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Water Quality Monitoring and Management: Basis, Technology and Case Studies [Pehme köide]

(College of Information and Electrical Engineering, China Agricultural University, China), (College of Information, Guangdong Ocean University, Zhanjiang Guangdong, China)
  • Formaat: Paperback / softback, 368 pages, kõrgus x laius: 229x152 mm, kaal: 590 g
  • Ilmumisaeg: 12-Oct-2018
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128113308
  • ISBN-13: 9780128113301
Teised raamatud teemal:
Water Quality Monitoring and Management: Basis, Technology and Case StudiesSuurem pilt
  • Formaat: Paperback / softback, 368 pages, kõrgus x laius: 229x152 mm, kaal: 590 g
  • Ilmumisaeg: 12-Oct-2018
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128113308
  • ISBN-13: 9780128113301
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128113301.html
Märksõnad:

Water Quality Monitoring and Management: Basis, Technology and Case Studies presents recent innovations in operations management for water quality monitoring. It highlights the cost of using and choosing smart sensors with advanced engineering approaches that have been applied in water quality monitoring management, including area coverage planning and sequential scheduling. In parallel, the book covers newly introduced technologies like bulk data handling techniques, IoT of agriculture, and compliance with environmental considerations. Presented from a system engineering perspective, the book includes aspects on advanced optimization, system and platform, Wireless Sensor Network, selection of river water quality, groundwater quality detection, and more.

It will be an ideal resource for students, researchers and those working daily in agriculture who must maintain acceptable water quality.

  • Discusses field operations research and application in water science
  • Includes detection methods and case analysis for water quality management
  • Encompasses rivers, lakes, seas and groundwater
  • Covers water for agriculture, aquaculture, drinking and industrial uses
About the Author xiii
Preface xv
1 Sensors in Water Quality Monitoring
1.1 pH Measurement and Value
1(2)
1.1.1 pH and How to Measure It
1(1)
1.1.2 What Does the pH Value of a pH Measurement Mean?
1(1)
1.1.3 How Do I Measure the pH Value?
2(1)
1.2 ORP-Redox Potential Measurement for Water Quality
3(4)
1.2.1 What Is ORP?
3(2)
1.2.2 Measurement of ORP
5(1)
1.2.3 The Application of ORP
6(1)
1.3 Measuring Dissolved Oxygen
7(10)
1.3.1 What Is Dissolved Oxygen?
7(2)
1.3.2 Dissolved Oxygen Measurement Methods
9(8)
1.4 Measuring Turbidity, Total Suspended Solids, and Water Clarity
17(21)
1.4.1 What Are Total Suspended Solids?
17(1)
1.4.2 What Is Turbidity?
18(1)
1.4.3 What Is Water Clarity?
18(1)
1.4.4 Turbidity vs. Suspended Solids-What Is the Difference?
19(1)
1.4.5 Turbidity and Total Suspended Solids Measurement Methods
19(19)
1.5 The Basics of Chlorophyll Measurement
38(5)
1.5.1 What Is Chlorophyll?
38(1)
1.5.2 The Importance of Chlorophyll as a Water Quality Parameter
39(1)
1.5.3 Reasons to Measure Chlorophyll
39(1)
1.5.4 How Is Chlorophyll Measured?
40(3)
1.6 Blue-Green Algae Sensors
43(1)
1.6.1 What Is Blue-Green Algae?
43(1)
1.6.2 Methodology
43(1)
1.6.3 Calibration Considerations
44(1)
1.7 Conductivity Sensors
44(5)
1.7.1 Background
44(1)
1.7.2 Conductivity Definitions
45(1)
1.7.3 How Is Conductivity Measured?
46(3)
1.8 Ammonia
49(3)
