Rivers’ Temporal Sustainability through the Evaluation of Predictive Runoff Methods

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.

Modeling River Runoff Temporal Behavior through a Hybrid Causal–Hydrological (HCH) Method

“…Furthermore, the usage of a specific RRM model represents an improvement in this research line, which is focused on causality, because it overcomes the traditional limitations related to the availability of hydrological runoff data in natural regimes [16,26]. Moreover, it is also worth highlighting the fact that causal models improve and increase the knowledge on the temporal behavior of a basin's water resources [13,17,18,27].…”

“…In this sense, the frequency of droughts in Southern Europe is increasing significantly [14,15]. This is making it necessary to improve the knowledge on the temporal behavior of rivers [16][17][18], as not all the reasons that explain this increasing variability are new [16,18].…”

“…Additionally, this work aims to overcome the lack of suitable and available hydrological data for CR analysis, as causal models need to be populated by as much information as possible to be representative [16]. This scarcity is largely due to several reservoirs having been built in the study basin (Almodovar, Celemín, and Barbate reservoirs) at the end of the 20th century in order to solve the problems related to recurrent droughts, floods, and water availability in this study zone.…”

Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO

“…In the study of the hydrological component, mathematical models [6] have increasingly been applied through predictive and descriptive methods that are classified into deterministic and stochastic. Stochastics are characterized by using multivariate statistical methods [7]. These methods are considered helpful for studying water quality [8] using evaluation factors such as correlation, covariation, similarities and distances [7].…”

“…Stochastics are characterized by using multivariate statistical methods [7]. These methods are considered helpful for studying water quality [8] using evaluation factors such as correlation, covariation, similarities and distances [7]. In addition, in order to analyse temporal hydrological behaviour from a stochastic perspective, it is necessary to study the temporal-spatial correlation of hydrological parameters [7].…”