Periodic Reporting for period 1 - FORENSHYD (Forensic Hydrogeology)
Période du rapport: 2021-01-11 au 2023-01-10
The Forensic Hydrogeology project studied the identification of point sources that release contaminants into groundwater systems. Although aquifers possess a natural shield for pollutant activities on the surface, it is estimate that 2,500 million of potentially contaminated exist in Europe. When aquifers become contaminated the characterization of the new status and the source identification requires: (i) effective observation networks; (ii) and complex modelling methods.
The research idea was to identify the source parameters by analysing the aquifer's response predicted by a numerical model with observations. It required the application of the Ensemble Kalman Filter (EnKF), a sound and precise data assimilation method for linear systems, but with constraints to overcome when model parameters and state variables relate nonlinearly. We aimed to generate synthetic scenarios that mimic flow, transport, and reactive systems that account for the complexity found in nature, i.e. the spatial and temporal variability of parameters and nonlinear processes. This had been poorly explored in biogeochemical models and might reduce uncertainty in reactive parameter estimation in several types of reactive systems.
In the absence of information, the risk of evading environmental liability increases. Better knowledge on this topic provides a more reliable characterization of the natural processes and their site-specific parameters, improving the efficiency of remediation techniques and mitigating the effects of contaminant events, which may compromise human and ecosystem health conditions.
The scientific objectives of the project Forensic Hydrogeology were: (i) to develop a novel, flexible, and reliable ensemble Kalman filter data assimilation method for the optimal identification of contaminant sources of reactive pollutants in near-actual conditions by using synthetic scenarios, sandbox experiments, and demonstration sites; (ii) to transfer this novel technology in well-reported, practical, and universal open-source packages. Additionally, the MSCA-IF aimed to provide the opportunity for the Principal Investigator to gain experience as an independent scientist, in this case, in developing and applying advanced algorithms to study biogeochemical processes in the subsurface with stochastic inverse approaches.
The research idea was to identify the source parameters by analysing the aquifer's response predicted by a numerical model with observations. It required the application of the Ensemble Kalman Filter (EnKF), a sound and precise data assimilation method for linear systems, but with constraints to overcome when model parameters and state variables relate nonlinearly. We aimed to generate synthetic scenarios that mimic flow, transport, and reactive systems that account for the complexity found in nature, i.e. the spatial and temporal variability of parameters and nonlinear processes. This had been poorly explored in biogeochemical models and might reduce uncertainty in reactive parameter estimation in several types of reactive systems.
In the absence of information, the risk of evading environmental liability increases. Better knowledge on this topic provides a more reliable characterization of the natural processes and their site-specific parameters, improving the efficiency of remediation techniques and mitigating the effects of contaminant events, which may compromise human and ecosystem health conditions.
The scientific objectives of the project Forensic Hydrogeology were: (i) to develop a novel, flexible, and reliable ensemble Kalman filter data assimilation method for the optimal identification of contaminant sources of reactive pollutants in near-actual conditions by using synthetic scenarios, sandbox experiments, and demonstration sites; (ii) to transfer this novel technology in well-reported, practical, and universal open-source packages. Additionally, the MSCA-IF aimed to provide the opportunity for the Principal Investigator to gain experience as an independent scientist, in this case, in developing and applying advanced algorithms to study biogeochemical processes in the subsurface with stochastic inverse approaches.
The project was structured in four scientific Work Packages (WP). WP1 covered the selection of synthetic scenarios to test the EnKF methods: the first case simulated biodegradation and sorption of solutes under kinetic chemical reactions; isotherm conditions were considered in a mildly heterogeneous hydraulic conductivity field coupled with a binary (reactive / non-reactive) field; the second case included transient boundary conditions and the Dual-Domain Mass Transfer approach in heterogeneous conditions; the third case assumes multiple contaminant sources; and the fourth case attempts to distinguish among sorption isotherm processes. Observed concentrations at sampling locations were the unique state variable data used. WP2 comprised the laboratory experiments undertaken at the Università degli Studi di Parma. Seven sandbox experiments and four recovery experiments were performed under saturated and stable conditions to capture the luminosity of a fluorescent tracer injected through two different injection points; the observations at selected locations feed the algorithm to identify hydraulic heterogeneity and source parameter values. In WP3, the method was tested on a real contaminant site with a chlorinated solvent, which implies working with sparse observations during the calibration process and carefully selecting the set of unknown parameters to be identified by the algorithms. WP4 benefited from developing an open-source package on EnKF to solve various hydraulic problems by researchers from the UPV and the UNIPR; such synergies were identified at the beginning of the project, and the Fellow has contributed synthetic cases on the topic of biogeochemical reactive systems.
