. Preservation of rainfall properties in stochastic disaggregation by a simple random cascade model. Atmospheric Research, 77:137-151.

14. Menable M., Seed A., and Pegram G. 1999. A simple scaling model for extreme rainfall. Water Resources , 35: 335-339.

15. Nasri M., Soleimani, F., and Katani, M. 2011. Simulation of the Rainfall-Runoff Process Using of HEC-HMS Hydrological Model (A Case Study of Sheikh Bahaei Dam Basin). World Academy of Science, Engineering and Technology, 54: 548-562.

16. Nhat L.M, Tachikawa Y., Sayama T., and Takara K. 2007. Regional rainfall intensity – duration – frequency relationships for ungauged catchments based on scaling properties. Disaster Prevention Research Institute, Kyoto University, 50: 33-43.

17. Noori Gheidari M.H. 2012, Extracting the Intensity - Duration – Frequency Curves with Daily Precipitation Data Using Fractal Theory. Journal of Water and Soil, 26(3): 718-726. (in Persian with English abstract)

18. Soltani A., Gorbani M.A., Fakheri Fard A., Darbandi S., and Farsadizadeh D. 2009. Genetic Programming and Its Application in Rainfall-Runoff Modeling. Journal of Water and Soil, 20.1(4): 63-73. (in Persian with English abstract)

19. Taheri Tizro A., Pakdel Khasmakhi H., Marofi S., and Vazifedoust M. 2016. Integrated HEC-HMS and GLDAS models to runoff estimate of ungauged area. Journal of Water and Soil Conservation, 23(4):. 101-118. (in Persian with English abstract)

20. US Army Corps of Engineers. 2000. Hydrologic Modeling System HEC_HMS: Technical Reference Manual, USA.

21. Yu P.S., Yang T.C., and Lin C.S. 2004. Regional rainfall intensity formulas based on scaling property of rainfall. Journal of Hydrology, 295:108-123.