بررسی عملکرد مدل اتوماتای سلولی در شبیه‌سازی سیلاب‌های شهری

افزایش فراوانی و شدت سیلاب‌ها در حوضه‌های شهری باعث ایجاد خسارات جدی به شهرها می‌شود. یکی از چالش‌های مهم در تحلیل سیلاب‌های شهری، شبیه‌سازی دو بعدی جریان‌های سطحی ناشی از پس‌زدگی رواناب از سیستم زهکشی است. بنابراین توسعه یک مدل شبیه‌سازی سیلاب که بتواند سیلاب را با دقت و سرعت قابل قبول در حوضه‌های شهری با توپوگرافی پیچیده شبیه‌سازی و بخش‌های متاثر از سیلاب را در این حوضه‌ها مشخص کند از اهمیت بالایی برخوردار است. در این تحقیق یک مدل عددی شبیه‌سازی سیلاب بر پایه روش اتوماتای سلولی با هدف کاهش زمان و حجم محاسبات نسبت به روش‌های معمول تحلیل دو بعدی سیلاب، توسعه داده شدهاست. عملکرد مدل اتوماتای سلولی توسعه داده شده در مطالعه حاضر با مدل‌های هک راس ، مدلی بر پایه معادلات آب کم عمق و مدل تیوفلو که با روش‌های معمول شبیه‌سازی هیدرولیکی جریان آب را روندیابی می‌کنند، در حالات شبیه‌سازی یک و دو بعدی مورد آزمون قرار گرفته است. همچنین شرایط پایداری با توجه به ابعاد شبکه و اندازه گام زمانی مورد بررسی قرار گرفته است. نتایج این مدل نشان می دهد که روش پیشنهادی با استفاده از داده‌های توپوگرافی و زبری سطح به عنوان ورودی، با دقت قابل قبول جریان روان‌آب‌های سطحی را در حالات یک بعدی و دو بعدی روندیابی می‌کند. همچنین زمان شبیه‌سازی جریان در این مدل حدود 60 برابر کمتر از روش معادلات آب کم عمق است.

Investigation of Cellular Automata Method to Urban Flood Modeling

Increasing frequency and intensity of flooding in urban areas have led to serious damage in urban areas. One of the major challenges in urban flood analysis is the two dimensional simulation of surface runoff caused by surcharged flows from urban drainage systems. Thus, development of an urban flood simulation model, which can rout the water flow on complex topography of urban catchments and determine flooded areas with acceptable computational time and accuracy is very important. In this study, a flood simulation model based on cellular automata approach is developed to reduce time and computational effort in compare with other 2D conventional hydraulic models. The developed model performance is compared with HECRAS, shallow water equation and TUFLOW models which simulate the water movement using conventional numerical schemes. Also the model’s stability is assessed by considering different time step and mesh size. The obtained results show that the proposed model, using topographic and surface roughness data as inputs, can simulate water movement with acceptable accuracy one and twodimensionally. In addition, the computational time is reduced up to roughly 60 times compared to the model which is based on shallow water equations. Increasing frequency and intensity of flooding in urban areas have led to serious damage in urban areas. One of the major challenges in urban flood analysis is the two dimensional simulation of surface runoff caused by surcharged flows from urban drainage systems. Thus, development of an urban flood simulation model, which can rout the water flow on complex topography of urban catchments and determine flooded areas with acceptable computational time and accuracy is very important. In this study, a flood simulation model based on cellular automata approach is developed to reduce time and computational effort in compare with other 2D conventional hydraulic models. The developed model performance is compared with HECRAS, shallow water equation and TUFLOW models which simulate the water movement using conventional numerical schemes. Also the model’s stability is assessed by considering different time step and mesh size. The obtained results show that the proposed model, using topographic and surface roughness data as inputs, can simulate water movement with acceptable accuracy one and twodimensionally. In addition, the computational time is reduced up to roughly 60 times compared to the model which is based on shallow water equations. Increasing frequency and intensity of flooding in urban areas have led to serious damage in urban areas. One of the major challenges in urban flood analysis is the two dimensional simulation of surface runoff caused by surcharged flows from urban drainage systems. Thus, development of an urban flood simulation model, which can rout the water flow on complex topography of urban catchments and determine flooded areas with acceptable computational time and accuracy is very important. In this study, a flood simulation model based on cellular automata approach is developed to reduce time and computational effort in compare with other 2D conventional hydraulic models. The developed model performance is compared with HECRAS, shallow water equation and TUFLOW models which simulate the water movement using conventional numerical schemes. Also the model’s stability is assessed by considering different time step and mesh size. The obtained results show that the proposed model, using topographic and surface roughness data as inputs, can simulate water movement with acceptable accuracy one and twodimensionally. In addition, the computational time is reduced up to roughly 60 times compared to the model which is based on shallow water equations. Increasing frequency and intensity of flooding in urban areas have led to serious damage in urban areas. One of the major challenges in urban flood analysis is the two dimensional simulation of surface runoff caused by surcharged flows from urban drainage systems. Thus, development of an urban flood simulation model, which can rout the water flow on complex topography of urban catchments and determine flooded areas with acceptable computational time and accuracy is very important. In this study, a flood simulation model based on cellular automata approach is developed to reduce time and computational effort in compare with other 2D conventional hydraulic models. The developed model performance is compared with HECRAS, shallow water equation and TUFLOW models which simulate the water movement using conventional numerical schemes. Also the model’s stability is assessed by considering different time step and mesh size. The obtained results show that the proposed model, using topographic and surface roughness data as inputs, can simulate water movement with acceptable accuracy one and twodimensionally. In addition, the computational time is reduced up to roughly 60 times compared to the model which is based on shallow water equations.