Extended Abstract
Introduction
Today, climate change and the subsequent alteration in precipitation patterns have caused floods, which have overshadowed urban management. The financial and human losses caused by urban floods have significantly increased, and there are no signs of their reduction. Urban flooding occurs when the amount of precipitation exceeds the capacity of the drainage channel network, which lacks sufficient capacity. Two main factors contribute to the exacerbation of damage caused by urban floods. The first factor is population growth and the expansion of urbanization. The second factor is heavy rainfall caused by climate change, which plays an essential role in intensifying and accelerating the hydrological cycle, potentially altering the amount and frequency of precipitation. This factor impacts the probability of flooding, runoff volume, and peak flow. It is particularly pronounced in arid and semi-arid areas where rainfall is typically brief but intense. One critical urban infrastructure is the runoff collection network, which is subject to increased wear and tear due to the growth of impervious surfaces. Changes in rainfall patterns resulting from climate change have amplified the occurrence of urban floods, which makes essential the use of new approaches such as low-impact developments (LIDs).
Materials and methods
In this research, the runoff collection network of district 10 of Tehran Municipality was simulated, and its performance was evaluated under current and future conditions. This district is located in the relatively dense fabric of Tehran metropolis, has a population of 327,000 people, and covers an area of 807 hectares. The simulation and evaluation of the runoff collection network's performance, using the vulnerability and reliability indices, necessitate a precise model with detailed information. To accomplish this, SWMM version 5.1 software was used for simulating the runoff collection network. The study area was divided into 285 sub-catchments to allow for more detailed simulation of the sub-channels. Information such as slope, area, and the percentage of impervious space was incorporated into the catchment data using ArcMap software version 10.3.1. The sub-catchment width parameter was calculated by dividing the sub-catchment area by its greatest length, employing Q-GIS software, and then applied to the sub-catchments. The LARS-WG model was also employed to generate the micro-scale output of climate models exponentially. To simulate the network under current conditions, historical precipitation data from Mehrabad synoptic station was used. For simulating future conditions, precipitation data from the climate models presented in the sixth climate change report were employed. Among the climate model predictions, the scenario with the highest projected rainfall was chosen as the pessimistic scenario. Subsequently, low-impact development tools (LIDs) were employed to enhance the network's performance against climate change. Specifically, swale and permeable pavement, which are recognized as two of the most common and efficient LIDs, were selected and implemented under three different scenarios.
Results and Discussion
The runoff collection network of district 10 in Tehran municipality was simulated under current and future conditions using the SWMM hydraulic model. Initially, the SWMM simulation model was applied to the current rainfall conditions, considering various return periods. The results indicated that the total runoff volume for the 2, 5, and 10-year return periods was 45.9, 51.14, and 59.7 thousand cubic meters, respectively. This increase in runoff volume led to an increase in vulnerability from 10.4 to 12.2 percent and a decrease in reliability from 97.5 to 95.8 percent. In the second stage, the runoff collection network was simulated under future conditions using climate change data from the SWMM model. Previous studies' findings were used to determine the most suitable climate model for the sixth climate change report. The top 5 climate models were identified, and the model with the highest precipitation was selected as the pessimistic scenario. The simulation results for the network under future conditions revealed an increase in runoff volume, reaching 64.04 and 72.18 thousand cubic meters for the 5 and 10-year return periods, respectively. Consequently, the vulnerability index increased to 12.7 and 13.9 percent for the 5 and 10-year return periods, respectively. Meanwhile, the reliability index stood at 95.3 and 94.3 percent during the same return periods. Then, two low-impact development tools of swale and permeable pavement were selected to improve the network performance and were introduced to the pseudo-model under three scenarios. The results showed that after the use of LIDs, the total runoff volume decreased by an average of 10.5% in the first scenario, an average of 17% in the second scenario, and an average of 21% in the third scenario. This reduction in water flow volume caused the vulnerability index to decrease by 8.3% and the reliability index to increase by 98.9%.
Conclusion
In this research, the stormwater collection network of district 10 of Tehran Municipality was simulated using the SWMM software under current and future conditions. The network simulation under current conditions was based on the precipitation data from Mehrabad synoptic station, while the simulation under future conditions used precipitation data from climate model outputs of the sixth climate change report. After simulating both scenarios, the performance of the network was evaluated. The simulation results indicated that as the return period increased, the vulnerability index increased, while the reliability index decreased. The impact of LIDs on the network was further investigated through a re-simulation with LIDs incorporated under three scenarios. The results showed that the implementation of LIDs improved the network's performance, leading to a reduction in vulnerability and an increase in reliability. Furthermore, the results demonstrated that LIDs had better efficiency in improving the performance of the stormwater collection network under lower return periods. It is recommended that future studies use optimization methods to better implement these LID tools, aiming to reduce costs and enhance their effectiveness.