Olive-oil mill wastewater transport under unsaturated and saturated laboratory conditions using the geoelectrical resistivity tomography method and the FEFLOW model

An integrated approach for monitoring the vertical transport of a solute into the subsurface by using a geophysical method and a simulation model is proposed and evaluated. A medium-scale (1 m³) laboratory tank experiment was constructed to represent a real subsurface system, where an olive-oil mill wastewater (OOMW) spill might occur. High-resolution cross-hole electrical resistivity tomography (ERT) was performed to monitor the OOMW transport. Time-lapse ERT images defined the spatial geometry of the interface between the contaminated and uncontaminated soil into the unsaturated and saturated zones. Knowing the subsurface characteristics, the finite element flow and transport model FEFLOW was used for simulating the contaminant movement, utilizing the ERT results as a surrogate for concentration measurements for the calibration process. A statistical analysis of the ERT measurements and the corresponding transport model results for various time steps showed a good agreement between them. In addition, a sensitivity analysis of the most important parameters of the simulation model (unsaturated flow, saturated flow and transport) was performed. This laboratory-scale study emphasizes that the combined use of geophysical and transport-modeling approaches can be useful for small-scale field applications where contaminant concentration measurements are scarce, provided that its transferability from laboratory to field conditions is investigated thoroughly.     

Origin and mobility of hexavalent chromium in North-Eastern Attica,Greece

An integrated framework that is comprised of field surveys of groundwater, surface water and soils, laboratory process experiments and hydrologic and geochemical modeling is used to identify the origin (anthropogenic versus geogenic sources), fate and transport of hexavalent Cr in Tertiary and Quaternary deposits of Oropos plain in Greece. Groundwater and soils were analyzed in May 2008 and exhibited considerable Cr concentrations. Mineralogical analysis and micro-XRF analysis of the heavy soil fractions (metallic components) showed Cr bearing phases like chromites, Cr-silicate phases with positive correlation between Si, Al, Fe and Cr soil concentrations. Column experiments showed the Cr(VI) desorption ability of soils, e.g. concentration of 20 μg L⁻¹ was detected after the application of 50 mm of rain. The groundwater model simulated the variability of Cr concentrations emanating from both anthropogenic and geogenic sources, successfully using rate constants obtained from the laboratory experiments, e.g. 4.24 nM h⁻¹ for serpentine soil and 0.77 nM h⁻¹ for soil in alluvial deposits. The mineralogical and geochemical results support a geogenic origin for Cr in soils and groundwater of Oropos plain while modeling results suggest that contaminants transported by Asopos River have affected only the upper layers of the subsurface in the vicinity of the river. The framework can be used to establish background concentrations or clean up levels of Cr-contaminated soils and groundwater.     

Predicting Vertical LNAPL Distribution in the Subsurface under the Fluctuating Water Table Effect

The present study proposes a methodology for predicting the vertical light nonaqueous-phase liquids (LNAPLs) distribution within an aquifer by considering the influence of water table fluctuations. The LNAPL distribution is predicted by combining (1) information on air/LNAPL and LNAPL/water interface elevations with (2) the initial elevation of the water table without LNAPL effect. Data used in the present study were collected during groundwater monitoring undertaken over a period of 4 months at a LNAPL-impacted observation well. In this study, the water table fluctuations raised the free LNAPL in the subsurface to an elevation of 206.63 m, while the lowest elevation was 205.70 m, forming a thickness of 0.93 m of LNAPL-impacted soil. Results show that the apparent LNAPL thickness in the observation well is found to be three times greater than the actual free LNAPL thickness in soil; a finding that agrees with previous studies reporting that apparent LNAPL thickness in observation wells typically exceeds the free LNAPL thickness within soil by a factor estimated to range between 2 and 10. The present study provides insights concerning the transient variation of LNAPL distribution within the subsurface and highlights the capability of the proposed methodology to mathematically predict the actual LNAPL thickness in the subsurface, without the need to conduct laborious field tests. Practitioners can use the proposed methodology to determine by how much the water table should be lowered, through pumping, to isolate the LNAPL-impacted soil within the unsaturated zone, which can then be subjected to in situ vadose zone remedial treatment.     

