DESIDS: An Integrated Decision Support System for the Planning, Analysis, Management and Rehabilitation of Pressurised Irrigation Distribution Systems

Pressurized irrigation distribution systems (PIDSs) play a vital role in irrigation intensification, especially in the Mediterranean region. The design, operation and management of these systems can be complex, as they involve several intertwined processes which need to be considered simultaneously. For this reason, numerous decision support systems (DSSs) have been developed and are available to deal with these processes, but as independent components. To this end, a comprehensive DSS called DESIDS has been developed and tested. This DSS has been developed to bear in mind the needs of irrigation district managers for an integrated tool that can assist them in taking strategic decisions for managing and developing reliable, adequate and sustainable water distribution plans which provide the best services to farmers. Hence, four modules were integrated in DESIDS: (i) irrigation demand and scheduling module; (ii) hydraulic analysis module; (iii) operation and management module; and (iv) design and rehabilitation module. DESIDS was tested on different case studies, proving itself a valuable tool for irrigation district managers, as it provides a wide range of decision options for the proper operation and management of PIDSs. The developed DSS can be used as a platform for future integrations and expansions, and to include other processes needed for better decision-making support

Estudio de la gestión del agua de riego y aplicación de las técnicas de benchmarking a las zonas regables de Andalucía

Las técnicas de benchmarking son una metodología para la detección de las mejoras prácticas mediante comparaciones entre distintas organizaciones. De esta forma, las organizaciones con peores rendimientos, en algún determinado aspecto, podrán mejorar al adoptar las prácticas existentes en las mejores. En esta Tesis, se aplican las técnicas de benchmarking a diversas Comunidades de Regantes, utilizando para detectar las diferencias existentes entre unas y otras, un conjunto de indicadores de gestión desarrollados por el IPTRID (International Programme for Technology and Research in Irrigation and Drainaje) y una amplicación de indicadores financieros desarrollados para este trabajo. La aplicación conjunta de los indicadores y de las técnicas de benchmarking, ha permitido clasificar (mediante técnicas de análisis de fronteras de producción, análisis de clúster y de componentes principales) los distintos tipos de Comunidades de Regantes existentes en Andalucía y detectar las que poseen una gestión más eficiente. Además, se desarrolla un Índice de Calidad, el cual es una herramienta, basada en técnicas de análisis multivariante de datos, para la aplicación del proceso de benchmarking y facilita las comparacione

Generating Hydrants’ Configurations for Efficient Analysis and Management of Pressurized Irrigation Distribution Systems

Water scarcity is a mounting problem in arid and semi-arid regions such as the Mediterranean. Therefore, smarter and more effective water management is required, especially in irrigated agriculture. One of the most challenging uncertainties in the operation of on-demand collective Pressurized Irrigation Distribution Systems (PIDSs) is to know, a priori, the number and the position of hydrants in simultaneous operation. To this end, a model was developed to generate close to reality operating hydrants configurations, with 15, 30 or 60 min time steps, by estimating the irrigation scheduling for the entire irrigation season, using climatic, crop and soil data. The model is incorporated in an integrated DSS called Decision Support for Irrigation Distribution Systems (DESIDS) and links two of its modules, namely, the irrigation demand and scheduling module and the hydraulic analysis module. The latter is used to perform two types of analyses for the performance assessment and decision-making processes. The model was used in a real case study in Italy to generate hydrants’ operation taking into consideration irrigation scheduling. The results show that during the peak period, hydrants simultaneity topped 62%. The latter created pressure deficit in some hydrants, thus reducing the volume of water supplied for irrigation by up to 87 m3 in a single hydrant during the peak demand day. The developed model proved to be an important tool for irrigation managers, as it provides vital information with great flexibility and the ability to assess and predict the operation of PIDSs at any period during the irrigation season

Modelling and Management of Irrigation System

Irrigation is becoming an activity of precision, where combining information collected from various sources is necessary to optimally manage resources. New management strategies, such as big data techniques, sensors, artificial intelligence, unmanned aerial vehicles (UAV), and new technologies in general, are becoming more relevant every day. As such, modeling techniques, both at the water distribution network and the farm levels, will be essential to gather information from various sources and offer useful recommendations for decision-making processes. In this book, 10 high quality papers were selected that cover a wide range of issues that are relevant to the different aspects related to irrigation management: water source and distribution network, plot irrigation systems, and crop water management

Development of a Low-Cost Open-Source Platform for Smart Irrigation Systems

Nowadays, smart irrigation is becoming an essential goal in agriculture, where water and energy are increasingly limited resources. Its importance will grow in the coming years in the agricultural sector where the optimal use of resources and environmental sustainability are becoming more important every day. However, implementing smart irrigation is not an easy task for most farmers since it is based on knowledge of the different processes and factors that determine the crop water requirements. Thanks to technological developments, it is possible to design new tools such as sensors or platforms that can be connected to soil-water-plant-atmosphere models to assist in the optimization and automation of irrigation. In this work, a low-cost, open-source IoT system for smart irrigation has been developed that can be easily integrated with other platforms and supports a large number of sensors. The platform uses the FIWARE framework together with customized components and can be deployed using edge computing and/or cloud computing systems. To improve decision-making, the platform integrates an irrigation model that calculates soil water balance and wet bulb dimensions to determine the best irrigation strategy for drip irrigation systems. In addition, an energy efficient open-source datalogger has been designed. The datalogger supports a wide range of communications and is compatible with analog sensors, SDI-12 and RS-485 protocols. The IoT system has been deployed on an olive farm and has been in operation for one irrigation season. Based on the results obtained, advantages of using these technologies over traditional methods are discussed

