جستجوی مقالات مرتبط با کلیدواژه "آلودگی شبکه آب" در نشریات گروه "آب و خاک"

Pollution entrance into water resources systems, such as urban drinking water distribution networks, can cause irreparable damage to human health as a result of the suction phenomenon.Awareness and understanding of pollutant sources and transport of contamination process in the water network cause suitable modeling of this phenomenon as well as perform a proper crisis management when the contaminants enter the network. In order to simulate the movement of nitrate in the soil, the nitrate advection-dispersion equation was programmed in MATLAB. Zahedan drinking water distribution network has been considered as the study area and potential points with high concentration of pollutants in the network have been identified. Scenario of 24-hour water network simulation, after two hours of contamination, was tested for water contamination by using WATERGEMS, EPANET and EPANET-BAM software., to manage the network pollution crisis, two tools were proposed including detention time and dilution flow. To calculate detention time, the network was divided into four parts including: near, middle, far and very far. The results demonstrated that nitrate concentration near the pipe is unallowable and greater than 50 mg/l and required detention time to treat the quality of water in the nodes of the middle, far and very far decreased 33 to 50, 58 to 62.5 and 75 percent compared to the near nodes, respectively. Moreover, efficiency and positive performance of dilution flow as a tool for quality management was proved. Required dilution flow to treat the quality water was determined from 10.6 to 15.9% of the base pipe flow.

Population growth and urbanization are the main reasons for increased pollution nowadays. Pollution entrance into urban drinking water distribution networks, can cause irreparable damage to human health as a result of the suction phenomenon. Awareness and understanding of pollutant sources and the process of contamination transport in the water network leads to advancements in the development of suitable modeling of this phenomenon, as well as, enabling proper crisis management, when the contaminants enter the network. In order to simulate the movement of nitrate in the soil, the nitrate advection-dispersion equation was programmed in MATLAB. The second zone of water distribution network of Zahedan has been considered as the study area and potential points with high concentration of pollutants in the network have been identified. Network simulation, after two hours of contamination, was tested for water contamination by using EPANET software. To manage the network pollution crisis, two water quality management tools were used in the distribution network, including polluted water discharging and dilution flow, then their results were compared in the crisis management. The results of simulating the movement of pollutants in the soil demonstrated that nitrate concentration near the pipe is unallowable and greater than 50 mg/l. The results of discharging of the polluted water showed that by closing pipes from 1.1 to 1.3 of the pollution injection time and also discharging water from 5 to 8% of the base pipe flow can prevent the pollution from entering   other parts of the network. Moreover, For the first time, efficiency and positive performance of dilution flow as another tool for quality management of water distribution network was proved. The Required dilution flow to treat the quality of water was determined to be approximately 16% of the base pipe flow. In order to manage the pollution crisis in the water distribution network, it is vital to use these valuable tools in different situations.

In order to detect pollutants in water distribution systems, sensors are used which, in addition to detecting pollution, also provide useful information to identify the source of pollutants. This information is useful for finding a suitable solution for quality management of the distribution network. The purpose of this study is to determine four characteristics of the pollution source to the system by a simulator-optimizer approach with optimally allocating two sensors in EPANET Example 2. These characteristics are: the contaminant injection node, injection mass rate, injection starting time and injection duration time. EPANET and genetic algorithm were linked as the simulator and optimizer tools to achieve these goals, simultaneously. For this purpose, first ten different pollution events were generated randomly, then the best place to install sensors in the network for identifying the source of pollution was found. Moreover, the shortest time of detection was selected among fourteen different combinations with a contamination source identification likelihood equal to 90%. The results showed that by placing sensors in two nodes 15 and 27 of the benchmark problem, the highest contamination source identification likelihood equal to 90% and the minimum detection time equal to 58 minutes were achieved.