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Water quality management : assessment and interpretation

Author: Gholamreza Asadollahfardi
Publisher: Heidelberg : Springer, [2014] ©2015
Series: SpringerBriefs in water science and technology
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Asadollahfardi, Gholamreza.
Water Quality Management : Assessment and Interpretation.
Berlin, Heidelberg : Springer Berlin Heidelberg, ©2014
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Gholamreza Asadollahfardi
ISBN: 9783662447253 3662447258 366244724X 9783662447246
OCLC Number: 892623244
Description: 1 online resource (ix, 118 pages) : illustrations (some color).
Contents: Acknowledgments; Contents; 1 Introduction; Abstract; 1.1 Introduction; References; 2 Selection of Water Quality Monitoring Stations; Abstract; 2.1 Historical Background; 2.2 Sanders Method; 2.3 Multiple-Criteria Decision Making (MCDM) Method; 2.3.1 Making Dimensionless; 2.3.2 Assessment of Weighting (Wj) for Attributes; 2.4 Dynamic Programming Approach (DPA) Method; 2.4.1 The DPA Theory; 2.4.2 Normalization and Uniformization Procedure; 2.5 Application of Sanders Method; 2.5.1 Comment on the Application; References; 3 Water Quality Indices (WQI); Abstract; 3.1 Historical Background. 3.2 Summary of WQI Methods3.3 National Sanitation Foundation's Water Quality Index (NSFWQI) Method; 3.4 British Colombia Water Quality Index as (BCWQI) Method; 3.5 Application of NFSWQI Method, a Case Study: K0101r016Bn River (Iran); 3.6 Application of NSFWQI Method in Sefid-Rud River (Iran); 3.7 Application of BCWQI Method in Sefid-Rud River (Iran); 3.8 Comments on Application; References; 4 Time Series Modeling; Abstract; 4.1 Introduction; 4.2 Historical Background; 4.3 Time Series; 4.4 Forecast Error; 4.5 Box-Jenkins Methodology for Time Series Modeling. 4.6 Stationary and Non-stationary Time Series4.7 The Sample Autocorrelation and Partial Autocorrelation Functions; 4.8 Classification of Non-seasonal Time Series Models; 4.9 Guidelines for Choosing a Non-seasonal Models; 4.10 Seasonal Box-Jenkins Models; 4.11 Guidelines for Identification of Seasonal Models; 4.12 Diagnostic Checking; 4.13 Exponential Smoothing Methods; 4.13.1 Simple Exponential Smoothing; 4.14 Winter's Method; 4.15 One and Two-Parameter Double Exponential Smoothing; 4.16 Adaptive Control Procedures; 4.17 Application of Time Series. 4.17.1 A Case Study: Latian Dam Water Quality4.17.1.1 The Software; 4.17.1.2 Selected Models of Few Water Quality Parameters in Zir-e-Pol Station; Ca++; SO4 & hx2013; & hx2013; ; Acidity (pH); Total Dissolved Solid (TDS); 4.18 Summary; References; 5 Artificial Neural Network; Abstract; 5.1 Introduction; 5.2 Historical Background; 5.3 Artificial Neural Network Theory; 5.3.1 Theory of ANN; 5.3.2 Dynamic ANN Models; 5.3.3 Data Preparation; 5.3.4 Learning Rate; 5.3.5 Model Efficiency; 5.4 Application of Artificial Neural Network; 5.4.1 A Case Study: Zaribar Water Quality (Iran); 5.4.1.1 Comment.
Series Title: SpringerBriefs in water science and technology
Responsibility: Gholamreza Asadollahfardi.

Abstract:

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.

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