Optimización de la predicción de demanda de agua mediante algoritmos neuro-genéticos para un conjunto de datos reducido

La predicción de la demanda de agua es uno de los factores principales en el diseño y gestión de sistemas de abastecimiento y distribución de agua. Recientemente, avanzadas técnicas en inteligencia computacional como las Redes Neuronales Artificiales (RNAs) han sido aplicadas para la predicción de series temporales con importantes resultados. En este trabajo se ha desarrollado una metodología híbrida que combina RNAs y Algoritmos Genéticos multiobjetivo para la predicción a corto plazo de la demanda de agua en una Comunidad de Regantes cuando la disponibilidad de datos es escasa. El modelo fue desarrollado utilizando datos de series temporales del Sector VII de la Zona Regable Bembézar M.D. Tras el proceso de optimización con un algoritmo genético multiobjetivo se obtuvo una RNA de tipo perceptrón multicapa entrenada mediante el algoritmo Regularización Bayesiana con 24 neuronas en la primera capa oculta y 21 en la segunda. El modelo desarrollado fue capaz de explicar el 95 % de la varianza total de los datos observados con un Error Estándar de Predicción del 9.38 % (periodo de test).Ministerio de Economía y Competitivida

New memory-based hybrid model for middle-term water demand forecasting in irrigated areas

The energy demand and their associated costs in pressurized irrigation networks together with water scarcity are currently causing serious challenges for irrigation district’s (ID) managers. Additionally, most of the new water distribution networks in IDs have been designed to be operated on-demand complexing ID managers the daily decision-making process. The knowledge of the water demand several days in advance would facilitate the management of the system and would help to optimize the water use and energy costs. For an efficient management and optimization of the water-energy nexus in IDs, longer term forecasting models are needed. In this work, a new hybrid model (called LSTMHybrid) combining Fuzzy Logic (FL), Genetic Algorithm (GA), LSTM encoder-decoder and dense or full connected neural networks (DNN) for the one-week forecasting of irrigation water demand at ID scale has been developed. LSTMHybrid was developed in Python and applied to a real ID. The optimal input variables for LSTMHydrid were mean temperature (°C), reference evapotranspiration (mm), solar radiation (MJ m−2) and irrigation water demand of the ID (m3) from 1 to 7 days prior to the first day of prediction. The optimal LSTMHybrid model selected consisted of 50 LSTM cells in the encoder submodel, 409 LSTM cells in the decoder submodel and three hidden layers in the DNN submodel with 31, 96 and 128 neurons in each hidden layer, respectively. Thus, LSTMHybrid had a total of 1.5 million parameters, obtaining a representativeness higher than 94 % and an accuracy around of 20 %

REUTIVAR: Model for Precision Fertigation Scheduling for Olive Orchards Using Reclaimed Water

Olive orchard is the most representative and iconic crop in Andalusia (Southern Spain). It is also considered one of the major economic activities of this region. However, due to its extensive growing area, olive orchard is also the most water-demanding crop in the Guadalquivir River Basin. In addition, its fertilization is commonly imprecise, which causes over-fertilization, especially nitrogen. This leads to pollution problems in both soil and water, threating the environment and the system sustainability. This concern is further exacerbated by the use of reclaimed water to irrigate since water is already a nutrient carrier. In this work, a model which determines the real-time irrigation and fertilization scheduling for olive orchard, applying treated wastewater, has been developed. The precision fertigation model considers weather information, both historical and forecast data, soil characteristics, hydraulic characteristics of the system, water allocation, tree nutrient status, and irrigation water quality. As a result, daily information about irrigation time and fertilizer quantity, considering the most susceptible crop stage, is provided. The proposed model showed that by using treated wastewater, additional fertilization was not required, leading to significant environmental benefits but also benefits in the total farm financial costs

Reducing the energy demand in irrigation water supply systems. Experiences from southern Europe

In recent years, many modernization processes have been undertaken in irrigation districts with a view to improving water use efficiency. In southern Spain, many irrigation districts have either been modernized or are currently being upgraded. However, as part of the modernization process some unexpected side effects have been observed. This paper analyzes the relative advantages and limitations of modernization based on field data collected in a typical Andalusian irrigation district. Although the amount of water diverted for irrigation to farms has been considerably reduced, consumptive use has increased. The costs for operation and system maintenance have dramatically risen (400%), as the energy for pumping water is much higher now compared to the gravity fed systems used previously. Then a regional analysis of the relationship between energy requirements and irrigation water applied in ten irrigation districts, in Southern Spain, has been carried out. Results show that 1000 kWh ha–1 is the energy required to apply an average depth of 2590 m3 ha-1. Finally, energy saving options are identified and discussed

Electrical properties of reduced 3YTZP ceramics consolidated by spark plasma sintering

3 mol% Yttria doped zirconia ceramics were consolidated by spark plasma sintering (SPS) at two sintering temperatures with the aim of achieving two different reduction levels. Microstructural characterization of the ceramics was performed by scanning electron microscopy (SEM). Electrical properties were investigated by means of impedance spectroscopy from room temperature up to 500 °C. The two ceramics presented a remarkably different electrical behavior. The effect of the extra electrons introduced by reduction during SPS on both the bulk and the grain boundary conductivity was analyzed and discussed.España Mineco MAT2009-11078 MAT2012-34217Junta de Andalucia P12-FQM-107

