| تعداد نشریات | 286 |
| تعداد نشریات سازمان | 84 |
| تعداد شماره‌ها | 2,846 |
| تعداد مقالات | 32,300 |
| تعداد مشاهده مقاله | 41,386,891 |
| تعداد دریافت فایل اصل مقاله | 18,562,123 |
امکان‌سنجی کاربرد مفهوم سرعت مشخصه در برآورد دبی جریان در مقاطع مرکب | ||
| تحقیقات مهندسی سازه های آبیاری و زهکشی | ||
| دوره 24، شماره 91، آبان 1402، صفحه 1-21 اصل مقاله (1.21 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/idser.2023.363374.1553 | ||
| نویسندگان | ||
| زهرا قربانی1؛ عبدالرضا ظهیری* 2؛ حسین خلیلی شایان3؛ امیر احمد دهقانی2؛ خلیل قربانی2 | ||
| 1دانشجوی مقطع دکتری سازه‌های آبی، دانشکده مهندسی آب و خاک، دانشگاه علوم کشاورزی و منابع طبیعی گرگان | ||
| 2دانشیار گروه علوم و مهندسی آب، دانشکده مهندسی آب و خاک، دانشگاه علوم کشاورزی و منابع طبیعی گرگان. | ||
| 3دانش‌آموخته مقطع دکتری سازه‌های آبی، دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران | ||
| چکیده | ||
| تعیین دبی جریان در رودخانه ها از روش سرعت-سطح مقطع بهویژه تحت شرایط سیلابی، با چالش های جدی همراه است. یک روش جایگزین، استفاده از مفهوم سرعت مشخصه مبتنی بر تعمیم سرعت سطحی به سرعت متوسط و دبی جریان است. با توجه به اینکه کارایی روش سرعت مشخصه برای مقاطع مرکب هنوز ناشناخته می باشد، بنابراین طی پژوهش حاضر با تکیه بر برداشت های آزمایشگاهی، شاخص سرعت در مقاطع مرکب در شیب کف ثابت و به ازای عمق نسبی 0/3، 0/42 و 0/5، زبری نسبی 0/0031-0/0003 و عدد فرود 0/79-0/14 مطالعه شده است. نتایج نشان داد مقدار بهینه شاخص سرعت جهت برآورد دبی در کل مقطع مرکب با متوسط قدر مطلق خطای نسبی 3/3 درصد، 0/88 می باشد. همچنین شاخص سرعت در مقطع اصلی 0/92 و در سیلاب‌دشت 0/86 می باشد و در صورت استفاده از آن ها، برآورد بهتری از دبی در کانال های مرکب به دست می آید. همچنین نتایج نشان داد افزایش پارامترهای زبری نسبی و عدد فرود جریان و کاهش عمق نسبی، سبب کاهش شاخص سرعت می گردد. بررسی مدل های تحلیلی توزیع سرعت نیز نشان داد که قانون توانی سرعت با شاخص صحیح توانی نسبت به سایر مدلها برآورد بهتری از شاخص سرعت ارائه می دهد. | ||
| کلیدواژه‌ها | ||
| سرعت سطحی؛ شاخص سرعت؛ شرایط سیلابی؛ دبی جریان؛ کانال‌های مرکب | ||
| عنوان مقاله [English] | ||
| Feasibility of Applying the Concept of Index Velocity in Estimating Discharge in Compound Channels | ||
| نویسندگان [English] | ||
| Zahra Ghorbani1؛ abdolreza zahiri2؛ Hossein Khalili-Shayan3؛ amirahmad dehghani2؛ Khalil Ghorbani2 | ||
| 1Ph.D. Student of Water Structures, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran. | ||
| 2Associate Professor, Department of Water Science and Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran. | ||
| 3Ph.D. Graduated of Water Structures, Faculty of Agricultural Engineering and Technology, Tehran University, Tehran, Iran. | ||
| چکیده [English] | ||
| Extended Abstract Introduction Determining the discharge in rivers using the cross-sectional area-velocity method, especially under flood conditions, is associated with serious challenges. Due to advances in measurement techniques, many researchers have strongly suggested the use of non-contact methods. The non-contact method that use surface velocity radar to determine the discharge are becoming more and more popular especially in flood conditions. This method is to use the concept of index velocity based on the generalization of surface velocity to mean velocity and discharge. Also index-velocity method was used for discharge monitoring or recording at streamflow- gaging stations with flow reversals, backwater effects, hysteresis effects and channel-roughness changes that the use of conventional "stage-discharge rating" method impractical or impossible. During floods, natural rivers appear in the form of a compound cross-section in their middle and end sections. Due to momentum exchange between main channel and flood plains, the flow hydraulic in compound channels is complicate. Most studies