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Advanced Hydroinformatics in Vulnerability Assessments and Mitigative Interventions is a comprehensive guide that explores the role of hydroinformatics in managing peri-urban watersheds amidst challenges such as climate change and urbanization.

Leveraging artificial intelligence, data science, and Internet of Things, this book presents innovative strategies for optimal management of natural resources. The book uniquely combines theory and case studies to illustrate the application of data science, AI, and other technologies in assessing vulnerabilities and developing mitigation strategies for peri-urban watersheds.

Readers will find Advanced Hydroinformatics in Vulnerability Assessments and Mitigative Interventions an invaluable resource for understanding and applying hydroinformatics to address their water-related challenges.

  • Provides real-world case studies demonstrating the application of AI, data science, and Internet of Things in watershed management
  • Offers practical strategies for assessing vulnerabilities and crafting mitigative interventions in the face of water scarcity
  • Unpacks the complex role of hydroinformatics in managing peri-urban watersheds, particularly under climate change and urbanization pressures

1. Cover image - p. ii 2. Title page - p. ii 3. Table of Contents - p. iii 4. Developments in Environmental Science - p. i 5. Copyright - p. iv 6. Contributors - p. xxvii 7. Foreword - p. xxxi 8. Preface - p. xxxiii 9. Acknowledgment - p. xxxvii 10. Chapter 1. Impact of manholes in flood simulation of microcatchments: An AHP—MCDM approach - p. 1 11. Chapter 2. Assessing the impacts of climate and urban dynamics on peri-urban watershed vulnerability - p. 13 12. Chapter 3. Minimization of virtual water of a peri-urban capital city in face of climate change: Case study of tea industry - p. 35 13. Chapter 4. Application of modified version of the first innovative approach for prioritization of blocks in the Barmer district - p. 55 14. Chapter 5. Location selection for rainwater harvesting plants with the help of GWA-based neural networks - p. 69 15. Chapter 6. Identification of groundwater blocks needing groundwater recharge and determination of causal factors affecting declining groundwater by using innovative approaches: A case study of Udaipur division - p. 85 16. Chapter 7. Impact of brick industry on surface water vulnerability analysis: A PROMETHEE-ELECTRE approach - p. 121 17. Chapter 8. Vulnerability analysis of peri-urban watershed with respect to climate change and urbanization - p. 183 18. Chapter 9. Assessment of groundwater potential zone mapping of Haora River Basin, Tripura, by MCDM and GIS - p. 227 19. Chapter 10. Impact of climate change on pollution content of periurban river—A polynomial neural network approach - p. 241 20. Chapter 11. Development of a spatial predictive model for estimation of flow rate in penstock networks - p. 263 21. Chapter 12. Wave powered desalination for delivering clean water to developing countries and island nations - p. 271 22. Chapter 13. Application of nature-based optimization techniques in optimizing water used in renewable energy - p. 311 23. Chapter 14. Minimization of energy use in surface water treatment plant - p. 321 24. Chapter 15. Performance optimization wave energy conversion system with the help of multicriteria decision techniques and nature-based algorithms - p. 333 25. Chapter 16. Development of indicator-based real-time penstock condition monitoring system by the application of GIS and cognitive tools - p. 353 26. Chapter 17. Selection of a suitable location for the installation of a wave energy converter in the Indian coastal zone: An MCDM and reliability analysis approach - p. 363 27. Chapter 18. Design and development of low-cost solar based domestic water filter - p. 381 28. Chapter 19. Impact of saline water intrusion on water conservation of a coastal zone in equatorial India - p. 403 29. Chapter 20. Flood mitigation in farmlands: Modeling and simulation techniques - p. 417 30. Chapter 21. Application of satellite remote sensing for flood prediction and management - p. 439 31. Chapter 22. Predictive hydroinformatics: Reducing flood risks through advanced modeling - p. 459 32. Chapter 23. Application of artificial intelligence in impact analysis of saline water intrusion on coastal wetlands - p. 483 33. Chapter 24. Impact of tsunami on island coasts: The most effected parameter approach - p. 501 34. Chapter 25. Impact of paper and pulp industry on Coastal Zone Vulnerabilities: Moth-flame, fire fly, and water cycle optimization approach - p. 529 35. Chapter 26. Impact of climate change on tropical coasts: An OPAAHP approach for coastal vulnerability assessment in India - p. 541 36. Chapter 27. Optimal resource allocation within peri-urban consumers of a coastal zone with the help of mine burst and glowworm optimization technique - p. 559 37. Chapter 28. Vulnerability analysis of tropical coastal zone under changed climate scenarios with the help of water cycle and poly-neural networks - p. 571 38. Chapter 29. Vulnerability analysis of a shallow coastal zone with respect to volcanic storms: A MERC—GWA approach - p. 595 39. Chapter 30. Monitoring graywater recycle potential of a wetland: A Group Method of Data Handling Approach - p. 613 40. Chapter 31. Data-driven strategies for reducing agricultural water footprint - p. 631 41. Chapter 32. WetMAN: an app to manage Wetland resources - p. 651 42. Chapter 33. Hydroinformatics-driven strategies for drought mitigation in agricultural systems - p. 663 43. Chapter 34. Vulnerability analysis of wetlands under changed climate scenarios with the help of water cycle and poly-neural networks - p. 685 44. Chapter 35. Application of particle swarm algorithm in vulnerability assessment of blue water management with respect to wetlands - p. 729 45. Chapter 36. Risk minimization of wetlands from climatic vulnerabilities by firefly and glowworm optimization - p. 753 46. Chapter 37. Application of water cycle algorithms and polynomial neural networks in Wetland vulnerability - p. 769 47. Chapter 38. Insightful of regional climate models in temperature dynamics under climate change scenarios for Junagadh district, Gujarat, India: A case study - p. 789 48. Chapter 39. Satellite remote sensing for flood prediction and management: A case study - p. 807 49. Index - p. 835

