Technical Note: Field experiences using UV/VIS sensors for high-resolution monitoring of nitrate in groundwater

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Abstract. Two different in situ spectrophotometers are compared that were used in the field to determine nitrate-nitrogen (NO3-N) concentrations at two distinct spring discharge sites. One sensor was a double wavelength spectrophotometer (DWS) and the other a multiple wavelength spectrophotometer (MWS). The objective of the study was to review the hardware options, determine ease of calibration, accuracy, influence of additional substances and to assess positive and negative aspects of the two sensors as well as troubleshooting and trade-offs. Both sensors are sufficient to monitor highly time-resolved NO3-N concentrations in emergent groundwater. However, the chosen path length of the sensors had a significant influence on the sensitivity and the range of detectable NO3-N. The accuracy of the calculated NO3-N concentrations of the sensors can be affected if the content of additional substances such as turbidity, organic matter, nitrite or hydrogen carbonate significantly varies after the sensors have been calibrated to a particular water matrix. The MWS offers more possibilities for calibration and error detection but requires more expertise compared with the DWS.

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Hydrol. Earth Syst. Sci., 19, 1589–1598, 2015
www.hydrol-earth-syst-sci.net/19/1589/2015/
doi:10.5194/hess-19-1589-2015
© Author(s) 2015. CC Attribution 3.0 License.

# Technical Note: Field experiences using UV/VIS sensors for high-resolution monitoring of nitrate in groundwater

M. Huebsch 1,2 , F. Grimmeisen 1 , M. Zemann 1 , O. Fenton 2 , K. G. Richards 2 , P. Jordan 3 , A. Sawarieh 4 , P. Blum 1 , and
N. Goldscheider 1

1Karlsruhe Institute of Technology (KIT), Institute of Applied Geosciences (AGW), Kaiserstr. 12, 76131 Karlsruhe, Germany
2Teagasc, Environment Research Centre, Johnstown Castle, Co. Wexford, Ireland
3University of Ulster, School of Environmental Sciences, Cromore Road, Coleraine, BT52 1SA, Northern Ireland
4National Resources Authority, Amman, Jordan

_Correspondence to:_ F. Grimmeisen (felix.grimmeisen@kit.edu)

Received: 30 September 2014 – Published in Hydrol. Earth Syst. Sci. Discuss.: 4 November 2014
Revised: 21 February 2015 – Accepted: 4 March 2015 – Published: 2 April 2015

Abstract. Two different in situ spectrophotometers are compared that were used in the field to determine nitrate-nitrogen
(NO3-N) concentrations at two distinct spring discharge
sites. One sensor was a double wavelength spectrophotometer (DWS) and the other a multiple wavelength spectrophotometer (MWS). The objective of the study was to review the
hardware options, determine ease of calibration, accuracy, influence of additional substances and to assess positive and
negative aspects of the two sensors as well as troubleshooting
and trade-offs. Both sensors are sufficient to monitor highly
time-resolved NO3-N concentrations in emergent groundwater. However, the chosen path length of the sensors had a
significant influence on the sensitivity and the range of detectable NO3-N. The accuracy of the calculated NO3-N concentrations of the sensors can be affected if the content of
additional substances such as turbidity, organic matter, nitrite
or hydrogen carbonate significantly varies after the sensors
have been calibrated to a particular water matrix. The MWS
offers more possibilities for calibration and error detection
but requires more expertise compared with the DWS.

1 Introduction

Present and predicted future shortage of drinking water
is a worldwide problem and global population growth increases the demand for high-quality potable water (Schiermeier, 2014). Thus, the importance of the protection of drinking water quality is acknowledged worldwide by the imple

mentation of international programs such as the European
Union (EU) Water Framework Directive (OJEC, 2000) and
daughter directives, the US National Water Quality Assessment Program (NAWQA) and Maximum Daily Load Program (TMDL) (Elshorbagy et al., 2005) or the Australian
National Water Quality Management Strategy (ANZECC,
2000). Built into these regulations is a fundamental need to
monitor the quality of drinking water supplies. However, especially in karst and/or fractured aquifers, water quality can
change rapidly in a time frame from hours to days (Huebsch et al., 2014; Mahler et al., 2008; Pronk et al., 2009). Nitrate (NO − 3 _)_ is particularly noted as being a risk to human

health when in high concentrations in source drinking water
(L’hirondel, 2002) and also contributes significantly to eutrophication of water (Stark and Richards, 2008).

