Joint estimation of states and parameters of two-layer coastal aquifers based on ENKF

Management of groundwater resources has become a source of heated discussion in coastal hydrogeology. Thus, we introduced an Ensemble Kalman Filter (ENKF) into a two-layer confined groundwater model based on the interactive operation between the MATLAB and GMS to investigate the capability of ENKF u...

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Autores principales:	Xiaohua Huang, Guodong Liu, Yu Chen, Jun Li
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	coastal areas in tianjin data assimilation ensemble kalman filter (enkf) groundwater level forecasting hydraulic conductivity identification Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
Acceso en línea:	https://doaj.org/article/cf974c4c427f428191a819ba50719ff6
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id	oai:doaj.org-article:cf974c4c427f428191a819ba50719ff6
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spelling	oai:doaj.org-article:cf974c4c427f428191a819ba50719ff62021-11-06T07:12:52ZJoint estimation of states and parameters of two-layer coastal aquifers based on ENKF1606-97491607-079810.2166/ws.2020.378https://doaj.org/article/cf974c4c427f428191a819ba50719ff62021-05-01T00:00:00Zhttp://ws.iwaponline.com/content/21/3/1277https://doaj.org/toc/1606-9749https://doaj.org/toc/1607-0798Management of groundwater resources has become a source of heated discussion in coastal hydrogeology. Thus, we introduced an Ensemble Kalman Filter (ENKF) into a two-layer confined groundwater model based on the interactive operation between the MATLAB and GMS to investigate the capability of ENKF under complex conditions and obtain a relatively new forecasting method. ENKF was employed to assimilate and forecast groundwater levels, and invert the hydraulic conductivity (K) of the heterogeneous study area, where the initial values of K were obtained by using trial-and-error based on the two-period groundwater levels. After comparing the efficiencies in forecasting groundwater levels among ENKF, the modified model, and the initial model, four major conclusions could be drawn. ENKF converged fast when forecasting groundwater levels and the accuracy was high. Various convergent results would be represented by ENKF when K in different layers was observed in the same error. ENKF performed better than the initial simulation when monitored data subjected to a certain range of interferences. Forecasting accuracy in the middle of the study area could be enhanced by the large improvement degree of K through ENKF. Therefore, this analytical method could be a theoretical reference for groundwater resources management in coastal areas. HIGHLIGHTS First employed ENKF into a two-layer confined coastal model.; Modified groundwater model by ENKF.; Provided the theoretical reference for groundwater resources management in coastal areas.;Xiaohua HuangGuodong LiuYu ChenJun LiIWA Publishingarticlecoastal areas in tianjindata assimilationensemble kalman filter (enkf)groundwater level forecastinghydraulic conductivity identificationWater supply for domestic and industrial purposesTD201-500River, lake, and water-supply engineering (General)TC401-506ENWater Supply, Vol 21, Iss 3, Pp 1277-1290 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	coastal areas in tianjin data assimilation ensemble kalman filter (enkf) groundwater level forecasting hydraulic conductivity identification Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
spellingShingle	coastal areas in tianjin data assimilation ensemble kalman filter (enkf) groundwater level forecasting hydraulic conductivity identification Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506 Xiaohua Huang Guodong Liu Yu Chen Jun Li Joint estimation of states and parameters of two-layer coastal aquifers based on ENKF
description	Management of groundwater resources has become a source of heated discussion in coastal hydrogeology. Thus, we introduced an Ensemble Kalman Filter (ENKF) into a two-layer confined groundwater model based on the interactive operation between the MATLAB and GMS to investigate the capability of ENKF under complex conditions and obtain a relatively new forecasting method. ENKF was employed to assimilate and forecast groundwater levels, and invert the hydraulic conductivity (K) of the heterogeneous study area, where the initial values of K were obtained by using trial-and-error based on the two-period groundwater levels. After comparing the efficiencies in forecasting groundwater levels among ENKF, the modified model, and the initial model, four major conclusions could be drawn. ENKF converged fast when forecasting groundwater levels and the accuracy was high. Various convergent results would be represented by ENKF when K in different layers was observed in the same error. ENKF performed better than the initial simulation when monitored data subjected to a certain range of interferences. Forecasting accuracy in the middle of the study area could be enhanced by the large improvement degree of K through ENKF. Therefore, this analytical method could be a theoretical reference for groundwater resources management in coastal areas. HIGHLIGHTS First employed ENKF into a two-layer confined coastal model.; Modified groundwater model by ENKF.; Provided the theoretical reference for groundwater resources management in coastal areas.;
format	article
author	Xiaohua Huang Guodong Liu Yu Chen Jun Li
author_facet	Xiaohua Huang Guodong Liu Yu Chen Jun Li
author_sort	Xiaohua Huang
title	Joint estimation of states and parameters of two-layer coastal aquifers based on ENKF
title_short	Joint estimation of states and parameters of two-layer coastal aquifers based on ENKF
title_full	Joint estimation of states and parameters of two-layer coastal aquifers based on ENKF
title_fullStr	Joint estimation of states and parameters of two-layer coastal aquifers based on ENKF
title_full_unstemmed	Joint estimation of states and parameters of two-layer coastal aquifers based on ENKF
title_sort	joint estimation of states and parameters of two-layer coastal aquifers based on enkf
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/cf974c4c427f428191a819ba50719ff6
work_keys_str_mv	AT xiaohuahuang jointestimationofstatesandparametersoftwolayercoastalaquifersbasedonenkf AT guodongliu jointestimationofstatesandparametersoftwolayercoastalaquifersbasedonenkf AT yuchen jointestimationofstatesandparametersoftwolayercoastalaquifersbasedonenkf AT junli jointestimationofstatesandparametersoftwolayercoastalaquifersbasedonenkf
_version_	1718443821773094912

Joint estimation of states and parameters of two-layer coastal aquifers based on ENKF

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