Advanced redox zonation of the San Pedro Sula alluvial aquifer (Honduras) using data fusion and multivariate geostatistics

Fe and As geochemical self-removal dynamics in mineral waters: evidence from the Ferrarelle groundwater system (Riardo Plain, Southern Italy)

A theoretical pattern for Fe and As co-precipitation was tested directly in a groundwater natural system. Several monitoring wells were sampled to identify the different endmembers that govern the hydrodynamics of the Ferrarelle Groundwater System in the Riardo Plain (Southern Italy). In agreement with recent investigations, we found a mix of a deep and a shallow component in different proportions, resulting in a specific chemical composition of groundwater in each well depending on the percentages of each component. The shallow component was characterized by EC ~ 430 µS/cm, Eh ~ 300 mV, Fe ~ 0.06 µmol/L and As ~ 0.01-0.12 µmol/L, while the deep component was characterized by EC ~ 3400 µS/cm, Eh ~ 170 mV, Fe ~ 140 µmol/L and As ~ 0.59 µmol/L. A general attenuation of As and Fe concentration that was not due to a simple dilution effect was observed in the mixing process. The oxidation of Fe(II) to Fe(III) produces solid precipitates which adsorb As from solution and then co-precipitate. The reactions pattern of Fe(II) oxidation and As adsorption gave a linear function between [As] and [Fe], where the angular coefficient depends on the [O₂]/[H⁺] ratio. Chemical data obtained from our samples showed a very good agreement with this theoretical relationship. The investigated geochemical dynamics represented a natural process of attenuation of Fe and As, two undesirable elements that usually affect groundwater quality in volcanic aquifers in central-southern Italy, which are exploited to supply drinking water.

A multivariate non-parametric approach for estimating probability of exceeding the local natural background level of arsenic in the aquifers of Calabria region (Southern Italy)

The concept of natural background level (NBL) aims at distinguishing the natural and anthropogenic contributions to concentrations of specific contaminants, as groundwater management and protection tools. This is usually defined as a unique value at a regional scale, even when the hydrogeological and geochemical features of a certain territory are far from homogeneous. The concentration of target contaminants is affected by multiple hydrogeochemical processes. This is the case of arsenic in the Calabria region, where concentrations are definitely variable in groundwater. To overcome the limitation of a traditional approach and to include the intrinsic hydrogeological and geochemical heterogeneity into the definition of the natural contribution to As content in groundwater, an integrated probabilistic approach to the NBL assessment combining aquifer-based preselection criteria and multivariate non-parametric geostatistics was proposed. In detail, different NBL values were selected, based on the aquifer type and/or hydrogeochemical features. Then, these aquifer-based NBL values of arsenic were used in the Probability Kriging method to map the probability of exceedance and to provide contamination risk management tools. This multivariate geostatistical approach that takes advantage of the physico-chemical variables used in the aquifer-based NBL values definition allowed mapping the probability of exceedance of As in a physically-based way. The hydrogeochemical diversity of the study area and all the processes affecting As concentrations in the aquifers have been considered too. As a result, the obtained map was characterized by a short-range and long-range variability due to local hydrogeochemical anomalies and water-rock interaction and/or atmospheric precipitation. By this approach, the NBL exceedance probability maps proved to be less "noisy", because the local hydrogeochemical conditions were filtered, and more capable of pointing out anthropogenic inputs or very anomalous natural contributions, which need to be investigated more in detail and properly managed.

Modelling groundwater quality of the Athabasca River Basin in the subarctic region using a modified SWAT model

Groundwater is a vital resource for human welfare. However, due to various factors, groundwater pollution is a paramount environmental concern. It is challenging to simulate groundwater quality dynamics with the Soil and Water Assessment Tool (SWAT) because it does not adequately model nutrient percolation processes in the soil. The objectives of this study were to extend the SWAT module to simulate groundwater quality for the parameters nitrate and Total Dissolved Solids (TDS). The results of the SWAT model for the Athabasca River Basin in Canada revealed a linear relationship between observed and calculated groundwater quality. This result achieved satisfactory values for coefficient of determination (R²), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS). For nitrate, the model performance measures R² ranged from 0.66–0.83 during calibration and NSE from 0.61–0.83. R² is 0.71 during validation and NSE ranged from 0.69–0.75. Likewise, for TDS, the model performance measures R² ranged from 0.61–0.82 during calibration and from 0.58–0.62 during validation. When coupled with soil zone and land surface processes, nitrate and TDS concentrations in groundwater can be simulated with the SWAT model. This indicated that SWAT may be helpful in evaluating adaptive management scenarios. Hence, the extended SWAT model could be a powerful tool for regional-scale modelling of nutrient loads, and to support and effective surface and groundwater management.

Simulation-Based Solutions Reducing Soil and Groundwater Contamination from Fertilizers in Arid and Semi-Arid Regions: Case Study the Eastern Nile Delta, Egypt

Intensive agriculture requires increasing application of fertilizers in order to sustain food production. Improper use of these substances in combination with increasing seawater intrusion results in long-term and nonpoint soil and groundwater contamination. In this work, a 3-D groundwater and solute transport numerical model was created to simulate the effect of excessive fertilizers application along the Bahr El Baqar drain system, in the eastern Nile Delta, Egypt. The geotechnical properties of the soils, hydrologic parameters, and unconfined compressive strength were determined at different sites and used as input parameters for the model. Model results showed that silty clay soils are able to contain the contaminations and preserve the groundwater quality. Nevertheless, sandy soils primarily located at the beginning of the Bahr El Baqar drain allow leakage of fertilizers to the groundwater. Thus, fertilizer application should be properly managed in the top sandy layers to protect the groundwater and soil, as increasing aquifer by excess irrigation water increased the groundwater contamination in confined layers due to the high value of cumulative salt for the current situation while the unconfined zone decreased groundwater and soil contamination. A mass transport 3-D multi-species (MT3D) model was set to identify the optimal measure to tackle soil and groundwater contamination along the Bahr El-Baqar drain system. A potential increase of the abstraction rates in the study area has a positive impact in reducing the transfer of fertilizer contamination to groundwater while it has a negative impact for soil contamination. The scenario analysis further indicated that the installation of a drainage network decreases the groundwater and soil contamination. Both solutions are potentially effective for protection against nonpoint contamination along the Bahr El Baqar drain system. However, a more sustainable management approach of fertilizer application is needed to adequately protect the receptors located further downstream in the Nile Delta.

Regional rainfall threshold maps drawn through multivariate geostatistical techniques for shallow landslide hazard zonation

The Empirical Rainfall Thresholds (ERTs) for shallow landslide initiation are commonly devised worldwide mostly to be implemented within landslide early warning systems. Nonetheless, since the pioneering works on ERTs in the 1980s, only meteorological variables - that are cumulated E or intensity I and duration D values of rainfalls that are likely to trigger landslides - have been used to predict landslide occurrence, even though they are characterized by a large uncertainty. Over time, many efforts have been devoted to constrain ERT to geo-morphological characters of the landslide locations but, since nowadays, they did not get to a sound new method to derive ERT and strengthen its ability to forecast future rainfall-induced landslide. In this study, local geo-morphological characters have been taken into account by means of the co-kriging technique to constrain the E and D mean values of a regional ERT and their confidence intervals. The study area, where the proposed method was trained, is the hilly side of the Abruzzo region (Italy). Here, 62 shallow landslides have been analyzed in the time span of 2013-2017 by collecting 62 (D,E) pairs related to the rainfalls that were likely to trigger them. The relevant geo-morphological features for the considered territory have been selected through the principal component analysis. Then, the Multi-Collocated Co-Kriging technique, through ISATIS Geovariances software, has been applied to derive the spatial variability structures of E and D values conditioned by the selected geo-morphological parameters. Therefore, threshold values of E and D and their confidence intervals have been calculated generating a new shape of regional ERT, consisting of maps of continuous estimated threshold values of (D,E) and confidence interval values suitable for being used in early warning systems for shallow landslide initiation.