Feasibility Study of Anzali Wetland Quality Monitoring Using Remote Sensing

Document Type : Research Paper


1 Water Engineering, Agricultural Sciences Faculty, University of Guilan

2 Assistance professor, Water Engineering Department, University of Guilan, Rasht, Iran

3 Water Engineering Department, Agricultural Sciences Faculty, University of Guilan


The need for good quality water resources, in line with population growth and the diversity and multiplicity of pollutants and contaminants dictate the quantitative and qualitative management of water resources. In this regard, water resources monitoring and the real time availability of spatial and temporal information can play an important role in water resources management. Real time remote sensing technology using satellite images with proper accuracy is able to determine some of the qualitative parameters of water affecting the temperature or spectrum of light from the surface of the water. The aim of this study was to investigate the accuracy of water quality monitoring of Anzali wetland using remote sensing. For this purpose, after field study of Anzali wetland and rivers leading to it, suitable sites for sampling were selected. After selection of suitable points for sampling, in order to increase the accuracy of the regression models, satellite images were used in different seasons of the year (November, 2002, February, 2002, May 2003 and August 2003). During the satellite (landsat 7 and 8) passing above the area, samplings were done and the quality parameters including nitrate, ammonium, soluble phosphorus, total dissolved solids, suspended solids, conductivity and acidity were measured. After extracting satellite images and their reflections, the effective bands on water quality values were determine and regression models of the images were obtained. The results showed that the use of remote sensing technique in Anzali wetland could be able to estimate the acidity, total suspended solids and temperature well (with root mean percentage of normalized error less than 10%). Other qualitative parameters including nitrate, salinity, total soluble solids and ammonium (with root mean of normalized error less than 30%) and orthophosphate (with root mean percentage of normalized error greater than 30%) were estimated fairly and poorly, respectively. Therefore, the remote sensing technique is able to estimate most of the qualitative parameters with acceptable accuracy. Surely increasing the number of sampling points and frequencies, the accuracy of regression models and consequently the accuracy of estimation of qualitative parameters will increase.


Main Subjects

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