Search

Keywords: ground water pollution, Kalpitiya peninsula, methaemoglobinaemia, nitrate, nitrite Doi: 10.4038/jnsfsr.v28i2.2679 J.Natn.Sci.Foundation Sri Lanka 2000 28 (2): 101-112

This article looks at the development of the politics of nitrate pollution control in Britain between its emergence on the agenda in the early 1970s and 1988. Using and adapting Blowers’ development of the key approaches to policy analysis it explores the way in which the issue, which was for a long while treated as a minor one, of concern only to the experts within the water industry, has moved towards the centre of the political stage as a consequence of British difficulties in complying with the requirements of the EEC Drinking Water Directive, the privatisation of the water industry and a decline in the political influence of agriculture. It suggests, however, that this shift has been slow and tentative, and that it remains unclear to what extent actual controls will be imposed upon farmers and who will bear the cost of those controls.

The Mitidja aquifer, a 1300 Km2 plain oriented east west, north of Algeria, is very important in size and role. It is infortunately very sensitive to pollution. Sources of nitrates pollution are numerous: domestic, agricultural and industrial. An association of Na + , K + and CL − elements with nitrates was observed. In order to determine a probable source of contamination, we studied this association. A high rate of these elements is more likely to indicate a possible nitrate contamination of organic origin. To precise the origin of this pollution, a coupling of natural isotope tracing with values of Bore is necessary. In a second phase, a mathematical model will be proposed to predict the evolution of nitrate concentration in time and space in that region.

Yield, N uptake and residual NO 3 − -N data for wheat and maize, raised in a long-term experiment, have been discussed to determine optimum rates of fertilizer N application at which yields are least affected, while unused nitrogen, which is a potential pollutant, is reduced to a permissible level. Computation of fertilizer N rates corresponding to the points of greatest economic return and permissible N loss has been described. Optimum fertilizer N rate is the smaller of the two fertilizer N rates. By assuming a loss of 60 kg N/ha or less, as environmentally permissible, it was observed that a small yield increment of maize would have to be sacrificed for the protection of the environment; whereas, for wheat, nitrogen can be applied safely upto the point of greatest economic return. Coincidence of the rainy season with the growth period of maize in the study area seems to have reduced the fertilizer N rate, corresponding to the point of permissible N loss, lower than that for greatest economic return.

The combination of increasing nitrate concentrations in the River Thames and the recent EEC Directive on the acceptable level in potable water is posing a potential problem. In assessing the impact of nitrates on water-resource systems, extensive use has been made of time-series analysis and simulation. These techniques are being used to define the optimal mix of alternatives for overcoming the problem on a regional basis.

A nation-wide investigation of nitrate concentrations in groundwater in Denmark has been carried out. The investigation is based on analyses of groundwater samples from app. 11,000 wells and drinking water from 2,800 groundwaterworks spread equally all over the country, 43,000 km2. Furthermore the trends in nitrate concentrations have been investigated on the basis of time-series of nitrate concentrations for 184 waterworks. The investigation shows that: - the overall mean level of nitrate concentrations in the groundwaters has trebled within the last 20-30 years, - there are pronounced regional differences in the nitrate concentrations of the groundwaters and in the trends of the nitrate concentrations, - in the western parts of the country the groundwaters are more seriously affected than in the eastern parts and rising trends are significantly more pronounced, - 36% of the investigated time-series of nitrate concentrations in drinking water from 184 groundwaterworks show a rising trend of 1 to 6 mg NO3/1 per year with a mean value of 3.3, and there is no sign of levelling off, - drinking water from 8% of the waterworks exceed the EEC maximum admissible concentration for nitrate of 50 mg/1 and 18% EEC guide level of 25 mg/1. The causes of the general rising trends in the nitrate concentrations in the groundwaters and the regional differences of the trends are discussed. In particular, the impact of agricultural activities and the role of the geological conditions are considered.

