Rivers’ Temporal Sustainability through the Evaluation of Predictive Runoff Methods

José-Luis Molina, Santiago Zazo, Ana-María Martín-Casado and María-Carmen Patino-Alonso
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José-Luis Molina: IGA Research Group. High Polytechnic School of Engineering, University of Salamanca, Av. de los Hornos Caleros, 50, 05003 Ávila, Spain
Santiago Zazo: IGA Research Group. High Polytechnic School of Engineering, University of Salamanca, Av. de los Hornos Caleros, 50, 05003 Ávila, Spain
Ana-María Martín-Casado: IGA Research Group. Department of Statistics, University of Salamanca, Campus Miguel de Unamuno, C/Alfonso X El Sabio s/n, 37007 Salamanca, Spain
María-Carmen Patino-Alonso: IGA Research Group. Department of Statistics, University of Salamanca, Campus Miguel de Unamuno, C/Alfonso X El Sabio s/n, 37007 Salamanca, Spain

Sustainability, 2020, vol. 12, issue 5, 1-21

Abstract: 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’ 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.

Keywords: runoff; temporal dependence; rivers’ sustainability; predictive methods; causal reasoning; runoff fractions; water management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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