Evaluation of substrate clogging in a full-scale horizontal subsurface flow treatment wetland using electrical resistivity tomography with an optimized electrode configuration

Shaping the concentration of petroleum hydrocarbon pollution in soil: A machine learning and resistivity-based prediction method

A new method relying on machine learning and resistivity to predict concentrations of petroleum hydrocarbon pollution in soil was proposed as a means of investigation and monitoring. Currently, determining pollutant concentrations in soil is primarily achieved through costly sampling and testing of numerous borehole samples, which carries the risk of further contamination by penetrating the aquifer. Additionally, conventional petroleum hydrocarbon geophysical surveys struggle to establish a correlation between survey results and pollutant concentration. To overcome these limitations, three machine learning models (KNN, RF, and XGBOOST) were combined with the geoelectrical method to predict petroleum hydrocarbon concentrations in the source area. The results demonstrate that the resistivity-based prediction method utilizing machine learning is effective, as validated by R-squared values of 0.91 and 0.94 for the test and validation sets, respectively, and a root mean squared error of 0.19. Furthermore, this study confirmed the feasibility of the approach using actual site data, along with a discussion of its advantages and limitations, establishing it as an inexpensive option to investigate and monitor changes in petroleum hydrocarbon concentration in soil.

Impact of clogging on accumulation and stability of phosphorus in the subsurface flow constructed wetland

Substrate clogging is one of the major operation challenges of subsurface flow constructed wetlands (SSF-CWs). And the phosphorus (P) removal performance and stability of P accumulation of SSF-CWs would be varied with the development of substrate clogging. In this study, three horizontal SSF-CWs microcosms with different clogging degrees were conducted to explore the mechanism of P accumulation behavior influenced by substrate clogging. Increase in clogging degree resulted in hydraulic retention time (HRT) diminution and adsorption sites increase, which jointly led to reduced P removal efficiency at low clogging degree (L-CW), however, higher P removal efficiency was obtained as adsorption sites increase offset HRT diminution at high clogging degree (H-CW). Substrate adsorption was the primary removal pathway in all SSF-CW systems. It accounted for 77.86 ± 2.63% of the P input in the H-CW, significantly higher than the control (60.08 ± 4.79%). This was attributed to a higher proportion of Fe/Al-P accumulated on the substrate of H-CW, since clogging aggravated the anaerobic condition and promoted the generation of Fe ions. The increase in clogging degree also elevated the release risk of the accrued P in SSF-CWs, since Fe/Al-P was considered bioavailable and readily released under environmental disturbance. The obtained results provide new insights into the P transport and transformation in SSF-CWs and would be helpful to optimize substrate clogging management.

INV-FLOW: New Possibilities to Evaluate the Technical Condition and Function of Extraction Wells

The declining supply of available groundwater resources is increasing the importance of extraction wells. To maximize the yield of extraction wells, the operators do not always respect the sustainable use of groundwater resources. These efforts can affect water quality and impact the service life of an extraction well, mainly through the clogging process. As part of the INV-FLOW project, an apparatus for evaluating the functionality of an extraction well by measuring the vertical water flow through its screen and filter was designed and tested. The apparatus consists of two electromagnetic induction flowmeters, two pneumatic seals, and a pump with the possibility of regulation. After an initial laboratory verification of the fundamental concept, the apparatus was successfully tested in real conditions. Two extraction wells, HJ-3 and HJ-4, intended for water supply to an agricultural production plant, were measured at a pilot site in the Czech Republic using the INV-FLOW apparatus. Although the HJ-3 extraction well is at the end of its service life, the HJ-4 extraction well is a newly installed well. In the new extraction well, HJ-4, a high proportion of water flowing through the gravel pack relative to the total pumping flow (93–97%) was measured using the INV-FLOW apparatus at different pumping rates. In the case of the HJ-3 extraction well, screen and filter clogging contributed significantly to the limited water flow through the gravel pack. In the most affected parts of the extraction well (15–20 m b.g.l.), the proportion of water flowing through the gravel pack relative to the total pumping flow ranged from 10 to 20%. The pilot tests confirmed the functionality of the apparatus and the possibility of using it to evaluate the degree of clogging and incrustation of an extraction well. The pilot tests thus demonstrated the usability of the INV-FLOW apparatus. The extraction well operator can assess the level of clogging or incrustation of the extraction well and decide on the need for the rehabilitation of an extraction well, or the termination of its operation.