Scope for reducing two inputs, nitrogen fertilizer and fungicide sprays, while maintaining farm profits is considered. Nitrogen taxes have been proposed as a means to reduce nitrate pollution and so the effect of such a policy was examined using nitrogen response curves obtained from trials data. Optimum application rates derived from the curves for various price levels were supplied to the IER Arable Farm Model which indicated farm scale effects. Doubling the price of N reduced the amount used by 10 to 24% depending on the availability of low-N break-crops. The tax required to significantly reduce N use was found to be far in excess of that required to pay for water treatment. The potential for more efficient use of fungicide sprays was considered with a computer model which simulates the growth of a cereal crop and the progress of a mildew epidemic within it. Four commonly used spray timing rules were tested and found to attain 65 to 75% of the potential profit from fungicide use. It is found that an alternative strategy making full use of our knowledge of the crop and disease can attain over 90% of potential profit and require fewer sprays.

This survey deals with world aspects of nitrate pollution in water and soils mainly due to excess application of artificial fertilisers. Arising from this abuse, problems of eutrophication have been widely reported and also those of degradation of soil structure and fertility. The uptake of excess nitrate from soil directly into plants including grass is demonstrated, and the effects described of its subsequent breakdown, particularly after ingestion, to nitrite and nitrosamines in animals and humans. Special mention is made relative to the onset of methaemoglobinaemia and the recently observed connections between nitrosamines, cancer and spina bifida. Attention is drawn to the banning of nitrate preservatives in meat products by the Norwegian Government as from January, 1973. Control measures are suggested via the combined efforts of Ministries of Health, Agriculture and the Environment.

A comparison was made of the use of natural variations in /sup 15/N abundance vs. /sup 15/N-enriched and /sup 15/N-depleted fertilizers in determining the contribution of inorganic ammonium fertilizers to the NO/sub 3/-N extracted from a Webster soil following a 30C aerobic incubation for 2.5 weeks. The natural abundance approach was unsatisfactory even in this simplified system and its lack of success is shown to be due in part to replicate variability. The fluctuations in /sup 15/N-content of the nitrate from carefully replicated samples of each fertilizer treatment were of the same order of magnitude as the mean difference between the /sup 15/N-contents of natural ferttlizer-N and the soil-derived NO/sub 3/-N. Therefore, the use of labeled fertilizers with /sup 15/ N-contents substantially higher or lower than the natural abundance figure is the only valid approach to the measurement of fertilizer contribution to the NO/sub 3/ -N appearing in tile drains under field condition. (auth)

Groundwater contamination is a major problem related strongly to both; protection of environment and the need of water. In the present study groundwater quality was investigated in the central part of the Nile Delta (El-Gharbiya Governorate). El-Gharbiya Governorate is an agricultural land and its densely populated area inhabited, includes small communities which totally not served by public sewers. Hydrochemical analyses were used to assess the quality of water in samples taken from the canals, drains and groundwater. A laboratory study and mathematical modeling works were presented. Two numerical computer models by the applying of finite difference method were adopted. Both models deal with the flow as a three-dimensional and unsteady. Results obtained include determining the levels of water and the values of solute concentration and distribution of it in the region at different times. The groundwater model MODFLOW was used to deal with the hydrodynamics of the flow through porous media. A solute transport model which can be communicated with MODFLOW through data files MT3DMS, was used to solve the problem of contaminants transport and the change of their concentrations with time. A proposed groundwater remediation scheme by using group of extraction wells was suggested at Birma region where the concentration values of ammonium contaminant are the up most according to hydrochemical analyses results. Proposed scenario for cleaning is to use a set of wells to pump contaminated groundwater extraction for treatment and reused to irrigation.

Dug wells serve as the source of supply to individual homes and farms in some rural regions of Hungary. Nitrate pollution in these waters has been reported from many areas of the country in the early fifties already. The water obtained from drilled wells reaching down into confined aquifers and that piped to public water works from karstic springs has shown occasionally signs of deterioration by nitrate pollution in the last decade only. In order to obtain a picture on the extent of pollution due to nitrates, a survey was run in 1979 on all sources of supply to public water works in the country. The results and conclusions of major interest emerging from this survey are described in the present paper.

