The Experts below are selected from a list of 22617 Experts worldwide ranked by ideXlab platform
Bithin Datta - One of the best experts on this subject based on the ideXlab platform.
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Application of dedicated monitoring: network design for unknown Pollutant-Source identification based on dynamic time warping
Journal of Water Resources Planning and Management, 2015Co-Authors: Manish Jha, Bithin DattaAbstract:AbstractImplementation of monitoring strategy for increasing the efficiency of groundwater Pollutant Source characterization is often necessary, especially when inadequate and arbitrary concentration measurement data are initially available. The research reported in this paper focuses on estimating three main parameters that are essential for efficient and accurate characterization of groundwater pollution Sources, as follows: (1) location of Source, (2) its starting time of release, and (3) duration of its activity. Most of the methodologies developed so far for unknown Pollutant Source identification have not adequately addressed the complexities involved with estimation of starting time of release and the duration of activity. Estimation of the time gap between the first observation of contamination in the aquifer at a location and the starting time of release is important for Source identification. The main complexity arises due to the fact that the spatial location and the duration of activity of a p...
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Linked Simulation-Optimization based Dedicated Monitoring Network Design for Unknown Pollutant Source Identification using Dynamic Time Warping Distance
Water Resources Management, 2014Co-Authors: Manish Jha, Bithin DattaAbstract:Implementation of monitoring strategy for increasing the efficiency of groundwater Pollutant Source characterization is often necessary, especially when only inadequate and arbitrary concentration measurement data are initially available. Two main parameters that need to be estimated for efficient and accurate characterization of groundwater pollution Sources are: location of the Source and the time when the Source became active. Complexities involved with the explicit estimation of the time of start and Source activity have not been addressed so far in previous studies. The main complexity arises due to the fact that the spatial location and time of activity are inter-related. Therefore, specifying one and solving for the other simplifies the Source characterization problem. Hence, in this study, both the Source location and time of initiation are treated as unknowns. The developed methodology uses dynamic time warping distance in the linked simulation-optimization model to address some complex issues in designing a monitoring network to efficiently estimate Source characteristics including the time of first activity of unknown groundwater Source. Performance of the developed methodology is evaluated on illustrative contaminated aquifer. These evaluation results demonstrate the potential use of the developed methodology.
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Identification of Pollutant Source characteristics under uncertainty in contaminated water reSources systems using adaptive simulated anealing and fuzzy logic
International Journal of GEOMATE, 2014Co-Authors: Mahsa Amirabdollahian, Bithin DattaAbstract:Effective environmental management and remediation strategies are required to remediate contaminated water reSources. Accurate characterizing of unknown contaminant Sources is vital for selection of appropriate environmental management plan and reduction of long term remedial costs. In order to characterize the Sources of contamination, the aquifer boundary conditions and hydrogeologic parameter values need to be estimated or specified. In real life contaminated aquifers, often there are sparse and inaccurate information available. On the other hand, extensive collection of data is very costly. The uncertain and highly variable natures of water reSources systems affect the accuracy of contaminant Source identification models. In this study, an optimal Source identification model incorporating Adaptive Simulated Annealing optimization algorithm linked with the numerical flow and transport simulation models, is designed to identify contaminant Source characteristics. The fuzzy logic concept is used to identify the effect of hydrogeological parameter uncertainty on groundwater flow and transport simulation. The fuzzy membership values incorporate the reliability of specified parameter values in to the optimization model. An illustrative study area is used to show the potential applicability of the proposed methodology. The incorporation of fuzzy logic in Source identification model increases the applicability of contaminant Source detection models in real-life contaminated water reSources systems.
Anna Ledin - One of the best experts on this subject based on the ideXlab platform.
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a Source classification framework supporting Pollutant Source mapping Pollutant release prediction transport and load forecasting and Source control planning for urban environments
Environmental Science and Pollution Research, 2012Co-Authors: Hanschristian Holten Lutzhoft, Erica Donner, Tonie Wickman, Eva Eriksson, Primož Banovec, Peter Steen Mikkelsen, Anna LedinAbstract:Purpose Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured Pollutant Source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose.
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A Source classification framework supporting Pollutant Source mapping, Pollutant release prediction, transport and load forecasting, and Source control planning for urban environments
Environmental Science and Pollution Research, 2012Co-Authors: Hanschristian Holten Lutzhoft, Erica Donner, Tonie Wickman, Eva Eriksson, Primož Banovec, Peter Steen Mikkelsen, Anna LedinAbstract:Purpose Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured Pollutant Source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose. Methods Existing Source classification systems were examined by a multidisciplinary research team, and an optimised SCF was developed. The performance and usability of the SCF were tested using a selection of 25 chemicals listed as priority Pollutants in Europe. Results The SCF is structured in the form of a relational database and incorporates both qualitative and quantitative Source classification and release data. The system supports a wide range of pollution monitoring and management applications. The SCF functioned well in the performance test, which also revealed important gaps in priority Pollutant release data. Conclusions The SCF provides a well-structured approach for European Pollutant Source and release classification and management. With further optimisation and demonstration testing, the SCF has the potential to be fully implemented throughout Europe.
Manish Jha - One of the best experts on this subject based on the ideXlab platform.