in index-velocity method are focused on prediction of the discharge in simple channels. Due to the hydraulic difference between the flow of simple and compound cross-sections, the velocity index (ratio of surface velocity to average velocity) for compound channels is still unknown. Methodology The purpose of this study is how to apply the index velocity method in flood conditions (compound sections) and actually determine the optimal velocity index in compound sections and the highest percentage of its location in the width of the compound section. Also, by performing dimensional analysis, the influence of relative roughness parameters, Froude number, relative depth and relative width on the velocity index in compound channels was investigated. In order to build a laboratory compound channel, a channel with a rectangular cross-section with a width and height of 60 cm with a metal frame and glass walls was used. The height of the flood plain in all tests is constant and equal to 7 cm and three different widths of the flood plain 40, 45 and 50 cm in the smooth state and also one state of the flood plain with a width of 40 cm with metal mesh in compound form was made. Velocity distribution measurements were made in the compound channel, in the main channel and floodplain at 7 or 8 transverse points. In the present study, the velocity index in compound channels at a fixed bed slope of 0.1% and for the relative depth of the main section is 4.2-6.12 relative roughness 0.0003-0.0031 and Froude number 0.14-0.79 has been studied. Results and discussion By examining the velocity index values across the compound cross-section it was found that the range of average of the velocity index in the width of the compound channels is 0.76-0.98 and with 63% relative frequency is in the range of 0.87-0.93. By fitting between all surface velocity and average velocity data in the entire compound cross-section, it was determined that the optimal value of the velocity index (with R2=0.95) for compound channels is 0.88 with value of absolute relative error of about 0.01-10.06% and an average relative error of 3.3%. The results showed that the increase in the relative roughness and Froude number of the approaching flow and the decrease in the relative depth in the floodplain cause a decrease in the velocity index. The relative error values of discharge estimation showed that in flood conditions (overbank), the velocity index value is different from the normal conditions (inbank) of the river and considering the same velocity index value for both normal and flood conditions will cause more error in the discharge estimation. By examining the location of the optimal value of the velocity index of 0.88 in the entire width of the compound section, it was determined that 71% of the density of points is located on the border of the compound channel and in the last quarter of the flood plain and the first half of the main section. Also, the velocity index is 0.92 in the main channel and 0.86 in flood plain, and if use them, a better estimate of the discharge in the compound channel is obtained. Analytical models of velocity distribution also showed that the velocity power law provides the best estimation of the velocity index than other models if the power index is chosen correctly. Conclusion The results showed that the use of the velocity index value of 0.88 for compound channels has an average relative error of about 3.3% in flow estimation. Therefore, by adjusting the default value, it is possible to improve the accuracy of flow estimation in flood conditions. In situations where the possibility of direct measurement in open channels (flood conditions) is not available, it is possible to use the cross section, the surface velocity at the border of flood plain and the main channel and the optimal velocity index of 0.88 can be accurately estimated. | ||
| کلیدواژه‌ها [English] | ||
| Surface Velocity, Velocity Index, Flood Conditions, Flow Discharge, Compound Channels | ||
| مراجع | ||
|
Ackers, P. (1992). Hydraulic design of two-stage channels. J. Water Maritime Eng. 96, 247-257. Bahmanpouri, F., Barbetta, S., Gualtieri, C., Ianniruberto, M., Filizola, N., Termini, D. & Moramarco, T. (2022). Prediction of river discharges at confluences based on Entropy theory and surface-velocity measurements. Journal of Hydrology, 606, 127404. Bazargan, J. & Rajabi, M. (2020). Estimation of Discharge in Straight Compound Channels Based on the Equivalent Roughness Using the Particle Swarm Optimization Algorithm. J. of Iran-Water Resources Research, 15(4), 214-226 (In Persion). Biggs, H., Smart, G., Holwerda, N., Doyle, M., McDonald, M. & Ede, M. (2021). River discharge from surface velocity measurements - A field guide for selecting alpha. Envirolink Advice Report. Christchurch, New Zealand. Cao, L., Weitbrecht, V., Li, D. & Detert, M. (2021). Airborne feature maching velocimetry for surface flow measurements in rivers. Journal of Hydraulic Research, 59(4), 637-650. Chen, Y.C., Hsu, Y.C. & Zai, E.O. (2022). Streamflow Measurement Using Mean Surface Velocity. Water. 14(15), 2370. Chen, Y.C., Liao, Y.J. & Chen, W.L. (2018). Discharge estimation in lined irrigation channels by using surface velocity radar. Paddy Water Environ, 16, 857–866. Cipolla, S., Nones, M. & Maglionico, M. (2018). Estimation of flow discharge using water surface velocity in reclamation canals: a case study, Proc. of the 5th IAHR Europe Congress - New Challenges in Hydraulic Research and Engineering, Editor(s) Aronne Armanini and Elena Nucci. Costa, J. E., Cheng, R. T., Haeni, F. P., Melcher, N., Spicer, K. R., Hayes, E., Plant, W., Hayes, K., Teague, C. & Barrick, D. (2006). Use of radars to monitor stream discharge by noncontact methods. Water Resour. Res., 42, W07422. Creutin, J.D., Muste, M., Bradley, A.A., Kim, S.C. & Kruger, A. (2003). River gauging using PIV techniques: a proof of concept experiment on the Iowa River. Journal of Hydrology, 277(3-4), 182-194. Detert, M., Johnson, E. & Weitbrecht, V. (2017) Proof-of-concept for low-cost and non-contact synoptic airborne river flow measurements. International Journal of Remote Sensing, 38(8-10), 2780-2807. Fujita, I. (2017). Discharge measurements of snowmelt flood by space-time image velocimetry during the night using far-infrared camera. Water, 9(4), 269. Fujita, I. (2018). Principles of surface velocity gaugings. The 4th IAHR-WMO-IAHS Training Course on Stream Gauging. Fujita, I., Notoya, Y., Tani, K. & Tateguchi, S. (2019) Efficient and accurate estimation of water surface velocity in STIV. Environmental Fluid Mechanics, 19(5), 1363-1378. Fulton, J. W., Anderson, I. E., Chiu, C. L., Sommer, W., Adams, J. D., Moramarco, T., Bjerklie, D. M., Fulford, J. M., Sloan, J. L., Best, H. R., Conaway, J. S., Kang, M. J., Kohn, M. S., Nicotra, M. J. & Pulli, J. J. (2020a). QCam: SUAS-based Doppler radar for measuring river discharge. Remote Sensing, 12(20), 3317. Fulton, J. W., Mason, Ch. A., Eggleston, J. R., Nicotra, M. J., Chiu, Ch., Henneberg, M. F., Best, H. R., Cederberg, J. R., Holnbeck, S. R., Lotspeich, R. R., Laveau, Ch. D., Moramarco, T., Jones M. E., Gourley, J. J. & Wasielewski, D. (2020b). Near-Field Remote Sensing of Surface Velocity and River Discharge Using Radars and the Probability Concept at 10 U.S. Geological Survey Streamgages. Remote Sens, 12(8), 1296. Genç, O., Ardıçlıoglu, M. & Agıralioglu, N. (2015). Calculation