1.8.1 What Is Ammonia?
49(1)
1.8.2 Ways to Measure Ammonia
49(3)
References
52(3)
2 Wireless Sensor Networks in Water Quality Monitoring
2.1 Introduction
55(17)
2.1.1 Background and Overview
55(2)
2.1.2 Water Quality Monitoring Parameters and Sensors
57(1)
2.1.3 Classification of WSNs for Water Quality Monitoring
58(4)
2.1.4 Research Issues
62(10)
2.2 Mainstream Technologies of WSN
72(18)
2.2.1 Medium Access Control
72(2)
2.2.2 Time Synchronization
74(2)
2.2.3 Wireless Networking Technologies
76(9)
2.2.4 System on Chip Technologies
85(5)
2.3 Applications of WSNs in Water Quality Monitoring
90(6)
2.3.1 WSN in Water Resource Protection
90(2)
2.3.2 WSNs in Sewage Treatment
92(1)
2.3.3 WSN in Aquaculture Water Management
93(3)
References
96(5)
3 System and Platform for Water Quality Monitoring
3.1 Design of System and Platform for Water Quality Monitoring
101(2)
3.1.1 Principles of System and Platform Design
101(1)
3.1.2 Modeling for System and Platform
101(1)
3.1.3 System Requirements Analysis
101(1)
3.1.4 Realizing a Water Quality Monitoring System
102(1)
3.2 Hardware Platform Design
103(2)
3.2.1 Power Supply and Ports
103(1)
3.2.2 Intelligent Water Sensors
103(1)
3.2.3 Information Transmission: Wireless Sensor Network
104(1)
3.2.4 Processor and Actuators
104(1)
3.3 Software System Development
105(2)
3.3.1 Software Structure and Workflow
105(1)
3.3.2 Structure of Database
106(1)
3.3.3 Model and Blocks Development
106(1)
3.3.4 Development of Human-Machine Interface
106(1)
3.3.5 Software Testing and Packaging
106(1)
3.4 Cases and Applications
107(5)
3.4.1 Wireless Aquaculture Monitoring System for River Crab (Yixing)
107(1)
3.4.2 Wireless Mariculture Monitoring System for Grouper (Laizhou)
108(1)
3.4.3 Urban Water Supply Monitoring System (Water Supply Station)
109(1)
3.4.4 Hydrological Monitoring Application (Lakes, Rivers, Coastal Waters)
110(1)
3.4.5 Wastewater Quality Monitoring System (Sewage Treatment Plant)
110(2)
References
112(1)
4 Water Quality Evaluation
4.1 Introduction to Water Quality Evaluation
113(9)
4.1.1 Theoretical Foundation
113(2)
4.1.2 Development History
115(2)
4.1.3 Research Issues in Water Quality Evaluation
117(5)
4.2 Water Quality Evaluation Methods
122(20)
4.2.1 Decision-Making Methods
122(5)
4.2.2 Index Evaluation Methods
127(2)
4.2.3 Artificial Intelligence Evaluation Methods
129(13)
4.3 Practical Water Evaluation Applications
142(14)
4.3.1 Application of Identification Index Method in River Water Quality Evaluation
142(2)
4.3.2 Application of Principal Component Analysis in the Evaluation of Rural Drinking Water Quality
144(9)
4.3.3 Application of Gray Relational Analysis in the Water Quality Evaluation of a Freshwater Aquaculture Pond
153(3)
References
156(3)
Further Reading
159(2)
5 Prediction of Water Quality
5.1 Introduction to Prediction
161(2)
5.1.1 Prediction Classification
162(1)
5.2 Mainstream Water Quality Technologies
163(10)
5.2.1 Mechanism Model
163(1)
5.2.2 Nonmechanism Models
163(10)
5.3 Typical Case Analysis
173(21)
5.3.1 Prediction of Dissolved Oxygen Content in River Crab Culture Based on Least-Squares Support Vector Regression Optimized by Improved Particle Swarm Optimization
173(9)
5.3.2 A Hybrid WA-CPSO-LSSVR Model for Dissolved Oxygen Content Prediction in Crab Culture
182(12)
References
194(5)
6 Water Quality Early Warnings
6.1 Introduction to Early Warning
199(1)
6.1.1 Warning Classification
199(1)
6.2 Technologies of Water Quality Warnings
200(3)
6.2.1 Wireless System
200(2)
6.2.2 Sensor System
202(1)
6.3 Direct Observation
