Fertilizers mobilization in alluvial aquifer: laboratory experiments

Nitrate and Dissolved Organic Carbon Release in Sandy Soils at Different Liquid/Solid Ratios Amended with Graphene and Classical Soil Improvers

This study emphasizes the importance of employing parallel batch tests with different liquid/solid (L/S) ratios to assess their dissolution mechanisms. Changes in physicochemical parameters (electrical conductivity, pH, and oxidation-reduction potential), as well as the sorption/desorption of dissolved organic carbon (DOC) and nitrate (NO3−) due to graphene addition in a calcareous sandy soil (CS) and in a siliciclastic riverine sandy soil (SS) were assessed via batch experiments at different L/S ratios. Graphene’s production is growing at a great pace, so it’s important to test methods to reuse graphene wastes. The results of soil batch experiments mixed with graphene were compared with classical soil improvers (compost, biochar, and zeolites). The batches were performed using the saturation soil extraction method with deionized water as a proxy of rainwater. The contact time was 48 h. At the end of the experiment, water samples were collected to be analyzed for NO3−, DOC, DIC, Ca, and Mg. Graphene did not alter the physiochemical parameters of both soils. Moreover, its addition did not trigger any NO3− increase respect to control and to other improvers. Biochar increased EC and pH beyond recommended limits for most crops’ growth in both soils. As expected, compost addition produced the highest NO3− release.

Enhancing nitrate and strontium concentration prediction in groundwater by using new data mining algorithm

Groundwater resources constitute the main source of clean fresh water for domestic use and it is essential for food production in the agricultural sector. Groundwater has a vital role for water supply in the Campanian Plain in Italy and hence a future sustainability of the resource is essential for the region. In the current paper novel data mining algorithms including Gaussian Process (GP) were used in a large groundwater quality database to predict nitrate (contaminant) and strontium (potential future increasing) concentrations in groundwater. The results were compared with M5P, random forest (RF) and random tree (RT) algorithms as a benchmark to test the robustness of the modeling process. The dataset includes 246 groundwater quality samples originating from different wells, municipals and agricultural. It was divided for the modeling process into two subgroups by using the 10-fold cross validation technique including 173 samples for model building (training dataset) and 73 samples for model validation (testing dataset). Different water quality variables including T, pH, EC, HCO₃^-, F^-, Cl^-, SO₄^2-, Na⁺, K⁺, Mg²⁺, and Ca²⁺ have been used as an input to the models. At first stage, different input combinations have been constructed based on correlation coefficient and thus the optimal combination was chosen for the modeling phase. Different quantitative criteria alongside with visual comparison approach have been used for evaluating the modeling capability. Results revealed that to obtain reliable results also variables with low correlation should be considered as an input to the models together with those variables showing high correlation coefficients. According to the model evaluation criteria, GP algorithm outperforms all the other models in predicting both nitrate and strontium concentrations followed by RF, M5P and RT, respectively. Result also revealed that model's structure together with the accuracy and structure of the data can have a relevant impact on the model's results.

Evaluating the suitability of urban groundwater resources for drinking water and irrigation purposes: an integrated approach in the Agro-Aversano area of Southern Italy

Deterioration of groundwater quality due to the introduction of pollutants from natural and anthropic sources has become a major environmental issue. We tested three methodologies in assessing groundwater quality and intrinsic aquifer vulnerability in the Agro-Aversano area (Southern Italy). A geographic information system (GIS)-based groundwater quality index (GQI) was realized to assess groundwater quality for drinking and irrigation use and, in parallel, standard SINTACS was applied to evaluate the intrinsic vulnerability of the aquifer. Nitrate concentrations and sodium absorption ratio (SAR) in groundwater samples were used to verify the reliability of vulnerability data. GQI analysis pointed to a general poor quality of groundwater both for drinking and irrigation use, especially in sub-urban areas. The spatial pattern of water quality from GQI analysis was positively related to nitrate and fluoride concentrations for drinking use and to bicarbonate and sodium concentrations for irrigation use, whose levels exceeded the WHO and FAO recommended thresholds, respectively. Standard SINTACS was found to be inadequate for describing the aquifer state, its results showing no correlation with nitrate concentration or SAR. Because of this inconsistency, we tested a novel approach combining GQI with SINTACS analysis. Results showed positive correlation with nitrate (r = 0.63) and SAR (r = 0.64) contents, thus pointing to combined SINTACS-GQI as a more reliable approach than standard methodologies.

