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Methodology for flushing pressurised irrigation networks for fertigation and operation maintenance purposes

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Methodology for flushing pressurised irrigation networks for fertigation and operation maintenance purposes

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dc.contributor.author Jiménez Bello, Miguel Angel es_ES
dc.contributor.author Alonso Campos, J. C. es_ES
dc.contributor.author Manzano Juarez, Juan es_ES
dc.contributor.author Martínez Alzamora, Fernando es_ES
dc.date.accessioned 2022-11-07T19:01:41Z
dc.date.available 2022-11-07T19:01:41Z
dc.date.issued 2021-05 es_ES
dc.identifier.issn 0342-7188 es_ES
dc.identifier.uri http://hdl.handle.net/10251/189383
dc.description.abstract [EN] Pressurised irrigation networks with a certain degree of automation allow centralized fertigation and maintenance operations such as cleaning subunits and preventing the proliferation of invasive species such as zebra mussels. Until now, there is no methodology that guarantees the total cleaning of the network of a substance in the shortest possible time. In the same way, it does not exist to guarantee reaching all consumption points with a certain concentration of a substance, injecting the minimum possible amount. For that purpose, a general novel methodology has been developed that makes use of the network¿s hydraulic model and parallel multi-objective genetic algorithms to flush the network of a certain substance or to get it to all consumption points in the shortest possible time and supplying a minimum volume. This method assumes that the available pressure at the source is always over a minimum value. The arrival times to the consumption points are minimized and the injected volume is reduced to the minimum of replacement, that is, the volume of the network pipes. The methodology applied to the study case allowed the entire network to be flushed in a minimum time of 2.46 h. On a normal irrigation day, without making any changes to the irrigation schedule the time to completely flush the network is 11.76 h. Furthermore, the injected volume differs greatly from the total volume of the pipes. es_ES
dc.description.sponsorship This study has been partially supported by the ADAPTAMED project (RTI2018-101483-B-I00), funded by the Ministerio de Economia y Competitividad (MINECO) of Spain and with EU FEDER funds. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Irrigation Science es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Irrigation networks es_ES
dc.subject Fertigation es_ES
dc.subject Flushing es_ES
dc.subject Tracing es_ES
dc.subject Zebra mussels es_ES
dc.title Methodology for flushing pressurised irrigation networks for fertigation and operation maintenance purposes es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00271-021-00724-4 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-101483-B-I00/ES/PLANIFICACION, DISEÑO Y EVALUACION DE LA ADAPTACION DE CUENCAS MEDITERRANEAS A ESCENARIOS SOCIOECONOMICOS Y DE CAMBIO CLIMATICO/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Jiménez Bello, MA.; Alonso Campos, JC.; Manzano Juarez, J.; Martínez Alzamora, F. (2021). Methodology for flushing pressurised irrigation networks for fertigation and operation maintenance purposes. Irrigation Science. 39(3):375-384. https://doi.org/10.1007/s00271-021-00724-4 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s00271-021-00724-4 es_ES
dc.description.upvformatpinicio 375 es_ES
dc.description.upvformatpfin 384 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 39 es_ES
dc.description.issue 3 es_ES
dc.relation.pasarela S\433019 es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.description.references Aldridge DC, Elliott P, Moggridge GD (2004) The recent and rapid spread of the zebra mussel (Dreissena polymorpha) in Great Britain. Biol Conserv 119:253–261. https://doi.org/10.1016/j.biocon.2003.11.008 es_ES
dc.description.references Alonso Campos JC, Jiménez-Bello MA, Martínez Alzamora F (2020a) Real-time energy optimization of irrigation scheduling by parallel multi-objective genetic algorithms. Agric Water Manag. https://doi.org/10.1016/j.agwat.2019.105857 es_ES
dc.description.references Alva AK, Mattos D, Quaggio JA (2008) Advances in nitrogen fertigation of citrus. J Crop Improv 22:121–146. https://doi.org/10.1080/15427520802072967 es_ES
dc.description.references Azad N, Behmanesh J, Rezaverdinejad V et al (2018) Developing an optimization model in drip fertigation management to consider environmental issues and supply plant requirements. Agric Water Manag 208:344–356. https://doi.org/10.1016/j.agwat.2018.06.030 es_ES
dc.description.references Bracy RP, Parish RL, Rosendale RM (2003) Fertigation uniformity affected by injector type. HortTechnology 13:103–105. https://doi.org/10.21273/horttech.13.1.0103 es_ES
dc.description.references Burt C (1998) Fertigation. Irrigation Training and Research Center California Polytechnic State University, San Luis Obispo es_ES
dc.description.references CAJAMAR (2014) Limpieza de la instalación de riego. Boletín nº 114. https://www.cajamar.es/pdf/bd/agroalimentario/innovacion/investigacion/documentos-y-programas/boletin-huerto-114-1496655961.pdf es_ES
