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Hydrological Insights

Hashemi, Hossein LU orcid ; Kumar, Amit and Kumar, Krishna LU orcid (2026)
Abstract

Hydrological Insights: Synergizing Groundwater Models, Remote Sensing, and AI for Water Sustainability offers an in-depth exploration of hydrological modeling and its cutting-edge advancements, presented across six comprehensive sections. Part I establishes the foundational principles and methodologies of hydrological modeling, while Part II delves into sophisticated techniques and tools that enhance the accuracy and efficiency of hydrological studies. Part III highlights the powerful integration of remote sensing and artificial intelligence, showcasing how these technologies revolutionize modern hydrological practices. Part IV focuses on environmental impact assessment and management strategies, outlining effective methods for... (More)

Hydrological Insights: Synergizing Groundwater Models, Remote Sensing, and AI for Water Sustainability offers an in-depth exploration of hydrological modeling and its cutting-edge advancements, presented across six comprehensive sections. Part I establishes the foundational principles and methodologies of hydrological modeling, while Part II delves into sophisticated techniques and tools that enhance the accuracy and efficiency of hydrological studies. Part III highlights the powerful integration of remote sensing and artificial intelligence, showcasing how these technologies revolutionize modern hydrological practices. Part IV focuses on environmental impact assessment and management strategies, outlining effective methods for sustainable water resource management. Part V covers the latest advancements in remote sensing and machine learning, emphasizing their pivotal role in contemporary hydrology. Finally, Part VI presents real-world case studies and future directions, offering practical insights and forward-looking perspectives. With meticulously crafted chapters that combine theoretical foundations with practical applications, this book is an essential resource for students, researchers, and professionals seeking to advance their understanding of hydrology through the integration of remote sensing and AI.

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Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Book/Report
publication status
published
subject
pages
277 pages
publisher
Elsevier
external identifiers
  • scopus:105032954907
ISBN
9780443363955
9780443363948
DOI
10.1016/C2024-0-01751-1
language
English
LU publication?
yes
id
371cbff8-529d-41ef-b649-cc2d3fca1a35
date added to LUP
2026-04-28 15:58:44
date last changed
2026-05-26 17:42:30
@book{371cbff8-529d-41ef-b649-cc2d3fca1a35,
  abstract     = {{<p>Hydrological Insights: Synergizing Groundwater Models, Remote Sensing, and AI for Water Sustainability offers an in-depth exploration of hydrological modeling and its cutting-edge advancements, presented across six comprehensive sections. Part I establishes the foundational principles and methodologies of hydrological modeling, while Part II delves into sophisticated techniques and tools that enhance the accuracy and efficiency of hydrological studies. Part III highlights the powerful integration of remote sensing and artificial intelligence, showcasing how these technologies revolutionize modern hydrological practices. Part IV focuses on environmental impact assessment and management strategies, outlining effective methods for sustainable water resource management. Part V covers the latest advancements in remote sensing and machine learning, emphasizing their pivotal role in contemporary hydrology. Finally, Part VI presents real-world case studies and future directions, offering practical insights and forward-looking perspectives. With meticulously crafted chapters that combine theoretical foundations with practical applications, this book is an essential resource for students, researchers, and professionals seeking to advance their understanding of hydrology through the integration of remote sensing and AI.</p>}},
  author       = {{Hashemi, Hossein and Kumar, Amit and Kumar, Krishna}},
  isbn         = {{9780443363955}},
  language     = {{eng}},
  month        = {{01}},
  note         = {{Book Editor}},
  publisher    = {{Elsevier}},
  title        = {{Hydrological Insights}},
  url          = {{http://dx.doi.org/10.1016/C2024-0-01751-1}},
  doi          = {{10.1016/C2024-0-01751-1}},
  year         = {{2026}},
}