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    Joint identification of contaminant source location, initial release time, and initial solute concentration in an aquifer via ensemble Kalman filtering

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    [EN] When a contaminant is detected in a drinking well, source location, initial contaminant release time, and initial contaminant concentration are, in many cases, unknown; the responsible party may have disappeared and the identification of when and where the contamination happened may become difficult. Although contaminant source identification has been studied extensively in the last decades, we proposeto our knowledge, for the first timethe use of the ensemble Kalman filter (EnKF), which has proven to be a powerful algorithm for inverse modeling. The EnKF is tested in a two-dimensional synthetic deterministic aquifer, identifying, satisfactorily, the source location, the release time, and the release concentration, together with an assessment of the uncertainty associated with this identification.Financial support to carry out this work was received from the Spanish Ministry of Economy and Competitiveness through project CGL2014-59841-P. All data used in this analysis are available from the authors.Xu, T.; Gómez-Hernández, JJ. (2016). Joint identification of contaminant source location, initial release time, and initial solute concentration in an aquifer via ensemble Kalman filtering. Water Resources Research. 52(8):6587-6595. https://doi.org/10.1002/2016WR019111S65876595528Aral, M. M., Guan, J., & Maslia, M. L. (2001). Identification of Contaminant Source Location and Release History in Aquifers. Journal of Hydrologic Engineering, 6(3), 225-234. doi:10.1061/(asce)1084-0699(2001)6:3(225)Butera, I., Tanda, M. G., & Zanini, A. (2012). Simultaneous identification of the pollutant release history and the source location in groundwater by means of a geostatistical approach. Stochastic Environmental Research and Risk Assessment, 27(5), 1269-1280. doi:10.1007/s00477-012-0662-1Chen, Y., Oliver, D. S., & Zhang, D. (2009). Data assimilation for nonlinear problems by ensemble Kalman filter with reparameterization. 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Journal of Hydraulic Research, 42(sup1), 9-18. doi:10.1080/00221680409500042Neupauer, R. M., & Lin, R. (2006). Identifying sources of a conservative groundwater contaminant using backward probabilities conditioned on measured concentrations. Water Resources Research, 42(3). doi:10.1029/2005wr004115Neupauer, R. M., & Wilson, J. L. (1999). Adjoint method for obtaining backward-in-time location and travel time probabilities of a conservative groundwater contaminant. Water Resources Research, 35(11), 3389-3398. doi:10.1029/1999wr900190Woodbury, A., Sudicky, E., Ulrych, T. J., & Ludwig, R. (1998). Three-dimensional plume source reconstruction using minimum relative entropy inversion. Journal of Contaminant Hydrology, 32(1-2), 131-158. doi:10.1016/s0169-7722(97)00088-0Woodbury, A. D., & Ulrych, T. J. (1996). Minimum Relative Entropy Inversion: Theory and Application to Recovering the Release History of a Groundwater Contaminant. Water Resources Research, 32(9), 2671-2681. doi:10.1029/95wr03818Xu, T., & Gómez-Hernández, J. J. (2015). Probability fields revisited in the context of ensemble Kalman filtering. Journal of Hydrology, 531, 40-52. doi:10.1016/j.jhydrol.2015.06.062Xu, T., Jaime Gómez-Hernández, J., Zhou, H., & Li, L. (2013). The power of transient piezometric head data in inverse modeling: An application of the localized normal-score EnKF with covariance inflation in a heterogenous bimodal hydraulic conductivity field. Advances in Water Resources, 54, 100-118. doi:10.1016/j.advwatres.2013.01.006Yeh, H.-D., Chang, T.-H., & Lin, Y.-C. (2007). Groundwater contaminant source identification by a hybrid heuristic approach. Water Resources Research, 43(9). doi:10.1029/2005wr004731Zheng , C. 2010 MT3DMS v5. 3 Supplemental User's Guide Technical Report to the US Army Engineer Research and Development CenterZhou, H., Gómez-Hernández, J. J., Hendricks Franssen, H.-J., & Li, L. (2011). An approach to handling non-Gaussianity of parameters and state variables in ensemble Kalman filtering. Advances in Water Resources, 34(7), 844-864. doi:10.1016/j.advwatres.2011.04.01

    Rapid Assessment of Intertidal Wetland Sediments

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    Urbanization of coastal areas poses a severe threat to ecologically valuable intertidal wetlands. This paper presents a pragmatic approach called Rapid Assessment for Intertidal Wetland Sediments (RAITWS) for evaluating the sediment quality of intertidal wetlands. RAITWS involves construction of reference groups, selection of a subset of environmental variables, matching of test sites to reference groups, prediction of the benthic fauna community structure (e. g. of macroinvertebrates) at test sites, evaluation of the Observation to Expectation ratio (O/E ratio), quantification of environmental variables with series of dynamic numerical models, and interpretation of the O/E findings. The proposed method extends the existing rapid biological assessment approach from static to dynamic applications. In particular, RAITWS provides a fast method of assessing intertidal wetland sites which are undergoing ecological change due to nearby coastal development.Environmental SciencesSCI(E)EI0ARTICLE5574-5852