Farming practices and their implications for the environment have come under increasing scrutiny in recent years with mounting pressures on farmers to reduce pollution and achieve higher environmental standards. The Nitrates Directive is an outstanding example, at EU level, of the pressure on farmers to redirect agriculture toward greater sustainability. This paper examines the implementation process of the Nitrates Directive in Spain, analysing the causes of the delay in implementing the directive, and examining farmer’s views of nitrate pollution and their attitudes toward environmental regulation of their activity.

The protection of water resources and development of mitigation strategies require large-scale information on water pollution such as nitrate. Machine learning techniques like random forest (RF) have proven their worth for estimating groundwater quality based on spatial environmental predictors. We investigate the potential of RF and quantile random forest (QRF) to estimate redox conditions and nitrate concentration in groundwater (1 km × 1 km resolution) using the European Water Framework Directive groundwater monitoring network as well as spatial environmental information available throughout Germany. The RF model for nitrate achieves a good predictive performance with an R2 of 0.52. Dominant predictors are the redox conditions in the groundwater body, hydrogeological units and the percentage of arable land. An uncertainty assessment using QRF shows rather large uncertainties with a mean prediction interval (MPI) of 53.0 mg l−1. This study represents the first nation-wide data-driven assessment of the spatial distribution of groundwater nitrate concentrations for Germany.

In the present study an overlay method to assess groundwater vulnerability is proposed. This new method based on multicriteria decision analysis (MCDA) was developed and validated using an appropriate case study in Aragon area (NE Spain). The Vulnerability Index to Nitrates from Agricultural Sources (VINAS) incorporates a novel Logic Scoring of Preferences (LSP) approach, and it has been developed using public geographic information from the European Union. VINAS-LSP identifies areas with five categories of vulnerability, taking into account the hydrogeological and environmental characteristics of the territory as a whole. The resulting LSP map is a regional screening tool that can provide guidance on the potential risk of nitrate pollution, as well as highlight areas where specific research and farming planning policies are required. In the present study an overlay method to assess groundwater vulnerability is proposed. This new method based on multicriteria decision analysis (MCDA) was developed and validated using an appropriate case study in Aragon area (NE Spain). The Vulnerability Index to Nitrates from Agricultural Sources (VINAS) incorporates a novel Logic Scoring of Preferences (LSP) approach, and it has been developed using public geographic information from the European Union. VINAS-LSP identifies areas with five categories of vulnerability, taking into account the hydrogeological and environmental characteristics of the territory as a whole. The resulting LSP map is a regional screening tool that can provide guidance on the potential risk of nitrate pollution, as well as highlight areas where specific research and farming planning policies are required.

