Evaluation Urban Drainage Network Using SWMM Model (Case Study: Shahrood City)

Document Type : Original Article

Authors

1 Master of Water Structure Engineering, Department of Water and Soil Engineering, Agriculture Collage, Shahrood University of Technology, Iran

2 Professor, Department of Water and Environmental Engineering, Civil Engineering Collage, Shahrood University of Technology

3 Associate Professor, Department of Applied Geology, Earth Sciences Collage, Kharazmi University, Iran

4 Soil And Water Department, Agricultrul Faculty, Shahrood University Of Technology

5 Assistant Professor, Department of Water and Soil, Agriculture Collage, Shahrood University of Technology, Iran

10.22125/iwe.2023.357737.1666

Abstract

The change of land use and the reduction of permeable surfaces due to urban development have caused an increase in the peak discharge and volume of runoff due to rainfall, which causes flooding of roads and damage to urban areas. By accurately estimating the amount of runoff and properly designing the urban drainage network, as well as managing this runoff, the damages of urban floods can be reduced. SWMM rainfall-runoff model is one of the most efficient models in the design of drains and urban runoff management. Since the hydrological models must be evaluated before use, in this study the SWMM model was evaluated using 6 rainfall-runoff events for the city of Shahrood and the efficiency of the urban drainage network for floods with return periods of 2 to 15 years was investigated. For this purpose, six flood hydrographs of precipitation events was measured at the two main outlets of the city. he results showed that the SWMM model with the mean square root of the normalized error (NRMSE) of about 20% and R2= 0.90 in the validation stage has a suitable efficiency in simulating the flood hydrograph. Also, also the examination of the performance of urban drains showed for precipitation with a return period of 2, 5, 10 and 15 years, 9.1, 31.8, 36.4 and 41% of the canals are flooded, respectively.

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