203(1)
6.4 Early Warning System for River Basin
203(1)
6.5 Decision Support System
203(6)
6.5.1 Introduction to Support Systems
203(1)
6.5.2 Structure and Module
204(4)
6.5.3 Characteristics of Knowledge and Systematic Knowledge Base
208(1)
References
209(2)
7 Detection of River Water Quality
7.1 Introduction to River Water Quality
211(2)
7.1.1 Significance of River Water Quality Monitoring
211(1)
7.1.2 River Water Quality
212(1)
7.2 General Indicators for the Detection of River Water Quality
213(4)
7.2.1 Physical Parameters
213(1)
7.2.2 Chemical Parameters
213(4)
7.3 River Water Quality Detection Method
217(1)
7.4 Standards of River Water Detection
217(1)
References
218(3)
8 Water Quality Detection for Lakes
8.1 Detection Indicators
221(4)
8.1.1 Contaminant Indicators
221(2)
8.1.2 Noncontaminant Indicators
223(2)
8.2 Detection Methods and Processes
225(1)
8.3 Detection Standards
225(3)
8.3.1 Nemerow's Water Quality Indicator Standards
225(1)
8.3.2 Horton Water Quality Indicator Standards
226(1)
8.3.3 Brown Water Quality Indicator Standard
227(1)
8.3.4 Prati Water Quality Indicator Standards
227(1)
References
228(5)
9 Seawater Quality Detection
9.1 Introduction of Seawater Quality Detection
233(2)
9.2 Basic Index of Seawater Detection
235(3)
9.2.1 Physical Index
235(1)
9.2.2 Chemical Index
236(1)
9.2.3 Microbial Indexes
237(1)
9.3 Steps in Seawater Detection
238(5)
9.3.1 Collection
238(1)
9.3.2 Preservation
239(1)
9.3.3 Preprocessing
240(2)
9.3.4 Analysis
242(1)
9.3.5 Calculation
242(1)
9.3.6 Report
243(1)
9.4 Methods of Sea Water Detection
243(5)
9.4.1 Titration
243(2)
9.4.2 Gravimetric Analysis
245(1)
9.4.3 Spectroscopic Analysis
245(1)
9.4.4 Microbial Detection
246(1)
9.4.5 Radioactivity Analysis
246(1)
9.4.6 Electrochemical Analysis
247(1)
9.4.7 Chromatography
247(1)
References
248(1)
Further Reading
249(4)
10 Drinking Water Detection
10.1 Water-Quality Index
253(5)
10.1.1 Horton's Index
254(1)
10.1.2 Brown's Index
255(1)
10.1.3 Prati's Implicit Index of Pollution
256(1)
10.1.4 Dinius' Water-Quality Index
256(1)
10.1.5 Bhargava's Index
257(1)
10.1.6 A "Universal" Water-Quality Index
257(1)
10.2 Method of Drinking Water Detection
258(5)
10.2.1 Multiple-Tube Fermentation Technique
258(1)
10.2.2 Membrane Filter Technique
259(1)
10.2.3 Enzyme Substrate Method
260(1)
10.2.4 Ion Chromatography
261(1)
10.2.5 Gas Chromatography
262(1)
10.3 Standard of Drinking Water
263(3)
10.3.1 EPA Drinking Water Standards
263(1)
10.3.2 USP Pharmaceutical Water Standards
264(1)
10.3.3 Lab Animal Drinking Water
265(1)
References
266(3)
11 Groundwater Quality Detection
11.1 Introduction
269(2)
11.2 Detection Indices
271(4)
11.2.1 Regular Indices
271(4)
11.2.2 Nonregular Indices
275(1)
11.3 Detection Methods
275(6)
11.3.1 Electrode Method
275(2)
11.3.2 Gas Chromatography
277(1)
11.3.3 High Performance Liquid Chromatography
278(2)
11.3.4 Hydride Atomic Absorption Spectrophotometric Method
280(1)
11.4 Detection Steps
281(5)
11.4.1 Creation of Groundwater Quality Monitoring Wells
281(1)
11.4.2 Sampling of Groundwater
282(1)
11.4.3 Analysis of Groundwater Samples
283(2)
11.4.4 Determination of Groundwater Quality
285(1)
11.5 Detection Standards
286(11)
11.5.1 Standard for Groundwater Quality (China)
287(1)
11.5.2 National Water Quality Management Strategy: Guidelines for Groundwater Protection in Australia
287(5)
11.5.3 Groundwater Quality Standards in the United States
292(5)
References
297(6)
12 Water Quality Monitoring in Aquaculture
12.1 General Description
303(2)