Περίληψη: Στην παρούσα διπλωματική εργασία επιχειρείται η χρήση τεχνητού νευρωνικού δικτύου για την εκτίμηση των συγκεντρώσεων νιτρικών ιόντων (NO3-) σε υπόγεια ύδατα. Η νιτρορύπανση προκαλείται με την άμεση ή έμμεση απόρριψη στο υδάτινο περιβάλλον αζωτούχων ενώσεων και οδηγεί στην πρόκληση βλαβών στην ανθρώπινη υγεία και στην υποβάθμιση των υδατικών οικοσυστημάτων. Στα υπόγεια ύδατα, εμφανίζεται κυρίως με τη μορφή αθροιστικής συσσώρευσης νιτρικών, τα οποία σε ορισμένες περιπτώσεις φθάνουν σε επίπεδα που είναι απαγορευτικά για τη χρήση του νερού για σκοπούς ύδρευσης. Ως οριακή τιμή έχει καθορισθεί από την Ελληνική και Διεθνή νομοθεσία η συγκέντρωση των 50 mg/l, ωστόσο ακόμα και σε μικρότερες συγκεντρώσεις (μεγαλύτερες από 25 mg/l) δημιουργείται προβληματισμός για μακροχρόνια χρήση του νερού για πόση (ypeka, 2018). Η μοντελοποίηση της νιτρορύπανσης των υπόγειων υδάτων με τις κλασικές αριθμητικές μεθόδους μπορεί να καταστεί ιδιαίτερα δύσκολη διαδικασία και απαιτεί πολύ καλές γνώσεις της γεωμορφολογίας της περιοχής, η οποία εν γένει χαρακτηρίζεται από ετερογένεια (Tanty & Desmukh, 2015; Gutiérrez et al, 2018). Επιπλέον, οι τεχνικές ανίχνευσης και μέτρησης των συγκεντρώσεων των νιτρικών ιόντων στο νερό χαρακτηρίζονται από υψηλό κόστος και υψηλές απαιτήσεις σε χρόνο, ενώ οι φορητές συσκευές που χρησιμοποιούνται δεν είναι ικανοποιητικής ακρίβειας. Ακόμη, στις διάφορες μεθόδους που χρησιμοποιούνται για τη χημική ανάλυση του νερού, η ανίχνευση των νιτρικών επηρεάζεται από την ύπαρξη άλλων ιόντων, κυρίως των Cl- (Alahi & Mukhopadhyay, 2018). Το γεγονός αυτό οδηγεί σε σημαντική υποβάθμιση του προβλήματος, ιδιαίτερα σε περιοχές με υψηλές συγκεντρώσεις αλάτων, όπως σε παράκτιους υδροφορείς. Με γνώμονα τα προαναφερθέντα ζητήματα, στην παρούσα εργασία εξετάζεται η δυνατότητα χρήσης νευρωνικών δικτύων για την εκτίμηση των συγκεντρώσεων των νιτρικών ιόντων σε υπόγειους υδροφορείς. Το νευρωνικό δίκτυο δεν απαιτεί γνώση των γεωμορφολογικών χαρακτηριστικών της περιοχής, η οποία είναι δύσκολο να αποκτηθεί, ενώ ως παράμετροι εισόδου μπορούν να χρησιμοποιηθούν μεταβλητές χωρίς να υπάρχει γνώση των σχέσεων που τις διέπουν στο σύστημα που μελετάται (Trichakis et al., 2011). Για το σκοπό της εργασίας, αναπτύχθηκαν συνολικά τρία νευρωνικά δίκτυα σε περιβάλλον Matlab. Για το πρώτο δίκτυο χρησιμοποιήθηκαν εύκολα μετρήσιμα δεδομένα πεδίου. Οι παράμετροι που μελετήθηκαν αρχικά ήταν το pH, η ηλεκτρική αγωγιμότητα, η θερμοκρασία του νερού και του αέρα και η στάθμη του υδροφορέα. Με αυτές τις παραμέτρους, το μοντέλο πέτυχε αρκετά καλή προσομοίωση (R=0.92259, NSE=0.8406). Κατόπιν, για την καλύτερη περιγραφή του συστήματος επιλέχθηκε να εισαχθεί στο μοντέλο και το ποσοστό χρήσεων γης σε ακτίνα 1000 m από το κάθε πηγάδι. Με την είσοδο αυτής της μεταβλητής, παρατηρήθηκε σημαντική αύξηση της απόδοσης του μοντέλου (R=0.97412, NSE=0.9481). Στο τρίτο μοντέλο, η προσομοίωση βασίστηκε σε τυπικές μετρήσεις ποιότητας νερού. Συγκεκριμένα, χρησιμοποιήθηκαν το pH, η ηλεκτρική αγωγιμότητα, τα ανθρακικά ιόντα (HCO3-) και τα ιόντα Cl-, Ca2+, Mg2+, Na+, K+, SO42-. Στο συγκεκριμένο μοντέλο σημειώθηκε η καλύτερη προσομοίωση (R=0.96545, NSE=0.987838), το οποίο πιθανά οφείλεται στην ύπαρξη περισσότερων δεδομένων. Τέλος, χρησιμοποιώντας το δεύτερο μοντέλο, στο οποίο θεωρείται ότι έχουν συμπεριληφθεί παράγοντες που επηρεάζουν σημαντικά τη μεταφορά νιτρικών, εξετάστηκαν σενάρια κλιματικής αλλαγής και αλλαγών χρήσεων γης ώστε να εκτιμηθούν οι επιπτώσεις τους στα επίπεδα των συγκεντρώσεων NO3-. Τα αποτελέσματα των σεναρίων καταδεικνύουν τη σημαντική συμβολή των αγροτικών αλλά και των βιομηχανικών δραστηριοτήτων στα αυξημένα επίπεδα της νιτρορύπανσης. Για την κατασκευή των μοντέλων αντλήθηκαν δεδομένα από μετρήσεις που έγιναν στο χρονικό διάστημα 2000-2008 σε γεωτρήσεις του Νομού Βοιωτίας, στο πλαίσιο υδρογεωλογικής και υδροχημικής έρευνας του ΙΓΜΕ (Γιαννουλόπουλος, 2008). Πιο συγκεκριμένα, χρησιμοποιηθήκαν δεδομένα από γεωτρήσεις που είναι τοποθετημένες στο Κωπαϊδικό Πεδίο και την ευρύτερη περιοχή της Λεκάνης Απορροής του