Investigating the effectiveness of the SWMM model in simulating and evaluating the capacity of Kalat Naderi urban channels for the passage of flood flows

Document Type : Research Article

Authors

1 aMSc Graduate of Watershed Sciences and Engineering, Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Mashhad, Iran

2 Professor, Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Mashhad, Iran

3 phD in Watershed Sciences and Engineering, Rgional Water Company of Kalat-Nader, Razavi Khorasan Province, Iran

10.22067/geoeh.2023.82144.1357

Abstract

Urban development and industrialization, combined with the lack of proper drainage systems and the disorder of canals and channels, have had adverse effects on urban areas, leading to flooding of roads and inundation. This research, conducted in a region of Kalat city, aimed to analyze these issues. First, the physical characteristics of the area—such as area size, slope, equivalent width, percentage of impervious surfaces, and other parameters—were estimated. After determining the average water flow velocity, the concentration time of the study area was calculated based on the length of the largest waterway.
Using rainfall parameters such as intensity-duration-frequency (IDF) and the temporal and spatial distribution of rainfall, the SWMM (Storm Water Management Model) was simulated, sensitivity-analyzed, and evaluated for different return periods. Sensitivity analysis revealed that among the eight parameters analyzed, the percentage of impervious surfaces had the greatest effect on peak flow rate.
To calibrate and evaluate the model, five measured events were analyzed. Three events were used for calibration, where criteria such as Nash-Sutcliffe Efficiency (NS), Root Mean Square Error (RMSE), BIAS%, and Kling-Gupta Efficiency (KGE) were employed to assess performance. The calibration results indicated good agreement between simulated and observed runoff, with NS values greater than 0.5 for all three events.
For model evaluation, two additional events were analyzed using the same criteria. The RMSE values for the calibration simulations were 0.01, 0.003, and 0.01 cubic meters per second, respectively, while the RMSE values for the evaluation simulations were 0.04 and 0.04 cubic meters per second. These results demonstrate the model's acceptable performance.
The findings indicate a strong agreement between simulated and observed runoff, proving that the SWMM model has the required accuracy for urban runoff simulation. Thus, this model can be effectively used for urban runoff management plans and drainage network design. Additionally, it was determined that the upstream watershed of the study area, characterized by good permeability and a small size, supports channels with suitable dimensions for return periods ranging from 2 to 50 years.

