Water Suitability Analysis: Advanced Research Approaches for Sustainable and Resilient Resource Management
暫譯: 水資源適宜性分析：可持續與韌性資源管理的進階研究方法
Sharma, Lokeshwar, Singh, Sandeep, Anand, Abhineet
- 出版商: CRC
- 出版日期: 2026-05-19
- 售價: $5,610
- 貴賓價: 9.5 折 $5,329
- 語言: 英文
- 頁數: 204
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1041162464
- ISBN-13: 9781041162469
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相關分類:
地理資訊系統 Gis、人工智慧
尚未上市，無法訂購
相關主題
商品描述
This edited volume presents a comprehensive exploration of modern techniques and methodologies for evaluating water quality and suitability. It bridges traditional experimental approaches with cutting-edge artificial intelligence and remote sensing tools, offering an innovative perspective on sustainable water resource management.
It delves into multidisciplinary insights that combine environmental science, data analytics, and hydrological modeling. Key topics include experimental water quality analysis, GIS-based assessment, groundwater and surface water case studies, and AI applications in hydroinformatics. Readers will benefit from practical frameworks, real-world case studies, and research-driven solutions designed to address complex challenges in water suitability evaluation.
This is an essential resource for researchers, academicians, environmental engineers, policymakers, and postgraduate students working in water resource management, environmental sustainability, and artificial intelligence applications. It serves as both a reference guide and an inspiration for professionals seeking to implement intelligent, data-driven, and sustainable approaches to water assessment and planning.
商品描述(中文翻譯)
這本編輯的專著全面探討了現代水質評估和適用性的方法與技術。它將傳統的實驗方法與尖端的人工智慧和遙感工具相結合，提供了一種創新的可持續水資源管理視角。
本書深入探討了結合環境科學、數據分析和水文模型的多學科見解。主要主題包括實驗水質分析、基於地理資訊系統（GIS）的評估、地下水和地表水案例研究，以及人工智慧在水文資訊學中的應用。讀者將受益於實用的框架、真實案例研究和以研究為驅動的解決方案，旨在應對水質適用性評估中的複雜挑戰。
這是一本對於從事水資源管理、環境可持續性和人工智慧應用的研究人員、學者、環境工程師、政策制定者及研究生來說必不可少的資源。它既是參考指南，也是激勵專業人士實施智能、數據驅動和可持續水質評估與規劃方法的靈感來源。
作者簡介
Lokeshwar Sharma is an academic and researcher specializing in environmental and water resources engineering. His research interests include water quality analysis, groundwater modeling, and sustainable resource management. He has been actively involved in projects related to AI-based water suitability assessment and environmental monitoring. As an editor, he contributes his expertise in hydrological modelling and interdisciplinary environmental systems to ensure the book reflects modern approaches to water research and sustainability.
Sandeep Singh is a distinguished researcher in civil and environmental engineering, focusing on sustainable water management and GIS-based hydrological analysis. His expertise lies in remote sensing applications, water resources planning, and policy development for environmental sustainability. He has published numerous papers in Scopus-indexed journals and guided several research projects integrating machine learning in water quality assessment. His editorial contribution ensures a scientific and policy-oriented approach to the study of water suitability.
Abhineet Anand is an Assistant Professor and researcher with expertise in groundwater hydrology, water suitability analysis, and computational modelling. His academic and professional work focuses on developing data-driven and AI-based solutions for assessing groundwater potential and quality. He has contributed extensively to research on MODFLOW modelling and the application of machine learning in hydrogeological studies. His involvement in this book strengthens its technical and analytical depth in AI-driven water suitability assessment.
Abhishek Kumar is a researcher and educator specializing in environmental engineering and water resource management. His research focuses on integrating artificial intelligence, GIS, and remote sensing for water quality monitoring and prediction. With several peer-reviewed publications, Dr. Kumar has made notable contributions to the field of sustainable water management and SDG 6 implementation strategies. As an editor, he brings valuable experience in data analytics and interdisciplinary research for advancing AI-driven water assessment methodologies.
作者簡介(中文翻譯)
Lokeshwar Sharma 是一位專注於環境與水資源工程的學者和研究員。他的研究興趣包括水質分析、地下水模型以及可持續資源管理。他積極參與與基於人工智慧的水適宜性評估和環境監測相關的項目。作為編輯，他貢獻了在水文模型和跨學科環境系統方面的專業知識，以確保本書反映現代水研究和可持續性的做法。
Sandeep Singh 是一位傑出的土木與環境工程研究員，專注於可持續水管理和基於地理資訊系統（GIS）的水文分析。他的專長在於遙感應用、水資源規劃以及環境可持續性的政策發展。他在 Scopus 索引的期刊上發表了多篇論文，並指導了幾個將機器學習整合到水質評估中的研究項目。他的編輯貢獻確保了水適宜性研究的科學性和政策導向。
Abhineet Anand 是一位助理教授和研究員，專長於地下水水文學、水適宜性分析和計算模型。他的學術和專業工作專注於開發基於數據和人工智慧的解決方案，以評估地下水的潛力和質量。他在 MODFLOW 模型和機器學習在水文地質研究中的應用方面做出了廣泛的貢獻。他在本書中的參與增強了其在基於人工智慧的水適宜性評估中的技術和分析深度。
Abhishek Kumar 是一位專注於環境工程和水資源管理的研究員和教育者。他的研究重點在於整合人工智慧、GIS 和遙感技術進行水質監測和預測。Kumar 博士在可持續水管理和可持續發展目標第六項（SDG 6）實施策略方面做出了顯著貢獻，並發表了多篇同行評審的論文。作為編輯，他帶來了在數據分析和跨學科研究方面的寶貴經驗，以推進基於人工智慧的水評估方法。
