برآورد رواناب شهری به‌منظور تعیین نقاط سیل گرفتگی با استفاده از مدل SWMM در شهر ملایر

نوع مقاله : پژوهشی

نویسندگان

1 دانش‌آموخته‌ی کارشناسی ارشد آبخیزداری، دانشکده ی منابع‌طبیعی و محیط‌زیست، دانشگاه ملایر، ملایر، ایران

2 استادیار گروه مهندسی طبیعت، دانشکده ی منابع‌طبیعی و محیط‌زیست، دانشگاه ملایر، ملایر، ایران

چکیده

مقدمه و هدف
با توجه به حجم زیاد فعالیت‌های انسانی و تجاری یکی از مهم‌ترین اهداف زیرساخت‌ها، جمع‌آوری و انتقال رواناب­ های شهری، مهار سیلاب و جلوگیری از آب‌گرفتگی در شهرها است. به‌منظور برآورد صحیح رواناب و خصوصیات واحدهای آب‌شناخت و کانال‌ها به­ کارگیری مدل ­های مناسب آب‌شناختی و آبی مهم است. با توجه به اهمیت موضوع، این پژوهش با هدف برآورد رواناب شهری ملایر به‌منظور تعیین نقاط احتمالی سیل گرفتگی با استفاده از مدل مدیریت طوفان آب (SWMM) انجام شد.
مواد و روش‌ها
بر پایه‌ی گزارش‌های فنی موجود، ابتدا محدوده‌ی زیر آبخیز‌ها، گره‌ها و کانال‌های اصلی شهر تعیین شد. با استفاده از مدل رقومی ارتفاعی جهت جریان و شیب منطقه تعیین شد و 11 عدد زیر آبخیز شناسایی شد. همچنین با صرف‌نظر از اندازه‌ی ژرفای اولیه‌ی آب و سطح ماندابی 11 عدد گره تعیین شد. با استفاده از داده‌های بارش روزانه ایستگاه همدید ملایر در دوره‌ی آماری 2020- 1992، بارش نه‌ساعته با دوره‌ی بازگشت دو سال به­ عنوان بارش طرح محاسبه و وارد مدل شد. شکل هندسی کانال­ ها، مستطیل باز و از روش موج جنبشی برای روندیابی جریان در کانال ­ها استفاده شد. اندازه‌های بیشترین آب‌دهی عبوری کانال‌ها با استفاده از رابطه‌ی سطح مقطع جریان و سرعت جریان برای بارش طرح 9 ساعته با دوره‌ی بازگشت دو سال محاسبه شد. برای واسنجی مدل از متغیرهای درصد مناطق نفوذناپذیر، ذخیره‌ی چالابی و ضریب زبری مناطق نفوذناپذیر در بازه‌ی تغییر دامنه‌ی مجاز اصلاح استفاده شد. به‌منظور ارزیابی مدل از ضریب کارایی نش-ساتکلیف و ریشه‌ی میانگین مربعات خطا استفاده شد.
نتایج و بحث
نتایج نشان داد پس از بهینه‌سازی اندازه‌های متغیرها، ضریب کارایی نش-ساتکلیف و جذر میانگین مربعات خطا به‌ترتیب 0/73 و 0/02 بود. از کل بارش 14/54 میلی‌متری، اندازه‌ی 5/53 میلی‌متر مربوط به تلفات نفوذ، اندازه‌ی 7/55 میلی‌متر مربوط به رواناب سطحی و اندازه‌ی 1/45 میلی‌متر مربوط به ذخیره‌ی چالابی بود. نتایج نشان داد زیرآبخیز‌هایی که در شمال شهر و مشرف‌به بلندی‌ها بودند و به گره‌ی شماره‌ی 10 منتهی می‌شدند حجم و آب‌دهی رواناب بیش­تری داشتند و لازم است در این منطقه در طراحی و گسترش کانال‌ها تجدیدنظر شود. همچنین زیر آبخیز‌های بخش غربی شهر (زیر آبخیز شماره‌ی 4) و بخش جنوب‌غربی (زیر آبخیز شماره‌ی 8) با 0/651 و 0/547 به‌ترتیب بیش­ترین و کم‌ترین توان سیل‌خیزی را داشتند.
نتیجه‌گیری و پیشنهادها
در این پژوهش نتایج نشان داد تقریباً نیمی از شهر در رخداد بارش‌ها، تحت تأثیر خطرهای سیلاب قرار خواهند گرفت. ازاین‌رو شبکه‌ی زهکشی کنونی کارایی لازم برای تخلیه رواناب شهری در بخش شمال شهر را ندارند و تعیین ابعاد بهینه‌ی کانال‌ها ضروری است. به‌دلیل برف‌گیر بودن بلندی‌های شرقی منطقه‌ی مطالعه‌شده و با توجه به زمین شناسی آن پیشنهاد می‌شود از مدل‌هایی که توانایی محاسبه‌ی رواناب ناشی از ذوب برف را دارند در پژوهش‌های آتی استفاده شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Estimation of Urban Runoff for Determine Potential Flooding Points Using SWMM Model in Malayer City