High resolution flow and nitrate-nitrogen (NO3-N) concentration data from short residence time aquifers enable an
improved understanding of the mobilisation/dilution dynamics in karst aquifers (Huebsch et al., 2014) and to prevent
negative consequences from NO3-N concentrations exceeding the maximum allowable concentration (MAC) for drinking water. In the EU, for example, the MAC is 11.3 mg NO3N L −1, to prevent health concerns (Knobeloch et al., 2000),
abortion to cattle or toxicity in livestock (Di and Cameron,
2002).
Photometrical ultraviolet/visible light (UV/VIS) sensors
have been first employed at municipal wastewater treatment
plants to control NO3-N effluent concentrations (Langergraber et al., 2003; Rieger et al., 2004). In addition, UV/VIS

Published by Copernicus Publications on behalf of the European Geosciences Union

1590 M. Huebsch et al.: Field experiences using UV/VIS sensors for monitoring of nitrate in groundwater

sensors have been recently used in groundwater and surface
water applications to assess highly resolved NO3-N concentrations (Pu et al., 2011; Wade et al., 2012). The technique
gives the opportunity to observe trends and rapid changes
of NO3-N whilst using a solid-state methodology without
reagents. Thus, less frequent calibration and maintenance
than other common in situ methods such as ion sensitive electrode applications is required (Bende-Michl and Hairsine,
2010). Some technical information about UV/VIS sensors
in natural waters can be found in the literature (e.g. Drolc
and Vrovsek, 2010; Thomas and Burgess, 2007; van den
Broeke et al., 2006); however, to date there is no technical
information available that describes a detailed comparison of
widespread and commonly used online spectrophotometers
and their positive and negative aspects. There is sparse information from the two manufacturers on sensor performance
in natural waters.

The technical note provides an assessment of two different spectrophotometric sensors, i.e. a double wavelength
spectrophotometer (DWS) and a multiple wavelength spectrophotometer (MWS) used at field sites in Ireland and Jordan, respectively, which were originally used for two different scientific studies (Grimmeisen et al., 2014; Huebsch et
al., 2014). The following issues are addressed in the present
study: hardware options, ease of calibration, accuracy, influence of additional substances, positive and negative aspects
of the two sensors, troubleshooting and trade-offs.

2 Materials and methods

NO3-N dissolved in water absorbs light below 250 nm (Armstrong, 1963) although the specification for NO3-N determination due to absorbance varies in the literature. Karlsson
et al. (1995) and Drolc and Vrtovšek (2010) describe specific parameter determination of NO3-N at 205 nm, Thomas
et al. (1990) at 205–210 nm, Ferree and Shannon (2001) at
∼ 224 nm and Armstrong (1963) at 227 nm. The relationship
between absorbance, i.e. extinction of light ( _E_ ) at a specific
wavelength, and NO3-N concentration is linear and follows
the Lambert Beer law:

_E_ = log _I_ 0 (1)

_I_ _,_

where _I_ 0 is the light intensity emitted by the sensor lamp
and _I_ is the light intensity after the light has passed the
water matrix. Hence, physically increased light absorption
of NO3-N dissolved in water correlates to increased NO3N concentrations. However, in natural water, additional substances other than NO3-N occur. Turbidity has a major influence on light absorbance as the presence of suspended
material such as organic particles can lead to scattering effects on the recorded absorption values of NO3-N (Chýlek,
1977; Rieger et al., 2008; Vaillant et al., 2002). In addition, substances that absorb in the investigated spectral range

_x_ ′ _n_ = _xn_ +1 + _xn_ _._ (3)

In this study, a DWS (NITRATAX plus sc, Hach Lange
GmbH, Germany) and a MWS (s::can sprectro::lyser TM,
s::can Messtechnik GmbH, Austria) were used (Fig. 1). The
DWS was installed in a flowing spring emergence (spring A)
in a karst spring in an agriculture-dominated area in southwest Ireland and the MWS in a flowing spring emergence
(spring B) in an urbanised catchment in north-west Jordan.
The study sites are described in more detail in a previous
study of Huebsch et al. (2014) and Grimmeisen et al. (2014),
respectively. Both springs discharge karst aquifers; however,
spring A is located in an agricultural catchment and spring B
in an urban catchment.

