Surface and Groundwater Resources Development and Management in Semi-arid Region

ISBN: 9783031293931
Код товара 153951

Chaitanya B. Pande, Manish Kumar, N.L. Kushwaha

Surface and Groundwater Resources Development and Management in Semi-arid Region

Surface and Groundwater Resources Development and Management in Semi-arid Region

ISBN: 9783031293931
Код товара 153951

XML_ID: 16105169

18 294 ₽

Доставка под заказ

Если Вы закажете книгу до 28.10.2026, то мы привезём её ориентировочно 02.12.2026.

  • Автор

    Chaitanya B. Pande, Manish Kumar, N.L. Kushwaha

  • Издатель

    Springer

  • Тип обложки

    Hardback

  • Год издания

    2023

  • ISBN

    9783031293931

  • Язык

    ENG

  • Кол-во страниц

    427

О чём книга?

This book explains the challenges for efficient sustainable surface and groundwater development and management with the focus on India and other countries, providing a stable output presentation by using machine learning data mining methods, and modeling. It is a combination of machine learning, modeling, google earth engine, climate data modeling, remote sensing and GIS techniques, surface water modeling, AHP modeling, groundwater quality analysis, aquifer mapping, land use and land cover analysis, forecasting of water and rainfall and so on, its use to sustainable development, planning, and management of groundwater purposes in India and other countries. The main purpose of this book will develop better outlines for the development of surface and groundwater and management in the semi-arid region climate, which supports the Sustainable Development Goals (SDGs) in India, especially on sustainable surface water and groundwater resources management. This book provides a multidisciplinary overview for the faculty members, administrators scientists, policymakers, social science, and professionals involved in the various aspects of sustainable groundwater development, planning, and management.

Chapter 1. Evapotranspiration importance in water resources management through cutting-edge approaches of Remote sensing and machine learning algorithms (Ali Raza).- Chapter 2. Application of Remote Sensing and GIS for Morphometric Analysis: A Case Study

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