ARTICLE pubs.acs.org/est
Major Issues Regarding the Efficiency of Monitoring Programs for Nitrate Contaminated Groundwater T. Y. Stigter,*,† A. M. M. Carvalho Dill,‡ and L. Ribeiro† † ‡
Geo-Systems Centre/CVRM - Instituto Superior Tecnico, Av. Rovisco Pais, 1049-001 Lisbon, Portugal Geo-Systems Centre/CVRM - Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal ABSTRACT: Major issues regarding the efficiency of monitoring programs for nitrate contaminated groundwater are analyzed in this paper: (i) representativeness of monitoring networks; (ii) correct interpretation of the monitoring data and resulting time series and trends; and (iii) differentiation among the different sources of nitrates in groundwater. Following an overview of the nitrate contamination problem and possible solutions, as well as some of the difficulties found, a relatively straightforward method for assessing monitoring network representativity is presented, namely interpolation standard error assessment. It is shown how nitrate-concentration time series resulting from periodic observations can be corrected with a conservative tracer, in order to avoid misinterpretation and confirm or correct apparent trends. Finally, coupled 15N and 18O isotope signatures of nitrate (NO3) in groundwater are used to differentiate among nitrogen (N) sources, to ensure correct targeting of restoration measures. The case study regards a Nitrate Vulnerable Zone in the south of Portugal, designated in compliance with the European Nitrates Directive, where coastal discharge of nutrient-rich groundwater threatens the good qualitative and ecological status of the Ria Formosa coastal lagoon. Results show that mineral fertilizer is the main source of N in groundwater, and that increases in N load can be masked by dilution phenomena.
’ INTRODUCTION Groundwater contamination by nitrate (NO3, hereafter referred to as NO3) has been recognized for decades as a major concern for mankind. Despite the existence of a large number of point and diffuse sources of nitrogen (N), including septic tanks, sewage discharge, cattle feedlots, oxidation of soil organic N and atmospheric deposition, the excessive application of mineral and organic fertilizers in agriculture is the principal source of N in groundwater on a regional scale.1,2 In Europe, at a large scale agriculture contributes to 5080% of the total N load on the aquatic environment.3 Protecting and restoring the NO3contaminated groundwater resources in the world not only concerns their direct use (i.e., consumption), but also the impact that groundwater discharge has on the qualitative and ecological status of surface water bodies, particularly coastal estuaries and lagoons. This is because ratios of dissolved inorganic N over phosphorus (P) in contaminated aquifers are usually much higher than the Redfield ratio that defines the nutrient requirements by phytoplankton,4 contrary to what occurs in natural coastal waters, which are often N-limited ecosystems.58 There is much reported evidence that in the past few decades increased inputs of N to coastal waters have led to a global increase in eutrophication, resulting in widespread hypoxia and anoxia, habitat degradation, and increased occurrence of harmful algal blooms.916 Goals to reduce the volume of NO3 transport in groundwater can be approached by controlling the sources or by enhancing the r 2011 American Chemical Society
sinks. As NO3 neither forms insoluble minerals that can precipitate, nor is significantly adsorbed, its removal from groundwater predominantly occurs through denitrification.17 However, this process is largely restricted to anaerobic environments, which are often difficult to obtain in shallow and even in deep aquifer systems.18,19 The control of the N source is therefore considered more effective, but depends on the possibility to implement such measures, which in turn depends on the type of source. Point sources are generally easier to control, and progress has been made in Europe and the United States in reducing nutrient pollution from wastewater sources.20 Reducing nonpoint source pollution has proven much more difficult.10,20,21 In the European Union the EC Nitrates Directive was drawn up with the specific purpose to reduce water pollution caused by NO3 from agricultural sources and prevent further such pollution. EU member states had to identify waters affected by NO3 pollution, designate Nitrate Vulnerable Zones (NVZs), implement monitoring programs, and establish action programs and codes of good agricultural practice containing mandatory measures concerning the land application and storage of mineral and organic fertilizers.22,23 Despite the progress made in recent years, many areas still require NVZ designation, particularly with regard Received: May 26, 2011 Accepted: August 24, 2011 Revised: August 5, 2011 Published: August 24, 2011 8674
dx.doi.org/10.1021/es201798g | Environ. Sci. Technol. 2011, 45, 8674–8682
Environmental Science & Technology
ARTICLE
