Applications of Machine Learning in Hydroclimatology

Srivastav, Roshan, Nayak, Purna C.

Applications of Machine Learning in Hydroclimatology
  • 出版商: Springer
  • 出版日期: 2024-11-05
  • 售價: $6,380
  • 貴賓價: 9.5 折 $6,061
  • 語言: 英文
  • 頁數: 142
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031644026
  • ISBN-13: 9783031644023
  • 相關分類: Machine Learning

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商品描述

Applications of Machine Learning in Hydroclimatology is a comprehensive exploration of the transformative potential of machine learning for addressing critical challenges in water resources management. The book explores how artificial intelligence can unravel the complexities of hydrological systems, providing researchers and practitioners with cutting-edge tools to model, predict, and manage these systems with greater precision and effectiveness. It thoroughly examines the modeling of hydrometeorological extremes, such as floods and droughts, which are becoming increasingly difficult to predict due to climate change. By leveraging AI-driven methods to forecast these extremes, the book offers innovative approaches that enhance predictive accuracy. It emphasizes the importance of analyzing non-stationarity and uncertainty in a rapidly evolving climate landscape, illustrating how statistical and frequency analyses can improve hydrological forecasts. Moreover, the book explores the impact of climate change on flood risks, drought occurrences, and reservoir operations, providing insights into how these phenomena affect water resource management.

To provide practical solutions, the book includes case studies that showcase effective mitigation measures for water-related challenges. These examples highlight the use of machine learning techniques such as deep learning, reinforcement learning, and statistical downscaling in real-world scenarios. They demonstrate how artificial intelligence can optimize decision-making and resource management while improving our understanding of complex hydrological phenomena. By utilizing machine learning architectures tailored to hydrology, the book presents physics-guided models, data-driven techniques, and hybrid approaches that can be used to address water management issues. Ultimately, Applications of Machine Learning in Hydroclimatology empowers researchers, practitioners, and policymakers to harness machine learning for sustainable water management. It bridges the gap between advanced AI technologies and hydrological science, offering innovative solutions to tackle today's most pressing challenges in water resources.

商品描述(中文翻譯)

《機器學習在水文氣候學中的應用》是對機器學習在解決水資源管理中關鍵挑戰的變革潛力的全面探索。本書探討了人工智慧如何揭示水文系統的複雜性，為研究人員和實務工作者提供尖端工具，以更高的精確度和有效性來建模、預測和管理這些系統。它深入研究了水文氣象極端事件的建模，例如由於氣候變遷而變得越來越難以預測的洪水和乾旱。通過利用人工智慧驅動的方法來預測這些極端事件，本書提供了增強預測準確性的創新方法。它強調在快速變化的氣候環境中分析非穩定性和不確定性的重要性，說明統計和頻率分析如何改善水文預測。此外，本書探討了氣候變遷對洪水風險、乾旱發生和水庫運作的影響，提供了這些現象如何影響水資源管理的見解。

為了提供實用的解決方案，本書包含了展示有效減緩水相關挑戰的案例研究。這些例子突顯了在現實情境中使用機器學習技術，如深度學習、強化學習和統計降尺度。它們展示了人工智慧如何優化決策制定和資源管理，同時增進我們對複雜水文現象的理解。通過利用針對水文學量身定制的機器學習架構，本書提出了物理引導模型、數據驅動技術和混合方法，這些方法可用於解決水資源管理問題。最終，《機器學習在水文氣候學中的應用》使研究人員、實務工作者和政策制定者能夠利用機器學習來實現可持續的水資源管理。它架起了先進人工智慧技術與水文科學之間的橋樑，提供創新解決方案以應對當今水資源中最緊迫的挑戰。

作者簡介

Dr. Roshan Karan Srivastav is an Associate Professor in the Department of Civil and Environmental Engineering at IIT Tirupati, serving since June 2018. He holds a Ph.D. in Water Resources Management from IIT Madras, a M.Tech in Water Resources Management from Motilal Nehru National Institute of Technology, and a B.E in Civil Engineering from University College of Engineering, Osmania University. His extensive research encompasses hydro-climatology, flood forecasting, reservoir operation, and stochastic hydrology. Before his tenure at IIT Tirupati, he was a Post-Doctoral Fellow at the University of Western Ontario, focusing on weather generators, system dynamics, and integrated water resources management. Dr. Srivastav has made significant contributions to the field through numerous publications in top-tier journals and international conferences. He also serves as the Project Director for the Technology Innovation Hub at IIT Tirupati Navavishkar I-Hub Foundation (IITTNiF), where he leads initiatives in positioning and precision technologies.

Dr P. C. Nayak is Scientist F in Surface Water Hydrology Division at National Institute of Hydrology, Roorkee. Dr. Nayak hold a B. Tech in Civil Engineering from College of Engineering and Technology, Bhubaneswar and M. Tech in Water Resources Engineering from Indian Institute of Technology, Kharagpur, and Ph.D in Water Resources Engineering from Indian Institute of Technology Madras, Chennai. Dr. Nayak has more than 25 years of experience in the field of water resources, surface water hydrological modelling, flood management and application of machine learning techniques and his major research contributions include development of models and software tools for hydrologic modeling using conceptual, distributed and data driven algorithm. Soft computing has to date been the main topic of investigation, in particular exploring the potential benefits and pitfalls. He has published more than 150 research papers in journals as well as book chapters and technical reports. He was a core committee member in development of Decision Support System (DSS) funded by World Bank. He was serving as Associate Editor in Journal of Hydrology, Elsevier Sciences.

作者簡介(中文翻譯)

羅尚·卡蘭·斯里瓦斯塔夫博士是印度理工學院提魯帕提分校土木與環境工程系的副教授，自2018年6月以來任職。他擁有印度理工學院馬德拉斯分校水資源管理的博士學位、莫蒂拉爾·尼赫魯國立技術學院的水資源管理碩士學位，以及奧斯曼尼亞大學工程學院的土木工程學士學位。他的廣泛研究涵蓋水文氣候學、洪水預測、水庫運作和隨機水文學。在加入印度理工學院提魯帕提分校之前，他曾在西安大略大學擔任博士後研究員，專注於氣象生成器、系統動力學和綜合水資源管理。斯里瓦斯塔夫博士通過在頂尖期刊和國際會議上發表的多篇論文，對該領域做出了重要貢獻。他還擔任印度理工學院提魯帕提分校技術創新中心Navavishkar I-Hub Foundation (IITTNiF)的項目主任，負責推動定位和精密技術的相關計畫。

P. C. 奈克博士是印度水文學研究所魯爾基分所表面水文學部的F級科學家。奈克博士擁有布巴內斯瓦爾工程技術學院的土木工程學士學位、印度理工學院卡哈拉古爾的水資源工程碩士學位，以及印度理工學院馬德拉斯分校的水資源工程博士學位。奈克博士在水資源、表面水文模型、洪水管理及機器學習技術應用方面擁有超過25年的經驗，他的主要研究貢獻包括開發使用概念性、分佈式和數據驅動算法的水文建模模型和軟體工具。至今，軟計算一直是他研究的主要主題，特別是探索其潛在的好處和陷阱。他在期刊、書籍章節和技術報告中發表了超過150篇研究論文。他曾是世界銀行資助的決策支持系統(DSS)開發的核心委員會成員，並擔任《水文學期刊》（Journal of Hydrology, Elsevier Sciences）的副編輯。

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