The fellow got relevant experience as a lecturer on Hydrogeology, Geostatistics and Modelling Groundwater Flow and Solute Transport Processes. The fellow took advantage of the opportunities to establish new contacts within global research networks. The fellow was currently involved in the International Association of Mathematical Geosciences, the International Association of Hydrogeologists, the Marie Curie Alumni Association, and the Spanish InterPore Chapter. The training received during the MSCA was focused on geostatistics, inverse methods, uncertainty analysis, optimization, and machine learning. Among the soft skills acquired were how Communication of scientific results and Transfer Knowledge.
The research results were communicated at 5 conferences: Climate Change Workshop IIAMA, ICSH-STAHY, CIAS, geoENV, IGMA, IAHR. The fellow supervised high school alumni on the research project 'CAAP-ACITADOS' aimed to evaluate groundwater resources. Her tale “The wandering Fountain” was awarded in the “Tales from MedNight - 2021”. The fellow also prepared didactic material for schooling Alcoa ceramic producers on heavy metals contamination.
The fellow got relevant experience as a lecturer on Hydrogeology, Geostatistics and Modelling Groundwater Flow and Solute Transport Processes. The fellow took advantage of the opportunities to establish new contacts within global research networks. The fellow was currently involved in the International Association of Mathematical Geosciences, the International Association of Hydrogeologists, the Marie Curie Alumni Association, and the Spanish InterPore Chapter. The training received during the MSCA was focused on geostatistics, inverse methods, uncertainty analysis, optimization, and machine learning. Among the soft skills acquired were how Communication of scientific results and Transfer Knowledge.
The research results were communicated at 5 conferences: Climate Change Workshop IIAMA, ICSH-STAHY, CIAS, geoENV, IGMA, IAHR. The fellow supervised high school alumni on the research project 'CAAP-ACITADOS' aimed to evaluate groundwater resources. Her tale “The wandering Fountain” was awarded in the “Tales from MedNight - 2021”. The fellow also prepared didactic material for schooling Alcoa ceramic producers on heavy metals contamination.
The Forensic Hydrogeology project aimed to improve the identification of contaminant sources and their fate in the subsurface, which is fundamental for correctly evaluating mitigation and remediation techniques and, ultimately, facilitating the application of environmental protection laws. The approach innovated in exploring the stochastic inverse method that will be applied to the chemical interaction of released contaminants when those reach saturated media. The specific studies of the project Forensic Hydrogeology tackled: (i) the identification of reactive parameters in kinetic chemical reactions observed in contaminant sites; (ii) the analysis of the effects of coupled hydraulic and chemical heterogeneity in the uncertainty of the outcome of inverse methods; (iii) the study of nonunique solutions on multiple source identification; (iv) the characterization of hydraulic conductivity in nature-like layering stratigraphy at laboratory scale; (v) the test of the previous findings in an actual field site with sparse data available to optimize acquisition of data in further sample campaigns.
Results show simultaneous identification of source locations and reactive parameter estimation was affordable even when those were subject to spatial variability within acceptable uncertainty levels. The EnKF algorithms provided uncertainty analysis together with parameter estimation, which was relevant for considering such a methodology in court and in the design of observation networks and remediation techniques. The optimal algorithm was the Ensemble Smoother Multiple Data Assimilation, which required observations in space and time. In conclusion, the project validated the use of the open-source software package by multidisciplinary and intersectoral agents involved in the protection and exploitation of natural resources such as soil and groundwater. The FORENSHYD project demonstrated that the stochastic inverse methods might help to reduce uncertainty in reactive parameter estimation due to the continuous increase of computations capacities and its versatility to adapt to several types of reactive systems.
Results show simultaneous identification of source locations and reactive parameter estimation was affordable even when those were subject to spatial variability within acceptable uncertainty levels. The EnKF algorithms provided uncertainty analysis together with parameter estimation, which was relevant for considering such a methodology in court and in the design of observation networks and remediation techniques. The optimal algorithm was the Ensemble Smoother Multiple Data Assimilation, which required observations in space and time. In conclusion, the project validated the use of the open-source software package by multidisciplinary and intersectoral agents involved in the protection and exploitation of natural resources such as soil and groundwater. The FORENSHYD project demonstrated that the stochastic inverse methods might help to reduce uncertainty in reactive parameter estimation due to the continuous increase of computations capacities and its versatility to adapt to several types of reactive systems.