Descripcion
Descripción

Advanced Hydroinformatics in Vulnerability Assessments and Mitigative Interventions is a comprehensive guide that explores the role of hydroinformatics in managing peri-urban watersheds amidst challenges such as climate change and urbanization.

Leveraging artificial intelligence, data science, and Internet of Things, this book presents innovative strategies for optimal management of natural resources. The book uniquely combines theory and case studies to illustrate the application of data science, AI, and other technologies in assessing vulnerabilities and developing mitigation strategies for peri-urban watersheds.

Readers will find Advanced Hydroinformatics in Vulnerability Assessments and Mitigative Interventions an invaluable resource for understanding and applying hydroinformatics to address their water-related challenges.

  • Provides real-world case studies demonstrating the application of AI, data science, and Internet of Things in watershed management
  • Offers practical strategies for assessing vulnerabilities and crafting mitigative interventions in the face of water scarcity
  • Unpacks the complex role of hydroinformatics in managing peri-urban watersheds, particularly under climate change and urbanization pressures

1. Cover image - p. ii 2. Title page - p. ii 3. Table of Contents - p. iii 4. Developments in Environmental Science - p. i 5. Copyright - p. iv 6. Contributors - p. xxvii 7. Foreword - p. xxxi 8. Preface - p. xxxiii 9. Acknowledgment - p. xxxvii 10. Chapter 1. Impact of manholes in flood simulation of microcatchments: An AHP—MCDM approach - p. 1 11. Chapter 2. Assessing the impacts of climate and urban dynamics on peri-urban watershed vulnerability - p. 13 12. Chapter 3. Minimization of virtual water of a peri-urban capital city in face of climate change: Case study of tea industry - p. 35 13. Chapter 4. Application of modified version of the first innovative approach for prioritization of blocks in the Barmer district - p. 55 14. Chapter 5. Location selection for rainwater harvesting plants with the help of GWA-based neural networks - p. 69 15. Chapter 6. Identification of groundwater blocks needing groundwater recharge and determination of causal factors affecting declining groundwater by using innovative approaches: A case study of Udaipur division - p. 85 16. Chapter 7. Impact of brick industry on surface water vulnerability analysis: A PROMETHEE-ELECTRE approach - p. 121 17. Chapter 8. Vulnerability analysis of peri-urban watershed with respect to climate change and urbanization - p. 183 18. Chapter 9. Assessment of groundwater potential zone mapping of Haora River Basin, Tripura, by MCDM and GIS - p. 227 19. Chapter 10. Impact of climate change on pollution content of periurban river—A polynomial neural network approach - p. 241 20. Chapter 11. Development of a spatial predictive model for estimation of flow rate in penstock networks - p. 263 21. Chapter 12. Wave powered desalination for delivering clean water to developing countries and island nations - p. 271 22. Chapter 13. Application of nature-based optimization techniques in optimizing water used in renewable energy - p. 311 23. Chapter 14. Minimization of energy