Comparison of deterministic and stochastic methods to predict spatial variation of groundwater depth

Adhikary, Partha Pratim; Dash, Ch. Jyotiprava

doi:10.1007/s13201-014-0249-8

Cited by 72 publications

(32 citation statements)

References 32 publications

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“…The parameters included the characteristics of stratigraphic horizons, groundwater levels, geophysical information, and the chemical analysis of the sampled water. Data belonging to different scientific spheres were elaborated with the inverse distance weighted geostatistical method [50][51][52] to obtain an integrated multidisciplinary model. The interpolation of punctual data, performed using the appropriate algorithm, generated 3-dimensional models, which illustrate the spatial distribution of the parameters obtained from all investigations.…”

Section: Methodsmentioning

confidence: 99%

An Integrated Approach Supporting Remediation of an Aquifer Contaminated with Chlorinated Solvents by a Combination of Adsorption and Biodegradation

et al. 2019

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Hydrogeological uniqueness and chemical-physical peculiarities guide the contamination dynamics and decontamination mechanisms in the environmental arena. A single composite geodatabase, which integrates geological/hydrological, geophysical, and chemical data, acts as a “cockpit” in the definition of a conceptual model, design of a remediation strategy, implementation, near-real-time monitoring, and validation/revision of a pilot test, and monitoring full-scale interventions. The selected remediation strategy involves the creation of "reactive" zones capable of reducing the concentration of chlorinated solvents in groundwater through the combined action of adsorption on micrometric activated carbon, which is injected into the aquifer, and degradation of organic contaminants, stimulating the dechlorinating biological activity by the addition of an electron donor. The technology is verified through a pilot test, to evaluate the possibility of scaling up the process. The results of post-treatment monitoring reveal abatement of the concentration of chlorinated solvents and intense biological dechlorination activity. Achieving the remediation objectives and project closure is based on the integration of multidisciplinary data using a multiscale approach. This research represents the first completed example in European territory of remediation of an aquifer contaminated with chlorinated solvents by a combination of adsorption and biodegradation.

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Section: Methodsmentioning

confidence: 99%

An Integrated Approach Supporting Remediation of an Aquifer Contaminated with Chlorinated Solvents by a Combination of Adsorption and Biodegradation

et al. 2019

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“…The parameters include the characteristics of stratigraphic horizons, groundwater levels and the chemical analysis of water sampled. Data belonging to different scientific spheres were elaborated with the inverse distance weighted geostatistical method [33][34][35] to obtain an integrated multidisciplinary model. The 3D georeferenced model allows useful information for the decision-making process to be extracted in a short time and in a versatile way [31].…”

Section: Methodsmentioning

confidence: 99%

“…The 3D georeferenced model allows useful information for the decision-making process to be extracted in a short time and in a versatile way [31]. The geo-referencing of previous data and new periodic measurements in 95 piezometers installed inside the plant allowed the realization of the hydrogeological structure modeling and the reconstruction of the groundwater circulation scheme [33,35,36]. The storage, processing and representation of data monitoring in a geographic information system (GIS) environment allowed us to reconstruct the evolution of the groundwater contamination status over time [33,34,37].…”

Section: Methodsmentioning

confidence: 99%

Hydrogeochemical Model Supporting the Remediation Strategy of a Highly Contaminated Industrial Site

Ciampi

Esposito

Papini

2019

Water

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Delineation and understanding the geology and the hydrogeology of a contaminated site, considering its chemical and its biological aspects, are fundamental requirements for successful environmental remediation. The aim of this research is to provide some evidence about the effectiveness of a hydrogeochemical geodatabase to facilitate the integrated management, representation and analysis of heterogeneous data, enabling the appropriate selection, design and optimization of an effective remediation strategy. This study investigates a new technology for the remediation of a dense non-aqueous phase liquid aged source zone, with the aim of enhancing in situ bioremediation by coupling groundwater circulation wells with a continuous production system of electron donors. The technology was verified through a pilot test carried out at an industrial site highly contaminated by chlorinated aliphatic hydrocarbons. The multidisciplinary conceptual model confirmed a complex hydrogeological situation, with the occurrence of active residual sources in low permeability layers. The pilot test results clearly demonstrate a significant mobilization of contaminants from the low permeability zone, and the possibility of favoring the in situ natural attenuation mechanisms based upon biological reductive dechlorination. Different information related to the hydrogeochemical sphere must be integrated and taken into consideration when developing a reliable remediation strategy for contaminated sites.

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“…IDW is a deterministic interpolation technique traditionally used to interpolate groundwater depth (Reed et al 2000). In IDW, deterministic interpolation techniques create surface from sample points using mathematical functions, based on either the extent of similarity or the degree of smoothing (radial basic function RBF) (Adhikary and Dash 2014). In mathematical terms, IDW is written as:…”

Section: Data Usedmentioning

confidence: 99%

Spatial mapping of artesian zone at Iraqi southern desert using a GIS-based random forest machine learning model

Al-Abadi

Shahid

2016

Model. Earth Syst. Environ.

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Random forest (RF) machine learning technique and geographical information system (GIS) have been applied to delineate groundwater flowing well zones in the southern desert of Iraq. A spatial database consists of target variable, i.e., geographic locations of 93 flowing wells and predictor variables, i.e., the factors that control groundwater occurrence was prepared for this purpose. Eleven predictor variables were selected based on data availability, literature review, and field conditions which include elevation, slope, profile curvature, aspect, topographic wetness index, stream power index, distance to Abu Jir fault, distance to Euphrates River, major aquifer group, total hydraulic head, and well depth. The RF model in R package along with ArcGIS 10.2 was used to generate groundwater flowing well potential index for the study area. The obtained potential indices were classified using natural break classification scheme into five categories namely, very low, low, moderate, high, and very high. The results revealed that high or very high groundwater flowing well potential zones occupy 15 %, moderate potential zone covers 6 %, and low or very low potential zones cover 79 % of the southern desert of Iraq. The groundwater flowing well zone map was validated using relative operating characteristic (ROC) curve. The areas under the ROC curve for success and prediction rates were 0.98 and 0.97, respectively, indicating excellent capability of RF model to delineate groundwater potential. It is expected that the method development in this study can be used for rapid but efficient evaluation of groundwater flowing well potential from limited amount of data.

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Comparison of deterministic and stochastic methods to predict spatial variation of groundwater depth

Cited by 72 publications

References 32 publications

An Integrated Approach Supporting Remediation of an Aquifer Contaminated with Chlorinated Solvents by a Combination of Adsorption and Biodegradation

An Integrated Approach Supporting Remediation of an Aquifer Contaminated with Chlorinated Solvents by a Combination of Adsorption and Biodegradation

Hydrogeochemical Model Supporting the Remediation Strategy of a Highly Contaminated Industrial Site

Spatial mapping of artesian zone at Iraqi southern desert using a GIS-based random forest machine learning model

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