Ασωπού ποταμού, όπου υπάρχει ιδιαίτερα υψηλή αγροτική, κτηνοτροφική και βιομηχανική δραστηριότητα. Για το λόγο αυτόν, στις υπό εξέταση περιοχές έχει παρουσιαστεί εκτεταμένη ρύπανση και σύμφωνα με τα κριτήρια της Οδηγίας 91/676/ΕΟΚ, καθορίστηκαν με τις ΚΥΑ 19652/1906/1999 (ΦΕΚ Β’ 1575/05-08-1999) και ΚΥΑ 106253/08.11.10 ως ζώνες ευπρόσβλητες σε νιτρορύπανση γεωργικής προέλευσης. Η καλή προσομοίωση που επετεύχθη στα μοντέλα, τα καθιστά ένα χρήσιμο εργαλείο για την πρόβλεψη των επιπέδων ρύπανσης, που θα αποτελεί τη βάση για την κατάστρωση σχεδίων από τις αρμόδιες αρχές, με σκοπό τη βέλτιστη διαχείριση των υπόγειων υδάτων και την πρόληψη της νιτρορύπανσης. Summarization: The scope of the present study is the estimation of groundwater pollution by nitrates (NO3-), using artificial neural networks (ANNs). Nitrate pollution is caused through the introduction of excessive amounts of nitrogen to surface and groundwater, mainly as a result of agricultural practices because of the overuse of nitrogen based fertilizers. NO3- are particularly mobile through water and soil, so excess nitrates from sewage and agricultural fertilizers easily make their way into groundwater and surface waters. The guideline value for nitrate in drinking water is set by Greek and international legislation at a concentration of 50 mg/l, but even at lower concentrations (greater than 25 mg/l), concerns are being raised about long-term use of drinking water. Modeling of nitrate pollution with the commonly used mathematical methods can be a particularly difficult process and requires very good knowledge of the geomorphology of the study area, which in most cases is characterized by heterogeneity. In addition, techniques for detecting and measuring nitrate concentrations in water are characterized by high cost and high demands of time, while portable devices used are not of sufficient accuracy. Furthermore, in the various methods used for chemical analysis of water, the detection of nitrates is affected by the presence of other ions, especially Cl-. Based on the aforementioned issues, this thesis examines the possibility of using neural networks for the assessment of concentrations of nitrate in groundwater. ANNs do not require the knowledge of the geomorphology characteristics of the area, which is hard to obtain, while it is possible to use variables as inputs parameters without knowing the relationships that condition them in the system being studied. For the aforementioned purpose of this thesis, three neural networks were developed using Matlab toolbox. For the first network, easily measurable field data were used. The parameters initially studied were pH, electrical conductivity, water temperature, air temperature and aquifer level. This model achieved a fairly good simulation (R=0.92259, NSE=0.8406). Then, for the better description of the underground system, it was chosen to include in the model, the percentage of land uses in a radius of 1000 m from each well. The performance of the model increased significantly by the use of these variables (R=0.97412, NSE=0.9481). In the third model, the simulation was based on typical water quality measurements. In particular, pH, electrical conductivity, HCO3-, Cl-, Ca2+, Mg2+, Na+, K+, and SO42- were used. This model achieved the best simulation (R=0.96545, NSE=0.987838), possibly due to the larger number of available data. Finally, scenarios of climate change and land use changes were examined, in order to assess their impact on NO3- levels, using the second model, which is considered to have included factors that significantly affect nitrate transport into the geoenvironment. The results of the scenarios demonstrate the important contribution of agricultural and industrial activities to increased nitrate pollution. The models achieved a good simulation, which indicates that they are a possible useful tool for the estimation of groundwater pollution by nitrates and so, they may constitute the basis for the development of groundwater management plans.

