Monitoring Eutrophic Shallow Lake Environments through
Airborne Remote Sensing and In-Situ Spectroradiometry: The
Norfolk Broads, UK, and Lake Balaton, Hungary
P. D. Hunter*, A.N. Tyler*, N.J. Willby# & D.J. Gilvear*
*
School of Biological and Environmental Sciences
#
Institute of Aquaculture
University of Stirling
Stirling
FK9 4LA
United Kingdom
Email: p.d.hunter@stir.ac.uk; a.n.tyler@stir.ac.uk
T. Preston†, M. Présing‡, V. Toth‡ & M. Green+
†
Isotope Biochemistry Laboratory, Scottish Universities Environmental Research Centre
‡
Balaton Limnological Research Institute of the Hungarian Academy of Sciences
+
The Norfolk Broads Authority
Abstract
Shallow lake environments are known to exhibit two alternative ecological states under
eutrophication: (1) a favourable clear water state dominated by littoral macrophytes, and (2) an
unfavourable turbid state dominated by dense blooms of phytoplankton often composed of
harmful cyanobacteria. The alternation from the favourable macrophyte dominated state to the
unfavourable phytoplankton dominated state can have a debilitating effect on the function and
biodiversity of shallow lake environments. The Norfolk Broads (UK) and Lake Balaton
(Hungary) represent two shallow lake environments that have been severely affected by cultural
eutrophication. The adverse impacts that can arise from the eutrophication demands that
effective monitoring strategies are developed that can identify dynamic change in the condition
of shallow lake wetlands.
However, monitoring the impacts of eutrophication in shallow lakes environments is
problematic. The spatial and temporal complexity inherent in shallow lake environments
demands that monitoring should be conducted in a synoptic manner. This paper outlines how
airborne remote sensing (CASI and ATM) and in-situ spectroradiometry is being used in the
Norfolk Broads and Lake Balaton to (1) monitor spatial and temporal variability in water quality
and, potentially, the formation of harmful cyanobacteria blooms, and (2) monitor the distribution
and physiological condition of macrophyte communities. Preliminary results obtained from
spectroradiometry of emergent macrophyte stress in Lake Balaton demonstrate that remote
sensing may be used to monitor changes in the physiological condition of emergent
communities. This may potentially enable the pre-emptive identification of macrophyte
instability at a stage where mitigatory action could be undertaken.
1.
Introduction
1.1
The Impact of Eutrophication in Shallow Lake Environments
Many European shallow waters have been subject to cultural eutrophication and are now
excessively fertile. Eutrophication has lead many shallow lake environments to develop
problems with ecosystem stability (Scheffer et al., 1993). Shallow lakes are characterised by a
natural state of macrophyte dominance which is fostered in shallow and clear waters. The
sequestration of nutrients (N & P) by macrophyte communities creates an environment of mild
nutrient stress (Ozimek et al., 1990) which suppresses the turbid growth of phytoplankton in the
open water and contributes to the maintenance of clear water conditions.
However, excessive external nutrient loads have precipitated a loss of macrophyte
dominance in many shallow waters (Scheffer and Carpenter, 2003).
The increased
bioavailability of nutrients stimulates the excessive growth of phytoplankton and epiphytic algae
(Jones and Sayer, 2003). The consequential increases in water column turbidity and shade
effects reduce the insolation of the submerged macrophyte communities causing regression to
occur. The loss of macrophyte cover reduces the stability of the rooting substrate and, thus,
promotes the increased resuspension of bottom sediments. Consequentially, the escalating
resuspension of bottom sediments increases the internal loading of nutrients which drives further
phytoplankton growth and subsequent reductions in water clarity. The deteriorating water
quality conditions often results in the eventual exclusion of submerged and, potentially, floatingleaved macrophyte communities.