dc.description.references Confederación hidrográfica del Ebro (2014) Mejillón cebra; Manual de control para instalaciones afectadas. 2ª ed. Zaragoza, p 42. http://www.chebro.es/contenido.streamFichero.do?idBinario=18109 es_ES
dc.description.references Davis MJ, Janke R, Taxon TN (2018) Mass imbalances in EPANET water-quality simulations. Drink Water Eng Sci 11:25–47. https://doi.org/10.5194/dwes-11-25-2018 es_ES
dc.description.references Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6:182–197. https://doi.org/10.1109/4235.996017 es_ES
dc.description.references Durillo JJ, Nebro AJ (2011) JMetal: a Java framework for multi-objective optimization. Adv Eng Softw 42:760–771. https://doi.org/10.1016/j.advengsoft.2011.05.014 es_ES
dc.description.references Fan J, Wu L, Zhang F et al (2017) Evaluation of drip fertigation uniformity affected by injector type, pressure difference and lateral layout. Irrig Drain 66:520–529. https://doi.org/10.1002/ird.2136 es_ES
dc.description.references Fares A, Abbas F, Deb SK, Paramasivam S (2009) Citrus chemigation. In: Tree and forestry science and biotechnology, vol 3, special issue 1. Global Science Books, pp 22–31 es_ES
dc.description.references Fernández García I, Rodríguez Díaz JA, Camacho Poyato E, Montesinos P (2013) Optimal operation of pressurized irrigation networks with several supply sources. Water Resour Manag 27:2855–2869. https://doi.org/10.1007/s11269-013-0319-y es_ES
dc.description.references Fernández García I, Montesinos P, Camacho Poyato E, Rodríguez Díaz JA (2017) Optimal design of pressurized irrigation networks to minimize the operational cost under different management scenarios. Water Resour Manag 31:1995–2010. https://doi.org/10.1007/s11269-017-1629-2 es_ES
dc.description.references Gallardo B, Aldridge DC (2020) Priority setting for invasive species management by the water industry. Water Res 23:115771. https://doi.org/10.1016/j.watres.2020.115771 es_ES
dc.description.references González Perea R, Moreno MA, Ortega JF et al (2020) Dynamic simulation tool of fertigation in drip irrigation subunits. Comput Electron Agric 173:105434. https://doi.org/10.1016/j.compag.2020.105434 es_ES
dc.description.references Iglesias-Rey PL, Martínez-Solano FJ, Ribelles-Aquilar JV (2017) Extending EPANET capabilities with add-in tools. In: Procedia engineering. Elsevier Ltd, pp 626–634 es_ES
dc.description.references Jiménez-Bello MA, Martínez Alzamora F, Bou Soler V, Ayala HJB (2010) Methodology for grouping intakes of pressurised irrigation networks into sectors to minimise energy consumption. Biosyst Eng 105:429–438. https://doi.org/10.1016/j.biosystemseng.2009.12.014 es_ES
dc.description.references Jiménez-Bello MA, Alzamora FM, Castel JR, Intrigliolo DS (2011a) Validation of a methodology for grouping intakes of pressurized irrigation networks into sectors to minimize energy consumption. Agric Water Manag 102:46–53. https://doi.org/10.1016/j.agwat.2011.10.005 es_ES
dc.description.references Jimenez-Bello MA, Martínez F, Bou V, Bartolín H (2011b) Analysis, assessment, and improvement of fertilizer distribution in pressure irrigation systems. Irrig Sci 29:45–53. https://doi.org/10.1007/s00271-010-0215-7 es_ES
dc.description.references Jiménez-Bello MA, Royuela A, Manzano J et al (2015) Methodology to improve water and energy use by proper irrigation scheduling in pressurised networks. Agric Water Manag 149:91–101. https://doi.org/10.1016/j.agwat.2014.10.026 es_ES
dc.description.references Keller J, Bliesner RD (1990) Sprinkle and trickle irrigation. Van Nostrand Reinhold, New York, pp 652 es_ES
dc.description.references Li J, Meng Y, Li B (2007) Field evaluation of fertigation uniformity as affected by injector type and manufacturing variability of emitters. Irrig Sci 25:117–125. https://doi.org/10.1007/s00271-006-0039-7 es_ES
dc.description.references Morales-Hernández M, Playán E, Gimeno Y et al (2018) Assessing zebra mussel colonization of collective pressurized irrigation networks through pressure measurements and simulations. Agric Water Manag 204:301–313. https://doi.org/10.1016/j.agwat.2018.04.025 es_ES
dc.description.references Moreira Barradas JM, Matula S, Dolezal F (2012) A decision support system-fertigation simulator (DSS-FS) for design and optimization of sprinkler and drip irrigation systems. Comput Electron Agric 86:111–119. https://doi.org/10.1016/j.compag.2012.02.015 es_ES
dc.description.references Ortega-Reig M, Sanchis-Ibor C, Palau-Salvador G et al (2017) Institutional and management implications of drip irrigation introduction in collective irrigation systems in Spain. Agric Water Manag 187:164–172. https://doi.org/10.1016/j.agwat.2017.03.009 es_ES
dc.description.references Reca J, Martínez J (2006) Genetic algorithms for the design of looped irrigation water distribution networks. Water Resour Res. https://doi.org/10.1029/2005WR004383 es_ES
dc.description.references Rossman LA (2000) EPANET 2: users manual. National Risk Management Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Cincinnati, OH, pp 300 es_ES
dc.subject.ods 02.- Poner fin al hambre, conseguir la seguridad alimentaria y una mejor nutrición, y promover la agricultura sostenible es_ES


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