The DWS measures UV absorbance at a wavelength of
218 nm at a measuring receiver (EM - element for measuring) and at 228 nm at a reference receiver (ER - element
for reference). The recorded measurements at two different

Figure 1. UV/VIS sensors: (a) double wavelength spectrophotometer (DWS) with measuring path of 5 mm; (b) multiple wavelength
spectrophotometer (MWS) with measuring path of 35 mm; (c) principle of horizontal installation of the sensors.

such as nitrite nitrogen (NO2-N) or humic acids can lead
to superposition of absorbance (Kröckel et al., 2011). The
consequences are that multivariate data analysis approaches
are needed to determine NO3-N, such as principal component analysis or partial least square regression (Dahlén et al.,
2000; Gallot and Thomas, 1993a; Karlsson et al., 1995; Macintosh et al., 2011). The statistical approaches take the variances of the raw and observed data set of absorbance values
into account. Principal component analysis uses orthogonal
transformation. Partial least squares analysis is based on determining the lowest variance of a linear regression line. In
addition, the first derivative allows a finer interpretation of
the nitrate content in the water. The first derivative can be
determined as follows:

_y_ ′

_n_ = _yn_ +1 − _yn_

_xn_ +1 − _xn_

_,_ (2)

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M. Huebsch et al.: Field experiences using UV/VIS sensors for monitoring of nitrate in groundwater 1591

wavelengths at EM and ER are designed to compensate interference of organic and/or suspended matter (Thomas et
al., 1990) by interpreting the difference between the absorbance values at EM and ER which is expressed by _�E_ .
In comparison, a UV sensor using only one single wavelength is not able to compensate additional interferences (van
den Broeke et al., 2006). The MWS measures absorbance at
256 different wavelengths between 200 and 750 nm within
15 s (Rieger et al., 2004). Both sensors feature the possibility to export the monitored absorbance values and the calculated concentrations. As a result of the different measuring methods, the DWS makes no difference between NO3N and NO2-N and, therefore, reports the NOx-N concentration (or total oxidised nitrogen, TON) instead of NO3-N
(Drolc and Vrtovšek, 2010) and assumes negligible NO2-N.
Due to the range of measurements in the scan, the MWS
is able to provide the specific NO3-N concentration. NO3N/NOx-N concentrations observed with the DWS and MWS
were compared with NO3-N/NOx-N concentrations determined in the laboratory. Water samples used for determination of NO3-N/NOx-N concentrations were measured in the
water in situ with the sensors. For comparison, water samples were also filtered using a 0.45 µm micropore membrane
to determine NO3-N/NOx-N concentrations in the laboratory. For determination, Aquakem 600A (Thermo Scientific,
Finland) and Dionex ICS-2100 (Thermo Scientific, Finland)
were used, respectively. The DWS was installed in July 2011
in spring A. NOx-N concentrations were fluctuating between
approximately 10 and 14 mg L −1 until September 2014. The
MWS was installed in spring B in May 2011 and the observed approximate minimum and maximum concentrations
of 11 and 15 mg NO3-N L −1 until September 2014, respectively.

There are several sensor options available for the DWS
and the MWS from the manufacturers. The DWS is available
with three different path lengths of 1, 2 and 5 mm, which
cover a NOx-N detection range of 0.1–100.0, 0.1–50.0 and
0.1–25.0 mg L −1, respectively. The range of NOx-N detection increases with a shorter path length. However, a shorter
path length implies also a lowered overall sensitivity of the
measurement (Thomas et al., 1990). In this study, a DWS
with a path length of 5 mm was used.