The regression of macrophyte communities permits phytoplankton to dominate eutrophic
shallow waters. The development of nuisance phytoplankton blooms is a serious concern for the
management of inland waters. However, a greater concern is the potential development of
harmful algae blooms (HABs). Numerous species of phytoplankton are capable of producing
toxins. The formation of HABs in eutrophic shallow waters is most commonly associated with
the cyanobacteria (CyanoHABs). However, the detection of cyanobacteria in inland waters is
problematic. The monitoring of phytoplankton populations is generally based around biomass
estimates obtained from surrogate measures of chlorophyll a and arduous species counts. As
chlorophyll a is a photosynthetic pigment common to all phytoplankton species, this measure
can offer no information on the species composition of phytoplankton populations and,
specifically, the presence or absence of significant cyanobacterial biomass. Much interest is now
being invested in the use of biomarker pigments as a means for monitoring broad changes in the
species composition of phytoplankton populations.
Freshwater cyanobacteria can be
discriminated on the basis of the biomarker photosynthetic pigment C-phycocyanin (Rowan,
1989). However, monitoring the distribution of biomarker pigments in spatially complex and
temporally transient waters remains a significant obstacle.
Numerous workers have also reported that the eutrophication of shallow lake
environments can result in the regression of emergent macrophyte communities and, in
particular, Phragmites australis reedswamp. The extent of Phragmites australis reedswamp in
shallow waters throughout western and central Europe has declined as these environments have
become increasingly afflicted by excessive nutrient inputs. However, the cause of Phragmites
australis regression is not certain. Given that it cannot be linked to changes in the turbidity of
the shallow waters under eutrophication, several workers have proposed other explanations for
this phenomenon. These include the mobilisation and accumulation of heavy metals (Čížková et
al, 2001), nitrogen saturation (Boar, 1996), sediment anoxia and the production of sulphuric
compounds and phytotoxic organic acids (Studer & Brandle, 1988; Armstrong & Armstrong,
2001), and weak stem development under luxurious production (Boar et al, 1989).
1.2
Monitoring the Impacts of Eutrophication in Complex Environments
The severe impacts of eutrophication in shallow lake environments have increased the need for
effective site condition monitoring strategies. However, monitoring the impact of eutrophication
on water quality and macrophyte distribution and condition in wetland environments is
problematic. Aquatic environments are inherently spatially complex and temporally transient.
Monitoring water quality parameters through single-point sampling protocols can, therefore,
seldom adequately describe the full spatial and temporal complexity in the distribution of
phytoplankton, SPM, and other water quality parameters in shallow lake environments. The
main problem concerning monitoring the distribution of macrophytes in wetland environments is
the arduous nature, and often impracticality, of conventional field floristic and physiognomic
surveys. Furthermore, the extensive regression of macrophyte communities in eutrophic shallow
lake environments has underlined the need for a monitoring technique capable of the
presymptomatic identification of the impact of environmental stressors on the physiological
condition of vegetation.
1.3
Remote Sensing of Water Quality
Numerous studies have demonstrated the potential of remote sensing for the provision of
spatially synoptic and multitemporal characterisations of various water quality parameters (e.g.
Allee and Johnson, 1999; George and Malthus, 2001). Water quality parameters retrievable
from remote imagery include the concentration of chlorophyll a, SPM, coloured dissolved
organic matter (CDOM) or gelbstoff, and the Secchi disk depth (SDD). The advantage that
remote sensing has in terms of water quality monitoring is that it can provide information on the
distribution of water quality parameters as a systematic continuum thus overcoming the
problems of obtaining spatially representative data in complex environments.
Several workers have shown that accurate estimates of the concentration of chlorophyll a
can be retrieved from satellite imagery. Baban (1993) retrieved the concentration of chlorophyll
a in the Norfolk Broads with an accuracy of r2 = 0.73 using a simple empirical relationship with
the TM3 band of the Landsat TM platform. However, many inland waters are recognised as
being optically complex and have spectral signatures that are composed of many overlapping
spectral components. The masking of the chlorophyll a signature by high and heterogeneous
distributions of SPM is a particular problem with the retrieval of chlorophyll a estimates in many
inland waters (Lindell et al., 1999). The poor radiometric and spectral resolving capabilities of
many broad band Earth observation satellites (e.g. Landsat & SPOT) are not ideally suited to the
resolution of complex spectral features in inland waters. Furthermore, the spatial resolution of
the imagery provided by many of these platforms (i.e. 30 m (Landsat TM)) precludes the
monitoring of all but the largest inland waters.
