- -

Joint identification of contaminant source location, initial release time, and initial solute concentration in an aquifer via ensemble Kalman filtering

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Joint identification of contaminant source location, initial release time, and initial solute concentration in an aquifer via ensemble Kalman filtering

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Xu, Teng es_ES
dc.contributor.author Gómez-Hernández, J. Jaime es_ES
dc.date.accessioned 2018-02-19T05:11:34Z
dc.date.available 2018-02-19T05:11:34Z
dc.date.issued 2016 es_ES
dc.identifier.issn 0043-1397 es_ES
dc.identifier.uri http://hdl.handle.net/10251/98067
dc.description.abstract [EN] When a contaminant is detected in a drinking well, source location, initial contaminant release time, and initial contaminant concentration are, in many cases, unknown; the responsible party may have disappeared and the identification of when and where the contamination happened may become difficult. Although contaminant source identification has been studied extensively in the last decades, we proposeto our knowledge, for the first timethe use of the ensemble Kalman filter (EnKF), which has proven to be a powerful algorithm for inverse modeling. The EnKF is tested in a two-dimensional synthetic deterministic aquifer, identifying, satisfactorily, the source location, the release time, and the release concentration, together with an assessment of the uncertainty associated with this identification. es_ES
dc.description.sponsorship Financial support to carry out this work was received from the Spanish Ministry of Economy and Competitiveness through project CGL2014-59841-P. All data used in this analysis are available from the authors. es_ES
dc.language Inglés es_ES
dc.publisher John Wiley & Sons es_ES
dc.relation.ispartof Water Resources Research es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Ensemble Kalman filter es_ES
dc.subject Contaminant source identification, Inverse modeling es_ES
dc.subject Normal-score transform es_ES
dc.subject.classification INGENIERIA HIDRAULICA es_ES
dc.title Joint identification of contaminant source location, initial release time, and initial solute concentration in an aquifer via ensemble Kalman filtering es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1002/2016WR019111 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//CGL2014-59841-P/ES/¿QUIEN HA SIDO?/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Ingeniería del Agua y del Medio Ambiente - Institut Universitari d'Enginyeria de l'Aigua i Medi Ambient es_ES
dc.description.bibliographicCitation Xu, T.; Gómez-Hernández, JJ. (2016). Joint identification of contaminant source location, initial release time, and initial solute concentration in an aquifer via ensemble Kalman filtering. Water Resources Research. 52(8):6587-6595. https://doi.org/10.1002/2016WR019111 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1002/2016WR019111 es_ES
dc.description.upvformatpinicio 6587 es_ES
dc.description.upvformatpfin 6595 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 52 es_ES
dc.description.issue 8 es_ES
dc.relation.pasarela S\332202 es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES
dc.description.references Aral, M. M., Guan, J., & Maslia, M. L. (2001). Identification of Contaminant Source Location and Release History in Aquifers. Journal of Hydrologic Engineering, 6(3), 225-234. doi:10.1061/(asce)1084-0699(2001)6:3(225) es_ES
dc.description.references Butera, I., Tanda, M. G., & Zanini, A. (2012). Simultaneous identification of the pollutant release history and the source location in groundwater by means of a geostatistical approach. Stochastic Environmental Research and Risk Assessment, 27(5), 1269-1280. doi:10.1007/s00477-012-0662-1 es_ES
dc.description.references Chen, Y., Oliver, D. S., & Zhang, D. (2009). Data assimilation for nonlinear problems by ensemble Kalman filter with reparameterization. Journal of Petroleum Science and Engineering, 66(1-2), 1-14. doi:10.1016/j.petrol.2008.12.002 es_ES
dc.description.references Cupola, F., Tanda, M. G., & Zanini, A. (2014). Laboratory sandbox validation of pollutant source location methods. Stochastic Environmental Research and Risk Assessment, 29(1), 169-182. doi:10.1007/s00477-014-0869-4 es_ES