of mean velocity and discharge using water surface velocity in small streams. Journal of Flow Measurement and Instrumentation, 41,115–120. Ghorbani, Z., Zahiri, A.R., Khalili Shayan, H., Dehghani, A.A. & Ghorbani, Kh. (2023). Experimental Investigation of Effective Factors on the Velocity Index for Calculating Discharge in Open Channels. Accepted in Iranian journal of irrigation and drainage, 5(17) (In Persion). Hauet, A., Morlot, Th. & Daubagnan, L. (2018). Velocity profile and depth-averaged to surface velocity in natural streams: A review over a large sample of rivers. E3S Web of Conferences 40, 06015, River Flow. Huang, Y., Chen, H., Liu, B., Huang, K., Wu, Z. & Yan, K. (2023). Radar Technology for River Flow Monitoring: Assessment of the Current Status and Future Challenges. Water, 15(10), 1904. Jodeau, M., Hauet, A., Paquier, A., Le Coz, J. & Dramais, G. (2008). Application and evaluation of LSPIV technique for the monitoring of river surface velocities in high flow conditions. Journal of Flow Measurement and Instrumentation, 19(2), 117–127. Kästner, K., Hoitink, A.J.F., Torfs, P.J.J.F., Vermuelen, B., Ningshi, N.S. & Pramulya, M. (2018). Prerequisities for accurate monitoring of river discharge based on fixed-location velocity measurements. Water resources research, 54(2), 1058-1076. Kim, Y., Muste, M., Hauet, A., Krajewski, W. F., Kruger, A. & Bradley, A. (2008). Stream discharge using mobile large‐scale particle image velocimetry: A proof of concept. Water Resources Research, 44(9). Kordi, E. (2005). Estimation of critical depth in open compound channel. Master's thesis on water structures, Mazandaran University (In Persian). Koutalakis, P. & Zaimes, G. N. (2022). River Flow Measurements Utilizing UAV-Based Surface Velocimetry and Bathymetry Coupled with Sonar. Hydrology, 9(8), 148. Le Coz, J. (2018). Discharge rating using the velocity index method. 4th IAHR‐WMO‐IAHS Training Course on Stream Gauging Lyon-Villeurbanne, France. 2 –4 September 2018. Le Coz, J., Duby, P., Dramais, G., Camenen, B., Laronne, J., Zamler, D. & Zolezzi, G. (2011). Use of emerging non-intrusive techniques for flood discharge measurements. 5th International Conference on Flood Management. Tokyo, Japan. Le Coz, J., Hauet, A., Pierrefeu, G., Dramais, G. & Camenen, B. (2010). Performance of image-based velocimetry (LSPIV) applied to flash-flood discharge measurements in Mediterranean rivers. Journal of hydrology, 394(1-2), 42-52. Legleiter, C.J., Kinzel, P.J. & Nelson, J.M. (2017). Remote measurement of river discharge using thermal particle image velocimetry (PIV) and various sources of bathymetric information. J. Hydrol., 554, 490–506. Levesque, V. A. & Oberg, K. A. (2012). Computing Discharge Using the Index Velocity Method; U.S. Geological Survey Techniques and Methods 3–A23, p. 148. Liu, B., Wang, Y., Xia, J., Quan, J. & Wang, J. (2021). Optimal water resources operation for rivers-connected lake under uncertainty. Journal of Hydrology, 595,125863. Moramarco, T., Barbetta, S., & Tarpanelli, A. (2017). From surface flow velocity measurements to discharge assessment by the entropy theory. Water, 9(2), 120. Morlock, S. E., Nguyen, H. T. & Ross, J. H. (2002). Feasibility of acoustic Doppler velocity meters for the production of discharge records from U.S. Geological Survey streamflow-gaging stations. Water-Resources Investigations Report (No. 2001-4157). US Department of the Interior, US Geological Survey. Muste, M., Cheng, Z., Hulme, J. & Vidmar, P. (2015). Considerations on discharge 783 estimation using index-velocity rating curves. Proceedings of the 35 IAHR World Congress, June 28– July 3-2015, Delft – The Hague, the Netherlands. Nash, J. E. & Sutcliffe, J. V. (1970). River