Direct measurement of dissolved dinitrogen to refine reactive modelling of denitrification in agricultural soils

Nitrogen fertilizers used in agriculture often cause nitrate leaching towards shallow groundwater, especially in lowland areas where soil permeability, ploughing, clay content, and the flat topography minimizes surface runoff. The introduction of good agricultural practices to reduce the nitrate amount entering the groundwater system is crucial to ameliorate the kinetic control on nitrate denitrification capacity. With this aim, a series of anaerobic mesocosms, consisting of loamy and clay soils and nitrate rich water, were modelled using acetate and natural organic matter as electron donors. Acetate was chosen because it is the main intermediate in many biodegradation pathways of organic compounds, and hence it is a suitable carbon source for denitrification. To account for the spatial variability of soil parameters, the experiments were performed in triplicates. The geochemical code PHREEQC(3) was used to simulate kinetic denitrification, and equilibrium reactions of gas and mineral phases. The reactive modelling results highlighted a rapid acetate and nitrate degradation rate, a rapid production of dissolved inorganic carbon and dinitrogen, and a steady concentration of dissolved iron and sulphate, suggesting that the main pathway of nitrate attenuation is through denitrification; concomitantly excluding the occurrence of other processes leading to nitrate consumption. In the absence of acetate, the loamy soil, poor of natural organic matter, did not allow to complete the denitrification process. This modelling study investigates in detail the relationship between the denitrification process in natural soils, with excess and in limitation of organic substrates, and the occurrence and fate of dissolved dinitrogen analysed with a high precision membrane inlet mass spectrometer. Results demonstrate that modelling nitrate degradation processes as a whole, using geochemical datasets and codes, will improve the estimates of agricultural landscapes denitrification and support better nitrogen management, especially in lowland environments.

Preventing Groundwater Pollution Using Vulnerability and Risk Mapping: The Case of the Florina Basin, NW Greece

The alluvial aquifer system of the Florina basin (320 km2) in North Greece is a representative area where irrigated agriculture is applied. Groundwater is the main source of water. The highest and mean nitrate concentrations in groundwater are 67.9 mg/L and 25 mg/L, respectively. High values could be associated with the use of nitrogen fertilizers from agricultural activities. This study deals with the evaluation of the groundwater quality. For this reason, hydrochemical analyses from 29 groundwater samples and water level measurements were performed for the wet and dry periods of 2016. The suitability of groundwater quality for irrigation purposes is examined by using different indices (Chlorinity Index, SAR, Sodium Percentage, Potential Salinity and Kelly’s index). In addition, the DRASTIC method was modified by using statistical methods, land use map and nitrate concentrations and applied in order to assess the groundwater vulnerability to external pollution. Notably, there was no correlation between the standard DRASTIC method and nitrate concentrations. However, the modified version and the obtained risk map showed high correlation with nitrate concentrations (ρ = 0.55) and the Groundwater Quality; hence, it is suggested as the base for a protection plan of the alluvial aquifer.

Evaluation of saline tracer performance during electrical conductivity groundwater monitoring

Saline solutions are the most commonly used hydrological tracers, because they can be easily and economically monitored by in situ instrumentation such as electrical conductivity (EC) loggers in wells or by geoelectrical measurements. Unfortunately, these low-cost techniques only provide information on the total concentration of ions in solution, i.e., they cannot resolve the ionic composition of the aqueous solution. This limitation can introduce a bias in the estimation of aquifer parameters where sorption phenomena between saline tracers and sediments become relevant. In general, only selected anions such as Cl(-) and Br(-) are recognised to be transported unretarded and they are referred to as conservative tracers or mobile anions. However, cations within the saline tracer may interact with the soil matrix through a range of processes such as ion exchange, surface complexation and via physical mass-transfer phenomena. Heterogeneous reactions with minerals or mineral surfaces may not be negligible where aquifers are composed of fine alluvial sediments. The focus of the present study was to examine and to quantify the bias between the aquifer parameters estimated during model-based interpretation of experimental data of EC measurements of saline tracer relative to the aquifer parameters found by specific measurements (i.e. via ionic chromatography, IC) of truly conservative species. To accomplish this, column displacement experiments with alluvial aquifer materials collected from the Po lowlands (Italy) were performed under water saturated conditions. The behaviour of six selected, commonly used saline tracers (i.e., LiCl, KCl, and NaCl; LiBr, KBr, and NaBr) was studied and the data analysed by inverse modelling. The results demonstrate that the use of EC as a tracer can lead to an erroneous parameterisation of the investigated porous media, if the reactions between solute and matrix are neglected. In general, errors were significant except for KCl and KBr, which is due to the weak interaction between dissolved K(+) and the sediment material. The study shows that laboratory scale pre-investigations can help with tracer selection and to optimise the concentration range targeted for in situ multilevel monitoring by unspecific geoelectrical instrumentation.