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Application of dedicated monitoring: network design for unknown Pollutant-Source identification based on dynamic time warping
Journal of Water Resources Planning and Management, 2015Co-Authors: Manish Jha, Bithin DattaAbstract:AbstractImplementation of monitoring strategy for increasing the efficiency of groundwater Pollutant Source characterization is often necessary, especially when inadequate and arbitrary concentration measurement data are initially available. The research reported in this paper focuses on estimating three main parameters that are essential for efficient and accurate characterization of groundwater pollution Sources, as follows: (1) location of Source, (2) its starting time of release, and (3) duration of its activity. Most of the methodologies developed so far for unknown Pollutant Source identification have not adequately addressed the complexities involved with estimation of starting time of release and the duration of activity. Estimation of the time gap between the first observation of contamination in the aquifer at a location and the starting time of release is important for Source identification. The main complexity arises due to the fact that the spatial location and the duration of activity of a p...
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Linked Simulation-Optimization based Dedicated Monitoring Network Design for Unknown Pollutant Source Identification using Dynamic Time Warping Distance
Water Resources Management, 2014Co-Authors: Manish Jha, Bithin DattaAbstract:Implementation of monitoring strategy for increasing the efficiency of groundwater Pollutant Source characterization is often necessary, especially when only inadequate and arbitrary concentration measurement data are initially available. Two main parameters that need to be estimated for efficient and accurate characterization of groundwater pollution Sources are: location of the Source and the time when the Source became active. Complexities involved with the explicit estimation of the time of start and Source activity have not been addressed so far in previous studies. The main complexity arises due to the fact that the spatial location and time of activity are inter-related. Therefore, specifying one and solving for the other simplifies the Source characterization problem. Hence, in this study, both the Source location and time of initiation are treated as unknowns. The developed methodology uses dynamic time warping distance in the linked simulation-optimization model to address some complex issues in designing a monitoring network to efficiently estimate Source characteristics including the time of first activity of unknown groundwater Source. Performance of the developed methodology is evaluated on illustrative contaminated aquifer. These evaluation results demonstrate the potential use of the developed methodology.
Erica Donner - One of the best experts on this subject based on the ideXlab platform.
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a Source classification framework supporting Pollutant Source mapping Pollutant release prediction transport and load forecasting and Source control planning for urban environments
Environmental Science and Pollution Research, 2012Co-Authors: Hanschristian Holten Lutzhoft, Erica Donner, Tonie Wickman, Eva Eriksson, Primož Banovec, Peter Steen Mikkelsen, Anna LedinAbstract:Purpose Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured Pollutant Source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose.
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A Source classification framework supporting Pollutant Source mapping, Pollutant release prediction, transport and load forecasting, and Source control planning for urban environments
Environmental Science and Pollution Research, 2012Co-Authors: Hanschristian Holten Lutzhoft, Erica Donner, Tonie Wickman, Eva Eriksson, Primož Banovec, Peter Steen Mikkelsen, Anna LedinAbstract:Purpose Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured Pollutant Source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose. Methods Existing Source classification systems were examined by a multidisciplinary research team, and an optimised SCF was developed. The performance and usability of the SCF were tested using a selection of 25 chemicals listed as priority Pollutants in Europe. Results The SCF is structured in the form of a relational database and incorporates both qualitative and quantitative Source classification and release data. The system supports a wide range of pollution monitoring and management applications. The SCF functioned well in the performance test, which also revealed important gaps in priority Pollutant release data. Conclusions The SCF provides a well-structured approach for European Pollutant Source and release classification and management. With further optimisation and demonstration testing, the SCF has the potential to be fully implemented throughout Europe.
Hanschristian Holten Lutzhoft - One of the best experts on this subject based on the ideXlab platform.
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a Source classification framework supporting Pollutant Source mapping Pollutant release prediction transport and load forecasting and Source control planning for urban environments
Environmental Science and Pollution Research, 2012Co-Authors: Hanschristian Holten Lutzhoft, Erica Donner, Tonie Wickman, Eva Eriksson, Primož Banovec, Peter Steen Mikkelsen, Anna LedinAbstract:Purpose Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured Pollutant Source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose.
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A Source classification framework supporting Pollutant Source mapping, Pollutant release prediction, transport and load forecasting, and Source control planning for urban environments
Environmental Science and Pollution Research, 2012Co-Authors: Hanschristian Holten Lutzhoft, Erica Donner, Tonie Wickman, Eva Eriksson, Primož Banovec, Peter Steen Mikkelsen, Anna LedinAbstract:Purpose Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured Pollutant Source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose. Methods Existing Source classification systems were examined by a multidisciplinary research team, and an optimised SCF was developed. The performance and usability of the SCF were tested using a selection of 25 chemicals listed as priority Pollutants in Europe. Results The SCF is structured in the form of a relational database and incorporates both qualitative and quantitative Source classification and release data. The system supports a wide range of pollution monitoring and management applications. The SCF functioned well in the performance test, which also revealed important gaps in priority Pollutant release data. Conclusions The SCF provides a well-structured approach for European Pollutant Source and release classification and management. With further optimisation and demonstration testing, the SCF has the potential to be fully implemented throughout Europe.