dc.description.references Evensen, G. (2003). The Ensemble Kalman Filter: theoretical formulation and practical implementation. Ocean Dynamics, 53(4), 343-367. doi:10.1007/s10236-003-0036-9 es_ES
dc.description.references Gorelick, S. M., Evans, B., & Remson, I. (1983). Identifying sources of groundwater pollution: An optimization approach. Water Resources Research, 19(3), 779-790. doi:10.1029/wr019i003p00779 es_ES
dc.description.references Gzyl, G., Zanini, A., Frączek, R., & Kura, K. (2014). Contaminant source and release history identification in groundwater: A multi-step approach. Journal of Contaminant Hydrology, 157, 59-72. doi:10.1016/j.jconhyd.2013.11.006 es_ES
dc.description.references Franssen, H. J. H., & Kinzelbach, W. (2009). Ensemble Kalman filtering versus sequential self-calibration for inverse modelling of dynamic groundwater flow systems. Journal of Hydrology, 365(3-4), 261-274. doi:10.1016/j.jhydrol.2008.11.033 es_ES
dc.description.references Ma, R., Zheng, C., Zachara, J. M., & Tonkin, M. (2012). Utility of bromide and heat tracers for aquifer characterization affected by highly transient flow conditions. Water Resources Research, 48(8). doi:10.1029/2011wr011281 es_ES
dc.description.references Mahar, P. S. (2000). Water Resources Management, 14(3), 209-227. doi:10.1023/a:1026527901213 es_ES
dc.description.references McDonald , M. A. Harbaugh 1988 es_ES
dc.description.references Michalak, A. M., & Kitanidis, P. K. (2003). A method for enforcing parameter nonnegativity in Bayesian inverse problems with an application to contaminant source identification. Water Resources Research, 39(2). doi:10.1029/2002wr001480 es_ES
dc.description.references Michalak, A. M., & Kitanidis, P. K. (2004). Application of geostatistical inverse modeling to contaminant source identification at Dover AFB, Delaware. Journal of Hydraulic Research, 42(sup1), 9-18. doi:10.1080/00221680409500042 es_ES
dc.description.references Neupauer, R. M., & Lin, R. (2006). Identifying sources of a conservative groundwater contaminant using backward probabilities conditioned on measured concentrations. Water Resources Research, 42(3). doi:10.1029/2005wr004115 es_ES
dc.description.references Neupauer, R. M., & Wilson, J. L. (1999). Adjoint method for obtaining backward-in-time location and travel time probabilities of a conservative groundwater contaminant. Water Resources Research, 35(11), 3389-3398. doi:10.1029/1999wr900190 es_ES
dc.description.references Woodbury, A., Sudicky, E., Ulrych, T. J., & Ludwig, R. (1998). Three-dimensional plume source reconstruction using minimum relative entropy inversion. Journal of Contaminant Hydrology, 32(1-2), 131-158. doi:10.1016/s0169-7722(97)00088-0 es_ES
dc.description.references Woodbury, A. D., & Ulrych, T. J. (1996). Minimum Relative Entropy Inversion: Theory and Application to Recovering the Release History of a Groundwater Contaminant. Water Resources Research, 32(9), 2671-2681. doi:10.1029/95wr03818 es_ES
dc.description.references Xu, T., & Gómez-Hernández, J. J. (2015). Probability fields revisited in the context of ensemble Kalman filtering. Journal of Hydrology, 531, 40-52. doi:10.1016/j.jhydrol.2015.06.062 es_ES
dc.description.references Xu, T., Jaime Gómez-Hernández, J., Zhou, H., & Li, L. (2013). The power of transient piezometric head data in inverse modeling: An application of the localized normal-score EnKF with covariance inflation in a heterogenous bimodal hydraulic conductivity field. Advances in Water Resources, 54, 100-118. doi:10.1016/j.advwatres.2013.01.006 es_ES
dc.description.references Yeh, H.-D., Chang, T.-H., & Lin, Y.-C. (2007). Groundwater contaminant source identification by a hybrid heuristic approach. Water Resources Research, 43(9). doi:10.1029/2005wr004731 es_ES
dc.description.references Zheng , C. 2010 MT3DMS v5. 3 Supplemental User's Guide Technical Report to the US Army Engineer Research and Development Center es_ES
dc.description.references Zhou, H., Gómez-Hernández, J. J., Hendricks Franssen, H.-J., & Li, L. (2011). An approach to handling non-Gaussianity of parameters and state variables in ensemble Kalman filtering. Advances in Water Resources, 34(7), 844-864. doi:10.1016/j.advwatres.2011.04.014 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem