Operational coastal water quality monitoring: are space borne products an alternative to in-situ measurements - Where are we now?

Carsten Brockmann1, Steven Dury2, Gerald Hesselmanns3, Hans Hakvoort2, Richard Duin4,

Mark Slater5, Rob Jordans2, Kerstin Stelzer1

1 Brockmann Consult, Max-Planck-Str.2, D-21502 Geesthacht, Germany, carsten.Brockmann@brockmann-consult.de 2 Rijkswaterstaat, AGI ,, Derde Wereldreef 1, 2622 HA Delft, The Netherlands, s.j.dury@agi.rws.minvenw.nl

3 ARGOSS, Voorsterweg 28, 8316 PT Marknesse, The Netherlands, hessselmans@argoss.nl 4 Rijkswaterstaat, RIKZ, Postbus 20907, 2500 EX The Hague, The Netherlands, r.n.m.duin@rikz.rws.minvenw.nl

5 University Dundee, Nethergate, DD1 4HN Dundee, Scotland, m.t.slater@dundee.ac.uk

1 Abstract

Water quality monitoring is an essential part of the monitoring programmes of the North Sea countries, required by in-ternational regulations such as the EU Water Framework Directive or the HELCOM Agreement. Because of budget constraints cost-effective alternatives to the very expensive ship cruises are urgently needed. The potential usage of wa-ter quality products from the space-borne instruments MERIS, MODIS and SeaWiFS is presently assessed in close col-laboration with the monitoring agencies in the Netherlands and Germany in the framework of the EU project OROMA and the ESA GSE Coastwatch initiative. Standard products from these instruments are compared with in-situ data, taken by the monitoring agencies, and airborne measurements. Local inherent optical properties are available for the Dutch waters, which are used to improve the water quality products, and which results in a convincing comparison with in-situ data. This has been shown with SeaWiFS data on a statistical evaluation of a 2 year time series. MERIS products are compared on a case study basis because of the short period of data availability. However, the objective is also to prove the quality of the products on a sound statistical basis. The first reactions of the monitoring agencies is very positive.

2 Introduction

The nature of the coastal zone as being of crucial importance for mankind is stressed by a number of conflicting proc-esses. Coastal zones with their industry, traffic and tourism are in permanent interaction with nature. It is the task of the coastal management to balance these interactions in a way which allows an optimal use of the coastal zone and to miti-gate the impact humans may have on the natural environment. This requires long term monitoring, which is defined and guided by several international regulations: The HELCOM Declaration [1], the OSPARCOM Convention [2], the Euro-pean Water Framework Directive [3] and the European Strategy for Integrated Coastal Zone Management [4]. The in-ternational laws are complemented by several national regulations, e.g. the “Bund/Länder-Messprogramm für die Meeresumwelt von Nord- und Ostsee” in Germany [5]. A new initiative has been started very recently at the European level to combine and harmonize this multitude of regulations by a unique “Marine Strategy” [6].

All these national and international regulations define – more or less – precisely which parameters have to be measured, the spatial and temporal requirements for the measurements and the accuracy. Today these measurements are mostly taken as in-situ water samples during ship campaigns. The water samples have to be analysed in specialist laboratories.

The national agencies in the member states which are responsible for the monitoring programmes, e.g. Rijkswaterstaat in The Netherlands or the Federal Maritime and Hydrographic Agency in Germany, operate their own ships in order to carry out the necessary measurement campaigns. As an example, Rijkswaterstaat operates numerous research vessels and is measuring chemical, biological and physical parameters on 5 transects in the Dutch waters on a regular basis (Figure 1). The measurement data are processed, quality checked and archived in the DONAR database. This database is a long term reference of the parameters required by both national and international regulations. Any change of a meas-urement method has to be verified against this database in order to ensure consistency and continuation of the time se-ries.

_____________________________________________________________Proc. MERIS User Workshop, Frascati, Italy,10 – 13 November 2003 (ESA SP-549, May 2004)

Figure 1: Locations of the 5 monitoring transects in the Dutch waters

The maintenance of such a measurement procedure is very expensive. Owning and operating ships is very costly, and the time spent on laboratory analyses further increases costs.. The pressure on the monitoring agencies to reduce their expenses, while the requirements from the international regulations are increasing, feeds the demand for more cost effec-tive methods. Remote sensing is often cited as a potential alternative. However, one has to be very careful to respect the limitations of remote sensing and to understand the methodological differences. The requirements of coastal moni-toring are very high and a careful analysis of remotely sensed water quality parameters has to be performed in order to establish the relationship with the existing data bases. A simple scale analysis makes clear that air- and space-borne re-mote sensing have their strengths at the medium and large temporal and spatial scales, and that best use is made if they complement in-situ sampling stations and buoys. As a consequence the number of the latter might be reduced, which would bring the expected cost-reduction benefits, as well as providing enhanced spatial coverage

3 The OROMA and Coastwatch projects

With the launch of the SeaWiFS sensor by the US in 1997 a new era of ocean colour sensors began, which now provide the basic measurements which are required to measure water quality. MOS, MODIS and more recently MERIS and the Japanese GLI are complementing this suite of instruments. Algorithms to convert the raw measurements into geo-physical parameters have been developed and verified in recent years, and today’s activities have the objective to estab-lish and validate water quality products and related services. Two important activities are the EU FP5 OROMA project [7] and the Coastwatch project [8], which is part of the ESA GMES-GSE [9] initiative.

