عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Many variables such as volume and concentration of point and non-point pollutants, land use and geology, geometric and morphological characteristics, time and place of river sampling and etc., can affect the changes of water quality parameters in a river. Modeling is a suitable tool for managing water resources in terms of quantity and quality. Rivers are the most important water resources that can be used in arid and semi-arid regions. In recent years, quality management of rivers has become particularly important due to the discharge of various pollutants. The literature review shows that the Qual2kw model has a good ability to model the water quality parameters and evaluate the self-purification of the rivers. The objective of this research is to investigate the accuracy of Qual2kw model in simulation of the water quality parameters of Sefidrud river at the bottom of the dam. For this purpose, sampling and conducting field and laboratory studies for 12 stations in the range of 110 km in two summer (August) and autumn (November) seasons has been done. From 9 out of 12 sampling stations are located on the main tributary of the Sefidrud river and the other 3 stations are located on the tributaries of the Sefidrud, including Tutkabonrud, Tarikrud and Zilakirud. In addition to the water quality parameters such as temperature, pH, electrical conductivity, total suspended solids, dissolved oxygen, chemical and biochemical oxygen demand, total nitrogen, total phosphorus and fecal coliform, also the hydraulic characteristics of the flow such as depth, velocity and discharge were measured at these stations.
In this study, the Qual2kw model has been used to simulate the eight main parameters of the water quality including water temperature, pH, electrical conductivity, total suspended solids, soluble oxygen, biochemical oxygen demand, total nitrogen and total phosphorus. The hydraulic model was developed based on the Manning formula to simulate the flow characteristics including depth, velocity and discharge. The tributaries of the Sefidrud river (Tutkabon, Tarikrud and Zilakirud) were considered as sources of the pollutants in the model. The length of 110 km of the Sefidrud river between the dam and the Caspian Sea was divided into 70 unequal reaches in order to achieve more accurate results. The measured data on August and November 2019 are used to calibration and validation stages in the Qual2kw model, respectively. Auto calibration of the model was carried out by genetic algorithm after initial setup of the model. Three evaluation criteria including normalized root mean square error (NRMSE), mean bias error (MBE) and correlation coefficient (R) were used to measure and simulate the water quality parameters.
Due to the flow regulation in the Sefidrud river and its dependence on the amount of release from the dam, the maximum and minimum flow have been recorded in August and November 2019, respectively. The results of the flow’s hydraulic parameters indicate that the model is underestimate and overestimate in the minimum (November 2019) and maximum flows (August 2019), respectively. This is due to the additional withdrawals from the river in the high-flow and input runoff into the river in the low-flow conditions, which there is no accurate data for them. However, the values of depth, velocity and flow rate have been simulated with an acceptable accuracy in the calibration and validation steps. The results showed that the Qual2kw model was able to simulate the water quality parameters of Sefidrud river. The changes in quality parameters along the Sefidrud river indicate an improvement in water quality from the outlet of the Sefidrud dam to the entrance to the Caspian Sea. So that the amount of dissolved oxygen in Sefidrud river increases from upstream to downstream indicating the proper self-purification in the Sefidrud river. The results represented that the best and worse accuracy of the model in the base of average NRMSE values in calibration and validation stages are 3.3 and 47.5% for pH and total nitrogen parameters, respectively. The highest correlation values between the measured and simulated values for the parameters of total solids and electrical conductivity were equal to 0.97 and 0.96, respectively, in the model calibration stage. The results of the present study indicate the appropriate capability of the Qual2kw software in modeling the water quality parameters of the Sefidrud river. Generally, this study showed that by regulating the amount of flow released from the Sefidrud dam, the water quality parameters can be managed on river’s downstream. However, the changes in the quality parameters have many complexities and many factors may affect them.