文章基本信息

标题：Rivers’ Temporal Sustainability through the Evaluation of Predictive Runoff Methods
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作者：José-Luis Molina ; Santiago Zazo ; Ana-María Martín-Casado 等
期刊名称：Sustainability
印刷版ISSN：2071-1050
出版年度：2020
卷号：12
期号：5
页码：1720
DOI：10.3390/su12051720
语种：English
出版社：MDPI, Open Access Journal
摘要：The concept of sustainability is assumed for this research from a temporal perspective. Rivers represent natural systems with an inherent internal memory on their runoff and, by extension, to their hydrological behavior, that should be identified, characterized and quantified. This memory is formally called temporal dependence and allows quantifying it for each river system. The ability to capture that temporal signature has been analyzed through different methods and techniques. However, there is a high heterogeneity on those methods#8217; analytical capacities. It is found in this research that the most advanced ones are those whose output provides a dynamic and quantitative assessment of the temporal dependence for each river system runoff. Since the runoff can be split into temporal conditioned runoff fractions, advanced methods provide an important improvement over classic or alternative ones. Being able to characterize the basin by calculating those fractions is a very important progress for water managers that need predictive tools for orienting their water policies to a certain manner. For instance, rivers with large temporal dependence will need to be controlled and gauged by larger hydraulic infrastructures. The application of this approach may produce huge investment savings on hydraulic infrastructures and an environmental impact minimization due to the achieved optimization of the binomial cost-benefit.