Abstract:
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[EN] Understanding a contaminant source may help in a better management and risk assessment of a polluted aquifer. However, contaminant source information may not be available when a pollutant is detected in a drinking ...[+]
[EN] Understanding a contaminant source may help in a better management and risk assessment of a polluted aquifer. However, contaminant source information may not be available when a pollutant is detected in a drinking well. The restart ensemble Kalman filter (restart EnKF, also named r-EnKF) has been demonstrated in synthetic and laboratory experiments as an efficient solution for the identification of a contaminant source. Recently, the ensemble smoother with multiple data assimilation (ES-MDA) has been proposed as an alternative to the r-EnKF as a more efficient solution given that the r-EnKF needs to restart the simulation of the state equation from time zero after each data assimilation step. An analysis, in a synthetic aquifer, of the accuracy of the ES-MDA for the simultaneous identification of a contaminant source and the spatial distribution of hydraulic conductivity by assimilating both piezometric head and concentration observations is carried out using the r-EnKF as a benchmark. The conclusion is that the ES-MDA can outperform the r-EnKF, but the expected speed advantage, associated with the possibility of assimilating all data at once, does not exist. For the ES-MDA to reach the same level of accuracy as the r-EnKF, the number of multiple data assimilations must be large, and final computing time is similar for both approaches. However, the ES-MDA can do much better than the r-EnKF if the number of iterations increases even further, with the consequent increase of computational cost.
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Thanks:
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Financial support to carry out this work was received from the
Spanish Ministry of Economy and Competitiveness through project
CGL2014-59841-P, and from the Spanish Ministry of Education, Culture
and Sports through a ...[+]
Financial support to carry out this work was received from the
Spanish Ministry of Economy and Competitiveness through project
CGL2014-59841-P, and from the Spanish Ministry of Education, Culture
and Sports through a fellowship for the mobility of professors in foreign
research and higher education institutions of reference to the second
author, reference PRX17/00150. Teng Xu also acknowledges the
financial support from the Fundamental Research Funds for the Central
Universities (B200201015) and Jiangsu Specially-Appointed Professor
Program (B19052). Chunhui Lu acknowledges the financial support
from the National Natural Science Foundation of China (51679067 and
51879088), and Fundamental Research Funds for the Central Universities (B200204002).
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