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تعیین بیشینه‌ی آب‌دهی سیلاب با روش سطح پاسخ در زیرحوزه‌های دره‌رود استان اردبیل | ||
| پژوهش های آبخیزداری | ||
| مقاله 8، دوره 35، شماره 1 - شماره پیاپی 134، فروردین 1401، صفحه 88-104 اصل مقاله (4.14 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmrj.2021.354467.1409 | ||
| نویسنده | ||
| یاسر حسینی* | ||
| دانشیار دانشکده کشاورزی و منابع طبیعی مغان، دانشگاه محقق اردبیلی | ||
| چکیده | ||
| مدیریت اندوخته‌‌های آب در حوزه‌ها بی تعیینکردن دقیق آب‌دهی سیلاب امکان‌پذیر نیست. این پژوهش با هدف تعیینکردن بیشینه‌ی سیلاب با دورهی بازگشت‌های 10، 25، 50 و 100 ساله با شبیه‌ساز سطح پاسخ در زیرحوزه‌های دره‌رود (km212900) در استان اردبیل انجام شد. دادههای آب‌دهی 16 ایستگاه آب‌سنجی در دورهی 15 ساله (1394-1380) جمع‌آوری، و کم‌بودهای آماری در دورهی مشترک با روش‌های وایازی میان ایستگاه‌های آب‌سنجی برطرف شد، و سیلاب با دورهی بازگشت‌های گوناگون بررسی شد. ویژگی‌های گیتاشناسی موثر بر سیلاب (مساحت، شیب، ضریب شکل و ارتفاع متوسط، زمان تمرکز و شماره‌ی منحنی زیرحوزه‌ها) با نرمافزارهای آرک‌جی‌آی‌اس 10.2 و WMS7.1 استخراج شد. اندازه‌ی ضریب تبیین در دورهی بازگشت‌های 10، 25، 50 و 100 سال به‌ترتیب 0/96، 0/97، 0/95 و 0/94 برآورد شد، که نشان‌‌دهنده‌ی دقت زیاد شبیه‌ساز در پیش‌بینی اندازه‌ی سیلاب با ویژگی‌های گیتاشناسی حوزه است. شاخص‌های ارزیابی شبیه‌ساز برای دورهی بازگشت‌های 10، 25، 50 و 100 سال شامل ریشه‌ی میانگین مربع‌های خطا به‌ترتیب 20/99، 7/16، 29/05، 39/55، درصد خطای نسبی (ε) 52/7، 39/7، 45/1، 49/13، میانگین خطای مطلق 0/52، 0/45، 0/48، 0/55، ضریب باقی‌مانده‌ی جرم 0/28، 0/16، 0/56، 0/82 و کارآیی شبیه‌ساز 0/74، 0/85، 0/71 و 0/75 برآورد شد. نمودارهای پراکندگی نشان داد که پراکندگی نقطه‌های دور محور یک‌به‌یک برای همه‌ی دورهی بازگشت‌ها و آب‌دهی‌ها بسیار مناسب بود. بر پایه‌ی آزمون تی تفاوت میان اندازه‌های پیش‌بینی‌شده و واقعی در دورهی بازگشت‌های گوناگون در تراز اطمینان 1% معنی‌دار نشد. نتیجه‌های این پژوهش نشان‌داد که دقت روش سطح پاسخ برای برآوردکردن سیلاب در زیرحوزه‌های استان اردبیل مناسب است، اما دقت شبیه‌ساز با افزایش دورهی بازگشت کمی کاهش می‌یابد. | ||
| کلیدواژه‌ها | ||
| استان اردبیل؛ توزیع آماری؛ دورهی بازگشت؛ زیرحوزه؛ سطح پاسخ | ||
| عنوان مقاله [English] | ||
| Determining the Maximum Flood Discharge Using the Response Surface Methodology in Darrehrood Sub-Basins, Ardebil Province | ||
| نویسندگان [English] | ||
| Yaser Hoseini | ||
| Moghan College of Agriculture and Natural resources, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| چکیده [English] | ||
| It is impossible to manage water resources in basins without the accurate determination of the peak flood discharge. Therefore, this study was carried out to determine the peak flood discharge for the return period of 10, 25, 50, and 100 years using RSM model in Darrehrood sub-basins with 12900 km2 area in Ardebil Province. Flow data of 16 hydrometric stations were collected in a statistical period of 15 years (2001-2005) and statistical deficiencies in the joint period were eliminated by using regression methods between hydrometric stations. Floods were calculated with different return periods. Also, physiographic characteristics of sub-basins that affect flood rate including area, slope, shape factor, height average, concentration time, and curve number were achieved using ArcGIS10.2 and WMS7.1 (watershed modeling system). The Goodness of Fit (R2) in the return periods of 10, 25, 50, and 100 years was estimated to be 96, 97, 95, and 94%, respectively. This indicates the model's high accuracy to predict the peak discharge in the sub-basins using the basin physiographic parameters. Model performance indexes of the model evaluation for return period of 10, 25, 50 and 100 years were calculated respectively including root mean square error (RMSE) of 20.99, 7.16, 29.05, 39.55, relative percentage error (ε) of 52.7, 37.7, 45.1, 49.13, mean absolute error (MAE) of 0.52, 0.45, 0.48, 0.55, coefficient of residual mass (CRM) of 0.28, 0.16, 0.56, 0.82, and model efficiency (EF) of 0.74, 0.85, 0.71, 0.75. Cross-validation diagrams showed that RSM model was very suitable for the whole return periods. Paired t-test showed that the difference between predicted and actual values in different return periods was not significant (P< 0.01). The results of this study showed that the RSM has good accuracy for estimating floods in sub-basins of Ardebil Province. | ||