to eutrophication and shallow groundwater contamination criteria.24 Moreover, one-third of the monitoring stations located in the 15 countries that formed the EU before 2004 showed an upward NO3 trend in 20042007.25,26 The most promising groundwater restoration measures are targeted toward (i) an increase in nutrient efficiency and (ii) an improvement in nutrient balance in the application of fertilizers, with adequate timings based on crop requirements.21,2731 Overfertilization is a major problem in many areas, since farmers believe it guarantees maximum crop yield and quality, even though adding fertilizer N follows the classical crop response curve for yield-limiting nutrients as presented by Dibb,32 i.e., it significantly increases crop yield only up to a certain point, after which nutrient efficiency drops rapidly. Farmers also largely underestimate the N available from other sources, such as residues from previous crop cycles, soil, or irrigation water.20 As a result, in the U.S. about one-third of the N applied as fertilizer to the crops is lost to the environment.27 The lack of balanced nutrition may also be an important factor, as the presence of other macronutrient elements such as potassium and phosphorus in adequate proportions in soil and fertilizer is essential for N recovery by the crops (e.g., refs 3337). Comprehensive water monitoring networks lie at the basis of policy implementations, and significant progress in the EU26 has made spatial and temporal trend analysis possible. However, it is important to understand if these networks are sufficiently representative, an issue that is often neglected. Moreover, trends in observed NO3 concentrations can be misleading and it is important to separate variations caused by actual N sinks/ sources from those that are a consequence of dilution/concentration events. For instance, a decrease in dilution potential caused by a reduction in aquifer recharge, expected to occur in many regions due to climate change (e.g., 38,39), may increase NO3 concentrations even when the N load is reduced. Finally, in areas with more than one N source, differentiation is essential to support adequate policy implementation (e.g., 18,23). This paper will deal with these three issues of monitoring: (i) representativity, (ii) result interpretation, and (iii) source differentiation, supported by a case study in the south of Portugal.
’ METHODS Structural Analysis of the Spatial Distribution of NO3. Regarding the spatial distribution of NO3 concentrations, its structural analysis can be performed by calculating the data’s experimental variogram 2γ*(h), the arithmetic mean of the squared difference in value between pairs of data a distance and direction h apart:41,42
2γðhÞ ¼
1 nh ðCx Cxþh Þ2i nh i ¼ 1
∑
errors may account for a certain fraction of the total data variance (nugget effect) visible at the origin. Different spatial orientations should be analyzed to detect the presence of anisotropy. A theoretical model, frequently spherical in geostatistical applications to hydrogeology when no trend exists, is fitted to the experimental variogram. The obtained model parameter values are subsequently introduced into a kriging interpolation algorithm, based on the minimum error variance concept. Ordinary kriging assumes a constant but unknown mean. A large advantage of kriging is that it provides a measure of the estimation error, as the corresponding standard deviations of the estimation error are calculated, also known as standard errors (SE). A larger SE denotes a lower reliability of estimation. At short distances from sampled locations the SE is largely determined by the nugget effect, and as the distance increases, the error depends on the distribution of the sample network, as this determines the length of the search radius with respect to the range of influence in the experimental variogram. A large range of influence, particularly when combined with a high sill and a low nugget effect guarantees a trustworthy interpolation, since the variability among the data and thus also the spread of the SE is still relatively small at the maximum search radius. As a thumb rule, a SE larger than the original sample standard deviation (SD) denotes an unreliable estimate.42 The spatial distribution of the SE is an indicator of the representativeness of implemented monitoring networks. NO3 Time Series Analysis. NO3 often is a very stable and conservative contaminant, particularly in aerobic conditions. A conservative tracer can be used to separate N sources/sinks from dilution/concentration events. In many cases the conservative tracer can be chloride (Cl, hereafter referred to as Cl), but only if no significant sources of this ion exist in the aquifer, so that its variations truly reflect groundwater concentration (due to evapotranspiration) or dilution (due to mixing with fresh water). Where Cl is used in fertilizers, or where significant Cl sources exist, e.g., due to seawater intrusion or evaporate dissolution, its use as a tracer is pointless. To apply the correction to observed NO3 concentration time series, first a concentration factor between subsequent observation dates (time points) has to be calculated: mClðj, ti Þ ð2Þ Fj, ti ¼ mClðj, ti1 Þ where Fj,ti is the concentration factor in observation well j at time point ti, mCl(j,ti ) the Cl concentration in well j at time point ti, and mCl(j,ti-1) is the Cl concentration (in the same units) in well j at a previous time point ti-1. Values of Fj,ti > 1 indicate that concentration took place, whereas values
