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Simulation and Qualitative Assessment of Traditional Qanats with Automatic Genetic Algorithms Calibration (case study: Zarch qanat

عنوان مقاله: Simulation and Qualitative Assessment of Traditional Qanats with Automatic Genetic Algorithms Calibration (case study: Zarch qanat
شناسه ملی مقاله: TKWRM01_206
منتشر شده در همایش بین المللی دانش سنتی مدیریت منابع آب در سال 1390
مشخصات نویسندگان مقاله:

sona hatami bahman beiglou - .Sc.Student, Irrigation and Drainage Engineering, Shahrekord University
mohammad sedighi - Expert of Engineers company
habibollah aalianvari - Expert of Engineers company

خلاصه مقاله:
Groundwater is a main source of water supply in arid and semiarid regions. Qanats are used in arid regions of Iran. Thus, more than ever, application of technical methods and solutions for water management and preservations of its quality has become an important issue. In this research, QUAL2Kw applied to simulate qualitative parameters of Zarch qanat water quality. One of the new software in this field is QUAL2Kw which is upgrade of the QUAL2k. QUAL2Kw model was used for simulation of water quality in qanat. The model based on genetic algorithms and automatically calculates the required coefficients. The model was calibrated automatically with results obtained from analysis of samples. Results showed that qanat and an open channel behave similarly. This model has a high capacity to simulate water flow in the aqueduct. Zarch qanat, located in Yazd Province, polluted by discharge of hospital sewage, was studied as a case. All hydraulic and some qualitative parameters were used to examine this model's potential for simulation. Data consist of NO3, COD, BOD, coli form and discharge and they were measured in 4 surveys.In this article zarch qanat self-purification percentage was calculated and according to automatic calibration and genetic algorithm, these parameters were simulated.

کلمات کلیدی:
Genetic algorithms, Zarch qanat, QUAL2Kw, Automatic calibration

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/136311/