Transferencia de resultados de investigación para el ahorro de agua y de la energía en comunidades de regantes a través del entorno de gestión integrada CORENET-COREGEST

En la actualidad se está produciendo un incremento en la demanda para realizar una gestión optimizada del agua y de la energía empleadas en el regadío. Esto ha dado lugar a una importante actividad de I+D con diferentes sistemas, productos y servicios, que comparten el objetivo de mejorar la aplicación del agua y/o de la energía. Sin embargo, el conocimiento generado choca con dificultades a la hora de transferir los resultados hacia los usuarios finales. Esto es debido, al menos en parte, a la necesidad de que las Comunidades de Regantes cambien su modelo de gestión y sean capaces de integrar los resultados de este conocimiento con los procesos normales de gestión que se emplean en las mismas. SERINA ha desarrollado la metodología y el Enterprsise Resource Planning (ERP) de gestión CORENET-COREGEST, que permite modernizar los procesos de gestión de las Comunidades de Regantes e integrar herramientas/sistemas/servicios externos generados por los centros de I+D con el objetivo de mejorar la gestión, fundamentalmente, del agua y de la energía. En este trabajo se muestran algunos casos que ilustran lo anterior y se explican las ventajas para las Comunidades de Regantes usuarias así como por los centros de I+D que han integrado sus productos en CORENET-COREGEST

Differences in the response of carbon assimilation to summer stress (water deficits, high light and temperature) in four Mediterranean tree species

Daily changes in photoprotective mechanisms were studied in sun leaves of Quercus suber L., Quercus ilex L., Olea europaea L. and Eucalyptus globulus Labill. trees during the summer in Portugal. Even though stomatal closure explained most of the diurnal variation in carbon assimilation along the summer, a decline in the photochemical yield of photosystem II (F(v)/'/F(m)/') also occurred, as a result of an excess of intercepted solar radiation when carbon assimilation is limited by stomatal closure due to high vapour pressure deficits and/or soil water deficits. These changes were accompanied by the conversion of violaxanthin to antheraxanthin and zeaxanthin which were correlated with thermal dissipation of excess photon energy. In spite of a common general response, differences between species were observed - Olea europaea, which is a slow-growing tree, had the lowest net photosynthetic rates, the highest proportion of carotenoids in relation to chlorophyll and the highest rates of de-epoxidation of violaxanthin. This enabled a large thermal dissipation of the excess intercepted radiation but led to rather small values of light utilisation for photochemistry (ca 20%). In contrast, in E. globulus, a fast-growing tree, photosynthetic rates were the highest, thermal dissipation of absorbed radiation the lowest and maximal values of light utilisation for photochemistry reached ca 50%. The two Quercus species exhibited an intermediate response. A high degree of co-ordination is apparent between stomatal behaviour, photosynthetic capacity and photoprotection mechanisms.Peer Reviewe

A predictive hybrid reduced order model based on proper orthogonal decomposition combined with deep learning architectures

Producción CientíficaSolving computational fluid dynamics problems requires using large computational resources. The computa- tional time and memory requirements to solve realistic problems vary from a few hours to several weeks with several processors working in parallel. Motivated by the need of reducing such large amount of resources (improving the industrial applications in which fluid dynamics plays a key role), this article introduces a new predictive Reduced Order Model (ROM) applied to solve fluid dynamics problems. The model is based on physical principles and combines modal decompositions with deep learning architectures. The hybrid ROM, reduces the dimensionality of a database via proper orthogonal decomposition (POD), extracting the dominant features leading the flow dynamics of the problem studied. The number of degrees of freedom are reduced from hundred thousands spatial points describing the database to a few (20–100) POD modes. Firstly, POD divides the spatio-temporal data into spatial modes and temporal coefficients (or temporal modes). Next, the temporal coefficients are integrated in time using convolutional or recurrent neural networks. The temporal evolution of the flow is approximated after combining the spatial modes with the new temporal coefficients computed. The model is tested in two complex problems of fluid dynamics, the three-dimensional wake of a circular cylinder and a synthetic jet. The hybrid ROM uses data from the initial transient stage of numerical simulations to predict the temporally converged solution of the flow with high accuracy. The speed-up factor comparing the time necessary to obtain the predicted solution using the hybrid ROM and the numerical solver is ∼140–348 in the synthetic jet and ∼2897–3818 in the three dimensional cylinder wake. The robustness shown in the results presented and the data-driven nature of this ROM, make it possible to extend its application to other fields (i.e. video and language processing, robotics, finances)Ministerio de Ciencia, Innovación y Universidades Proyectos de I+D+i ‘‘Retos investigación’’, (grant RTI2018-098958- B-I00)Ministerio de Ciencia e Innovación y el Fondo Europeo de Desarrollo Regionales (FEDER) (grant PID2020-114173RB-I00