There are also several options for the MWS for possible
measuring paths and applications. For natural waters, it is
advisable to choose a measuring path of 5, 15 or 35 mm. A
measuring path of 5 mm covers a NO3-N detection range of
0.02–70.0 mg L −1, a measuring path of 15 mm a detection
range of 0.02–40.0 mg L −1 and a measuring path of 35 mm a
detection range of 0.02–10.0 mg L −1 . Thus, the advised measuring paths for both sensors differ by the manufacturers due
to the divergent measuring methods. The studied MWS had
a measuring path of 35 mm and the software capability to
measure turbidity, NO3-N, total organic carbon (TOC) and
dissolved organic carbon (DOC). The manufacturer advises
to use a path length of 35 mm in natural water, even if this

might not be the optimal path length for the monitored NO3N concentrations in the field (optimal at ≤ 10 mg L −1 ). The
reason is that if additional measuring options are included
such as turbidity, TOC and DOC, the path length has to be
suitable for the combined options. Those may occur at different ranges and the best compromise has to be selected.

For calibration, the applied DWS has the option for a
two-point calibration, in addition to a four-point manufacturer’s calibration with standard solutions at 0, 25, 50 and
100 mg L −1 . The MWS offers two main options for calibration, off-site and on-site calibration, which are also in addition to the manufacturer pre-adjustment. The off-site calibration is based on wavelength-concentration data sets previously analysed by the manufacturer (Langergraber et al.,
2004c), whereas the on-site calibration offers the possibility
for an improved adaption to the matrix of the monitored water (Rieger et al., 2006). This is also possible with the DWS.
On-site calibration can be performed with a linear (local 1)
or a polynomial (local 2) function. For both sensors the calibration that is normally chosen is based on a linear function. Calibration based on a polynomial function can lead to
higher accuracy if a path length needs to be chosen that on
the one hand represents a suboptimal path length for nitrate,
but on the other hand offers the possibility to measure additional parameters.

3 Results and discussion

3.1 Hardware options

Table 1 provides an overview of the available hardware and
software options, output format, maintenance, warranty and
costs of the DWS and MWS. Important differences between
both sensors despite the measuring method are that (1) the
cleaning device for the MWS is offered as an additional hardware option (but highly necessary in natural waters), whereas
the DWS is already equipped with a wiper for cleaning; and
(2) the purchase price for the DWS is lower than for the
MWS (EUR ∼ 16 000 and 20 000 excluding VAT in 2014,
respectively). Both sensors report the raw data set of the absorbance measurements, which is based on the two different
measuring methods (DWS: two wavelengths; MWS: full absorbance spectrum). The investment costs for both sensors
are based on the advanced and comparable version of both
manufacturers, which means that, first, turbidity can be compensated; second, the raw data set is included; and third, error
detection for both sensors is possible afterwards. The costs
are based on elementary equipment: sensor, cable and basic
handling device. Additional upgrades such as the remote control, advanced handling device and flow-through unit, which
ensures sufficient flow through the measuring slit, are also
available and lead to an increase in pricing.

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1592 M. Huebsch et al.: Field experiences using UV/VIS sensors for monitoring of nitrate in groundwater

Table 1. Description of the double wavelength spectrophotometer (DWS) and the multiple wavelength spectrophotometer (MWS).

Components DWS MWS

Hardware - Sensor incl. wiper for cleaning, cable, handling device
(station terminal)

- Internal memory included

Hardware options - Flow-through unit

- GSM modem

- Mobile display for on-site operations

- Additional analogue outputs for up to eight sensors

Software options - WINXP-based

- Remote control

- Alarm option

- Display on-site: concentrations and daily or weekly
trend line over time

- Password for protection of display possible

Output - Absorption values at EM and ER

- Calculated NOx-N concentrations

- Output via memory card and/or remote control

Maintenance - Low

- Manufacturer’s calibration of sensor needs to be
refreshed after 1–2 years

- Sensor, cable, handling device (station terminal)

- Internal memory included

- Cleaning device necessary in natural waters

- GSM modem

- Additional analogue outputs (terminal)

- Interfaces for one MWS and three other sensors

- WINXP-based

- Remote control

- Calibration menu for on-site calibration

- Alarm option

- Display on-site: switching between nitrate
concentrations over time and spectra

