شناسایی و تحلیل عدم قطعیت پارامترهای حساس مدل SWAT در برآورد رواناب حوضه کارده

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش‌آموخته کارشناشی‌ارشد، گروه مرتع و آبخیزداری، دانشکده آب و خاک، دانشگاه زابل، زابل، ایران.

2 استادیار گروه مرتع و آبخیزداری، دانشکده آب و خاک، دانشگاه زابل، زابل، ایران

3 استادیار گروه مهندسی آب، دانشکده آب و خاک، دانشگاه زابل، زابل، ایران.

4 استادیار پژوهشکده تالاب بین المللی هامون، دانشگاه زابل، زابل، ایران

چکیده

کارآیی مدل‌های هیدرولوژیکی در شبیه‌سازی رفتار یک حوضه به برآورد دقیق و اعتبار داده‌های خروجی مدل بستگی دارد. از آنجایی‌که مدل‌های هیدرولوژیکی توزیعی به دلیل جامعیت در تحلیل پدیده‌های چرخه هیدرولوژی دارای پارامترهای متعددی هستند، در معرض عدم­قطعیت خواهند بود. بنابراین، شناسایی و تجزیه و تحلیل عدم‏قطعیت پارامترهای حساس مدل ضروری می‌باشد. در این مطالعه عدم‌قطعیت ناشی از پارامترهای مدل SWAT در برآورد رواناب حوضه آبخیز کارده بررسی شد و واکنش مدل به تغییر در پارامترهای آن با روش آنالیز حساسیت فراگیر ارزیابی گردید. واسنجی و تحلیل عدم‌قطعیت مدل با استفاده از آمار ماهانه رواناب خروجی حـوضه در بـازه زمانی 2006-2000 انجام و همچنین عملکرد مــدل در بـازه 2012-2008 اعتبارسنجی شد. بـا تـوجـه بـه مقادیر ضریب کارآیی نش- ساتکلیف در دوره­های واسنجی (64/0) و اعتبارسنجی (68/0)، مدل توسعه‌یافته SWAT کارآیی خوبی برای شبیه‌سازی جریان رودخانه کارده نشان داد. همچنین در دوره­های‌ واسنجی و اعتبار‌سنجی به ترتیب 68 و 93 درصد داده‌های مشاهداتی در باند عدم‌قطعیت تولید شده توسط الگوریتم GLUE قرار گرفتند. این نتایج ضمن تأیید نکویی برازش مدل به شرایط حوضه آبخیز سد کارده، نشان داد که بازه عدم‌قطعیت تولید شده در تحلیل اثر عدم‌ایستایی پارامترهای مدل بر رواناب شبیه­سازی شده می­تواند بخش وسیعی از سناریوهای محتمل آبی در حوضه مطالعاتی را در برگیرد. در نتیجه، با شناخت بازه آماری تغییرات قابل قبول پارمترهای حساس مدل و کمّی‌سازی اثر این تغییرات بر خروجی مدل توسط الگوریتم GLUE، قابلیت اجرایی مدل واسنجی شده SWAT در شرایط مختلف عدم­قطعیت در حوضه مطالعاتی تضمین می­گردد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Parameter Identification and Uncertainty Analysis of SWAT in Kardeh Streamflow Simulation

نویسندگان [English]

  • Halime SalimiRad 1
  • ABDOLHAMID DEHVARI 2
  • Hadi Galavi 3
  • MAHBOUBEH EBRAHIMIAN 4
1 Graduate, Department of Range and Watershed Management, Faculty of Water and Soil, University of Zabol, Zabol, Iran.
2 Assistant Professor, Department of Range and Watershed Management, Faculty of Water and Soil, University of Zabol, Zabol, Iran
3 Assistant Professor, Department of Water Engineering, Faculty of Water and Soil, University of Zabol, Zabol, Iran.
4 Assistant Professor, Hamoun International Wetland Research Institute, University of Zabol, Zabol, Iran
چکیده [English]

Distributed hydrological models have a large number of parameters in their structure. Such models produce different results using different sets of parameters’ value resulting in model uncertainty. This study, therefore, analyzes the model uncertainty induced by its parameters instability. The soil and water assessment tool (SWAT)—a powerful semi-distributed hydrological model—is employed here to simulate the Kardeh river flow, in Iran. The model parameter sensitivity was assessed using the global sensitivity analysis method; and the generalized likelihood uncertainty estimation (GLUE) technique was used for uncertainty analysis. GLUE performs the uncertainty analysis and calibration of the model through inverse modeling. Thus, observed streamflow data of 2000-2006 and 2008-2012 were respectively used at uncertainty-analysis/calibration and validation periods. Consulting the Nash-Sutcliffe efficiency coefficient values obtained in calibration (0.64) and validation (0.68) steps, the developed SWAT model showed good performance for simulating Kardeh river flow. The produced uncertainty band was also able to encompass 68 % and 93 % of the observations during calibration and validation steps, respectively. Results, while confirming the model goodness of fit, showed that the generated uncertainty interval by GLUE covers a large spectrum of the probable streamflow scenarios in the study area. Therefore, the model applicability in the study area is confirmed under different uncertainty scenarios and it can be applied for its river basin planning and management. Then, the calibrated model can be reliably forced by climate change scenario driven data to assess the hydrological impacts of climate change in the study area.

کلیدواژه‌ها [English]

  • Parameter Uncertainty
  • GLUE
  • Sensitivity analysis
  • Inverse modeling
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