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A coupled stochastic inverse-management framework for dealing with nonpoint agriculture pollution under groundwater parameter uncertainty

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A coupled stochastic inverse-management framework for dealing with nonpoint agriculture pollution under groundwater parameter uncertainty

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dc.contributor.author Llopis Albert, Carlos es_ES
dc.contributor.author Palacios Marqués, Daniel es_ES
dc.contributor.author Merigó, José M. es_ES
dc.date.accessioned 2016-02-01T08:55:03Z
dc.date.available 2016-02-01T08:55:03Z
dc.date.issued 2014-04-16
dc.identifier.issn 0022-1694
dc.identifier.uri http://hdl.handle.net/10251/60407
dc.description.abstract In this paper a methodology for the stochastic management of groundwater quality problems is presented, which can be used to provide agricultural advisory services. A stochastic algorithm to solve the coupled flow and mass transport inverse problem is combined with a stochastic management approach to develop methods for integrating uncertainty; thus obtaining more reliable policies on groundwater nitrate pollution control from agriculture. The stochastic inverse model allows identifying non-Gaussian parameters and reducing uncertainty in heterogeneous aquifers by constraining stochastic simulations to data. The management model determines the spatial and temporal distribution of fertilizer application rates that maximizes net benefits in agriculture constrained by quality requirements in groundwater at various control sites. The quality constraints can be taken, for instance, by those given by water laws such as the EU Water Framework Directive (WFD). Furthermore, the methodology allows providing the trade-off between higher economic returns and reliability in meeting the environmental standards. Therefore, this new technology can help stakeholders in the decision-making process under an uncertainty environment. The methodology has been successfully applied to a 2D synthetic aquifer, where an uncertainty assessment has been carried out by means of Monte Carlo simulation techniques. (c) 2014 Elsevier B.V. All rights reserved. es_ES
dc.language Español es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Journal of Hydrology es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Stochastic inversion es_ES
dc.subject Gradual deformation es_ES
dc.subject Non-Gaussian es_ES
dc.subject Nitrate pollution es_ES
dc.subject Fertilizer standards es_ES
dc.subject Optimization es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.subject.classification INGENIERIA MECANICA es_ES
dc.title A coupled stochastic inverse-management framework for dealing with nonpoint agriculture pollution under groundwater parameter uncertainty es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.jhydrol.2014.01.021
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses es_ES
dc.description.bibliographicCitation Llopis Albert, C.; Palacios Marqués, D.; Merigó, JM. (2014). A coupled stochastic inverse-management framework for dealing with nonpoint agriculture pollution under groundwater parameter uncertainty. Journal of Hydrology. 511:10-16. doi:10.1016/j.jhydrol.2014.01.021 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.jhydrol.2014.01.021 es_ES
dc.description.upvformatpinicio 10 es_ES
dc.description.upvformatpfin 16 es_ES
dc.type.version info:eu repo/semantics/publishedVersion es_ES
dc.description.volume 511 es_ES
dc.relation.senia 281846 es_ES


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