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Developing a New Statistical Model to Estimate the River Quality Perspective From Macro Parameters in River Basins, Case Study: Siminehrood River Basin, Iran

Author(s): Farshid Bostanmaneshrad, Sadegh Partani, Roohollah Noori

Linked Author(s): Sadegh Partani

Keywords: Macro parameters, water quality, micro variable, river basin

Abstract: Prediction of micro chemicals through the macro parameters in river basin has led this research to find an estimation model to depict the micro water quality variables. The macro parameters include land use/land cover (LU/LC), erosion, geology and density which are significant factors that directly affect the river water quality. This research is carried out on one of the large rivers in Iran which terminates in Uremia Lake. 15 stations and three sampling periods for 9 National Sanitation Foundation (NSF) micro water quality variations are investigated. Four different statistical analyses that are carried out support both macro parameters and micro water quality variations of the study, where they have close conceptual and statistical relation with regard to primary screening. Then, a MLR model is applied to the micro water quality variables and macro parameters as dependent and independent variables, respectively. The results have demonstrated the significant relationship between land use and phosphorus, total solids, turbidity, erosion levels, electricity conductivity and solids. Discriminate analysis is applied to group ranging categories for prediction. Simple weighting is applied to groups of micro variables to calibrate the extracted model. Physical micro variables and phosphorus components are significantly related as dependent variables to LU/LC, erosion and geology. Biological Oxygen Demand and nitrate fluctuation are slightly affected by urban land use and population. The input data for extracted model is the macro parameters layer, while output data is the water quality prediction in downstream of the terminal of each reach where the discharge spot of submarine drain is located. New weighting and distance system employed in the model increase the outcome accuracy of the prediction. This model can be employed in river quality monitoring system. Online integrated estimation of water quality due to macro parameters monitoring as input data is recorded in the organization data bank. This study suggests that the inspection and monitoring, water operation administrators, etc. to focus more on polluted potential zones to make use of advanced data recoding sensors in new pattern of time step

DOI:

Year: 2017

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