Multi-objective optimization for free-phase LNAPL recovery using evolutionary computation algorithms

Abstract

A nonlinear, multi-objective optimization methodology is presented that seeks to maximize free product recovery of light non-aqueous phase liquids (LNAPLs) while minimizing operation cost, by introducing the novel concept of optimal alternating pumping and resting periods. This process allows more oil to flow towards the extraction wells, ensuring maximum free product removal at the end of the remediation period with minimum groundwater extraction. The methodology presented here combines FEHM (Finite Element Heat and Mass transfer code), a multiphase groundwater model that simulates LNAPL transport, with three evolutionary algorithms: the genetic algorithm (GA), the differential evolution (DE) algorithm and the particle swarm optimization (PSO) algorithm. The proposed optimal free-phase recovery strategy was tested using data from a field site, located near Athens, Greece. The PSO and DE solutions were very similar, while that provided by the GA was inferior, although the computation time was roughly the same for all algorithms. One of the most efficient algorithms (PSO) was chosen to approximate the optimal Pareto front, a method that provides multiple options to decision makers. When the optimal strategy is implemented, although a significant amount of LNAPL free product is captured, a spreading of the LNAPL plume occurs.

Editor Z.W. Kundzewicz; Associate editor L. See

Citation Dokou, Z. and Karatzas, G.P., 2013. Multi-objective optimization for free-phase LNAPL recovery using evolutionary computation algorithms. Hydrological Sciences Journal, 58 (3), 671–685.     

Saltwater intrusion estimation in a karstified coastal system using density-dependent modelling and comparison with the sharp-interface approach

Abstract

Saltwater intrusion is a naturally occurring phenomenon that is exacerbated significantly by excessive groundwater exploitation in coastal aquifers. In order to determine the extent of saltwater intrusion in a karstified coastal aquifer in Crete, Greece, a three-dimensional, density-dependent groundwater flow and transport model was developed and compared to the more traditional sharp-interface approach. The karstified medium was modelled using a combination of the equivalent porous medium approach (for lower-order fractures) and a discrete fracture approach (for the main fractures/faults). The model takes into consideration the geomorphologic characteristics of the karstic system, such as the depth and orientation of the fault network, and the diffusion phenomena associated with the variable densities of freshwater and saltwater—parameters that create a complex system, inducing uncertainty in the model. The model results showed that the orientation of the fractures, the pumping activity and the fluid density effects drive the seawater intrusion front asymmetrically inland.

Editor Z.W. Kundzewicz

Citation Dokou, Z. and Karatzas, G.P., 2012. Saltwater intrusion estimation in a karstified coastal system using density-dependent modelling and comparison with the sharp-interface approach. Hydrological Sciences Journal, 57 (5), 985–999.     

Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization

Abstract

Artificial neural networks (ANNs) have recently been used to predict the hydraulic head in well locations. In the present work, the particle swarm optimization (PSO) algorithm was used to train a feed-forward multi-layer ANN for the simulation of hydraulic head change at an observation well in the region of Agia, Chania, Greece. Three variants of the PSO algorithm were considered, the classic one with inertia weight improvement, PSO with time varying acceleration coefficients (PSO-TVAC) and global best PSO (GLBest-PSO). The best performance was achieved by GLBest-PSO when implemented using field data from the region of interest, providing improved training results compared to the back-propagation training algorithm. The trained ANN was subsequently used for mid-term prediction of the hydraulic head, as well as for the study of three climate change scenarios. Data time series were created using a stochastic weather generator, and the scenarios were examined for the period 2010–2020.

Editor Z.W. Kundzewicz; Associate editor L. See

Citation Tapoglou, E., Trichakis, I.C., Dokou, Z., Nikolos, I.K., and Karatzas, G.P., 2014. Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization. Hydrological Sciences Journal, 59(6), 1225–1239. http://dx.doi.org/10.1080/02626667.2013.838005