Next Article in Journal
The Application of a Modified Version of the SWAT Model at the Daily Temporal Scale and the Hydrological Response unit Spatial Scale: A Case Study Covering an Irrigation District in the Hei River Basin
Previous Article in Journal
To What Degree Can the Specifics of Occurrence of Glacial Relic Betula humilis Schrank Be an Indicator of Habitat Conditions of Moderate Climate Peatlands?
Previous Article in Special Issue
Three Geostatistical Methods for Hydrofacies Simulation Ranked Using a Large Borehole Lithology Dataset from the Venice Hinterland (NE Italy)
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Water 2018, 10(8), 1063; https://doi.org/10.3390/w10081063

An Effective Kalman Filter-Based Method for Groundwater Pollution Source Identification and Plume Morphology Characterization

1
Department of Hydraulic Engineering, Tongji University, Shanghai 200092, China
2
Shanghai Institute of Pollution Control and Ecological Security, Tongji University, Shanghai 200092, China
3
Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education Northwest A&F University, Yangling 712100, China
*
Authors to whom correspondence should be addressed.
Received: 28 May 2018 / Revised: 7 August 2018 / Accepted: 8 August 2018 / Published: 10 August 2018
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
Full-Text   |   PDF [5140 KB, uploaded 10 August 2018]   |  

Abstract

The identification of unknown groundwater pollution sources and the characterization of pollution plume remains a challenging problem. In this study, we addressed this problem by a linked simulation-optimization approach. This approach couples a contaminant transport simulation model with a Kalman filter-based method to identify groundwater pollution source and characterize plume morphology. In the proposed methodology, the concentration field library, the covariance reduction with a Kalman filter, an alpha-cut technique of fuzzy set, and a linear programming model are integrated for solving this inverse problem. The performance of this methodology is evaluated on an illustrative groundwater pollution source identification problem. The evaluation considered the random hydraulic conductivity filed, erroneous monitoring data, a prior information shortage of potential pollution sources, and an unexpected and unknown pumping well. The identified results indicate that, under these conditions, the proposed Kalman filter-based optimization model can give satisfactory estimations to pollution sources and plume morphology for domains with small and moderate heterogeneity but cannot validate the transport in the relatively high heterogeneous field. View Full-Text
Keywords: pollution source identification; monitoring network design; Kalman filter; alpha-cut technique; simulation-optimization pollution source identification; monitoring network design; Kalman filter; alpha-cut technique; simulation-optimization
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Jiang, S.; Fan, J.; Xia, X.; Li, X.; Zhang, R. An Effective Kalman Filter-Based Method for Groundwater Pollution Source Identification and Plume Morphology Characterization. Water 2018, 10, 1063.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Water EISSN 2073-4441 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top