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Time-varying characteristics of saturated hydraulic conductivity in grassed swales based on the ensemble Kalman filter algorithm -A case study of two long-running swales in Netherlands.
Yang, Feikai; Fu, Dafang; Zevenbergen, Chris; Boogaard, Floris C; Singh, Rajendra Prasad.
Afiliação
  • Yang F; School of Civil Engineering, Southeast University, Nanjing 210096, China; Southeast University-Monash University Joint Research Centre for Future Cities, Nanjing 210096, China; IHE-Delft Institute for Water Education, P.O. Box 3015, 2611DA Delft, the Netherlands; Department of Civil Engineering, Del
  • Fu D; School of Civil Engineering, Southeast University, Nanjing 210096, China; Southeast University-Monash University Joint Research Centre for Future Cities, Nanjing 210096, China.
  • Zevenbergen C; IHE-Delft Institute for Water Education, P.O. Box 3015, 2611DA Delft, the Netherlands; Department of Civil Engineering, Delft University of Technology (TU Delft), Gebouw 23, Stevinweg 1, 2628CN Delft, the Netherlands.
  • Boogaard FC; Research Centre for Built Environment NoorderRuimte, Hanze University of Applied Sciences, 9747 AS Groningen, the Netherlands; Deltares, Daltonlaan 600, 3584 BK Utrecht, the Netherlands.
  • Singh RP; School of Civil Engineering, Southeast University, Nanjing 210096, China; Southeast University-Monash University Joint Research Centre for Future Cities, Nanjing 210096, China. Electronic address: rajupsc@seu.edu.cn.
J Environ Manage ; 351: 119760, 2024 Feb.
Article em En | MEDLINE | ID: mdl-38086124
ABSTRACT
Saturated hydraulic conductivity (Ks) of the filler layer in grassed swales are varying in the changing environment. In most of the hydrological models, Ks is assumed as constant or decrease with a clogging factor. However, the Ks measured on site cannot be the input of the hydrological model directly. Therefore, in this study, an Ensemble Kalman Filter (EnKF) based approach was carried out to estimate the Ks of the whole systems in two monitored grassed swales at Enschede and Utrecht, the Netherlands. The relationship between Ks and possible influencing factors (antecedent dry period, temperature, rainfall, rainfall duration, total rainfall and seasonal factors) were studied and a Multivariate nonlinear function was established to optimize the hydrological model. The results revealed that the EnKF method was satisfying in the Ks estimation, which showed a notable decrease after long-term operation, but revealed a recovery in summer and winter. After the addition of Multivariate nonlinear function of the Ks into hydrological model, 63.8% of the predicted results were optimized among the validation events, and compared with constant Ks. A sensitivity analysis revealed that the effect of each influencing factors on the Ks varies depending on the type of grassed swale. However, these findings require further investigation and data support.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Solo / Poaceae País/Região como assunto: Europa Idioma: En Revista: J Environ Manage Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Solo / Poaceae País/Região como assunto: Europa Idioma: En Revista: J Environ Manage Ano de publicação: 2024 Tipo de documento: Article