Predicting leachate impact on groundwater using electrical conductivity and oxidation-reduction potential measurements: An empirical and theoretical approach.

This study developed innovative predictive models of groundwater pollution using in situ electrical conductivity (EC) and oxidation-reduction potential (ORP) measurements at livestock carcass burial sites. Combined electrode analysis (EC and ORP) and machine learning techniques efficiently and accurately distinguished between leachate and background groundwater. Two models-empirical and theoretical-were constructed based on a supervised classification framework.

Using isometric log-ratio in compositional data analysis for developing a groundwater pollution index.

This study introduces a novel groundwater pollution index (GPI) formulated through compositional data analysis (CoDa) and robust principal component analysis (RPCA) to enhance groundwater quality assessment. Using groundwater quality monitoring data from sites impacted by the 2010-2011 foot-and-mouth disease outbreak in South Korea, CoDa uncovers critical hydrochemical differences between leachate-influenced and background groundwater. The GPI was developed by selecting key subcompositional parts (NH-N, Cl, and NO-N) using RPCA, performing the isometric log-ratio (ILR) transformation, and normalizing the results to environmental standards, thereby providing a more precise and accurate assessment of pollution.

A supervised machine learning approach to discriminate the effect of carcass leachate on shallow groundwater quality around on-farm livestock mortality burial sites.

The evaluation of leachate leakage at livestock mortality burial sites is challenging, particularly when groundwater is previously contaminated by agro-livestock farming. Supervised machine learning was applied to discriminate the impacts of carcass leachate from pervasive groundwater contamination in the following order: data labeling, feature selection, synthetic data generation, and classification. Physicochemical data of 359 water samples were collected from burial pits (LC), monitoring wells near pits (MW), pre-existing shallow household wells (HW), and background wells with pervasive contamination (BG).

Delineating the impacts of poultry burial leachate on shallow groundwater in a reclaimed agro-livestock farming area, using multivariate statistical analysis of hydrochemical data.

Burial is applied to dispose of livestock carcasses due to its convenience and cost efficiency despite concerns about groundwater contamination by leachate from burial pits. In particular, the burial method has caused debates about groundwater contamination sources around on-farm livestock burial sites because of pre- and coexisting contamination from livestock production and agriculture. To assess the causes of groundwater contamination around poultry burial pits that were constructed after an outbreak of avian influenza in 2010-11 in Korea, hydrochemical data of groundwater samples from monitoring wells (MWs, n = 14) and household wells (HWs, n = 30) were monitored to differentiate contamination sources.

Impacts of leachates from livestock carcass burial and manure heap sites on groundwater geochemistry and microbial community structure.

We investigated the impacts of leachates from a swine carcass burial site and a cow manure heap on the geochemical and microbiological properties of agricultural water samples, including leachate, groundwater from monitoring wells and background wells, and stream water. The leachate from the livestock burial site showed extremely high electrical conductivity, turbidity, and major ion concentrations, but low redox potential and dissolved oxygen levels. The groundwater in the monitoring wells adjacent to both sites showed severe contamination from the leachate, as indicated by the increases in EC, turbidity, Cl-, and SO42-.