- Automated light source check

- Absorption spectra

- Calculated NO3-N concentrations

- Output via memory card and/or remote control

- Low

- After 2 years check of light source at the manufacturer
is necessary (cost intensive EUR ∼ 1000 excl. VAT)

Warranty - 5 years on light source - 3 years

Costs  - Low maintenance and labour costs

- Purchase price: EUR ∼ 16 000 excl. VAT

3.2 Ease of calibration and accuracy after calibration

Figure 2 shows the accuracy of the two sensors immediately after calibration using the available calibration methods. The error bars were determined by the manufacturer’s
specification of the expected concentration interval which is
“concentration error bar interval = 0 _._ 03· measured concentration + 0.5” for the DWS and “concentration error bar interval = 0 _._ 02· measured concentration + 1/path length of the
sensor”. The DWS was calibrated with standard solutions,
which provided a good result for the monitored water in
the area (spring water A). To test the accuracy of the DWS,
while considering the matrix composition of the studied water, spring water (highest concentration), water from a closeby river (lowest concentration) and a mix of river and spring
water was used. For testing the accuracy of the MWS, spring
water and water from other close springs were used. The
root mean square error (RMSE) to the ideal straight line
of _y_ = _x_ (measured sensor concentrations vs. concentrations
measured in the laboratory) was 0.42. For the MWS, higher
accuracy was reached by using water samples from adjacent
springs, which had a higher affinity to the water matrix of
the monitored spring than standard solutions (spring water B;
Fig. 3b). These water samples were also used to test the accuracy of the sensor. The best results were obtained with the

- Low maintenance and labour costs

- Purchase price: EUR ∼ 20 000 excl. VAT

on-site calibration using a second-order polynomial function
(local 2; Fig. 2d) including a RMSE of 0.36. For off-site calibration (Fig. 2b) and on-site calibration with a linear function (local 1; Fig. 2c) RMSE was 2.11 and 0.82, respectively.
In addition, Fig. 2 shows that the accuracy of the sensor decreases with higher NO3-N concentrations, especially for the
two-point calibration of the DWS sensor and the off-site calibration of the MWS. In general, the precision of the sensor
readings are dependent on the sensor path length (Kröckel
et al., 2011). The MWS with 35 mm path length becomes
less accurate with higher concentrations, as the optimal measurement range for a 35 mm path length is 0.02–10 mg L −1

NO3-N.

However, the manufacturer claims the NO3-N concentration range between 10 and 15 mg L −1 to be sufficient and applicable for monitoring. The path length of 35 mm was recommended for including additional measuring options such
as turbidity, TOC and DOC. The accuracy of both sensors is
dependent on (a) the selected path length for measuring the
concentrations, (b) a comparable and similar water matrix to
the standard solution used for calibration and/or (c) the option to use local water having minimum and maximum NO3N concentrations characteristic for the NO3-N measured with
a similar matrix structure for calibration. As the last two
points are rather challenging in the field, we suggest cali

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Figure 2. Accuracy of DWS and MWS immediately after calibration. Recorded sensor measurements are compared with measured concentrations analysed in the laboratory. The RMSE was calculated by relating the measured sensor concentrations with the optimum calibration
(ideal straight line _y_ = _x_ ).The DWS has one option for calibration, whereas the MWS offers three options for calibration. All calibration
options are in addition to the factory calibration provided by the manufacturer.

Figure 3. Absorbance vs. wavelength of four different samples measured with the MWS. Spring water A was constantly monitored by the
DWS, whereas spring water B was the monitored by MWS. (a) The isosbestic points, which describe the wavelength at which two absorbance
spectra are crossing, indicate different matrix compositions of the samples. Nitrate and nitrite are strongly absorbed below 250 nm. Other
substances such as of COD (chemical oxygen demand), trace organics, humic substances or turbidity in water can increase the absorbance
value below 250 nm. The maximum influence of those substances can be recognised at higher wavelengths, for example, at the obvious
differences of the samples between 250 and 400 nm. (b) The first derivative of samples allows a finer interpretation of the nitrate content in
the water. The samples with similar nitrate concentration show more similar curve progression than in (a) .

brating the sensors with water from the field site. If necessary, a number of those waters can be used that are diluted or
concentrated with standard solution to get approximate representative minimum and maximum values for calibration.
However, after calibration, changes of the water matrix in a
natural environment due to e.g. mixing of different groundwater can lead to less qualitative results. Complex changes
of the water matrix can affect the precision of the sensor
readings, because the sensor is calibrated to a specific water composition (Langergraber et al., 2004b; Maribas et al.,
2008; Stumwöhrer et al., 2003).