Keywords

Main Subjects


Afshari Azad, M. R., & Pourkey, H. (2012). The Urban Morphology and Passages Flooding of Rasht City. Environmental Based Territorial Planing(Amayesh), 5(17), 25-40. [In Persian]
Ahmadzadeh, H., Saeedabadi, R., & Nouri, E. (2015). A Study and Zoning of the Areas Prone to Flooding with an Emphasis on Urban Floods (Case Study: City of Maku). Hydrogeomorphology2(2), 1-24. [In Persian] https://dorl.net/dor/20.1001.1.23833254.1394.2.2.1.0
Ainlou, F. (2014). The effect of land use change and urban development on runoff production (case study: Zanjan city). Master's thesis, Faculty of Natural Resources, University of Tehran. [In Persian]
Alizadeh, A. (2015). Principles of Applied Hydrology (40th ed.). Mashhad: Imam Reza University Press. [In Persian]
Arabi, M., Govindaraju, R. S., & Hantush, M. M. (2002). A probabilistic approach for analysis of uncertainty in the evaluation of watershed management practice. Journal of Hydrology, 333, 459–471. [In Persian] https://doi.org/10.1016/j.jhydrol.2006.09.012
Arman, N., Shahbazi, A., Faraji, M., & Dehdari, S. (2019). Effect of urban development on runoff generation by SWMM, case study: Khuzestan Province, Izeh, Watershed Engineering and Management, 11(3), 750-758. [In Persian] https://doi.org/10.22092/ijwmse.2018.115272.1353
Chen, J., Hill, A. A., & Urbano, L. D. (2009). A GIS-based model for urban flood inundation. Journal of Hydrology373(1-2), 184-192. https://doi.org/10.1016/j.jhydrol.2009.04.021
Choi, K. S., & Ball, J. E. (2002). Parameter estimation for urban runoff modelling. Urban Water, 4,31–41. http://dx.doi.org/10.1016/S1462-0758(01)00072-3
Dongquan, Z., Jining, C., Haozheng, W., Qingyuan, T., Shangbing, C., & Zheng, S. (2009). GIS-based urban rainfall-runoff modeling using an automatic catchment-discretization approach: a case study in Macau. Environmental Earth Sciences59, 465-472. https://doi.org/10.1007/s12665-009-0045-1
Fallah Zawareh, F., Kamali, B., & Mirzaei, M. (2013). Investigating the influence of rainfall time pattern in SWMM and HEC-HMS models. In Proceedings of the 6th National Congress On Civil Engineering, Semnan University, Semnan. [In Persian] https://civilica.com/doc/120602/
Ghanavati, E., Karam, A., & Aghaalikhani, M. (2013). Flood risk zonation in the farahzad basin (Tehran) using Fuzzy model. Geography and Environmental Planning23(4), 121-138. [In Persian] https://dorl.net/dor/20.1001.1.20085362.1391.23.4.8.2
Hejazizadeh, Z., Khosravi, F., & Naserzadeh, M. H. (2011). Crisis management in the new city of Baharestan by using geographic information system, relying on flood and determining suitable urban drainage routes for disposal of surface water. Applied Researches in Geographical Sciences, 11(20), 31-50. [In Persian] http://jgs.khu.ac.ir/article-1-594-fa.html
Huber, W. C., & Dickinson, R. E. (1992). Storm water management model user’s manual. Georgia: Environmental Protection Agency.
Istomina, M. N., Kocharyan, A. G., & Lebedeva, I. P. (2005). Floods: genesis. socioeconomic and environmental impacts. Water Resources, 32(4), 349–358. https://doi.org/10.1007/s11268-005-0045-9
Jinkang, D., Shunping, X., Youpeng, X., Xu, C. Y., & Singh, V. P. (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
Khorsandi Kouhanestani, Z., & Zolfaghary, M. (2016). An Investigation of the Effect of Pervious Surfaces Distribution on Flood Hydrograph Peak in Urban Regions. International Bulletin of Water Resources and Development, 4(1), 237-245. [In Persian]  https://www.magiran.com/p1549663
Lhomme, J., Bouvier, C., & Perrin, J. L. (2004). Applying a GIS-based geomorphological routing model in urban catchments. Journal of Hydrology, 299(3–4) ,203–216. https://doi.org/10.1016/j.jhydrol.2004.08.006
Lin, S. S., Hsieh, S. H., Kuo, J. T., Liao, Y. P., & Chen, Y. C. (2006). Integrating legacy components into a software system for storm sewer simulation. Environmental Modelling & Software21(8), 1129-1140. https://doi.org/10.1016/j.envsoft.2005.05.012
Ogden, F. L., Pradhan, N. R., Downer, C. W., & Zahner, J. A. (2011). Relative importance of impervious area, drainage density, width function, and subsurface storm drainage on flood runoff from an urbanized catchment. Water Resource Research, 47(12). https://doi.org/10.1029/2011WR010550
Paron, P., Di Baldassarre, G., & Shrodor, J. F. (2023). Hydro-Meteorological Hazards, Risks and Disaster. Elsivier. https://shop.elsevier.com/books/hydro-meteorological-hazards-risks-and-disasters/paron/978-0-12-819101-9
Phillips, B. C., Yu, S., Thompson, G. R., & De Silva, N. (2005). 1D and 2D modelling of urban drainage systems using XP-SWMM and TUFLOW. In 10th International Conference on Urban Drainage, Copenhagen, Denmark, 21-26.
Rostami Khalaj, M. (2012). Sensitivity analysis of variables affecting on urban flooding using SWMM model. Journal of Watershed Management Research, 3(5), 81-91. [In Persian] http://jwmr.sanru.ac.ir/article-1-56-fa.html
Santhi, C., Arnold, J. G., Williams, J. R., Dugas, W. A., Srinivasan, R., & Hauck, L. M. (2001). Validation of the SWAT model on a large river basin with point and nonpoint sources. JAWRA Journal of the American Water Resources Association37(5), 1169-1188. https://doi.org/10.1111/j.1752-1688.2001.tb03630.x
Shahbazi, A., Khaliqi Sygarodi, S., Malekian, A., & Salajegheh, A. (2014). Selection of the best empirical formula to estimate time of concentration in urban watersheds (Case study: Mahdasht town). Journal of Range and Watershed Managment67(3), 419-435. [In Persian] https://doi.org/10.22059/jrwm.2014.52835
Sheng, J., & Wilson, J. P. (2009). Watershed urbanization and changing flood behavior across the Los Angeles metropolitan region. Natural Hazards, 48, 41–57. https://doi.org/10.1007/s11069-008-9241-7
Soleimani, M., Behzadian, K., & Ardeshir, A. (2016). Evaluatiopn of Strategies for Modifying Urban Storm Water Drainage System Using Risk-based Criteria. Journal of Water and Wastewater26(6), 16-29. [In Persian] https://www.wwjournal.ir/article_11135.html
Sourisseau, S., Bassères, A., Périé, F., & Caquet, T. (2008). Calibration, validation and sensitivity analysis of an ecosystem model applied to artificial streams. Water research42(4-5), 1167-1181. https://doi.org/10.1016/j.watres.2007.08.039
Temprano, J., Arango, O., Cagiao, J., Suarez, J., & Tejero, I. (2006). Storm water quality calibration by SWMM: a case study in Northern Spain. Water SA, 32(1), 55–63. https://doi.org/10.4314/wsa.v32i1.5240
Tsihrintzis, V., & Hamid, R. (1998).  Runoff quality prediction from small urban catchments using SWMM. Hydrol Process, 12(2), 311–329. https://doi.org/10.1002/(SICI)1099-1085(199802)12:2%3C311::AID-HYP579%3E3.0.CO;2-R
Yarahmadi, Y., Yousefi, H., Jahangir, M. H., & Sadatineghad, S. J. (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 Ecohydrology6(2), 415-429. [In Persian] https://doi.org/10.22059/ije.2019.277930.1071
Zoppou, C. (2001). Review of urban storm water models. Environmental Modelling & Software, 16(3), 195
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