use in surface water treatment plant - p. 321 24. Chapter 15. Performance optimization wave energy conversion system with the help of multicriteria decision techniques and nature-based algorithms - p. 333 25. Chapter 16. Development of indicator-based real-time penstock condition monitoring system by the application of GIS and cognitive tools - p. 353 26. Chapter 17. Selection of a suitable location for the installation of a wave energy converter in the Indian coastal zone: An MCDM and reliability analysis approach - p. 363 27. Chapter 18. Design and development of low-cost solar based domestic water filter - p. 381 28. Chapter 19. Impact of saline water intrusion on water conservation of a coastal zone in equatorial India - p. 403 29. Chapter 20. Flood mitigation in farmlands: Modeling and simulation techniques - p. 417 30. Chapter 21. Application of satellite remote sensing for flood prediction and management - p. 439 31. Chapter 22. Predictive hydroinformatics: Reducing flood risks through advanced modeling - p. 459 32. Chapter 23. Application of artificial intelligence in impact analysis of saline water intrusion on coastal wetlands - p. 483 33. Chapter 24. Impact of tsunami on island coasts: The most effected parameter approach - p. 501 34. Chapter 25. Impact of paper and pulp industry on Coastal Zone Vulnerabilities: Moth-flame, fire fly, and water cycle optimization approach - p. 529 35. Chapter 26. Impact of climate change on tropical coasts: An OPAAHP approach for coastal vulnerability assessment in India - p. 541 36. Chapter 27. Optimal resource allocation within peri-urban consumers of a coastal zone with the help of mine burst and glowworm optimization technique - p. 559 37. Chapter 28. Vulnerability analysis of tropical coastal zone under changed climate scenarios with the help of water cycle and poly-neural networks - p. 571 38. Chapter 29. Vulnerability analysis of a shallow coastal zone with respect to volcanic storms: A MERC—GWA approach - p. 595 39. Chapter 30. Monitoring graywater recycle potential of a wetland: A Group Method of Data Handling Approach - p. 613 40. Chapter 31. Data-driven strategies for reducing agricultural water footprint - p. 631 41. Chapter 32. WetMAN: an app to manage Wetland resources - p. 651 42. Chapter 33. Hydroinformatics-driven strategies for drought mitigation in agricultural systems - p. 663 43. Chapter 34. Vulnerability analysis of wetlands under changed climate scenarios with the help of water cycle and poly-neural networks - p. 685 44. Chapter 35. Application of particle swarm algorithm in vulnerability assessment of blue water management with respect to wetlands - p. 729 45. Chapter 36. Risk minimization of wetlands from climatic vulnerabilities by firefly and glowworm optimization - p. 753 46. Chapter 37. Application of water cycle algorithms and polynomial neural networks in Wetland vulnerability - p. 769 47. Chapter 38. Insightful of regional climate models in temperature dynamics under climate change scenarios for Junagadh district, Gujarat, India: A case study - p. 789 48. Chapter 39. Satellite remote sensing for flood prediction and management: A case study - p. 807 49. Index - p. 835

Indice
Autores
Muestra
Ficha Técnica