3.3 Influence of additional substances

In natural waters, the absorption spectra can vary significantly due to, for example, different contents of natural organic matter (Thomas and Burgess, 2007); so interference effects of substances that are absorbing light in a similar wavelength range to NO3-N are possible (Macintosh et al., 2011).
Figure 3 shows absorbance spectra and the first derivative of
four different water samples, which were determined with the
MWS, to illustrate the general working principle of UV/VIS
monitoring. Spring water samples A and B have similar NO3N concentrations of 11.4 and 11.1 mg L −1, respectively. For
comparison, two other samples with similar NO3-N concentrations of 3.9 and 4.1 mg L −1, respectively, were plotted: a
sample of mains water of the Jordanian city, and a water mix

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Table 2. Evaluation of applying the DWS and the MWS: positive (+), negative (−) and neutral (o) aspects.

Positive, negative
and neutral aspects DWS MWS

Installation + - Easy

- An L bracket provided by the manufacturer makes
it simple to install the instrument in the correct
position

- Easy

-     - Must be aware that the measuring path needs to
be orientated in a horizontal position with the
measuring path down especially if used without
cleaning device

Requirements - - Power source needed for operation - Power source needed for operation

Calibration + - Easy if water matrix is similar to standard
solutions provided by the manufacturer

-     - Only two point calibration possible for the user

- On-site calibration complicated if water matrix
differs significantly from standard solutions provided by the manufacturer or if collection of water
samples representing the monitored NO3-N range
remains difficult

Error detection + - Relationship _�E_ to calculated concentration
gives possibility for detection

-     - Dependence on manufacturer for provision of
additional information

- Off-site calibration provided by the manufacturer
and site specific on-site calibration possible offering
higher precision

- Recalibration of the raw data set possible

- Achievement of a sufficient level of expertise is
necessary if off-site calibration is not useful

- First derivative of spectra gives more detailed
information; e.g. if values between 220 and 240 nm
are positive, light or energy source is damaged

- Dependent on help of the manufacturer

of spring, river and pond water sampled and mixed at the
area in southern Ireland mentioned above. The mains water is a mix of treated spring and river water, whereas the
spring-river-pond water is a mix of water from spring water A, a nearby river and water from a pond. In Fig. 3a, the
high absorbance values below 250 nm specify the presence
of NO3-N in the water. Isosbestic points, which describe the
wavelength at which two absorbance spectra are crossing, are
an indicator for different matrix compositions of the samples
(Gallot and Thomas, 1993b; Vaillant et al., 2002). Other substances such as NO2-N, HCO − 3 or dissolved organic matter

in water can result in a superposition of the absorbance values (Kröckel et al., 2011; Langergraber et al., 2004a; van den
Broeke et al., 2006), even if the maximum absorbance values of those substances occur at different wavelengths than
NO3-N absorbance. In Fig. 3, the water mix of spring, river
and pond water has higher absorbance values than the other
samples, although the NO3-N content is low in relation to
spring waters A and B. This can be explained by the influence of interfering substances other than NO3-N, which
are leading to superposition of the absorbance values and
are clearly indicated by increased absorbance values above

250 nm. The first derivative allows for a more detailed interpretation of the NO3-N concentration: samples with similar
NO3-N concentration follow a much more similar curve progression (Fig. 3b) than the absorbance spectra (Fig. 3a). In
addition, positive values in the majority of the first derivative between 220 and 240 nm indicate that the light or energy
source is damaged and needs to be replaced. The MWS uses
derivative methods, amongst others, for calculating the NO3N concentrations, whereas the DWS records the absorbance
values at two wavelengths (218 and 228 nm) and defines the
NOx-N concentration by using the difference between those
wavelengths. This means that the DWS sensor takes the slope
into account as well as the interval of the absorbance difference at the two wavelengths, which implies that superposition by additional substances are considered. Nevertheless,
this and other studies indicate problems due to superposition
of substances (Maribas et al., 2008).

3.4 Positive and negative aspects of the two sensors

Table 2 gives an overview of positive and negative aspects
of the two sensors regarding installation, requirements, cal

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ibration and error detection. Installation of both sensors is
straightforward. The manufacturer of the DWS supplies L
brackets for installation of the instrument in the correct position. For both sensors, a mains power source is required
for operation, which may be a problem for field applications.
A power supply of 230 VAC is sufficient. Positive aspects
of both sensors are that the calibration intervals can be performed on a long-term basis which is an asset compared to
other NO3-N detection methods (Beaupré, 2010). Calibration
can be simple, if the water matrix is similar to standard solutions provided by the manufacturer, but more complicated
if the water matrix differs significantly from standard solutions or if collection of water samples representing a broad
range of NO3-N concentrations of the monitored water is difficult. The MWS offers more options for calibration than the
DWS, which can lead to higher precision (Fig. 2). In contrast,
the on-site calibration methods require more expertise and,
therefore, can be time consuming. Even if calibration intervals are on a long-term basis of up to 2 years, it is advisable
to perform regular controls in a time frame of 3–6 months
such as regular conventional measurements of NO3-N concentrations to ensure the reliability of the data provided by
the sensor. In addition, the manufacturer of the DWS advises
to return the sensor to the manufacturer on an annual basis
to refresh the four-point calibration, replace seals and check
the sensor. Error detection is possible with both sensors, but
costs more compared to similar sensor types provided by
the manufacturers with no error detection. The manufacturer
gives advice to check the light source every 2 years as this
has to be renewed. Because the MWS measures the full absorption range, more detailed information of possible disturbances can be utilised.

3.5 Troubleshooting and trade-offs

During operation of both sensors, two difficulties occurred
that affected the reliability of the recorded NOx-N concentrations (Figs. 4, 5). Figure 4 illustrates discrepancies between
wavelength measurements and calculated NOx-N concentrations above 12.12 mg L −1 of the DWS. In Fig. 4a, the raw
data set of the difference between absorbance values at 218
and 228 nm, _�E_, is shown. In Fig. 4b, the reported NOxN concentrations are illustrated, which were calculated from
the raw data set and followed an inverse trend if NOx-N concentrations were above 12.12 mg L −1, contrary to Lambert
Beer’s law. The manufacturer assumed a software problem
and the probe had a complete control check after the detection of the error. The manufacturer’s background calibration
was therefore refreshed and the software and light source
were replaced. However, because the raw absorption data set
was recorded, it was possible to eliminate the error retrospectively and quantitatively by using a regression line, which
was extrapolated from the correct calculated values (Fig. 4c).

During operation of the MWS, suspicious readings were
recorded, which occurred immediately after installation due

Figure 4. Example of discrepancies between wavelength and calculated NOx-N concentrations as displayed by the DWS. The shaded
grey area highlights the data set of incorrect NOx-N calculated
values. (a) Raw data set of recorded wavelength values during
2 months. _�_ E is the difference between light extinction at 218 and
228 nm. (b) Calculated NOx-N concentrations from the raw data
set as reported by the DWS. (c) Values of the raw data set ( _�E_ )
and the reported NOx-N concentrations of the DWS. Once NOx-N
values reached 12.12 mg L −1, values were incorrectly calculated in
an opposite trend.

Figure 5. Interference of deposition of suspended matter at the measuring path of the MWS due to vertical installation of the sensor.
The grey areas indicate the time range when the FTU signal is ≥ 20
and thus the reported NO3-N concentrations are not reliable during that time. Reporting of NO3-N concentrations breaks down at
80 FTU.

to a technical mistake (Fig. 5). The sensor was first installed
in a vertical position without a cleaning device. This led to
an accumulation of suspended material at the measuring slit.
Consequently, the recorded values for turbidity increased. If
the turbidity signal reaches values at or above 20 FTU (for

