ارزیابی تاثیر عمق و سرعت جریان بر نتایج دانه ‌بندی و شکل ذرات رسوبات سطحی بستر رودخانه‌های شنی با استفاده از روش پردازش تصویر

در بررسی رفتار رودخانه‌ها یک چالش مهم، تعیین دقیق ابعاد هندسی زبری بستر رودخانه‌هاست. پردازش تصویر روش جدیدی است که به منظور افزایش سرعت و دقت مورد توجه قرار گرفته است. در این تحقیق تاثیر عمق و سرعت جریان بر نتایج دانه‌بندی و شکل ذرات رسوبات سطحی بستر رودخانه‌های شنی با استفاده از پردازش تصویر ارزیابی گردید. سه مقطع جهت نمونه‌برداری با ابعاد قاب 20×20 سانتی‌متر از بستر رودخانه زنجانرود تعیین و پس از عکس‌برداری از سطح رسوبات، رسوبات نمونه‌ها جمع‌آوری و با روش الک دانه‌بندی شد. در آزمایشگاه، نمونه‌ها داخل قاب فلزی با همان ابعاد چیده در کانالی به طول 8 متر و عرض 20 سانتی‌متر نصب شد. با اعمال شرایط آب ساکن و جریان آب با عمق و سرعت‌های مختلف، عکس‌برداری مجدد از نمونه‌ها صورت و نتایج توسط نرم‌افزار image j و hydraulic toolbox پردازش گردید. مقایسه نتایج منحنی‌های دانه‌بندی دو نرم‌افزار نشان‌دهنده عملکرد بهتر نرم‌افزار image j در مقایسه با نرم‌افزار hydraulic toolbox می‌باشد. مطابق نتایج، عمق و سرعت جریان تاثیر محسوسی روی نسبت مقادیر قطرهای شاخص منحنی الک به قطرهای شاخص حاصل از نرم‌افزار image j (ضریب k) ندارد، بطوریکه میانگین k در قطر شاخص 50% در سه نمونه a، b و c به ترتیب برابر با 1.046، 1.16 و 1.1 بدست آمد. نتایج فاکتور شکل نشان داد از دید قائم، در نمونه a 88% ذرات مستطیلی و 12% ذرات، بیضی شکل هستند. در نمونه b 78% ذرات مستطیلی و 22% ذرات بیضوی و در نمونه c 80% ذرات مستطیلی و 20% ذرات، بیضی شکل هستند.

evaluation the effect of depth and flow velocity on the particle size and shape of surface sediments of sandy rivers using image processing methods

one of the important challenges in investigating the hydraulic, morphological and ecological behavior of rivers is to accurately determine the geometrical dimensions of river bed particles. the information extracted from the grain size curve of river bed particles has many applications in the field of river engineering, such as modeling of sediment transport, changes in sediment deposition or river bed erosion, and changes in river morphology (hasannejad sharifi et al., 2015).nowadays, despite the fact that determining the granularity of the bed particles and the boundaries of rivers is important, the removal of sediments from the natural environment leads to disturbing the sedimentary bed and causes changes in the river system (sadeghi and qara mahmoudoli, 2013). therefore, it is very important to use a method that can calculate the results of granulation with less cost and quickly. image processing methods are known as new method have been taken into consideration in order to increase rapidity and accuracy, along with the method of field measurement of granularity.methodology: in this research, by examining the morphological and sedimentary conditions of the rivers of the zanjan province, as well as the ease of access, zanjanrud river was selected as the study area. then three cross-sections for sampling with frame dimensions of 20×20 cm were determined from the bed of zanjanrud river and after photographing the surface of the samples, painting by spray paint in order to identify the surface grains, sampling was done from the determined sections. the samples were taken to the laboratory and the sieve test was performed. then, in the laboratory environment, each of the samples was arranged in a metal frame with dimensions of 20×20 cm and was installed in a channel with a length of 8 meters and a width of 20 cm. by applying the conditions of stagnant water at three depths of 4, 8 and 12 cm and water flow with different depths and velocities, the samples were re-photographed and the grain size curve were obtained by image j and hydraulic toolbox softwares.results and discussion: based on the results of sieve, in sample a, almost 85% of the particles have a diameter equal to and less than 31.7 mm. in sample b, almost 85% of the particles passed through the sieve of 1.38 mm. in sample c, more than 97% of the particles passed through the 38.1 mm sieve. according to the classification system of the united states, the sediments of all three sections of zanjanrud are gravel. also, according to the results, it can be seen that the standard deviation of the samples is less than 2, the uniformity coefficient is less than 4, and the sorting coefficient is less than 2, which shows that the examined samples are almost uniform. in sample a, atdepth of 8 cm, the average relative absolute error values were obtained similar to those at depth of 4 cm. in sample b, the average error value of the fine grains is the same coarse-grain.