Evaluating the Efficiency of the Surface Drainage Network and Nodes in Order to Contain Urban Runoff Using SWMM Software in the West of Tehran's Sixth District

Document Type : Research

Authors

1 Ph.D., Student in Watershed Science and Engineering, Kashan University

2 Professor, Faculty of Natural Resources and Earth Sciences, Kashan University

3 Associate Professor, Faculty of Natural Resources and Earth Sciences, Kashan University

Abstract

Introduction and Objective
Urban watersheds have become important due to the problems related to water resources management, including floods and pollution control. Therefore, the approach of engineers in recent years is toward computer software for estimating and simulating runoff. So far, many rainfall-runoff software with different capabilities and complexity have been developed and used for flood forecasting. The approach of the current research is to simulate the surface runoff and to identify the flood and critical nodes under the influence of climate change and to determine the efficiency of the surface drainage network in the west of six districts of Tehran municipality.
Materials and Methods
This research includes two parts of hydrology and water flow. In the hydrological department, after calculating the concentration time, in order to extract the rainfall intensity of the plan and to analyze the maximum rainfall for different durations of the base period (1980-2020), the near future period (2021-2050) and the far future (2051-2100) and preparing the IDF curve at different times and durations, based on the RCP2.6 and RCP8.5 scenarios, the Abkhezer-Qahraman method was used. In the water flow section, the assessment of the drainage network and flood control nodes in the western part of the six municipalities of Tehran in the base period (1980-2020) and under the influence of climate change (2021-2050), (2051-2100) in the RCP 2.6 and RCP8.5 scenarios for the period 25 and 50 year returns were made.
Results and Discussion
The results showed that the values ​​of rainfall intensity in the duration of rainfall and different return periods in all three scenarios have increased compared to the frequency intensity curve of the base period, and the maximum rainfall intensity has increased in the short-term time base, and with the passage of time, the maximum rainfall intensity has decreased. and IDF curves are affected by short-term rainfall. The results of the model calibration showed that there is a good agreement between the observed and simulated data in the simulation of water runoff in the five investigated rainfall events. The results of the sensitivity analysis showed that the impervious areas have the greatest impact on the change of peak water discharge. The results of the evaluation of flood nodes showed that, for example, the number of flood nodes in the base period (1980-2020) and under the influence of climate change in the RCP2.6 and RCP8.5 scenarios (2021-2050) for the 25-year return period are 7, 10, and 12, respectively. The number of flood nodes in the base period (1980-2020) and under the influence of climate change scenario RCP2.6 and RCP8.5 (2051-2100) for the return period of 50 years are 9, 14 and 17, respectively.
Conclusion and Suggestions 
The results of this research showed that the number of flood catchment nodes in the basin increased in the 25-year return period compared to the 50-year return period in each period. According to the identification of critical nodes in the research area, by applying modern methods of urban runoff control, such as creating permeable surfaces and gardens, absorption wells and reservoirs and storage ponds, the runoff can be controlled at the source to reduce the volume and peak water in the downstream, so that the probability of occurrence Minimize flooding and flooding. Since the percentage of impervious areas in the study area is high, it is recommended to increase the dimensions of the channels in terms of the passage of flood during rains and to have the ability to direct more amount of runoff and reduce the amount of peak flow of runoff in the location of super critical nodes.

Keywords


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