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1596 M. Huebsch et al.: Field experiences using UV/VIS sensors for monitoring of nitrate in groundwater

mazin turbidity units), determined NO3-N values are not reliable. For turbidity ≥ 20 FTU the recorded NO3-N values
showed a decreasing trend. At turbidity ≥ 80 FTU no NO3N concentrations were reported. The sensor was cleaned on
a weekly basis, which explains the periodic, weekly pattern
of turbidity and NO3-N values. After error detection, the sensor was reinstalled in a horizontal position with a downwards
oriented measuring path. However, it was necessary to purchase a cleaning device from the manufacturer as fouling of
the measuring slit still disturbed the readings. The manufacturer offers the sensor with the purchase of an air pressure
cleaning device as an option (Table 1). In contrast, the DWS
uses a wiper for cleaning, which is already included in the
standard probe. Hence, we strongly recommend purchasing
the cleaning device together with the MWS sensor if the system is operated in natural waters.

During operation of the DWS the computer system was
unstable and shut down several times, causing data gaps
of several hours until the system started recording again.
Maribas et al. (2008) also describe disturbances of the MWS
measurements caused by air bubbles in the water. They state
that where bubbles exist in the water, the measuring path
needs to be oriented to allow the bubbles to pass. Kröckel
et al. (2011) advise to use a filter such as a flow-through unit
to prevent inaccurate measurements due to air bubbles (Table 1) although these can be unreliable in highly turbid waters. One should also note that reliable measurements of both
sensors cannot be determined if the sensor measurements are
affected by saline water. If the measured water is influenced
by water with salt content, for example due to flooding and
close installation to the coast or in deeper wells, the determination of NO3-N by the UV sensors would be affected as salt
has a strong UV absorption in the NO3-N absorption range
(Kröckel et al., 2011). In addition, in highly heterogeneous
environments, such as karst aquifers, rapid groundwater fluctuations and temporary activated conduit inlets might result
in mixing of waters with different water quality and therefore
matrix. This can have an effect on the accuracy of the NO3-N
concentration data set. Even though the MWS measures over
the full absorption spectra, detections remain difficult in that
case and might result in less accurate concentrations. This
could be a problem especially if absolute values instead of
general water quality trends are necessary in a rapidly changing environment. However, both sensors offer a reliable detection of highly resolved NOx-N concentration trends with
low maintenance effort, which is an asset in the field compared to other common in situ methods such as ion sensitive
electrode applications (Bende-Michl and Hairsine, 2010).

4 Conclusions

Both sensors were efficient for continuously monitoring
highly time-resolved NO3-N in groundwater emergences
(i.e. flowing water) in this study and deemed fit for purpose.

Although the calibration procedure for the DWS is easier
than for the MWS, the wavelength spectra of the latter provides a more detailed insight of the absorption and consequently improved NO3-N calculations. If NO2-N is a major
concern in the studied water, the MWS should be chosen
for monitoring, as the DWS does not distinguish between
NO3-N and NO2-N. For ease of use and with an emphasis
on measuring TON (where NO2-N is known to be negligible), the DWS could be also considered. In addition, the path
length of the two sensors should be carefully chosen. The
chosen path length is significant for the accuracy of the sensor measurements at a specific measurement range. It is reasonable to conclude that high-resolution UV/VIS monitoring
will greatly contribute to a better understanding of groundwater processes in the future.

_Acknowledgements._ The authors would like to acknowledge
the Teagasc Walsh Fellowship scheme for funding the study
in Ireland, and the German federal Ministry of Education and
Research (BMBF) for sponsoring the SMART-project (grant
no. 02WM1079-1086, 02WM1211-1212) for the study in Jordan.
Furthermore, we would like to thank the Jordanian Ministry of
Water and Irrigation and the local water authority of the city
of Salt for their support. We also gratefully acknowledge Tristan G. Ibrahim, formerly of Teagasc, the farm staff at Dairygold
Farm and Brendan Horan for supporting the field work in Ireland
as well as the staff of Johnstown Castle water laboratories for
analysing groundwater samples and Deirdre Hennessey.

The article processing charges for this open-access
publication have been covered by a Research
Centre of the Helmholtz Association.

Edited by: F. van Geer

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