We present a non-parametric hydro-geostatistical approach for mapping design nitrate hazard in groundwater. The approach is robust towards the uncertainty of the parametric models used to map groundwater pollution. In particular, probability kriging (PK) estimates the probability that the true value of a pollutant exceeds a set of threshold values using a binary response variable (probability indicator). Such soft description of the pollutant can mitigate the uncertainty in pollutant concentration mapping. PK was used for assessing nitrate migration hazard across the Campania Plain groundwater (Southern Italy) as exceeding typical critical values set to 25 and 50 mg .L -1. Cross-validation indicated that the PK is more suitable than ordinary kriging (OK), which yields large uncertainty in absolute values prediction of nitrate concentration. This means that spatial variability is critical for contaminant transport because critical contaminants concentration could be exceeded due to preferential flows allowing the pollutant to migrate rapidly through the caveats aquifer. Accordingly with PK application, about 250 km 2 (40% of the total600 km 2 of the Campania Plain) were classified as very sensitive areas (western zone) to maximum permissible concentration of nitrates (>50 mg .L -1). When the probability to exceed 25 mg .L -1 was considered, the contaminated surface increased to 70% of the total area.
Rainfall is the main source for replenishment of groundwater resources that is the water taken into the ground after having saturated the soil [
Natural reactions of atmospheric forms of nitrogen with rainwater result in the formation of nitrate () and ammonium () ions [
Vulnerable lands for high nitrate concentration are in turn recorded in Italy (red colour in
Although studies have been performed attempting to link nitrate consumption to human illnesses, only for methemoglobinemia (also infant cyanosis or blue-baby syndrome) ingestion of water containing high nitrate concentrations proved to be a significant cause. Since 1945, there have been over 2000 cases of infant methemoglobinemia reported in Europe and North America with 7% - 8% of the afflicted infants dying [
Considering the above aspects of groundwater contamination and use of non-parametric hydro-geostatistical approaches in groundwater quality mapping, the present study was undertaken to map the groundwater quality in Campania Plain (Southern Italy) using Box-Cox probability kriging (PK). The main objective of this work is to make groundwater quality assessment based on the available physical-chemical data from 158 locations. The purposes of this assessment are (1) to provide an overview of present groundwater quality, and (2) to determine spatial distribution of groundwater quality parameters such as nitrate (NO3) to generate groundwater quality probability map for a target zone (the Campania Plain, southern Italy).
The study area (approximately 500 km2) is the southern
sector of the wider Campania Plain, a structural depression on the Tyrrhenian Coast (
Climate is very variable in spring and autumn and more stable in winter and summer. Dry season, from May to September, not enable to recharge the soil before of November-December, in order to inter-annual variability. A typical seasonal trend of different terms of water balance is illustrated in
The graben system of the area began to form during the Pliocene, between Mesozoic carbonate sequence outcropping to the east and south of the plain. During the Pleistocene this structural depression was filled with pyroclastic deposits (ashes, pumice, scoriae and tuffs) of Neapolitan volcanoes (Phlegraean Fields and SommaVesuvius) and alluvial (mainly sandy and partly clayey) and marine (mainly silt) sediments to a thickness of some thousands of metres. The first few hundred metres beneath the soil of the circumvesuvian plain, the zone of the most active groundwater circulation, are made up of the pyroclastic deposits (ashes, pumice and scoriae) and alluvial deposits interposed with marine sediments marshy layers and paleosols. The tuff aquitards divide the flow into two overlapping levels (
Travertine, debris and conglomerates lie at the base of the limestone mountains, while approaching the SommaVesuvius volcano lava flows prevail, interbedded with pyroclastic deposits.
The carbonate aquifers are the most important aquifers located at the boundaries of the plain. The Somma-Vesuvius volcano has a radial water table. Groundwater flows towards the sea and also feeds the aquifer of the surrounding plain. The aquifer of the Campania Plain is characteristically extremely heterogeneous due to granulometric variation in the unconsolidated sediments, the degree of fissuring of rock and complex stratification of deposits.
The map (
The hydraulic gradient varies from a few units per thousand to a few units per hundred. In particular, the highest values of the piezometric gradient found at the foot of Lattari mountains, may be related to high transmissivity from carbonate aquifers (10−1 - 10−2 m2∙s−1) compared with values in other areas the plain (10−2 - 10−4 m2∙s−1).
The main contributions to aquifer recharge are provided by direct infiltration and groundwater inflow from the nearby volcanic and carbonate aquifers. The mean annual effective infiltration is of 59.6 × 106 m3∙yr−1 [
Groundwater pollution sampling was initiated since 1992
in Campania Plain and continued in 2001 and 2006 years [24,25]. However, only in 1992 a wide and resolute sampling was conducted covering a surface of about 500 km2.
In 158 wells used for the reconstruction of the paper in the aquifer isopiezometric curves were also collected water samples for the determination of nitrate concentrations. The analysis refers to the period of low water of the aquifer. Nitrate in water samples was colorimetrically measured [26,27]. The wells were managed by one of the leading institutions of central-southern aqueduct (ARIN, Naples Water Resources Company, http://www.arin.na.it).
