SWAT model application through uncertainty assessment in a semiarid watershed, Iran
Publish Year: 1392
نوع سند: مقاله کنفرانسی
زبان: English
View: 1,529
This Paper With 10 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
PWSWM02_124
تاریخ نمایه سازی: 12 شهریور 1392
Abstract:
The use of hydrological distributed models to address water resource managementproblems has increased in recent years. Reasonable estimates of predictionuncertainty of hydrologic processes are valuable to water resources and otherrelevant decision making processes. Because of uncertainties associated withinput, model structure, parameter, and output, the model predictions are not acertain value, and should be represented with a confidence range. In this article theconceptual and semi-distributed Soil and Water Assessment Tool (SWAT) wasapplied for a semi-arid Nishabour watershed in Iran. Streamflow simulation isconsidered for 10 years period and Nishabour watershed modeling lead to 22subbasin and 146 Hydrologic Response Unit (HRU). SUfI2 approach was used forcalibration and uncertainty analysis of watershed modeling. Results showed thatcalibration and validation of the Nishabour watershed model are not verysatisfactory due to high conceptual model uncertainties such as dam structures,land subsidence and the complexity in hydrological system for arid regions.Furthermore, the results indicated that it is important to point out the importanceof evaluating the conceptual model uncertainty as well as the parameteruncertainty in hydrological watershed modeling.
Keywords:
Authors
فرهاد اکبرپور
PhD student, water engineering department, Collage of agriculture, Fredowsi University of Mashhad, Iran
مسعود صادق غضنفری مقدم
Associate Professor, water engineering department, Collage of agriculture, Fredowsi University of Mashhad, Iran
کامران داوری
Assistant Professor, Kerman Graduate University of Technology, Kerman, Iran.
حسین انصاری
Former MSc student, Water engineering department, Shahid Bahonar University of Kerman, Iran.
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :