Multi-method assessment of nitrate and pesticide contamination in shallow alluvial groundwater as a function of hydrogeological setting and land use

In this study deterministic, multivariate and stochastic methods are applied to a combined temporal and spatial monitoring data set, in order to assess nitrate and pesticide levels and contamination risk in shallow groundwater. The case study involves an area in the Mondego River alluvial body in central Portugal, where agriculture is the main land use, with predominantly maize, rice and some vegetable crops supported by river water irrigation. Factorial correspondence analysis (FCA), reducing the original data matrix to a small number of independent orthogonal factors, is applied to detect associations between nitrate levels, land use (crop type), lithology and groundwater depth. Indicator-geostatistical techniques are used to create maps indicating the probability of nitrate concentrations in groundwater exceeding predetermined threshold values, including the drinking water standard (98/83/EC) and vulnerable zone designation criterion (91/676/EEC) of 50mg/l NO3-. For pesticides the leaching potential is determined by calculating the Groundwater Ubiquity Score (GUS), based on the sorption coefficient and soil half-life for each pesticide compound. Results for nitrate show an overall very low risk of exceeding 50 or 25mg/l, whereas the risk of exceeding 9.5mg/l (third data quartile) is particularly high in areas where FCA shows correlation of nitrate contamination with vegetable and maize crops, aerobic conditions, lower groundwater levels and to some extent, coarser grained sediments. On the contrary, nitrate levels under rice are lowest and correlated to a reduced environment, finer-grained sediments and a higher water table. Denitrification is found to be an important attenuation process, as well as dilution by surface water irrigation and precipitation. Crop type and irrigation source are seen to have a large influence on the nitrate contamination potential of groundwater. Total concentrations of the analysed pesticide compounds above the regulatory limit of 0.5[mu]g/l are observed in 32% of the analysed water samples, with a maximum value of 16.09[mu]g/l. The probability maps provide a particularly interesting example of how multiple-well monitoring results over a certain period can be condensed into single maps and used by water engineers, managers and policy-makers.Shallow groundwater Agricultural contamination Surface irrigation Probability maps Correspondence analysis Denitrification Dilution

A hydrogeological and hydrochemical explanation of the groundwater composition under irrigated land in a Mediterranean environment, Algarve, Portugal.

In the Campina de Faro, in the south of Portugal, agricultural practices have a large impact on groundwater composition. These practices involve pumping of water for irrigation from combinations of large diameter, shallow wells (noras) and small diameter, deep boreholes (furos). Excess irrigation water returns to the aquifer and mixes with water from the regional groundwater flow system. This irrigation return flow is concentrated by strong evapotranspiration and by flushing of fertilisers. The concentration increase induces cation exchange, whereby Ca on the soil exchanger is replaced by Na. The mixing in the aquifer allows application of a mixing cell model which may then be used to calculate transmissivities from the Cl mass balance. The calculations are complicated by the time-variant behaviour of Cl and the method is adjusted to calculate the change of chloride in time. Results from the calculations appear to be in good agreement with hydrochemical observations

Comparative assessment of climate change and its impacts on three coastal aquifers in the Mediterranean

A comparative study on climate change and its impacts on coastal aquifers is performed for three Mediterranean areas. Common climate scenarios are developed for these areas using the ENSEMBLES projections that consider the A1b scenario. Temperature and precipitation data of three climate models are bias corrected with two different methods for a historic reference period, after which scenarios are created for 2020-2050 and 2069-2099 and used to calculate aquifer recharge for these periods based on two soil water budget methods. These multiple combinations of models and methods allow incorporating a level of uncertainty into the results. Groundwater flow models are developed for the three sites and then used to integrate future scenarios for three different parameters: (1) recharge, (2) crop water demand, and (3) sea level rise. Short-term predictions are marked by large ranges of predicted changes in recharge, only showing a consistent decrease at the Spanish site (mean 23 %), particularly due to a reduction in autumn rainfall. The latter is also expected to occur at the Portuguese site, resulting in a longer dry period. More frequent droughts are predicted at the Portuguese and Moroccan sites, but cannot be proven for the Spanish site. Toward the end of the century, results indicate a significant decrease (mean >25 %) in recharge in all areas, though most pronounced at the Portuguese site in absolute terms (mean 134 mm/year) and the Moroccan site in relative terms (mean 47 %). The models further predict a steady increase in crop water demand, causing 15-20 % additional evapotranspiration until 2100. Scenario modeling of groundwater flow shows its response to the predicted decreases in recharge and increases in pumping rates, with strongly reduced outflow into the coastal wetlands, whereas changes due to sea level rise are negligible

Proposal for an index to classify irrigation water quality: a case study in northeastern Brazil

One way of classifying water quality is by means of indices, in which a series of parameters analyzed are joined a single value, facilitating the interpretation of extensive lists of variables or indicators, underlying the classification of water quality. The objective of this study was to develop a statistically based index to classify water according to the Irrigation Water Quality Index (IWQI), to evaluate the ionic composition of water for use in irrigation and classify it by its source. For this purpose, the database generated during the Technology Generation and Adaptation (GAT) program was used, in which, as of 1988, water samples were collected monthly from water sources in the states of Paraíba, Rio Grande do Norte and Ceará. To evaluate water quality, the electrical conductivity (EC) of irrigation water was taken as a reference, with values corresponding to 0.7 dS m-1. The chemical variables used in this study were: pH, EC, Ca, Mg, Na, K, Cl, HCO3, CO3, and SO4. The data of all characteristics evaluated were standardized and data normality was confirmed by Lilliefors test. Then the irrigation water quality index was determined by an equation that relates the standardized value of the variable with the number of characteristics evaluated. Thus, the IWQI was classified based on indices, considering normal distribution. Finally, these indices were subjected to regression analysis. The method proposed for the IWQI allowed a satisfactory classification of the irrigation water quality, being able to estimate it as a function of EC for the three water sources. Variation in the ionic composition was observed among the three sources and within a single source. Although the water quality differed, it was good in most cases, with the classification IWQI II