Optimización del coste energético en redes de riego a presión mediante su rehablitación

La gestión óptima de los recursos agua y energía en todos los sectores económicos, incluida la agricultura, tiene cada vez más importancia. El sector del riego, que ha experimentado una profunda transformación hacia sistemas de riego a presión, más eficientes en el uso del agua, pero con mayor demanda energética, también requiere medidas encaminadas al aumento de la eficiencia en la gestión de estos recursos. Este trabajo presenta una metodología fundamentada en la rehabilitación de redes de riego, mediante su rediseño, que determina el funcionamiento óptimo de la estación de bombeo que conlleva un coste de operación mínimo. La estrategia planteada se ha desarrollado en varios módulos. El primero de ellos consiste en la aplicación del algoritmo multiobjetivo NSGA-II, enlazado al simulador hidráulico EPANET, que minimiza el coste de rediseño de la red y de operación considerando un 100 % de simultaneidad de hidrantes. El segundo módulo contempla un análisis de la operación a la demanda de la red, generando múltiples patrones aleatorios de hidrantes abiertos/ cerrados. El tercer módulo analiza la operación a la demanda de la red en cada uno de los rediseños propuestos en el primer módulo y determina el funcionamiento de la estación de bombeo que minimiza el coste energético, teniendo en cuenta la tarifa eléctrica. La metodología propuesta se ha analizado en la CR El Villar (Sevilla) proporcionando un frente de Pareto que ofrece soluciones quasi óptimas con distinto grado de satisfacción de los objetivos propuestos. Mediante el posterior análisis financiero se ha determinado que la solución más viable a largo plazo, considerando una vida útil para la red de riego de 40 años y un interés del 5 %, conlleva un coste de inversión asociado al reemplazo de tuberías de 205.627 €, un coste de operación anual de 300.532 € y un coste total (inversión en el diseño, costes asociados a la renovación de las bombas y coste de operación) a lo largo de la vida útil de 6.019.447 €, lo que supondría un importante ahorro económico para la comunidad aplicando mayores volúmenes de agua para satisfacer las necesidades de los cultivos, en comparación con la situación actual en la que se aplica un riego deficitario debido a los elevados costes energéticos

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

Energy Recovery Potential in Industrial and Municipal Wastewater Networks Using Micro-Hydropower in Spain

The use of micro-hydropower (MHP) for energy recovery in water distribution networks is becoming increasingly widespread. The incorporation of this technology, which offers low-cost solutions, allows for the reduction of greenhouse gas emissions linked to energy consumption. In this work, the MHP energy recovery potential in Spain from all available wastewater discharges, both municipal and private industrial, was assessed, based on discharge licenses. From a total of 16,778 licenses, less than 1% of the sites presented an MHP potential higher than 2 kW, with a total power potential between 3.31 and 3.54 MW. This total was distributed between industry, fish farms and municipal wastewater treatment plants following the proportion 51–54%, 14–13% and 35–33%, respectively. The total energy production estimated reached 29 GWh∙year−1, from which 80% corresponded to sites with power potential over 15 kW. Energy-related industries, not included in previous investigations, amounted to 45% of the total energy potential for Spain, a finding which could greatly influence MHP potential estimates across the world. The estimated energy production represented a potential CO2 emission savings of around 11 thousand tonnes, with a corresponding reduction between M€ 2.11 and M€ 4.24 in the total energy consumption in the country

Energy Saving Measures in Pressurized Irrigation Networks: A New Challenge for Power Generation

In Spain and other countries, open channel distribution networks have been replaced by on demand-pressurized networks to improve the water-use efficiency of the water distribution systems, but at the same time the energy requirements have dramatically risen. Under this scenario, methodologies to reduce the energy consumption are critical such as: irrigation network sectoring, critical hydrant detection, improving the efficiency of the pumping system and the irrigation system, or introducing solar energy for water supply. But once these measures are undertaken, the recovery of the energy inherent in excess pressure in the network should be investigated. Hydropower energy recovery in irrigation is still largely unexplored and requires further investigation and demonstration. All of these methodologies should be considered as useful tools for both, the reduction of energy consumption and the recovery of the excess energy in pressurized irrigation networks. To accomplish this, the REDAWN project (Reducing Energy Dependency in Atlantic Area Water Networks) aims to improve the energy efficiency of water networks through the installation of innovative micro-hydropower (MHP) technology. This technology will recover wasted energy in existing pipe networks across irrigation, public water supply, process industry, and waste-water network settings

Pump-as-Turbine Selection Methodology for Energy Recovery in Irrigation Networks: Minimising the Payback Period

In pressurized irrigation networks, energy reaches around 40% of the total water costs. Pump-as-Turbines (PATs) are a cost-effective technology for energy recovery, although they can present low efficiencies when operating outside of the best efficiency point (BEP). Flow fluctuations are very important in on-demand irrigation networks. This makes flow prediction and the selection of the optimal PAT more complex. In this research, an advanced statistical methodology was developed, which predicts the monthly flow fluctuations and the duration of each flow value. This was used to estimate the monthly time for which a PAT would work under BEP conditions and the time for which it would work with lower efficiencies. In addition, the optimal PAT power for each Excess Pressure Point (EPP) studied was determined following the strategy of minimising the PAT investment payback period (PP). The methodology was tested in Sector VII of the right bank of the Bembézar River (BMD), in Southern Spain. Five potential sites for PAT installation were found. The results showed a potential energy recovery of 93.9 MWh and an annual energy index per irrigated surface area of 0.10 MWh year−1 ha−1. Renewable energy will become increasingly important in the agriculture sector, to reduce both water costs and the contribution to climate change. PATs represent an attractive technology that can help achieve such goals