تحلیل عدم قطعیت ناشی از کاربرد روش‌های مختلف برآورد نفوذ بر عملکرد مدل بارش-رواناب HEC-HMS با استفاده از الگوریتم GLUE

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد مهندسی منابع آب/ دانشگاه بین المللی خمینی (ره)، قزوین.

2 استادیار /گروه مهندسی آب، دانشگاه بین‌المللی خمینی ، قزوین.

چکیده

تعداد زیاد پارامترهای ورودی مدل‌های بارش- رواناب و نبود درک فیزیکی از آن‌ها، کاربرد این مدل‌ها را به ویژه در مرحله واسنجی با مشکل مواجه می‌نماید. پژوهش حاضر با هدف بررسی عدم ‌قطعیت ناشی از روش‌های مختلف برآورد نفوذ (Green-Ampt، SCS-CN، Exponential، Smith-Parlange، Initial-Constant و Deficit-Constant) بر هیدروگراف سیلاب شبیه‌سازی شده توسط مدل‌ HEC-HMS و با استفاده از الگوریتم GLUE به انجام رسیده است. نتایج نشان که استفاده از هر کدام از روابط مختلف نفوذ، باند عدم قطعیت متفاوتی را بر هیدروگراف سیلاب شبیه‌سازی شده توسط مدل تحمیل می‌نماید. محاسبات انجام شده حاکی از آن است که در صورت استفاده از دو معادله نفوذ SCS و Smith-Parlange به علت دارا بودن بیشترین مقدار P-Factor (به ترتیب معادل 78/0 و 72/0) و کمترین مقدار ARIL (به ترتیب معادل 39/0 و 40/0)، عدم قطعیت کمتری بر خروجی مدل HEC-HMS می‌گردد. علاوه‌بر این، روابط مذکور به علت دارا بودن پارامترهای حساس کمتر از کارائی به مراتب بالاتری نسبت به دیگر روشها برخوردار می‌باشند. برخلاف روشهای مذکور، عدم قطعیت ناشی از کاربرد معادلات نفوذ Initial & Constant و Deficit & Constant برای برآورد هیدروگراف سیلاب نسبتاً بالا بوده و درصد کمتری از داده‌های مشاهداتی در پهنای باند عدم قطعیت 95% قرار می‌گیرند. تحلیل حساسیت پارامترهای ورودی هر کدام از معادلات نفوذ با استفاده از آماره d روش غیرپارامتریک کلموگراف-اسمیرنوف نیز نشان داد که پارامترهایی که دارای توزیع با شیب زیاد و شکل کشیده‌ای هستند، به ترتیب دارای عدم قطعیت کم و زیاد می‌باشند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Uncertainty Analysis due to the Application of Different Infiltration Methods on the Performance of HEC-HMS model Using GLUE Algorithm

نویسندگان [English]

  • Sara Roodaki 1
  • Asghar Azizian 2
1 M.Sc. in Water Resources Engineering, Water engineering Department, Khomeini International University, Qazvin, Iran.
2 Assistant Professor, Water engineering Department, Khomeini International University, Qazvin, Iran.
چکیده [English]

Quantifying the uncertainty contribution of important factors on the performance of rainfall-runoff models has always been one of the major challenges for researchers and hydrologists. The main problems of applying these models especially in calibration period are the large number of required parameters and the lack of physical understanding for some of them. This research addressed the uncertainty contribution of different infiltration methods (Green-Ampt, SCS-CN, Exponential, Smith-Parlange, Initial-Constant and Deficit-Constant) on the performance of HEC-HMS model using GLUE algorithm. Results showed that using each of infiltration methods imposes different uncertainty bounds on the simulated flood hydrograph by HEC-HMS. Findings indicate that SCS-CN and Smith-Parlange owing to have the higher P-factor (0.78 and 0.72) and lower ARIL (0.39 and 0.40) values, enforce minimum uncertainty on the model output. In addition, the mentioned infiltration methods have the fewer sensitive parameters and then performs better than other methods. In contrast, the uncertainty of applying Initial-Constant and Deficit-Constant methods for simulation of flood hydrograph is relatively high the smaller percentage of the observed data are within the 95% uncertainty bandwidth. Moreover, sensitivity analysis of the parameters of each of the infiltration methods using the nonparametric Kolmogorov–Smirnov (D) test showed that parameters with the sharp and peaked distributions indicate well-identifiable parameters, while flat and spread distributions indicate uncertain parameters. Overall, the outcomes of this study prove that GLUE algorithm has high ability to determine the optimal range of rainfall-runoff model parameters and the prediction uncertainty bandwidth.

