Tomographic inversion of time-domain resistivity and chargeability data for the investigation of landfills using a priori information. (January 2017)
- Record Type:
- Journal Article
- Title:
- Tomographic inversion of time-domain resistivity and chargeability data for the investigation of landfills using a priori information. (January 2017)
- Main Title:
- Tomographic inversion of time-domain resistivity and chargeability data for the investigation of landfills using a priori information
- Authors:
- De Donno, Giorgio
Cardarelli, Ettore - Abstract:
- Highlights: We present a new code for ERT/IP inversion using a priori information. We present an innovative procedure to improve resolution of the landfill models. We discuss two real-world examples related to characterization of landfills. The proposed methods increases the degree of accuracy of the landfill model. Abstract: In this paper, we present a new code for the modelling and inversion of resistivity and chargeability data using a priori information to improve the accuracy of the reconstructed model for landfill. When a priori information is available in the study area, we can insert them by means of inequality constraints on the whole model or on a single layer or assigning weighting factors for enhancing anomalies elongated in the horizontal or vertical directions. However, when we have to face a multilayered scenario with numerous resistive to conductive transitions (the case of controlled landfills), the effective thickness of the layers can be biased. The presented code includes a model-tuning scheme, which is applied after the inversion of field data, where the inversion of the synthetic data is performed based on an initial guess, and the absolute difference between the field and synthetic inverted models is minimized. The reliability of the proposed approach has been supported in two real-world examples; we were able to identify an unauthorized landfill and to reconstruct the geometrical and physical layout of an old waste dump. The combined analysis of theHighlights: We present a new code for ERT/IP inversion using a priori information. We present an innovative procedure to improve resolution of the landfill models. We discuss two real-world examples related to characterization of landfills. The proposed methods increases the degree of accuracy of the landfill model. Abstract: In this paper, we present a new code for the modelling and inversion of resistivity and chargeability data using a priori information to improve the accuracy of the reconstructed model for landfill. When a priori information is available in the study area, we can insert them by means of inequality constraints on the whole model or on a single layer or assigning weighting factors for enhancing anomalies elongated in the horizontal or vertical directions. However, when we have to face a multilayered scenario with numerous resistive to conductive transitions (the case of controlled landfills), the effective thickness of the layers can be biased. The presented code includes a model-tuning scheme, which is applied after the inversion of field data, where the inversion of the synthetic data is performed based on an initial guess, and the absolute difference between the field and synthetic inverted models is minimized. The reliability of the proposed approach has been supported in two real-world examples; we were able to identify an unauthorized landfill and to reconstruct the geometrical and physical layout of an old waste dump. The combined analysis of the resistivity and chargeability (normalised) models help us to remove ambiguity due to the presence of the waste mass. Nevertheless, the presence of certain layers can remain hidden without using a priori information, as demonstrated by a comparison of the constrained inversion with a standard inversion. The robustness of the above-cited method (using a priori information in combination with model tuning) has been validated with the cross-section from the construction plans, where the reconstructed model is in agreement with the original design. … (more)
- Is Part Of:
- Waste management. Volume 59(2017)
- Journal:
- Waste management
- Issue:
- Volume 59(2017)
- Issue Display:
- Volume 59, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 59
- Issue:
- 2017
- Issue Sort Value:
- 2017-0059-2017-0000
- Page Start:
- 302
- Page End:
- 315
- Publication Date:
- 2017-01
- Subjects:
- Electrical resistivity tomography -- Induced polarisation -- A priori information -- Landfill
Hazardous wastes -- Periodicals
Refuse and refuse disposal -- Periodicals
363.728 - Journal URLs:
- http://www.sciencedirect.com/science/journal/0956053X ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.wasman.2016.11.020 ↗
- Languages:
- English
- ISSNs:
- 0956-053X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9266.674500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2766.xml