نویسندگان [English]

  • Fatemeh Zandi 1
  • Mohammad Bashirgonbad 2
1 M.Sc. in Urban Watershed Management, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran
2 Assistant Professor, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran
چکیده [English]

Introduction and Goal
Due to the large volume of human and commercial activities, one of the most important goals of infrastructure is to collect and transfer urban runoff, control floods and prevent flooding in cities. To correctly estimate the runoff and characteristics of hydrological units and channels, it is important to use appropriate hydrological and water models. Considering the importance of this topic, this research was conducted with the aim of estimating the urban runoff of the Malayer to determine the potential flooding points using a storm water management model (SWMM).
Material and Methods
On the basis of available technical reports, the area of the sub-watersheds, nodes and main channels of the city were first determined. Flow direction and slope of the area was determined using a digital elevation model and 11 sub-watersheds were identified. In addition, 11 nodes were determined, regardless of the initial water depth and water level. Using the daily rainfall data of the Malayer synoptic station during the 1992–2020 statistical period, a nine-hour rainfall with a return period of 2 years was calculated and entered into the model. The geometrical shape of the channels was an open rectangle and the flow trend in the channels was determined using the kinetic wave method. The size of the maximum flow of water through the channels was calculated using the relationship between the cross-section of the flow and the speed of the flow a 9-hour the rainfall with a return period of 2 years. To calibrate the model, the variables of percentage of impervious areas, pond storage and roughness coefficient of impervious areas were used in the change range of the allowed modification range. In order to evaluate the model, Nash-Sutcliffe efficiency coefficient and the root mean square error were used.
Results and Discussion
The results showed that after optimizing the sizes of the variables, the Nash-Sutcliffe efficiency coefficient and the root mean square error were 0.73 and 0.02, respectively. Of the total rainfall of 14.54 mm, 5.53 mm was related to infiltration losses, 7.55 mm was related to surface runoff, and 1.45 mm was related to pond storage. The results showed that the sub-watersheds that were in the north of the city and overlooking the heights and leading to node number 10 had more volume and drainage and it is necessary to revise the design and expansion of the channels in this area. In addition, the sub-watersheds of the western part of the city (sub-watersheds no. 4) and the southwestern part (sub-watersheds no. 8) had the highest and lowest flood potential of 0.651 and 0.547, respectively.
Conclusion and Suggestion
In this research, the results showed that almost half of the city would be affected by flood risks in the event of rains. Therefore, the current drainage network does not have the necessary efficiency to discharge urban runoff in the northern part of the city, and it is necessary to determine the optimal dimensions of the channels. Because the eastern elevations of the studied area are snow-covered and considering the geology of the area, in future research, models capable of calculating the runoff caused by snow melting should be used.

کلیدواژه‌ها [English]