12.2 Water Quality Parameters
305(10)
12.2.1 General Parameters
305(3)
12.2.2 Pathogenic Bacterium
308(2)
12.2.3 Toxic Heavy Metals
310(2)
12.2.4 Toxic Compounds
312(3)
12.3 Monitoring Method
315(3)
12.3.1 Physical Detection
316(1)
12.3.2 Reagent Reaction
316(1)
12.3.3 Electrode Reaction
317(1)
12.3.4 Optics Detection
317(1)
12.4 Detecting Steps
318(5)
12.4.1 Detection Theory
318(1)
12.4.2 Testing Instruments and Conditions
319(1)
12.4.3 Measurement and Calibration
320(3)
12.5 Normal Index and Standard
323(2)
12.5.1 Normal Water Quality Index
323(1)
12.5.2 Testing Standards and References
323(2)
References
325(4)
13 Detection of Industrial Water Quality
13.1 Overview of Industrial Water Quality Detection
329(1)
13.1.1 Introduction to Industrial Water Quality Detection
329(1)
13.1.2 Categories of Industrial Water Quality Detection Indexes
329(1)
13.2 General Index and Detection Methods
329(4)
13.2.1 Water Temperature
329(1)
13.2.2 pH Value
330(1)
13.2.3 Conductivity
331(1)
13.2.4 Dissolved Oxygen
331(1)
13.2.5 Turbidity
331(1)
13.2.6 Chroma
332(1)
13.2.7 Suspended Matter
332(1)
13.3 Pollution Indexes for the Detection of Industrial Water Quality and Detection Methods
333(7)
13.3.1 Biochemical Oxygen Demand
333(2)
13.3.2 Chemical Oxygen Demand
335(1)
13.3.3 Absorbance
336(1)
13.3.4 TOC
337(2)
13.3.5 Total Oxygen Demand
339(1)
13.4 Indexes of Pollution Composition for the Detection of Industrial Water Quality and the Methods Used
340(4)
13.4.1 Detection of Organics
340(2)
13.4.2 Detection of Inorganics
342(2)
13.5 Biological Pollution Index on the Detection of Industrial Water Quality
344(1)
13.5.1 Escherichia coli
344(1)
13.6 Automatic Detection System for Industrial Water Quality
344(3)
13.6.1 Introduction to Automatic Detection System for Industrial Water Quality
344(1)
13.6.2 Automatic Detection System for Industrial Water Quality Detection
345(1)
13.6.3 The Prospects for Automatic Detection System for Industrial Water Quality
346(1)
References
347(2)
Further Reading
349(2)
Index 351
Dr. Daoliang Li is Professor of Agricultural Engineering at China Agricultural University and Director of the National Innovation Center for Digital Fishery, Key Laboratory of Smart Farming for Aquatic Animal and Livestock, Ministry of Agricultural and Rural Affairs. He has held visiting positions at the University of California, Davis (USA), University of Bedfordshire (UK), Wageningen University (Netherlands), and IOSB Fraunhofer (Germany). He obtained his BA from Shandong Agricultural University and PhD from China Agricultural Universitys College of Engineering. Dr. Lis research has mainly focused on intelligent information processing, smart sensors/instruments, and robots for aquaculture and fish farming. He is the founder and editor-in-chief of Elseviers International Journal of Information Processing in Agriculture and has published 12 books, including Water Quality Monitoring and Management (Academic Press, 2018). S. Liu received his B.E. degree in the Department of Computer Science, Air Force Engineering University in 2002 and his M.E. degree in Faculty of Computer, Guangdong University of Technology in 2006. He is a Ph.D. student in the College of Information and Electric Engineering of China Agriculture University. He is a lecturer in the College of Information, Guangdong Ocean University, and he is a member of China Computer Federation. He primary research interests are intelligent information system of agriculture, artificial intelligence, software engineering, computational intelligence.