Compositional cokriging for mapping the probability risk of groundwater contamination by nitrates

Comparative health risk assessment of nitrate in drinking groundwater resources of urban and rural regions (Isfahan, Iran), using GIS

Infantile methemoglobinemia, thyroid disorders, and probably some carcinogenic effects are health concerns associated with dietary nitrate. Isfahan province has a dry and semi-arid desert climate such that the main source of various applications in this province is groundwater resources. This study evaluated spatial analysis of the groundwater NO₃^- concentrations and its possible health risk to residents. Method 8171 Hach was used for nitrate measurement of 1319 groundwater samples from March 2018 to February 2019. Non-carcinogenic risk due to NO₃^- exposure through consumption of drinking water was assessed, and the associated zoning maps were presented using geographic information system (GIS). Nitrate concentrations in the rural and urban areas were within 0.4-137 mg/L NO₃^- and 2.9-209 mg/L NO₃^-, respectively. Also, 226 (25%) and 104 (24%) of samples in the rural and urban areas, respectively, were detected above the Iran and WHO guideline NO₃^- values of 50 mg/L. The highest levels of NO₃^-, which were found in the western and central groundwater resources, occurred in the agricultural and residential areas. The NO₃^- concentrations were higher in urban than rural areas in the many studied counties. Also, nitrate was higher in wet seasons than in dry ones. Infants' non-carcinogenic risks were higher than the other groups. Infants (HQ > 1) were the most vulnerable group compared with the other groups in some counties. Thus, there are potential risks of methemoglobinemia, especially for infants. It is critical to adopt specific strategies to reduce the nitrate concentration in the studied groundwater.

Multi-scaled response of groundwater nitrate contamination to integrated anthropogenic activities in a rapidly urbanizing agricultural catchment

Anthropogenic activities have a significant contribution to groundwater nitrate contamination at multiple spatial scales in urbanizing agricultural catchments, while how to derive the optimal researching scale and explore the relative importance among anthropogenic activities for groundwater nitrate contamination still remains challenging. In this study, 165 perched groundwater and 120 shallow groundwater samples were collected in two urbanizing agricultural catchments, to explore anthropogenic activity effects on groundwater nitrate contamination crossing multiple spatial scales, integrating the probability kriging, multi-scale comparison at spatial scales of 100 to 1900 m with an increment of 200 m at the block scales, and variance partitioning analysis. Probability of perched and shallow groundwater nitrate concentration > 3 mg L^-1 exhibited strong spatial autocorrelation, with effective ranges of 1091 m and 3743 m from semivariogram, respectively. Relationships between perched and shallow groundwater nitrate concentrations were more significant and robust (r = 0.30-0.52, p < 0.001) at the block scale from 300 to 1100 m, indicating that perched groundwater nitrate closely related to shallow groundwater nitrate. The responses of groundwater nitrate contamination on anthropogenic drivers presented strongly scaling correlation and had the highest correlation at the spatial scale of 1100 m, suggesting the optimal scale for exploring anthropogenic activity effects on groundwater nitrate contamination. The three categories of anthropogenic drivers (urbanization, agriculture intensification, and demographic driver) contributed to 31.0-84.0% part of the total variations in groundwater nitrate contamination at the spatial scale of 1100 m. Particularly, agriculture intensification was the most influential driver for groundwater nitrate contamination, while the urbanizing process and population growth played important roles surrounding urban cores. Our findings highlighted the importance of incorporating multi-scale comparisons on regional groundwater quality evaluation, and provided technical support to the groundwater resource management strategy development in urbanizing agricultural regions.

Nitrate trends in groundwater of the Campania region (southern Italy)

The Environmental Protection Agency of the Campania region in Italy (ARPAC) manages a groundwater quality monitoring network. For almost all the polluted waters, the key parameter driving the classification is the concentration of nitrate; hence, the Campania region, in coherence with the EU regulations, outlined the vulnerable areas and undertook remediation policies. The best groundwater quality is recorded for carbonate aquifers of the Apennine chain; on the contrary, the Tyrrhenian coastal plains are affected by severe contamination, with a locally very contaminated groundwater of the shallow and also the deeper aquifers. The study is especially focused on a large coastal plain of Campania region, where nitrate concentration sometimes exceeds 200 mg/L. The study, based on almost 200 sampling points for the whole region during the period 2003-2015 (approx two samples per year), verified the effectiveness of the groundwater monitoring network, the present distribution of nitrate in groundwater, and the evolution of nitrate trends at different scales: regional, groundwater body, and single well, using spatial and time series statistical approaches. Significant variations in contamination evolution within the study area have been observed and the correlation with land use has been highlighted.

Feature selection approaches for predictive modelling of groundwater nitrate pollution: An evaluation of filters, embedded and wrapper methods

Recognising the various sources of nitrate pollution and understanding system dynamics are fundamental to tackle groundwater quality problems. A comprehensive GIS database of twenty parameters regarding hydrogeological and hydrological features and driving forces were used as inputs for predictive models of nitrate pollution. Additionally, key variables extracted from remotely sensed Normalised Difference Vegetation Index time-series (NDVI) were included in database to provide indications of agroecosystem dynamics. Many approaches can be used to evaluate feature importance related to groundwater pollution caused by nitrates. Filters, wrappers and embedded methods are used to rank feature importance according to the probability of occurrence of nitrates above a threshold value in groundwater. Machine learning algorithms (MLA) such as Classification and Regression Trees (CART), Random Forest (RF) and Support Vector Machines (SVM) are used as wrappers considering four different sequential search approaches: the sequential backward selection (SBS), the sequential forward selection (SFS), the sequential forward floating selection (SFFS) and sequential backward floating selection (SBFS). Feature importance obtained from RF and CART was used as an embedded approach. RF with SFFS had the best performance (mmce=0.12 and AUC=0.92) and good interpretability, where three features related to groundwater polluted areas were selected: i) industries and facilities rating according to their production capacity and total nitrogen emissions to water within a 3km buffer, ii) livestock farms rating by manure production within a 5km buffer and, iii) cumulated NDVI for the post-maximum month, being used as a proxy of vegetation productivity and crop yield.

Nitrate and nitrite contents in in the private ground water wells

The aim of the study was to investigation and statistical evaluation of nitrate and nitrite in ground sources of drinking water, particularly in private wells and springs in the surroundings of town Nitra, in the river basin Žitava. Samples were taken in the spring month May and the autumn month October of the same water sources. The contents of nitrate and nitrite was determined by test strips QUANTOFIX Nitrate and nitrite. The results were evaluated in the system SAS program, version 8.2. The difference of nitrate in drinking water sources between spring and autumn months was statistically evaluated by t-test. The nitrate content in drinking water samples taken from the surroundings of town Nitra, in the river basin Žitava, was measured in the spring month of May with exceeding values that exceeded the 50 mg.L-1, which is the limit value for the adult human population, in the well of municipalities Veľká Maňa, Žitavce, Michal nad Žitavou, Malá Maňa, Uľany nad Žitavou, Hul, Kmeťovo and 50 mg.L-1 was measured in spring Vlkas, in well of municipality Lúčnica nad Žitavou, Veľká Maňa, part of the Stará Hora. In the autumn month October measured nitrate content was reduced in samples taken in the municipalities Lúčnica nad Žitavou, Malá Maňa, Kmeťovo and Uľany nad Žitavou. The difference of nitrate content in water from water sources investigated in surroundings of town Nitra was not statistically significant (p >0.05) between the months May and October. The nitrite content in the same water sources in the surrounding of town Nitra was not detected.