Contamination from agricultural sources and, in particular, nitrate pollution, is one of the main concerns in groundwater management. However, this type of pollution entails the entrance of other substances into the aquifer, as well as it may promote other processes. In this study, we deal with hydrochemical and isotopic analysis of groundwater samples from four distinct zones in Catalonia (NE Spain), which include 5 different aquifer types, to investigate the influence of fertilization on the overall hydrochemical composition of groundwater. Results indicate that intense fertilizer application, causing high nitrate pollution in aquifers, also homogenize the contents of the major dissolved ions (i.e.; Cl-, SO42-, Ca2+, Na+, K+, and Mg2+). Thus, when groundwater in igneous and sedimentary aquifers is compared, significant differences are observed under natural conditions for Cl-, Na+ and Ca2+ (with p-values ranging from

International audience; Chalk aquifer is the main water resource for domestic water supply in many parts in northern France. In this region, groundwater is frequently affected by quality problems concerning nitrates. Often close to or above the drinking water standards, nitrate content in groundwater is mainly due to historical agriculture practices, combined with aquifer recharge through the vadose zone. The complexity of processes occurring into such an environment leads to combine a lot of knowledge in agronomy, geochemistry and hydrogeology in order to understand, model and predict the spatiotemporal evolution of nitrate content and provide a decision support tool for the water producers and stakeholders. To succeed in this challenge, conceptual and numerical models representing accurately the Chalk aquifer specificity will be developed, including a multidisciplinary approach to simulate storage and transport from the ground surface to the underlying groundwater. This involves a new agronomic module " MONICA " (MOdelling NItrates transfert taking into account Crops and Agricultural practices), a soil-crop model calculating the nitrogen mass balance in arable soil, integrated in the 3D transient groundwater numerical code " MARTHE ". This approach integrating existing multidisciplinary tools is a real challenge. It enables to decrease the number of calibration parameters by selecting the relevant equations and simplifying them without altering the signal. The numerical development is applied on a 2D vertical cross-section in the vadose zone representing experimental nitrate vertical measurements in soil profiles (0-22 m depth) in the Somme region (France). The experiment results highlight the land use management effect on nitrate evolution into the vadose zone (e.g. forest instead of crops). Simulations constrained by climate forcing, land use and nitrogen inputs over several decades reproduce the nitrate spatial and temporal distribution. This approach will be ultimately used to model in 3D the drinking water catchment area. It will be calibrated using nitrate contents time series of nitrate content measured in the domestic water pumping well available since 1995 (field in northern France – Avre Basin region). This numerical tool will help the decision-making in all activities in relation with water uses.