| کلیدواژه‌ها [English] | ||
| Ardabil province, return period, RSM, sub basin, statistical distribution | ||
| مراجع | ||
|
Azam M, Hyung SK, Seung JM. 2017. Development of flood alert application in Mushim stream watershed Korea. International Journal of Disaster Risk Reduction. 21(1): 6–11. Azhar H. 2017. Estimation of design flood discharge for Kakkadavu dam in Kariangode River Basin. International Journal of Environmental Sciences & Natural Resources. 4(1): 555–560. Badri B, Zarebidaki R, Honarbakhsh A, Atashkhar F. 2017. Prioritization of Beheshtabad watershed sub-basins for flood potential. Natural Geography Research (Geographical Research). 48(1): 143–158. (In Persian). Box GEP, Wilson KB. 1951. On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society. Series B (Methodological). 13(1):1–45. Brouwer R, Van EK. 2004. Reintegrated ecological, economic and social impact assessment of alternative flood control policies in the Netherlands. Ecological Economics. 50(2):1–21. Chau VN, Holland J, Cassells S, Tuohy M. 2013. Using GIS to map impacts upon agriculture from extreme floods in Vietnam. Applied Geography. 41: 65–74. Dile YT, Srinivasan R. 2014. Evaluation of CFSR climate data for hydrologic prediction in data-scarce watersheds: An application in the Blue Nile River basin. The Journal of the American Water Resources Association. 50(5): 1226–1241. Eslami Z, Shojaei S, Hakimzadeh MA. 2017. Exploring prioritized sub-basins in terms of flooding risk using HEC-HMS model in Eskandari catchment, Iran. Spatial Information Research. 25(5): 677–684. Esmali A, Mirzaei Y, Madadi A, 2018. Assessment the soil erosion and sediment yield with using of rainfall-runoff WMS model (Case study: Sadal Watershed-west Azerbaijan Province). Journal of Natural Environmental Hazards. 7(17): 1–18. (In Persian). Fu MC. 2015. Handbook of simulation optimization. Vol. 216. New York: Springer Science and Business Media 387 p. Ghaemi H, Morid S.1996. Flood model of Karkheh sub-basins. Nivar. 30(2):10–27. (In Persian). Ghaffariegilandeh A, Behruz S, Ostadibabakandi E. 2016. Estimation of curve number and runoff height in ArcGIS, Case Study, Meshkinshahr City. Hydro Geomorphology. 3(9):159–175. (In Persian). Hejazi A, Marzbani M. 2015. Estimation of maximum runoff height and discharge using curve number method Case Study: Sarab Darehshahr watershed. Hydro Geomorphology. 2(5): 63–81. (In Persian). Hoseini Y, Azari A, Pilpayeh A. 2017. Flood modeling using WMS model for determining peak flood discharge in southwest Iran. Case study: Simili Basin in Khuzestan Province. Applied Water Science. 733):55–63. Hoseini Y .2020. Comparison of uniform and SCS unit hydrograph methods to estimate maximum flood discharge of Amughin basin. Hydro Geomorphology. 6(21):87–107. (In Persian). Jena J, Nath S. 2020. An empirical formula for design flood estimation of un-gauged catchments in Brahmani Basin, Odisha. Journal of the Institution of Engineers (India): Series A.101: 1–6. Johnson NL, Kotz S, Balakrishnan N. 1995. Continuous univariate distributions (Vol. 2, 2nd ed.), New York: John Wiley. 711 p. Karami HR, Keyhani M, Mowla.D. 2016. Experimental analysis of drag reduction in the pipelines with response surface methodology. Journal of Petroleum Science and Engineering, 138(2): 104–112. Keshtegar B, Allawi MF, Abdulmohsin Afan H, El-Shafie A. 2016. Optimized river stream-flow forecasting model utilizing high-order response surface method. Water Resource Management, 30(22): 3899–3914. Khosroshahi M, Saghafian B. 2002. Investigating the role of participation of watershed sub-basins in flood severity. Journal of Research and Construction. 