کلیدواژه‌ها [English]

  • Hydrological model
  • Uncertainty
  • GLUE algorithm
  • Flood routing
  • Effective rainfall
Abood M, Thamer AM, Ghazali AH, Mahmud AR and Sidek LM (2012) Impact of infiltration methods on the accuracy of rainfall-runoff simulation. Research Journal of Applied Sciences, Engineering and Technology 4:1708-1713
Chahinian N, Moussa R, Andrieux P, and Voltz M (2005) Comparison of infiltration models to simulate flood events at the field scale. Journal of Hydrology 306:191-214
Liu YB, Batelaan O, De Smedt F, Poórová J, and Velcická L (2005) Automated calibration applied to a GIS-based flood simulation model using PEST, in J. van Alphen, E. van Beek and M. Taal (eds.), Floods, from Defense to Management, Taylor-Francis Group, London, Pp:317-326
Bahremand A (2006) Simulating the effects of reforestation on floods using spatially distributed hydrologic modeling and GIS. Ph.D. Thesis, Vrije Universiteit Brussel, Belgium
Muleta MK and Nicklow JW (2005) Sensitivity and uncertainty analysis coupled with automatic calibration for a distributed watershed model. Journal of Hydrology 306:127-145
Gupta HV, Yapo PO, and Sorooshian S (1996) Automatic calibration of conceptual rainfall runoff models: Sensitivity to calibration data. Journal of Hydrology 181(1-4):23-48
Ndomba P, Mtalo F and Killingtveit A (2008) SWAT model application in a data scarce tropical complex catchment in Tanzania. Physics and Chemistry of the Earth 33(8-13):626-632
Yisa J and Jimoh T (2010) Analytical studies on water quality index of river Landzu. American Journal of Applied Sciences 458-453
Kumar A and D Jain (2008) Predicting direct runoff from hilly watershed using geomorphology and stream-order law ratios: Case study. Journal of Hydrologic Engineering, ASCE 13(7):570-576
Beven KJ and Binley A (1992) The future of distributed models: Model calibration and uncertainty prediction. Hydrological Processes 6(3):279-298
Kuczera G and Parent E (1998) Monte Carlo assessment of parameter uncertainty in conceptual catchment models: The Metropolis algorithm. Journal of Hydrology 211(1-4):69-85
Beven KJ and Freer J (2001) A dynamic topmodel. Hydrological Processes 15(10):1993-2011
Bahremand A (2006) Simulating the effects of reforestation on floods using spatially distributed hydrologic modeling and GIS. Ph.D. Thesis, Vrije Universiteit Brussel, Belgium
Stolte J (2003) Effects of land use and infiltration behavior on soil conservation strategies. Ph.D. Wageningen University, Mediterranean vineyards in Southern France. Catena 72:79-90
Gaither RE and Buckhouse JC (1983) Infiltration rates of various vegetative communities within the Blue Mountains of Oregon. Journal of Range Management 36:58-60
Kothyari BP, Verma PK, Joshi BK, Kothyari UC (2004) Rainfall-runoff-soil and nutrient loss relationships for plot size areas of Bhetagad watershed in Central Himalaya, India. Journal of Hydrology 293:137-150
Kresic N (2009) Ground water resources sustainability, management, and restoration. Copyright by The McGraw Hill Companies, Inc., 856p.
Tung YK (1996) Uncertainty analysis in water resources engineering, in stochastic hydraulics. 96, (Edited by K.S. Tickle et al.), Balkema, Rotterdam, The Netherlands, pp. 29-46
Yeh KC and Deng SL (1996) Uncertainty analysis of sediment transport formulas, in stochastic hydraulics. 96, Tickle et al. (Eds)
Nasseri M and Ahmadi A (2019) Simulation of parametric uncertainty of hydrological models using UNEEC-P framework: Monthly water balance model case study. Iran-Water Resources Research 14(5):164-176 (In Persian)
Montanari A (2011) Uncertainty of hydrological predictions. In: Peter Wilderer (ed.) Treatise on Water Science, Oxford: Academic Press 2:459-478
Montanari A (2007) What do we mean by 'uncertainty'? The need for a consistent wording about uncertainty assessment in hydrology. Hydrological Processes 21:841-845
Mosavinejad SH, Habashi H, Kiani F, Shataee SH, and Abdi O (2017) Evaluation of soil erosion using imagery SOPT5 satellite in Chehel chi catchment of Golestan province. Journal of Wood & Forest Science and Technology 24(2):73-86 (In Persian)
Sheikh V, Hezbi A, and Bahremand A (2015) Distributed dynamic modeling of water balance in the Chehelchai Watershed within A GIS Environment. Journal of Watershed Management Research 6(2):29-42 (In Persian)
Jafarzadeh MS, Rouhani H, Salmani H, and Fathabadi A (2016) Reducing uncertainty in a semi distributed hydrological modeling within the GLUE framework. Journal of Water and Soil Conservation 23(1):83-100 (In Persian)
Wei Z, Tian L, Meihong D (2015) Uncertainty assessment of water quality modeling for a small-scale urban catchment using the GLUE methodology: A case study in Shanghai, China. Environmental Science and Pollution Research 22(12):9241-9249
USACE (2000) HEC-HMS technical reference manual. Davis, CA. USA.
USACE (2017) HEC-HMS user’s manual. Davis, CA. USA.
Ratto M and Saltelli A (2001) Model assessment in integrated procedures for environmental impact evaluation: software prototypes. Joint Research Centre of European Commission, Institute for the Protection and Security of the Citizen, Ispra, Italia
Fathabadi A, Rouhani H, and Seyedian SM (2017) The efficiency of nonparametric methods based on residual analyzes and parametric method to estimate hydrological model uncertainty. Iranian Journal of Soil and Water Research 49(2):281-292 (In Persian)