The spatial, spectral, and radiometric, restrictions of many older generation satellites
have prompted several researchers to explore the potential of airborne imagery for inland water
quality monitoring. The spatial resolution of airborne imagery is more conducive to the
observation of small inland waters. Furthermore, the new generation of hyperspectral sensors,
and sensors with user-definable spectral bandsets (e.g. CASI), now have the spectral and
radiometric capabilities necessary for the discrimination of spectral features in optically complex
waters. For example, Flink et al. (2001) used hyperspectral and multispectral CASI (Compact
Airborne Spectrographic Imager) imagery to retrieve chlorophyll a concentrations (max. r2 =
0.96) in two Swedish inland waters.
The potential for chlorophyll a retrieval from remote imagery in optically complex
waters has also been improved due to recent advancements in image analysis methods. Sváb et
al. (in press.) and Sváb et al. (submitted) used a linear mixture model to map the concentration
of chlorophyll a in Lake Balaton (Hungary) from Landsat TM and MSS imagery (r2 = 0.95).
The linear mixture modelling (LMM) approach enabled the retrieval of chlorophyll a
concentrations despite the fact that the optical characteristics of the water were dominated by
high and heterogeneous concentrations of suspended sediment.
There are, however, some limitations regarding the application of remote sensing to the
monitoring of water quality in inland waters. One significant constraint of remote sensing as a
means of monitoring phytoplankton dynamics is that it cannot yet provide information on the
species composition of phytoplankton populations. As chlorophyll a is common to the
pigmentation of all phytoplankton its surrogate use in biomass mapping renders taxonomic
discrimination impossible. However, phytoplankton contain a range of accessory pigments
(carotenoids and phycobiliproteins) many of which are taxonomically significant. These
biomarker pigments present a means by which taxonomic information on the composition of
phytoplankton communities can be obtained. However, the identification of the biomarker
pigments in remote imagery has not been comprehensively addressed. Of particular interest is
the potential for mapping CyanoHABs on the basis of the biomarker C-phycocyanin. Vincent et
al. (2004) mapped cyanobacteria in Lake Erie (USA) on the basis of the distribution of Cphycocyanin using Landsat TM imagery obtaining a maximum calibration accuracy of r2 = 0.77.
Given the poor radiometric and spectral capabilities of the Landsat TM platform, the mapping of
C-phycocyanin and other important biomarker pigments should be improved through the use of
more advanced remote platforms (e.g. CASI).
1.4
Remote Sensing of Macrophyte Distribution and Condition
Remote sensing can provide synoptic and multitemporal information of the distribution and
condition of emergent macrophytes and, potentially, submerged macrophytes, in wetland
environments. Mapping the distribution and condition of macrophytes by remote sensing
provides a solution to the problems of obtaining spatially representative information in complex
and inaccessible wetland environments.
Several workers have used remote sensing to monitor macrophyte communities in
shallow wetland environments. Mumby and Edwards (2002) used CASI imagery to map the
distribution of macrophyte species and communities in the shallow marine waters surrounding
the Turks and Caicos Islands (British West Indies). Mumby and Edwards achieved a habitat
classification accuracy of 81% using CASI imagery. This compared favourably to the 64%
accuracy that was achieved with satellite imagery (IKONOS). Similar results were achieved by
Malthus and George (1997) who mapped the distribution and composition of macrophyte
functional groups in the Cefni Reservoir (Anglesey) using ATM imagery. A classification
accuracy of 79% was achieved despite the inherent spectral and radiometric limitations of the
ATM sensor.
These results indicate the potential of airborne remote sensing for mapping the
distribution macrophytes in shallow wetland environments. However, remote sensing can also
be used to gain information on the condition of macrophyte communities. Jensen (1980) used
remote sensing to monitor the biomass of macrophytes in a salt marsh community. However, the
use of remote sensing to monitor changes in the biomass of macrophyte communities has receive
only limited attention to date and some of the published results have been disappointing (e.g. Vis
et al., 2002). However, the recent advancements in the specifications of airborne platforms may
enable the biomass of macrophyte communities to be monitored with improved accuracy.