16(2):67–75. (In Persian). Kostic S, Stojkovic M, Prohaska S, Vasovic N. 2016. Modeling of river flow rate as a function of rainfall and temperature using response surface methodology based on historical time series. Journal of Hydro Informatics.18(4):651–666. Mahdavi M, 1999. Applied hydrology, Tehran University Publishers, 401 p. Mlinsky D, Walega A, Stachura T, Kaczor G, 2019. A New empirical approach to calculating flood frequency in ungauged catchments: A case study of the upper Vistula Basin, Poland. Water. 11(3): 601–622. Montgomery DC, Myers RH. 1995. “Response surface methodology: process and product optimization using designed experiments”, Raymond H. Meyers and Douglas C. Montgomery, A Wiley-Inter science Publications. 856 p. Nikpour, MR, Sanikhani H, Mahmodi Babelan S, Nastarani Amuqin S. 2018. Daily rainfall – runoff modeling of Darreh-Rud river in Ardabil province, Iran. Irrigation Sciences and Engineering. 41(4):133–146. (In Persian). Nohegar A, Ghashghaizadeh N, Hellisaz A. 2012. Determining flooded areas and prioritizing flooding of sub-basins (Case study: Jamash Watershed of Hormozgan Province). Research in Earth Science. 3(9):14–25. (In Persian). Purseifollahi B, Kanooni A, Nikpur MR, Ramazani moghadam J. 2018. Determination of homogeneous areas for flood estimation in catchment area in Darreroud, Ardabil Province. Sixth Comprehensive Conference on Flood Management and Engineering. Ministry of Energy, Tehran, Iran.10 p. (In Persian). Rahaman SA, Ajeez SA, Aruchamy S, Jegankumar R. 2015. Prioritization of sub watershed based on morphometric characteristics using fuzzy analytical hierarchy process and geographical information system – A study of Kallar watershed, Tamil Nadu. Modeling Earth Systems and Environment. 3(1): 1–9. Rasulzadeh A, Azartaj E, Farzi P. 2016. Derivation and investigation of regional flood analysis models as a function of return period (Case study: Ardabil province). Journal of Water and Soil Conservation. 22(4): 261–268. (In Persian). Razavizadeh S, Shahedi K. 2017. Combination of AHP and TOPSIS methods to prioritize of flooding in Taleghan sub watersheds. Natural Ecosystems of Iran. 7(4):33–46. (In Persian). Saghafian B, Noroozpour S, Kiani M, Rafiee Nasab. A. 2016. Coupled Modclark-curve Number Rainfall-runoff Model. Arabian Journal of Geosciences. 9 (4): 2–13. Shabanie bazneshin A, Emadi AR, Fazaveli R. 2016. Investigating the potential of flooding of watershed basins and determining flood generation areas (Case study: Neka Watershed). Management Basin Research. 7(1):20–28. (In Persian). Sharifi paichoon M, Omidvar K, Motazaker K. 2019. Assessment of flooding using cluster analysis and multivariable regression methods with emphasis on hydro geomorphological parameters (Case study: Maroon Catchment. Journal of Natural Environmental Hazards. 8(21):75–92. (In Persian). Shirazi M, Khademorasoul A, Safieddine-Ardabili, SM. 2019. Evaluation and optimization of the effects of soil salinity (EC) on soil erosive properties using response surface methodology. 16th Iranian Soil Science Congress, University of Zanjan. Zanjan. Iran.12 p. (In Persian). WMS7.1. 2006. User manual. Bringhum Young University. 250 p. Yu J, Qin X, Ole L, Chua LHC. 2014. Comparison between response surface models and artificial neural networks in hydrologic forecasting. Journal of Hydrologic Engineering. 19(3):473–481. Yousefi Mobarhan E, Farahmand K, Fahim N, Fahim E. 2016. Efficiency of flow-duration curves method for verifycation of a hydrological model (Case study: Zola-Chay Watershed). Water and Soil Science. 26 (2–1): 101–113. (In Persian). | ||
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