  • Calibration
  • Malayer city
  • modeling
  • SWMM
  • urban runoff

مراجع

Abkhezr H. 2004. Improvement in intensity-duration-frequency relationships of rainfall in Iran. Journal of Hydrology and Soil Science. 8(2):1-13. (In Persian).
Badiezadeh S, Bahremand A, Dehghani A. 2016. Urban flood management by simulation of surface runoff using SWMM model in Gorgan city Golestan Province- Iran. Journal of Water and Soil Conservation. 22(4):155­­­­­­-170. (In Persian).
Bai Y, Zhao N, Zhang R, Zeng X. 2018. Storm water management of low impact development in urban areas based on SWMM. Water (Switzerland). 11(1):1-16. https://doi.org/10.3390/w11010033.
Barco J, Wong M, Stenstrom K, Asce F. 2008. Automatic calibration of the U.S. EPA SWMM Model for a Large Urban Catchment. 135(12):1108­­­­­­-1110. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000016.
Barron OV, Pollock D, Dawes W. 2011. Evaluation of catchment contributing areas and storm runoff in flat terrain subject to urbanization. Hydrology and Earth System Sciences. 15(2):547-559. https://doi.org/10.5194/hess-15-547-2011.
Bates PD, De Roo APJ. 2000. A simple raster-based model for flood inundation simulation. Journal of Hydrology. 236(1):54–77. https://doi.org/10.1016/S0022-1694b (00)00278-X.
Bera D, Kumar P, Siddiqui A, Majumdar A. 2022. Assessing impact of urbanisation on surface runoff using vegetation-impervious surface-soil (V-I-S) fraction and NRCS curve number (CN) model. Modeling Earth Systems and Environment. 8(1):309-322. https://doi.org/10.1007/s40808-020-01079-z.
Bibi TS. 2022. Modeling urban stormwater management in the town of Dodola based on landuse and climate change using SWMM 5.1. Journal of Hydrology: Regional Studies 44:101267. https://doi.org/10.1016/j.ejrh.2022.101267.
Chen J, Hill A, Urbano LD. 2009. A GIS-based model for urban flood inundation. Journal of Hydrology. 373(1-2):184-192. https://doi.org/10.1016/j.jhydrol.2009.04.021.
Chithra SV, Harindranathannair M, Amarnath V, Anjana NS. 2015. Impacts of Impervious Surfaces on the Environment. International Journal of Engineering Science Invention. 4(5):27-31.
Du J, Xie S, Xu Y, yu Xu C, Singh VP. 2007. Development and testing of a simple physically-based distributed rainfall-runoff model for storm runoff simulation in humid forested basins. Journal of Hydrology. 336(3–4):334-346. https://doi.org/ 10.1016/j.jhydrol.2007.01.015.
Duan Q, Sorooshian S, Gupta VK. 1994. Optimal use of the SCE-UA global optimization method for calibrating watershed models. Journal of Hydrology. 158(3–4):265-284. https://doi.org/ 10.1016/0022-1694(94)90057-4.
Ebrahimzadeh Z, Malekian A, Mohsenmohseni M, Zarebidaki R. 2021. Determination of possible waterlogging points of drainage network of Fooladshahr city in urban flood. Ijwmse. 15(52):54-62. (In Persian).
Ellis JB, Viavattene C. 2014. Sustainable Urban Drainage System Modeling for Managing Urban Surface Water Flood Risk. CLEAN – Soil Air Water. 42(2):153-159. https://doi.org/10.1002/clen.201300225.
Emberger L. 1955. Une classification biogéographique des climats. Recueil, travaux de laboratoire géolo-zoologique, Faculté des sciences. Service botanique. Montpellier. 7(2): 3-43.
Ghimire B, Chen AS, Guidolin M, Keedwell EC, Djordjević S, Savić DA. 2013. Formulation of a fast 2D urban pluvial flood model using a cellular automata approach. Journal of Hydroinformatics. 15(3):676–686. https://doi.org/10.2166/hydro.2012.245.
Jiang L, Chen Y, Wang H. 2015. Urban flood simulation based on the SWMM model. Remote Sensing and GIS for Hydrology and Water Resources. 25(2):186-191. https://doi.org/10.5194/piahs-368-186-2015.
Khalighi Sigarodi S, Rostami Khalaj M, Mahdavi M, Salajegheh A. 2015. Calibration and validation SWMM model in order to simulate urban runoff (Case Study: Imam Ali Town in Mashhad). Journal of Range and Watershed Management. 68(3):487–498. (In Persian).
Luan Q, Fu X, Song C, Wang H, Liu J, Wang Y. 2017. Typical mountainous low-lying urban areas: A Case study in China. Water. 439(9):1-21. https://doi.org/10.3390/w9060439.
Ma B, Wu Z, Hu C, Wang H, Xu H, Yan D, Soomro S. 2022. Process-oriented SWMM real-time correction and urban flood dynamic simulation. Journal of Hydrology, 605:127269. https://doi.org/10.1016/j.jhydrol.2021.127269.
Mahdavi M. 2005. Applied Hydrology, 2nd Volume, University of Tehran Press. (In Persian).
McCuen RH, Johnson PA, Ragan RM. 1996. Highway hydrology: Hydraulic Design Series No. 2.
Mikovits C, Rauch W, Kleidorfer M. 2015. A dynamic urban development model designed for purposes in the fi eld of urban water management. Journal of Hydroinformatics. 17(3):390-403. https://doi.org/10.2166/hydro.2014.015
Miller D, Kim T, Kjeldsen R, Packman J, Grebby S, Dearden R. 2014. Assessing the impact of urbanization on storm runoff in a peri-urban catchment using historical change in impervious cover. Journal of Hydrology. 515:59-70. https://doi.org/ 10.1016/j.jhydrol.2014.04.011.
