Resilience, response, and risk in water systems : shifting management and natural forcings paradigms
著者
書誌事項
Resilience, response, and risk in water systems : shifting management and natural forcings paradigms
(Springer transactions in civil and environmental engineering)
Springer, c2020
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references
収録内容
- Intro
- Foreword by Dr. Virendra M. Tiwari
- Acknowledgements
- Contents
- Editors and Contributors
- Part I Risk Management and Data Science (Engineering) for Water Supply
- 1 History, Evolution, and Future of Rapid Environmental Assays Used to Evaluate Water Quality and Ecosystem Health
- 1.1 Introduction
- 1.2 Background and Theory of Immunoassays
- 1.3 History
- 1.4 Accreditation/Validation of Environmental Rapid/Field Tests
- 1.5 Current and Future Directions in Rapid Screening Methods
- 1.6 Summary and Conclusion
- References
- 2 Development of Operational Resilience Metrics for Water Distribution Systems
- 2.1 Water Distribution Networks
- 2.1.1 Disruption in Water Distribution Networks
- 2.2 Nodal-Level Performance of Water Distribution Networks
- 2.2.1 Head Ratio
- 2.2.2 Flow Ratio
- 2.3 Case Studies
- 2.3.1 Effect of Disruptions on Performance Measures
- 2.3.2 Sensitivity Analysis
- 2.4 Conclusion
- References
- 3 An Overview of Big Data Analytics: A State-of-the-Art Platform for Water Resources Management
- 3.1 Introduction
- 3.2 Big Water Data and Associated Characteristics
- 3.3 Big Data Analytical Methods
- 3.4 Big Data and Water Resources Management
- 3.4.1 Types of Water Data and Data-Sharing Methodologies
- 3.4.2 Appositeness of Big Data to Water Resources
- 3.4.3 Limitations of the Big Water Data Analytics
- 3.5 Big Water Data Platform Components and Structure
- 3.6 Modern Big Data Cycle in the Context of Water Resources
- 3.7 Future Perspectives of Big Data for Water Resources Management
- 3.8 Conclusion
- References
- 4 Role of Physical Parameters in Developing a Geogenic Contaminant Risk Approach
- 4.1 Introduction
- 4.2 Parameters Impacting the Water Quality-Mode of Acquisition and Assessment
- 4.2.1 Method of Integrating Multiparameter Data into a Common Index
- 4.3 Potential of Satellite Imageries in Developing an Ensemble
- 4.4 Understanding the Geogenic Impact and Sediment Connectivity on Water Quality
- 4.5 Conclusion
- References
- 5 Water Indices: Specification, Criteria, and Applications-A Case Study
- 5.1 Introduction
- 5.1.1 Categories of WQI (Tirkey et al. 2013)
- 5.1.2 Steps in Developing Water Quality Index (Sutadian et al. 2016, 2017)
- 5.1.3 Benefits of Application of WQIs
- 5.2 Overview of WQIs and Its Applications
- 5.2.1 Advantages and Disadvantages of Some Selected Water Quality Indices
- 5.2.2 Applications of Water Quality Indices in Groundwater Quality Assessment of Anuppur District of Madhya Pradesh
- 5.2.3 Entropy Weighted Irrigation Water Quality Index (EIWQI)
- 5.2.4 Classification of Water Quality in the Overall Pollution Index (Sargaonkar et al. 2008)
- 5.2.5 Result and Discussions
- 5.2.6 WQI Studies from Worldwide
- 5.2.7 Conclusion
- References
- Part II Water Resilence: Vulnerability and Response
内容説明・目次
内容説明
This book talks about the dynamics of the surface water-groundwater contaminant interactions under different environmental conditions across the world. The contents of the book highlight trends of monitoring, prediction, awareness, learning, policy, and mitigation success. The book provides a description of the background processes and factors controlling resilience, risk, and response of water systems, contributing to the development of more efficient, sustainable technologies and management options. It integrates methodologies and techniques such as data science and engineering, remote sensing, modelling, analytics, synthesis and indices, disruptive innovations and their utilization in water management, policy making, and mitigation strategies. The book is intended to be a comprehensive reference for students, professionals, and researchers working on various aspects of science and technology development. It will also prove a useful resource for policy makers and implementation specialists.
目次
Section 1: Water Resilience: Vulnerability and Response
i. Problem, perspective and challenges of water monitoring
ii. Water resilience to natural and human disasters
iii. Food-Energy-Water-Ecosystem Services Nexus
iv. Water supply, urbanization and climate change
v. Integrative risk assessment and water management
Section 2: Data science and engineering for water system
vi. Water Data: modeling, uncertainty, and security
vii. Standardization, Interoperability, and data sharing
viii. Analytics in Water Resource
ix. Visualization and synthesis of the multi-dimensional water system
x. Water Indices: specification, criteria and application
Section 3: Innovation in operational water management
xi. Engineering water supply for conservation, resiliency, and sustainability
xii. Water quality treatments and natural remediation of water contaminants
xiii. Shifts and trends of water quality analyses
xiv. Paradigms of life cycle, vulnerability and cost benefit analyses for water
xv. Modeling human behavior and decision making
Section 4: Policy and Mitigation
xvi. Bridging water quality and quantity for adaptive management
xvii. Preparedness and awareness in sanitization for health and prosperity
xviii. Science, sense and sensibility for water quality mitigation and policy making
xix. Collaborations and conflicting interest across government and interstate conflicts
xx. Language of water science: common ground for scientist, stake holders and managers
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