    Site investigation techniques for DNAPL source and plume zone characterisation

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    Establishing the location of the Source Area BioREmediation (SABRE) research cell was a primary objective of the site characterisation programme. This bulletin describes the development of a two-stage site characterisation methodology that combined qualitative and quantitative data to guide and inform an assessment of dense nonaqueous phase liquid (DNAPL) distribution at the site. DNAPL site characterisation has traditionally involved multiple phases of site investigation, characterised by rigid sampling and analysis programmes, expensive mobilisations and long decision-making timeframes (Crumbling, 2001a) , resulting in site investigations that are costly and long in duration. Here we follow the principles of an innovative framework, termed Triad (Crumbling, 2001a, 2001b; Crumbling et al., 2001, Crumbling et al. 2003), which describes a systematic approach for the characterisation and remediation of contaminated sites. The Triad approach to site characterisation focuses on three main components: a) systematic planning which is implemented with a preliminary conceptual site model from existing data. The desired outcomes are planned and decision uncertainties are evaluated; b) dynamic work strategies that focus on the need for flexibility as site characterisation progresses so that new information can guide the investigation in real-time and c) real-time measurement technologies that are critical in making dynamic work strategies possible. Key to this approach is the selection of suitable measurement technologies, of which there are two main categories (Crumbling et al., 2003). The first category provides qualitative, dense spatial data, often with detection limits over a preset value. These methods are generally of lower cost, produce real-time data and are primarily used to identify site areas that require further investigation. Examples of such "decisionquality" methods are laser induced fluorescence (Kram et al., 2001), membrane interface probing (McAndrews et al., 2003) and cone penetrometer testing (Robertson, 1990), all of which produce data in continuous vertical profiles. Because these methods are rapid, many profiles can be generated and hence the subsurface data density is greatly improved. These qualitative results are used to guide the sampling strategy for the application of the second category of technologies that generate quantitative, precise data that have low detection limits and are analyte-specific. These methods tend to be high cost with long turnaround times that preclude on-site decision making, hence applying them to quantify rather than produce a conceptual model facilitates a key cost saving. Examples include instrumental laboratory analyses such as soil solvent extractions (Parker et al., 2004)and water analyses (USEPA, 1996). Where these two categories of measurement technologies are used in tandem, a more complete and accurate dataset is achieved without additional site mobilisations. The aim of the site characterisation programme at the SABRE site was to delineate the DNAPL source zone rapidly and identify a location for the in situ research cell. The site characterisation objectives were to; a) test whether semi-quantitative measurement techniques could reliably determine geological interfaces, contaminant mass distribution and inform the initial site conceptual model; and b) quantitatively determine DNAPL source zone distribution, guided by the qualitative site conceptual model

    Modelling of radionuclide migration through the geosphere with radial basis function method and geostatistics

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    The modelling of radionuclide transport through the geosphere is necessary in the safety assessment of repositories for radioactive waste. A number of key geosphere processes need to be considered when predicting the movement of radionuclides through the geosphere. The most important input data are obtained from field measurements, which are not available for all regions of interest. For example, the hydraulic conductivity, as input parameter, varies from place to place. In such cases geostatistical science offers a variety of spatial estimation procedures. To assess the a long term safety of a radioactive waste disposal system, mathematical models are used to describe the complicated groundwater flow, chemistry and potential radionuclide migration through geological formations. The numerical solution of partial differential equations (PDEs) has usually been obtained by finite difference methods (FDM), finite element methods (FEM), or finite volume methods (FVM). Kansa introduced the concept of solving PDEs using radial basis functions (RBFs) for hyperbolic, parabolic and elliptic PDEs. The aim of this study was to present a relatively new approach to the modelling of radionuclide migration through the geosphere using radial basis functions methods and to determine the average and sample variance of radionuclide concentration with regard to spatial variability of hydraulic conductivity modelled by a geostatistical approach. We will also explore residual errors and their influence on optimal shape parameters

    Contamination source inference in water distribution networks

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    We study the inference of the origin and the pattern of contamination in water distribution networks. We assume a simplified model for the dyanmics of the contamination spread inside a water distribution network, and assume that at some random location a sensor detects the presence of contaminants. We transform the source location problem into an optimization problem by considering discrete times and a binary contaminated/not contaminated state for the nodes of the network. The resulting problem is solved by Mixed Integer Linear Programming. We test our results on random networks as well as in the Modena city network

    The impact of agricultural activities on water quality: a case for collaborative catchment-scale management using integrated wireless sensor networks

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    The challenge of improving water quality is a growing global concern, typified by the European Commission Water Framework Directive and the United States Clean Water Act. The main drivers of poor water quality are economics, poor water management, agricultural practices and urban development. This paper reviews the extensive role of non-point sources, in particular the outdated agricultural practices, with respect to nutrient and contaminant contributions. Water quality monitoring (WQM) is currently undertaken through a number of data acquisition methods from grab sampling to satellite based remote sensing of water bodies. Based on the surveyed sampling methods and their numerous limitations, it is proposed that wireless sensor networks (WSNs), despite their own limitations, are still very attractive and effective for real-time spatio-temporal data collection for WQM applications. WSNs have been employed for WQM of surface and ground water and catchments, and have been fundamental in advancing the knowledge of contaminants trends through their high resolution observations. However, these applications have yet to explore the implementation and impact of this technology for management and control decisions, to minimize and prevent individual stakeholder’s contributions, in an autonomous and dynamic manner. Here, the potential of WSN-controlled agricultural activities and different environmental compartments for integrated water quality management is presented and limitations of WSN in agriculture and WQM are identified. Finally, a case for collaborative networks at catchment scale is proposed for enabling cooperation among individually networked activities/stakeholders (farming activities, water bodies) for integrated water quality monitoring, control and management
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