ارزیابی تاب‌آوری شبکه جمع‌آوری فاضلاب تحت اثر سیلاب احتمالی؛ رویکرد منحنی‌های جریمه (مطالعه موردی: شهر هندیجان)

امروزه، شبکه‌های جمع‌آوری فاضلاب به‌دلیل آسیب‌پذیری در برابر سیل، نقش کلیدی در جمع‌آوری، انتقال و دفع انواع فاضلاب با هدف جلوگیری از مشکلات آتی بهداشتی، محیط‌زیستی و اقتصادی دارد. در دهه‌های اخیر، محققین به‌دنبال راهکار‌هایی برای مقابله این شبکه‌ها با عدم‌قطعیت‌های احتمالی در زمان وقوع سیل بوده‌اند. ارزیابی تاب‌آوری و اجزای آن، یک راهکار مناسب برای کاهش آسیب‌پذیری و افزایش پایداری است. در این مقاله، تاب‌آوری با رویکرد جدید استفاده از منحنی‌های جریمه ارزیابی می‌شود. این رویکرد بر اساس منحنی عملکرد هیدرولیکی امکان بررسی جزءهای اصلی تاب‌آوری و درک بهتری از عملکرد و نقاط قوت و ضعف شبکه فاضلاب را در طی وقوع سیل به کاربر می‌دهد و میزان تاب‌آوری را نزدیک‌تر به واقعیت در فاز بهره‌برداری نشان می‌دهد. نتایج ارزیابی تاب‌آوری بیانگر این مورد است که وقوع سیل علیرغم آسیب کلی به عملکرد شبکه، ممکن است باعث افزایش عملکرد در ساعات ابتدایی و انتهایی رخداد نیز ‌شود. هم‌چنین برای در نظر گرفتن اهمیت شبکه آب سطحی در افزایش تاب‌آوری، علیرغم عدم وجود این شبکه در منطقه مورد مطالعه، شهر هندیجان، این شبکه به‌صورت فرضی با هدف جذب رواناب در نظر گرفته شد و میزان تاب‌آوری را به‌طور میانگین حدوداً 9.86% افزایش و میزان افت تاب‌آوری را حدوداً 17.3% کاهش داده است که می‌تواند یک زیرساخت شهری مناسب در برابر سیلاب ناگهانی باشد.

evaluating the resilience of the wastewater collection network under the effect of a possible flood: penalty curves approach (case study: hendijan city)

introductionnowadays, wastewater collection networks play a crucial role in the collection, transportation, and disposal of various types of wastewater, primarily because of their vulnerability to flooding and preventing future health, environmental, and economic problems. in recent decades, researchers have been exploring ways of dealing with the uncertainties associated with floods in these networks. an assessment of resilience and its components is an effective means of reducing vulnerability and increasing sustainability. this article presents an innovative approach to quantifying resilience based on penalty curves. this approach, based on the hydraulic performance curve, allows the user to explore the main components of resilience and better understanding of the performance, strengths and weaknesses of the sewer network during floods, showing the level of resilience closer to reality in the operation phase. despite the overall damage to the network’s performance caused by floods, the resilience assessment indicates that performance can be enhanced during the initial and final hours of floods. furthermore, considering the importance of surface water networks in increasing resilience, despite the lack of such a network in the case study, hendijan city, was hypothetically implemented for absorbing runoff. this network resulted in an average increase in resilience of approximately 9.86% and a decrease in resilience loss of approximately 17.3% on average, making it an appropriate urban infrastructure for flash floods.methodologyto assess the resilience of the wastewater collection network under the potential impact of floods, a resilience framework is employed. this model consists of three sub-models: hydraulic, hydrological, and resilience. the hydraulic sub-model pertains to the physical characteristics of the sewage network and the amount of generated wastewater. the hydrological sub-model is related to the characteristics of watershed sub-basins, precipitation patterns, and determines the amount of runoff generated by floods. finally, the resilience sub-model is created using specified relationships, utilizing the output of the hydraulic-hydrological model of the wastewater collection network and hydraulic performance indices based on flow velocity penalty curves and conduit filling percentage. in this framework, these sub-models are integrated to establish a comprehensive evaluation of wastewater collection network resilience to floods.results and discussionthe wastewater collection network has a critical line consisting of 26 sewage conduits, representing the highest combined flow of runoff resulting from both floods and generated wastewater. during a 24-hour simulation, these conduits exhibit the highest percentage of filling (h/d) and velocity (v). with an increase in the rainfall return period in each main scenario, the resilience decreases, and the resilience loss increases. in the 25-year and 50-year rainfall return periods, the reduction in resilience and the increase in resilience loss are less compared to the 5-year and 10-year rainfall return periods. this is because the input floods into the network mainly affect the time required to discharge these runoff flows. in the hydraulic performance curve, the robustness index, rapidity in response, and rapidity in recovery decrease with an increase in the rainfall return. however, the application of a storm water network as a resourcefulness index has a significant effect on improving other indices.conclusionin this article, the resilience of the wastewater collection network after the flood simulation was calculated using the critical performance curve. the area under this performance curve indicates the level of resilience. using the penalty curve method, the network’s performance was determined based on actual conditions, unlike other performance calculation equations that assume the ideal performance level (hpi=1) for the beginning of the simulation period. therefore, this method resulted in a lower error in resilience calculation and appears to be more realistic. furthermore, considering the resilience components that each cover a whole of the performance curve, a better understanding and clearer insight into the strengths and weaknesses of the network can be obtained. by identifying the hydraulic performance of the network at each moment, appropriate strategies can be implemented based on available resources and budget to enhance the network resilience. in this article, using a resourcefulness indice, in addition to the direct impact on robustness and rapidity indices, resilience increased by 9.86%, and resilience loss decreased by 17.3%, respectively. it was also observed that by using the penalty curve method, which calculates resilience based on the analysis of wastewater collection network flow, the occurrence of floods will always lead to a reduction in performance and a decrease in resilience throughout the simulation period.