Recent research has also shown that the remote characterisation of the spectral variation
across areas of monospecific vegetation can be used as a basis from which quantitative indices of
plant stress or vigour can be derived. Variations in plant vigour and stress exposure are often
reflected through changes in the biochemistry of the leaves. In particular, the exposure to
environmental stress often results in changes in the pigmentation of leaves with systematic
decreases in the concentration of chlorophyll a with increased stress exposure. Several workers
have demonstrated that the position of the chlorophyll a absorption feature (chlorophyll rededge) in the red spectrum shifts to longer wavelengths as the concentration of chlorophyll a
increases (e.g. Sims and Gamon, 2002). The red edge position (REP) can therefore be used to
monitor changes in the vigour of vegetation communities (e.g. Davids and Tyler, 2003) and,
potentially, stress effects in macrophytes. The expression of vigour variations in vegetation is
often subtle and not easily identifiable in the field by conventional survey methods. The
realisation of sensitive remote technique for monitoring spatial and temporal changes in the
condition of macrophyte communities would allow the presymptomatic identification of
potential macrophyte instability at a stage where mitigatory action could be undertaken.
2.
Research Outline and Brief Methodology
2.1
Study Sites
2.1.1
The Norfolk Broads
The Norfolk Broads are an extensive wetland complex consisting of 63 distinct shallow (mean
depth >3 m) marl lakes (Broads) ranging in size from 0.1 – 130 ha. The Broads were subjected
to severe eutrophication over a period leading up to the early 1980s. The eutrophication of the
Broads has lead to the development of nuisance phytoplankton blooms, a loss of the
characteristic submerged macrophyte communities, and the extensive regression of Phragmites
australis reedswamp. The intrusion of saline water has been proposed as a possible cause of
ecological instability in the coastal Thurne Broads and the production of ochre is a serious
concern for many of the Broads and associated waterways.
2.1.2
Lake Balaton
Lake Balaton (Hungary) is the largest inland water body in central Europe by surface area (595
km2). Despite the size of Lake Balaton, the lake is in fact extremely shallow (mean depth < 3
m). Lake Balaton received excessive cultural nutrient inputs and reached a state of hypertrophy
by the early 1980s. The progressive eutrophication of Lake Balaton resulted in the extensive
regression of the Phragmites australis reedswamp habitat. The regression in Lake Balaton is
symptomatic of the extensive loss of Phragmites australis reedswamp that has been observed in
many eutrophic wetland environments throughout western and central Europe.
2.2
Airborne Remote Sensing of Water Quality in the Norfolk Broads
This project is utilising the National Environmental Research Council Airborne Remote Sensing
Facility (NERC ARSF) to acquire remote time-series imagery (CASI and ATM) of water quality
parameters in the Upper Thurne and Trinity region of the Norfolk Broads during 2004 and 2005.
During the 2004 airborne campaign CASI is being flown in the simulated SeaWiFS
configuration, providing imagery with a spatial resolution of 2 m. It is anticipated that CASI
may be deployed with a user defined bandset configuration during the 2005 airborne campaign
based on the results of a spectroradiometry investigation into the spectral characteristics of the
biomarker pigments of the phytoplankton in the Norfolk Broads. A maximum of four sets of
time-series imagery will be obtained during 2004. A further 8 sets of time-series imagery will be
collected during 2005. Each set of time-series imagery is composed of four flights lines
distributed between 10.00 and 16.00 (BST).
The CASI and ATM imagery will be calibrated to provide characterisations of several
important water quality parameters including chlorophyll a, C-phycocyanin, SPM, SPIM
(suspended particulate inorganic matter), SPOM (suspended particulate organic matter), ochre
(ferrous precipitates), and water temperature (for the identification of areas of upwelling saline
groundwater). Focus will be given to the extent of diurnal change in the spatial distribution of
phytoplankton during the 2004 airborne campaign. In particular, the effect of heterogeneous
vertical distributions of phytoplankton on the accuracy of chlorophyll a retrieval will be
addressed. The 2005 airborne campaign will concentrate on seasonal changes in the biomass and
the potential for monitoring the development of cyanobacteria blooms.
The imagery will be calibrated and validated by the laboratory analysis of water samples
collected concurrent with image acquisition. Linear mixture modelling will be used in
conjunction with conventional semi-empirical analysis to retrieve chlorophyll a, C-phycocyanin,
SPM, CDOM, and ochre, concentrations from the remote imagery. A detailed explanation of the
linear mixture modelling approach to chlorophyll a retrieval is provided by Tyler et al. (this
publication) and Sváb et al. (submitted).