Kriging and its derivatives have been recognized as the main spatial interpolation techniques from 1970s. Kriging is a method for making optimal, unbiased estimates of regionalized variables at unsampled points. It is possible to have a good estimation of the selected variable using the values collected in the surrounding stations and a structural analysis [
In the present paper, environmental risk assessments related to nitrate pollution are derived from the probability that a pollutant leaching rate can migrate from sub-surface to groundwater. The selected thresholds or the action level often determine the introduction or not of certain measures. The concentration in natural water is less than 10 mg∙L−1. Water containing more than 100 mg∙L−1 is bitter to taste and causes physiological distress. Water in shallow wells containing more than 50 mg∙L−1 causes methemoglobinemia, the so-called blue baby syndrome in humans [
Availability of the regionalization between indicator pollutant at nitrate threshold concentrations for each location sα within the study area would allow a grid layer α(sα) referring to “probable hydrogeological effectiveness” of the nitrate pollutant on the basis of the estimate when actually. The European Commission suggested two limits for nitrates: a first threshold, zk1 = 25 mg∙L−1, which represents the minimum concentration needed to overcome the drinking groundwater quality, and the second, zk2 = 50 mg∙L−1, which represents the maximum values for the drinking groundwater quality.
The ability to identify the true spatial variability of a dataset depends to a great extent, on ancillary knowledge of the underlying measured phenomenon. This is why exploratory data analysis is often the first step in hydrogeostatistical studies. Postplot, initial contour maps and basic statistics are used as a preliminary description of the dataset in a spatial context and to develop a strategy for future evaluation [
The presence of nitrates is considered an indicator of pollution in the Campania Plain because of the intensive agricultural land use, urbanization and industrial practices throughout the area. In several wells, nitrate concentrations exceed the maximum allowable concentration (50 mg∙L−1) as set by the Italian law. The statistics of nitrate data collected in October 1993 are summarized with mean and median values equal to 57 mg∙L−1, and 43 mg∙L−1, respectively. The maximum value is 239 mg∙L−1.
A two-stage model of regionalization was fitted using an iterative procedure [
Semivariogram values increase with the separation distance, reflecting the assumption that nearby nitrate-pollutant data tend to be more similar than data that are farther apart. The modelled variograms have been tested by the cross-validation method. The semivariograms reach 2000 to 10,000 m before dipping around a sill value.
In particular, while unidirectional semivariograms in
The three spatial structures for high nitrate concentration lead us to believe that there are different sources of pollution resulting from the landscape overlying the aquifer. At the local level the presence of nitrates may result from direct leakage into the groundwater of organic waste. At larger range, instead, nitrate may have derived from non-point source as agricultural manures.
The symbolic term in Equations (3) and (4), , is the spherical correlation function equal to
.
It represents a dimensional semivariance of unit sill with ranges given by the circle with a1 = 10000, zk1 = 25 mg∙L−1, and a2 = 3000 a3 = 10000 meters, for zk2. Ideally, the value of the semivariogram should reach a minimum value when the separation vector h is zero. In the case study, this is not true firstly because the measurement error exists in nitrate sampling data, and secondly because the distribution and number of wells could be poor. The range relative to the large threshold, zk2 = 50 mg∙L−1, has a minor nugget than with zk1 = 25 mg∙L−1 but the nugget/total sill ratio is roughly the same (0.46 - 0.47)which indicates moderate spatial correlation for both the thresholds.
Figures 8(a) and (b) show probability-kriged maps, based on 500 m by 500 m grid across Campania Plain. In kriged model pattern area of
Especially in the map of
In
As already outlined [
At the time of sampling, the only areas remaining free from high concentrations can be individuated between the surrounding of Palma Campania, Nola, Marigliano and Roccarainola municipalities. Local patterns with high nitrate concentration were also founded in Somma Vesuviana and Palma Campania, especially in PK [>50 mg∙L−1].
However, no spatial pattern variability can be detected below 2000 m, due to nugget effect. This represents unexplained or random variance, which is either caused by variability of data that cannot be detected at the scale of sampling, or measurement errors within Campania Plain. Although the monitoring phase refers to the period of lean ground when less effective infiltration is present, the maps presented here suggest a dramatic pattern with still high probability of exceeding the above limits. Therefore, it is suspected that nitrate concentrations in well water can be high during any month of the year and the issue of nitrate contamination and health effects should not be ignored.
The error involved on the expansion of the information from point to landscapes through probability kriging es-
timation can be assessed through a quantitative estimation standard error of indicator and cross-validation [
The result of the cross-validation is presented within the statistical errors and scatter diagram (above and below panels in
If we consider OK experiment, measurements versus the predicted values of nitrate are in disagreement (see the scatter diagram of
This study has attempted to predict the spatial distribution and uncertainty of groundwater nitrate concentration across some municipalities of the Campania Plain (Southern Italy). Probability kriging, a type of nonparametric geostatistical techniques, was applied to the groundwater nitrate hazard data for two distribution maps related to
the threshold values of 25 and 50 mg∙L−1, respectively. Geostatistics can provide tools to describe spatial and hazard behavior of hydrochemical parameters. Groundwater nitrate concentrations were log-normally distributed. The spherical model was found to be the best model representing the spatial variability of groundwater probability nitrate maps. The average value of the variograms for the spatial analysis was in a range of 2000 - 10,000 m in the spherical model. Nitrate pollution in the groundwater occurred most in the urban and periurban centre of the municipalities because of nitrate excess from biological, agricultural and, secondarily, industrial production. Although the modelling results indicate that the probability kriged groundwater nitrate maps satisfactorily matched the observed groundwater nitrate distribution, a newer and more continuos sampling is needed for reaching the areas with more hazard.