Middleware to Operate Smart Photovoltaic Irrigation Systems in Real Time

Climate change, water scarcity and higher energy requirements and electric tariff compromises the continuity of the irrigated agriculture. Precision agriculture (PA) or renewable energy sources which are based on communication and information technologies and a large amount of data are key to ensuring this economic activity and guaranteeing food security at the global level. Several works which are based on the use of PA and renewable energy sources have been developed in order to optimize different variables of irrigated agriculture such as irrigation scheduling. However, the large amount of technologies and sensors that these models need to be implemented are still far from being easily accessible and usable by farmers. In this way, a middleware called Real time Smart Solar Irrigation Manager (RESSIM) has been developed in this work and implemented in MATLABTM with the aim to provide to farmers a user-friendly tool for the daily making decision process of irrigation scheduling using a smart photovoltaic irrigation management module. RESSIM middleware was successfully tested in a real field during a full irrigation season of olive trees using a real smart photovoltaic irrigation system

EnjoyYourLAB: a mobile APP that supports the practical seasons in the Hydraulic Laboratories

EnjoyYourLAB es una aplicación móvil (APP)de apoyo a la docencia de las prácticas de laboratorio de Ingeniería Hidráulica La aplicación integra una recreación virtual de los laboratorios así como de los principales equipos que lo constituyen. A través de la App los alumnos tendrán acceso a la plataforma moodle, a las memorias de prácticas, material audiovisual e información técnica.EnjoyYourLAB is a mobile application that supports the practical seasons in the hydraulics laboratory. The App consists in a virtual rendering of the Lab and the main devices. Also, students have access to the moodle platform, guidelines for the practical exercises, audios, and technical information

Desarrollo de una plataforma IoT para la gestión del riego de precisión

Hoy en día el riego de precisión es cada vez más importante debido a la necesidad de optimizar el uso de los recursos agua y la energía, los cuales son cada vez más limitantes. Sin embargo, aplicar un riego de precisión no es una tarea fácil para la mayoría de los agricultores, ya que es necesario conocer los factores que influyen en el crecimiento del cultivo. El avance tecnológico está permitiendo que cada vez sea más factible medir, recopilar datos y analizar el manejo del riego, utilizando diferentes tipos de sensores y servidores, de esta manera se pueden calcular de forma automática las necesidades de riego y aplicar el agua de forma precisa justo cuando es más necesaria. No obstante, la mayoría de las plataformas IoT son sistemas cerrados que no permiten la integración con plataformas y sensores de terceros y se limitan a mostrar los valores de estos sensores de manera gráfica, sin entrar en el cálculo de las necesidades del cultivo y, por tanto, no son del todo útiles para funcionar como sistemas de apoyo a la toma de decisiones. El presente trabajo pretende mostrar la metodología para el desarrollo de una plataforma IoT de bajo coste para el riego de precisión, así como la integración de diferentes estrategias de riego en la misma. Para desarrollar la plataforma se ha utilizado el framework Django, de código abierto. Con el fin de conectar diferentes sensores a la plataforma se ha diseñado un dispositivo de toma de datos, de código abierto y eficiente energéticamente, que soporta una gran cantidad de protocolos de comunicación. Finalmente se ha calculado una programación de riego para una finca de estudio. Dicha finca consta de 44 hectáreas de almendros en intensivo y organizados en dos sectores de riego. Las estrategias se han desarrollado con el lenguaje de programación Python y se conectan automáticamente a la red de estaciones meteorológicas de la AEMET y a la página web de elTiempo.es para obtener tanto datos climáticos de la serie histórica como las predicciones para los próximos días. Todos estos datos se muestran en la plataforma de forma gráfica, a través de la cual también se pueden modificar las variables relacionadas con el sistema hidráulico, el cultivo y la explotació

Construction and content validation of a measurement tool to evaluate person-centered therapeutic relationships in physiotherapy services

Objectives: this study sought to develop a tool for evaluating person-centered therapeutic relationships within physiotherapy services, and to examine the content validity of the same. Methods: a mixed qualitative and quantitative study was performed in three distinct phases: 1) the items were generated based on a literature review and a content analysis of focus groups of patients and physiotherapists; 2) an e-Delphi survey process was performed based on three rounds to select and refine the proposed questionnaire; 3) two rounds of cognitive interviews were conducted to evaluate the comprehension of items, the clarity of language and the appropriateness and relevance of content. Results: thirty-one items were generated based on the seven domains identified after the analysis of four focus groups of physiotherapists and four patient focus groups. Nine experts participated in the e-Delphi survey. Fifty-five patients participated in the two rounds of the cognitive pre-tests. Participating patients were from public and private physical therapy services. Based on the participants' suggestions, four items were removed, and four were added, whereas 16 were reworded. Conclusions: the final tool comprised 31 items divided into seven domains. The response format was based on a 5-point Likert frequency scale. The response options ranged from "strongly agree" to "strongly disagree"

Ageing-resistant zirconia/graphene-based nanostructures composites for use as biomaterials

This work explores the incorporation of graphene-based two-dimensional nanostructures as moisture barriers to delay hydrothermal ageing of yttria-stabilized zirconia and strengthen its use in biomedical applications. Two sets of highly dense zirconia composites incorporating multilayered graphene with very different lateral dimensions, few layer graphene and exfoliated graphene nanoplatelets, were prepared. The effect of the addition of graphene nanostructures on zirconia ageing was investigated by conducting accelerated hydrothermal degradation experiments in an autoclave. An improved resistance to low-temperature degradation and a high tolerance to damage were achieved in the composites compared to those of monolithic zirconia. The incorporation of 1 vol% multilayered graphene was very effective in restricting the hydrothermal degradation. In particular, the composite incorporating exfoliated graphene nanosheets exhibited outstanding resistance to ageing because of their fine dispersion throughout the matrix, which effectively seemed to restrict grain growth and slow the propagation of the transformation front to the ceramic bulk.Ministerio de Ciencia, Innovación y Universidades PGC 2018-101377-B-100Universidad de Sevilla 2018/0000066