2.3
Remote Sensing of Macrophyte Distribution in the Norfolk Broads
The distribution of macrophytes in the Upper Thurne region of the Norfolk Broads will be
mapped using CASI imagery flown by the NERC ARSF. The CASI instrument is being flown
using the default ‘vegetation’ bandset configuration providing imagery with a spatial resolution
of 2 m. A maximum of 4 CASI images are to be flown during the course of 2004 airborne
campaign and a maximum of 8 images to be obtained during the 2005 airborne campaign. The
CASI imagery will be used to derive maps of macrophyte stands on the basis of the distribution
of functional groups, species dominance, and biomass. The interpolation of the chlorophyll REP
will also be evaluated as a means of monitoring changes in vegetation vigour. Research will also
concentrate on the potential for discriminating differences in the growth form of submerged
macrophytes. Image classification will be performed in conjunction with the aid of aerial
photographs acquired concurrently with CASI image acquisition and data from ground based
macrophyte surveys.
2.4
In-Situ and Laboratory Darkroom Spectroradiometry of Emergent Macrophyte Stress
The potential of remote sensing for the detection of environmental stress effects in emergent
macrophyte communities is being assessed by extensive in-situ and laboratory spectroradiometry
measurements of Phragmites australis reedswamp stress in the Norfolk Broads and Lake
Balaton. Research in Lake Balaton was conducted in June 2003 and July 2004. The research
conducted in Lake Balaton will be replicated in the Norfolk Broads during 2004 and 2005.
Lake Balaton
In-Situ and Laboratory Darkroom Spectroradiometry
In-situ spectral measurements were taken from 45 homogeneous Phragmites australis stands
using an ASD FieldSpecTM UV/VNIR spectroradiometer (350-1050 nm) during the 2003
campaign. A further 25 stands were examined in 2004 with spectra being acquired using two
GER 1500 spectroradiometers. The two GER 1500 spectroradiometers were used in dual cosconical mode with a cosine diffuser used to collected measurements of incident radiance
concurrent with target radiance measurements. Spectral measurements were acquired between
the hours of 10.00 and 15.00 to limit the effect of sun angle variations. Potential differences in
the spectral field of view were minimised by collecting all spectra at a constant 0.5 m above the
canopy of the Phragmites australis stand
Laboratory darkroom spectra were collected from 20 apical leaves removed from the
canopy of each Phragmites australis stand. The laboratory darkroom spectra were taken using
the ASD FieldSpecTM Pro UV/VNIR (2003) and a GER 1500 spectroradiometer in single beam
mode (2004) using 3.5˚ and 15˚ optics respectively. A 300W video lamp provided a light source
and non-target surfaces were covered with a black cloth with a maximum reflectance of < 5%
across all wavelengths. All spectral measurements were calibrated to reflectance through the use
of a white Spectralon calibration panel. The spectra were used to derive a number of vegetation
stress indices that have been previously reported in the literature (see Davids and Tyler, 2003).
Biometric, Biochemical, and Environmental Measurements
The concentration of chlorophyll a, chlorophyll b, and total carotenoids in the Phragmites
australis apical leaves was determined for the calibration of the chlorophyll REP index. The
pigment assays conducted on the same leaves as used in the spectroradiometry. Biometric
measurements were made as a means of assessing stand performance. These included stand
biomass, stand necromass, mean stem height, mean stem diameter, mean apical leaf fresh and
dry weight, mean number of live and dead leaves, and mean number of internodes. Furthermore,
a range of environmental measurements were taken to determine the cause of stress and
regression in the Phragmites australis stands. These included the concentration of heavy metals
(Ca, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, and Zn) and nutrients (N, P, and 13C) in the rooting
sediment and apical leaves. In addition to these measurements, stem and rhizome material was
collected during the 2004 fieldwork for lignin, cellulose, and heavy metal analysis.
3.
