River Basin Restoration and Management

A. Ostfeld, J. Tyson
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引用次数: 3

Abstract

River Basin Restoration and Management is the result of two workshops that took place at the 4th IWA World Water Congress: The Restoration of Degraded River Basins and River Basin Management Using Machine Learning. The Restoration of Degraded River Basins set out to share experience in the institutional, policy, and public participation elements of restoration programmes, the ‘soft’ issues surrounding restoration of a degraded river basin and the development of the river basin plan. The resulting papers include a number of case studies from a variety of river basins in Israel, South Africa, United Kingdom, Australia and Central Europe. The River Basin Management Using Machine Learning workshop highlighted and compared the two different approaches to watershed management: the physically based modelling approach relying on the system physics versus the data driven modelling approach based on exploring the system ‘data behaviour’. The workshop was motivated by the recent rapid advance in information processing systems. These have pushed the hydrological research community to explore the possibilities of using intelligent systems aimed at automatically-evolving models of natural phenomena. This is the discipline of machine learning (ML), the study of computer algorithms that improve automatically through experience. This title belongs to Water and Environmental Management Series (WEMS) ISBN: 9781843395102 (Print) ISBN: 9781780402581 (eBook)
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流域恢复与管理
流域恢复与管理是在第四届IWA世界水大会上举行的两个研讨会的成果:退化河流流域的恢复和使用机器学习的河流流域管理。“退化河流流域的恢复”旨在分享有关恢复项目的制度、政策和公众参与要素、围绕退化河流流域恢复的“软”问题以及河流流域规划的制定等方面的经验。由此产生的论文包括来自以色列、南非、英国、澳大利亚和中欧各种河流流域的一些案例研究。使用机器学习的流域管理研讨会强调并比较了两种不同的流域管理方法:依赖于系统物理的基于物理的建模方法与基于探索系统“数据行为”的数据驱动建模方法。最近信息处理系统的迅速发展推动了讲习班的开展。这推动了水文研究界探索使用智能系统的可能性,旨在自动发展自然现象的模型。这是机器学习(ML)的学科,研究通过经验自动改进的计算机算法。本书属于水与环境管理丛书(WEMS) ISBN: 9781843395102(印刷)ISBN: 9781780402581(电子书)
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