Using Statistical Methods for Water Quality Management Issues Problems and Solutions 1st Edition by Graham Mcbride ISBN 0471470163 9780471470168
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ISBN 10: 0471470163
ISBN 13: 9780471470168
Author: Graham Mcbride
STATISTICS IN PRACTICE
A practical exploration of alternative approaches to analyzing water-related environmental issues
Written by an experienced environmentalist and recognized expert in the field, this text is designed to help water resource managers and scientists to formulate, implement, and interpret more effective methods of water quality management.
After presenting the basic foundation for using statistical methods in water resource management, including the use of appropriate hypothesis test procedures and some rapid calculation procedures, the author offers a range of practical problems and solutions on environmental topics that often arise, but are not generally covered.
These include:
* Formulating water quality standards
* Determining compliance with standards
* MPNs and microbiology
* Water-related, human health risk modeling
* Trends, impacts, concordance, and detection limits
In order to promote awareness of alternative approaches to analyzing data, both frequentist and Bayesian, statistical methods are contrasted in terms of their applicability to various environmental issues. Each chapter ends with a number of set problems for which full answers are provided. The book also encourages discussion between technical staff and management before embarking on statistical studies.
Using Statistical Methods for Water Quality Management Issues Problems and Solutions 1st Edition Table of contents:
Chapter 1: Understanding Water Quality and Its Parameters
- Defining Water Quality: Chemical, Biological, and Physical Aspects
- Common Water Quality Parameters: pH, Dissolved Oxygen, Nutrients, Contaminants
- Water Quality Standards and Guidelines
- Overview of Water Bodies and the Impact of Pollution
Chapter 2: Statistical Concepts for Environmental Data Analysis
- Basics of Statistical Analysis
- Descriptive Statistics: Measures of Central Tendency, Dispersion, and Distribution
- Probability Distributions in Environmental Data
- Sampling Methods and Data Collection Techniques
- Dealing with Missing Data and Data Quality Issues
Chapter 3: Data Exploration and Preliminary Analysis for Water Quality
- Visualizing Water Quality Data: Graphs, Plots, and Charts
- Identifying Trends, Patterns, and Outliers
- Exploratory Data Analysis (EDA) Techniques for Water Quality Data
- Assessing the Normality of Data
- Transforming Data for Statistical Analysis
Chapter 4: Statistical Modelling for Water Quality Data
- Introduction to Statistical Modelling Techniques
- Linear and Nonlinear Models for Water Quality
- Regression Analysis: Predicting Water Quality Parameters
- Time Series Analysis: Assessing Temporal Variations in Water Quality
- Spatial Analysis: Modeling Variations Across Different Locations
Chapter 5: Multivariate Statistical Methods for Complex Water Quality Issues
- Introduction to Multivariate Statistics
- Principal Component Analysis (PCA) and Factor Analysis
- Cluster Analysis for Identifying Water Quality Groups or Trends
- Multivariate Regression Models for Predicting Water Quality
- Use of Multivariate Techniques in Environmental Impact Assessment
Chapter 6: Statistical Methods for Monitoring and Assessing Water Quality
- Sampling Design for Water Quality Monitoring Programs
- Statistical Techniques for Monitoring Water Quality Over Time
- Setting Up Control Charts and Statistical Process Control (SPC)
- Assessing the Effectiveness of Water Quality Management Programs
- Statistical Tests for Identifying Significant Changes in Water Quality
Chapter 7: Risk Assessment and Decision-Making in Water Quality Management
- The Role of Statistical Methods in Risk Assessment
- Estimating Health Risks from Pollutants in Water
- Decision-Making Models: Cost-Benefit and Risk-Benefit Analysis
- Integrating Statistical Findings into Water Quality Management Decisions
- Case Studies in Risk Assessment for Water Resources
Chapter 8: Solutions to Common Water Quality Problems Using Statistics
- Managing Nutrient Pollution and Eutrophication
- Addressing Heavy Metal Contamination in Water
- Solutions for Drinking Water Quality Issues
- Managing Water Quality in Agricultural Runoff
- Using Statistics to Address Industrial and Urban Water Quality Issues
Chapter 9: Advanced Topics and Emerging Techniques in Statistical Water Quality Management
- Bayesian Methods in Environmental Statistics
- Machine Learning and Artificial Intelligence in Water Quality Analysis
- The Role of Big Data in Water Quality Management
- Geostatistics and Remote Sensing in Water Quality Monitoring
- Future Directions for Statistical Methods in Water Quality
Chapter 10: Case Studies and Applications
- Case Study 1: Statistical Approaches to Managing River Water Quality
- Case Study 2: Applying Statistical Models in Groundwater Contamination
- Case Study 3: Water Quality Monitoring in Coastal Areas
- Case Study 4: Urban Water Quality Management Using Statistical Tools
- Lessons Learned and Best Practices from Real-World Applications
Conclusion: The Future of Statistical Methods in Water Quality Management
- Challenges in Managing Water Quality and Using Statistical Methods
- The Importance of Integrated Approaches in Water Quality Management
- Future Trends and Innovations in Statistical Applications for Environmental Management
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Graham Mcbride,Statistical Methods,Water Quality Management