Flow Forecasting Through Conceptual Models: Part I. A Discussion of Principles. Journal of Hydrology, 3(10), 282-290. Nelson, J. M., Kinzel, P. J., Legleiter, C. J., McDonald, R. R., Overstreet, B. & Conaway, J. S. (2017). Using remotely sensed data to estimate river characteristics including water-surface velocity and discharge. In 37th IAHR World Congress, Kuala Lumpur, Malaysia. Novak, G., Rak, G., Prešerena, T. & Bajcar, T. (2017). Non-intrusive measurements of shallow water discharge. Flow Meas. Instrum., 56, 14–17. Omori, Y., Fujita, I. & Watanabe, K. (2021). Application of an Entropic Method Coupled with STIV for Discharge Measurement in Actual Rivers. In IOP Conference Series: Earth and Environmental Science, (945)1, p. 012036. IOP Publishing. Patalano, A., García, C. & Rodríguez, A. (2017). Rectification of Image Velocity Results (RIVER): A simple and user-friendly toolbox for large scale water surface Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV). Computers and Geosciences, 109, 323-330. Peña-Haro, S., Carrel, M., Lüthi, B., Hansen, I. & Lukes, R. (2021). Robust image-based streamflow measurements for real-time continuous monitoring. Frontiers in Water, 3, 175. Perks, M. T. (2020). KLT-IV v1. 0: Image velocimetry software for use with fixed and mobile platforms. Geoscientific Model Development, 13(12), 6111-6130. Ran, Q. H., Li, W., Liao, Q., Tang, H. L. & Wang, M. Y. (2016). Application of an automated LSPIV system in a mountainous stream for continuous flood flow measurements. Hydrol. Process., 30(17), 3014–3029. Rantz, S. E. (1982). Measurement and computation of streamflow (Vol. 2175). US Department of the Interior, Geological Survey. Shiono, K. & Knight, D. W. (1991). Turbulent open-channel flows with variable depth across the channel. Journal of fluid mechanics, 222, 617-646. Smart, G. & Biggs, H. (2020). Remote gauging of open channel flow: Estimation of depth averaged velocity from surface velocity and turbulence. Proceedings of River Flow, Delft, Netherlands. Turnipseed, D. & Sauer, V. (2010). Discharge measurements at gaging stations (No. 3-A8). US Geological Survey. Weitbrecht, V., Kühn, G. & Jirka, G.H. (2002). Large scale PIV-measurements at the surface of shallow water flows. Journal of Flow Measurement and Instrumentation, 13(5-6), 237–245. Welber, M., Le Coz, J., Laronne, J.B., Zolezzi, G., Zamler, D., Dramais, G., Hauet, A. & Salvaro, M. (2016). Field assessment of noncontact stream gauging using portable surface velocity radars (SVR). Journal of Water Resources Research, (52), 1108–1126. Xia, C., Liu, G., Zhou, J., Meng, Y., Chen, K., Gu, P., Yang, M., Huang, X. & Mei, J. (2021). Revealing the impact of water conservancy projects and urbanization on hydrological cycle based on the distribution of hydrogen and oxygen isotopes in water. Environmental Science and Pollution Research, 28, 40160–40177. Yen, B.C. (1992). Hydraulic resistance in open channels. Channel flow resistance-Centennial of Manning's Formula 1-135. Zahiri, A. & Shabani, M. A. (2018). Modeling of stage-discharge relationship in compound channels using multi-stage gene expression programming. Iranian journal of Eco Hydrology, 5(1), 37-48. (In Persian). Zahiri, A.R. Salehi, M. & Ghorbani, Kh. (2015). Computation of the main channel and flood plains discharges using new methods of optimization. J. of Water and Soil Conservation, 22(1), 25-48 (In Persion). Zhang, J., Guo, L., Huang, T., Zhang, D., Deng, Z., Liu, L. & Yan, T. (2021). Hydro-environmental response to the inter-basin water resource development in the middle and lower Han River, China. Hydrology Research, 53(1), 141-155.
| ||
|
آمار تعداد مشاهده مقاله: 323 تعداد دریافت فایل اصل مقاله: 239 |
||