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Considering the significance of water quality for drinking, irrigation and industry, availability of accurate and sufficient water quality data is necessary and having enough data without proper interpretation is not helpful for water quality management decisions.
Hence, analysis of the existing data and prediction of future of water quality is vital. The current volume first defines the importance of water quality parameters regarding public health and irrigation. Secondly, the climatic situation and hydrological cycle of the area is considered for interpretation of the data.
Various methodologies such as Box-Jenkins time series analysis, water quality indices, artificial neural networks and principal component analysis are described and applied to actual data for different environmental conditions such as arid, semiarid and mountainous areas.
This book is a user manual for students and professionals involved in water quality planning and management.
Hence, analysis of the existing data and prediction of future of water quality is vital. The current volume first defines the importance of water quality parameters regarding public health and irrigation. Secondly, the climatic situation and hydrological cycle of the area is considered for interpretation of the data.
Various methodologies such as Box-Jenkins time series analysis, water quality indices, artificial neural networks and principal component analysis are described and applied to actual data for different environmental conditions such as arid, semiarid and mountainous areas.
This book is a user manual for students and professionals involved in water quality planning and management.