عنوان مقاله [English]
A major part of the decision-making framework in the field of water resources management was dedicated to the development of quantitative-qualitative management models of river systems. In addition, river water quality control with economic approaches is an important part of quality management and environmental issues. Urban, industrial and agricultural wastewaters discharged into rivers with various pollutants are associated with adverse effects on the river ecosystem. These effluents increase the suspended solids in water and drastically reduce the dissolved oxygen in the water, thereby reducing or completely disrupting the possibility of river self-purification. Sustainable water quality management should be able to measure pollutants, predict the effects of pollutants on water quality, and determine the quality of water quality. Since the pollution and environmental problems of rivers have been higher in all countries, especially in industrialized and developed countries, a major part of the studies in the field of quality management of water resources has been devoted to the development of quantitative and qualitative management models of river systems. Accordingly, in this research, the management of the river system with the approach of pollution permit clearance will be studied. Moreover, considering the need for planning for the future, Iran is currently facing an environmental crisis, which doubles the importance of planning in the field of environmental protection. Today, most cities in Iran, including Khorramabad, face environmental pollution issues, including surface and underground pollution. The economic parameters resulting from the optimal utilization of the capacity to accept pollution of water resources systems and the reduction of pollution treatment costs are among the main objectives in the quality management of water resources. Optimal economic conditions in the quality management of river systems were considered between the pollution sources in the decision model. Therefore, in order to develop the decision framework, each source is assigned a permit to discharge the pollution. The trading theory provides incentives for pollution discharge sources in the sustainable river system and for technological initiatives to reduce wastewater discharge and reduce treatment costs. In this paper, a new structure for real-time pollution load in river quality management is presented so that while maintaining water quality at the desired level, the optimal trade model is presented and important uncertainties are considered.
The city of Khorramabad in Lorestan province, Iran is located at 48˚ 21” longitude and 30˚ 43” latitude with 35 km2 area and 1180 m height above sea level. Khorramabad city is considered as a semi-industrial city with 28% of all industries in Lorestan province. A large number of small and large industrial units are located around and near the Khorramabad River and along its route, which directly and indirectly cause its pollution. Some industries discharge wastewater directly into the river, while others discharge it into the river after incomplete treatment. In this paper, combined samples were prepared and analyzed from the pollutant of 9 important industries whose wastewater now enters the river (with or without treatment).
Simulation model was used to predict the behavior of the system which is divided into four stages. In the first step, the necessary information was collected and summarized to enter the calibration model. In the next step, the governing equations of the system are formulated by MATLAB programming. The model was calibrated and verified based on the collected information. Finally, it can be used to simulate the effects of different plans on the water allocation strategies.
In this study, the Trading-Ratio System (TRS) proposed by Hung and Shaw (2005) was used to trade pollution discharge permits. This system determines the TRS values by considering the rate of river self-purification and the pattern of pollutant distribution to present the optimal trade model with the application of genetic algorithm.
Uncertain simulation models make it possible to consider the probabilistic properties of some system variables (such as river discharge and pollution loads). One of the accurate methods of uncertain simulation of water resource systems is multiobjective optimization. In this method, an initial values are randomly generated for each variable and the system is established based on the non-dominated theory and genetic algorithm. The output of the proposed model is two extreme points that are obtained by maximization and minimization of the objective function.
Results of calibration showed that the simulated BOD values were acceptable. The rate of BOD exchange between pollutant sources showed that location, distance and flow rate were significantly important in BOD exchange. Industrial towns have not played an effective role in increasing BOD exchange due to pollution control. Point pollutant sources can affect the flow of pollution in a shorter time and more quickly. The developed ratio-trade model is able to determine the optimal amount of wastewater discharge according to the flow conditions and the amount of pollutants in the form of an optimization model. In addition, the application of the maximum and minimum uncertainty model predicted the probability of each event based on the possible domain. The results of this forecast can determine the maximum risk available for each strategy and give the choice to the decision model. The economic evaluation of wastewater treatment showed that in the proposed model, treatment costs will be reduced by at least 11%.
An important consequence of this study is the development of a decision model that can be used for other chemical contaminants as well. Future research can be developed in the form of a probabilistic prediction model to involve different river flow regimes in the decision-making process.
Keywords: Biochemical oxygen demand, treatment cost, water quality, river