Preliminary Results and Discussion
Spectroradiometry of Emergent Macrophyte Stress in Lake Balaton, Hungary
The relationship between chlorophyll a and the position of the chlorophyll red edge is shown in
Figure 1. The REP, as derived from the laboratory darkroom spectra, was found to be a sensitive
index for the concentration of chlorophyll a in the apical leaves of Phragmites australis (r2 =
0.95). The chlorophyll red edge could also be used to predicted the concentration of chlorophyll
b and total carotenoids with a similar degree of accuracy (r2 = 0.82 and r2 = 0.77 respectively).
The range of REP values recorded demonstrates that there are significant differences in the
physiological condition of Phragmites australis stands in Lake Balaton.
The spectral indices derived from the in-situ spectroradiometry of Phragmites australis
showed no significant relationships with the pigmentation of the apical leaves. However, the insitu indices did demonstrate significant relationships with some of the biometric measurements
of Phragmites australis performance (see Table 1). For example, the REP was significantly
correlated with mean stem height, mean stem diameter (r > 0.51).
120
Chlorophyll a (μg/cm2)
100
r2 = 0.95
80
60
40
20
0
690
695
700
705
710
715
720
Red Edge Position (nm)
Figure 1. The regression relationship between chlorophyll a content and the red-edge position for Phragmites
australis apical leaves in Lake Balaton, Hungary.
There was no suggestion from the results obtained from this study that the concentration
of heavy metals in the rooting sediment and, consequently, the apical leaves, was having a
significantly adverse impact on the health of Phragmites australis (see Table 1). Analysis of the
relationship between the REP (and other spectral indices), derived from the in-situ and
laboratory spectra, and the concentration of heavy metals returned only weak positive
correlations. This suggests that heavy metals, with the possible exception of Fe and Ca, are not a
cause of Phragmites australis regression, but, on the contrary, the condition of the Phragmites
australis stands appears to improve with increased metal bioavailability. The generally positive
effect of heavy metal accumulation on the condition of Phragmites australis in Lake Balaton has
lead to a revised hypothesis for the causes of regression being adopted for the 2004 fieldwork.
Several workers have previously reported that under excessive nutrient loading the concentration
of lignin and cellulose in the stems of Phragmites australis decreases (e.g. Boar et al, 1989).
This leads to the development of weak stands open to damage by wave action and subsequent
dieback. This explanation for the regression of Phragmites australis in Lake Balaton is still
under investigation.
Table 1. The relationship between the spectral indices derived from the laboratory darkroom spectra and the
concentration of heavy metals in the water, sediment, and leaf material (correlation coefficient: p-value).
Spectral Indices
Heavy Metal
SIPI
R725/R670
R750/R550
R750/R670
R750/R700
K mg l-1 Water
-0.088:0.705
0.600: 0.040
0.493:0.023
0.627:0.002
0.454:0.039
Ca mg l-1 Water
-0.045:0.847
-0.626:0.002
-0.502:0.020
-0.622:0.007
-0.488:0.025
Fe mg l-1 Water
0.600:0.004
0.056:0.811
0.199:0.388
0.064:0.784
-0.011:0.962
Ca mg g-1 Sediment
0.542:0.017
-0.096:0.696
0.040:0.872
-0.108:0.660
-0.132:0.590
Mn mg g-1 Sediment
0.228:0.347
0.551: 0.014
0.554:0.014
0.574: 0.010
0.408:0.086
Pb mg g-1 Sediment
0.688:0.028
0.224:0.534
0.341:0.335
0.207:0.565
0.203:0.575
K mg g-1 Apical Leaves
0.698:0.000
-0.065:0.781
0.164:0.479
-0.045:0.848
-0.019:0.934
Fe mg g-1 Leaf
-0.566:0.007
0.207:0.367
0.173:0.452
0.278:0.223
0.267:0.241
5.
Acknowledgements
The authors acknowledge the financial and logistical support of the Northumbria Water Group,
The Norfolk Broads Authority, the Environmental Agency, the University of Stirling, the
Balaton Limnological Research Institute of the Hungarian Academy of Sciences, and the British
Council. The authors also acknowledge the support of the NERC Airborne Remote Sensing
Facility and the Equipment Pool for Field Spectroscopy for the provision of remote imagery and
spectroradiometry equipment respectively.
6.
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