Moriasi D, Arnold N, Jeffrey G, Michael W, Van Liew R, Bingner R, Harmel T, Veith L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE. 50(3):885-900.
Paquet E, Garavaglia F, Garçon R, Gailhard J. 2013. The SCHADEX method: A semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology. 495(3):23–37. http://dx.doi.org/10.1016/j.jhydrol.2013.04.045.
Rabori MA, Ghazavi R. 2018. Urban flood estimation and evaluation of the performance of an urban drainage system in a semi-arid urban area using SWMM. Water Environment Research. 90(12):2075-2082.
Ress L, Hung C, James A. 2020. Impacts of urban drainage systems on stormwater hydrology: Rocky Branch Watershed, Columbia, South Carolina. Journal of Flood Risk Management. 13(3):1-13. https://doi.org/10.2175/106143017X.
Rezayi F, Bahremand A, Sheikh V, Dastorani M, Tajbakhsh M. 2019. Determination of the most important SWMM. Journal of Watershed Management Research. 9(18):135-145. (In Persian). https://doi.org/10.29252/jwmr.9.18.135.
Rossman L. 2007. Storm Water Management Model User’s Manual Version 5.0, Report No. EPA/600/R-05/040. U.S. EPA National Risk Management Research Laboratory, Cincinnati, OH. 295.
Sadeghi S, Valisamani J, Valisaman H. 2020. Analyzing of hydraulic performance and possible damage to existing storm sewer networks Tehran region 2 using SWMM model. Iranian Journal of Watershed Management Science and Engineering. 14(50):59-67. (In Persian).
Saltelli A, Tarantola S, Campolongo F. 2000. Sensitivity analysis as an ingredient of modeling. Statistical Science. 15(4):377-395. https://doi.org/10.1214/ss/1009213004.
Shahab M, Günther L, Jiri M, Maria V. 2018. Modeling urban runoff from rain-on-snow events with the U.S. EPA SWMM model for current and future climate scenarios. Journal of Cold Regions Engineering. 32(1):4017021. https://doi.org/ 10.1061/(ASCE)CR.1943-5495.0000147.
Shahbazi A, KhalighiSigarodi S, Malekian A, Salajegh A. 2017. Sensitivity analysis of input parameters of SWMM model to urban runoff management (Case study: Mahdasht Town). Watershed Management Research Journal. 30(1):67-75. (In Persian).
Silva C de M, Silva GBL da. 2020. Cumulative effect of the disconnection of impervious areas within residential lots on runoff generation and temporal patterns in a small urban area. Journal of Environmental Management. 253(5):109719. doi:https://doi.org/10.1016/j.jenvman.2019.109719.
Tajbakhsh M, Khodashenas SR. 2012. Revision of surface- runoff drainage system by simulation and application of retention basins (Case study: East Eghbal Catchment Mashhad). Water and Soil Science. 22(1):109-123. (In Persian).
Thi HL, Pathirana A, Thuc T. 2012. Facing multiple challenges: the future of flooding in Can Tho city. VNU Journal of Science, Earth Sciences. 28(2):84-91.
Thomas K, Thomas J, Donald DA. 1978. Methodology for calibrating stormwater models. Journal of the Environmental Engineering Division. 104(3):485-501. https://doi.org/10.1061/JEEGAV.0000772.
Tobio J, Maniquiz-Redillas L, Kim H. 2015. Optimization of the design of an urban runoff treatment system using stormwater management model (SWMM). Desalination and Water Treatment. 53(11):3134-3141. https://doi.org/10.1080/19443994.2014.922288.
USWEF-Water Environment Federation, Gravity Sanitary Sewer Design and Construction. 1982. 275p.
Vakilitajareh A, Salajegheh A, Nazari Samani A, Malekian A, Shahbazi K. 2020. The impact of urban development and land use changes on runoff production in Abshouran Watershed. Iranian Journal of Watershed Management Science and Engineering. 14(51):20-30. (In Persian).
Xu H, Wang Y, Fu X, Wang D, Luan Q. 2023. Urban flood modeling and risk assessment with limited observation data: The Beijing Future Science City of China. International Journal of Environmental Research and Public Health. 20(5):4640. https://doi.org/10.3390/ijerph20054640
Yarahmadi Y, Yousefi H, Jahangir MH, Sadatineghad SJ. 2019. Evaluation of the network performance of surface water collection and guidance using the SWMM Hydrological Model (Case study: District 6 of Tehran Municipality). Iranian Journal of Ecohydrology. 6(2):415-429. (In Persian).
Zakizadeh F, Moghaddam Nia A, Salajegheh A, Fontaneda S, Alamdari N. 2022. Efficient urban runoff quantity and quality modelling using SWMM model and field data in an urban watershed of Tehran Metropolis. Sustainability (Switzerland). 14(3): 1086. https://doi.org/10.3390/su14031086.
Zhang Q, Tang Q, Knowles JF, Livneh B. 2019. Contribution of model parameter uncertainty to future hydrological projections. Hydrology Earth System Science Discussions. 85(3): 1–31. https://doi.org/10.5194/hess-2019-52.

فایل ها

سابقه مقاله

  • تاریخ دریافت: 09 بهمن 1401
  • تاریخ بازنگری: 03 فروردین 1402
  • تاریخ پذیرش: 31 خرداد 1402

هم رسانی

ارجاع به این مقاله

آمار