OROMA has the objective of establishing methods for monitoring and mapping near coastal bathymetry and related environmental parameters. Radar and optical remote sensing techniques are combined with inverse modelling in order to provide bathymetry and water quality maps, which includes chlorophyll and suspended matter concentration.

Figure 2: Schematic diagramme of the relationship between the EU FP5 project OROMA and the ESA GMES-GSE initiative Coastwatch. PPS is the remote sensing data processing system available at RIKZ.

These products will be generated and disseminated to the end-user in real time. They shall contribute to an actual as-sessment of the coastal system status and the system’s dynamic behaviour. Coastwatch has the objective to provide an operational service, which shall provide effective and reliable information to support decision-making in coastal man-agement. Figure 2 shows the relationship between the two projects. While the context of OROMA is large and includes methodological aspects, particularly the integration of airborne and space-borne remote sensing data and product valida-tion, Coastwatch is focusing on providing a cost-effective, operational service. This is important since the driving force for the end-user is the dilemma of increasing demand from international regulations and concurrent decrease in funding.

4 Statistical validation of remotely sensed water quality parameters

A point-to-point comparison of in-situ measurements with remote sensing data is questionable, because of methodologi-cal, spatial and temporal differences. For example, a water sample provides the measurement of 1 litre of sea water, taken at certain depth, while the remote sensing data are averaged horizontally over a much larger area and vertically over the euphotic zone. However, it is important to understand how the traditional in-situ data and the remote sensing data relate to each other. The best way to achieve this is to compare statistical quantities. Figure 3 shows the annual cy-cle of suspended matter and chlorophyll-a concentrations. The typical pattern of the spring plankton bloom and also the inter-annual variation becomes clear in such multi-year time series. Such time series have been derived for all DONAR stations. A first comparison with remote sensing data has been performed with SeaWiFS data from 2002. Two different processing chains are compared with the in-situ measurements, for both total suspended matter and chlorophyll determi-nation. The standard SeaDAS empirical algorithm (for chlorophyll) and the one band semi-analytical POWERS algo-rithm [10] (for total suspended matter) are compared to an alternative analytical one developed by ARGOSS, taking the special conditions of Dutch waters into account (Figure 4 One can see that the annual cycle corresponds very well, if the remote sensing data are processed with the local adaptation.

Figure 3: Time series of in-situ measured total suspended matter (left) and chlorophyll-a (right) concentrations at Station Noordwijk 2 (for location see Figure 1).

Figure 4: Comparison of the total suspended matter (left) and chlorophyll-a concentrations for the year 2002 between the DONAR in-situ measurements and SeaWiFS data, at Station Noordwijk 2, processed with the POWERS (TSM),

SEADAS (CHL) and the ARGOSS algorithms.

10-1 100 101 10210-1

100

101

102

DONAR TSM (g m-3)

Ana

lytic

al T

SM

(g m

-3)

3 month average

Walcheren

Noordwijk

Terschelling

Rottumerplaat

10-1 100 101 10210-1

100

101

102

DONAR CHL (mg m-3)

Ana

lytic

al C

HL

(mg

m-3

)

3 month averages

Walcheren

Noordwijk

Terschelling

Rottumerplaat

Figure 5: Comparison of 3 monthly averaged data of the DONAR transect stations (total suspended matter: left, chloro-phyll-a: right)

The annual cycle of suspended matter and chlorophyll concentrations shows that temporal averaging is possible. A 3 monthly average will preserve the typical phases whilst smoothing out tidal effects on the data, and thus permits a com-parison of how the cycle is resolved by the different methods. Figure 5 shows this comparison for all transects. While the suspended matter has almost no bias but significant scatter, the chlorophyll concentrations shows that the remote sensing data are systematically higher than the in-situ measurements.

5 Analysis of MERIS data

The statistical analysis presented in section 4 will be extended to other years and other instruments, namely MODIS and MERIS. Even though no complete yearly cycle of MERIS data is available, a first assessment in this context has been performed. The medium spatial resolution of MERIS favours this instrument for applications in the coastal waters of the North Sea, where the spatial variability is very high. However, the availability of MERIS Full Resolution data for the area needs to be improved. Sun glint is also a severe problem, because 50% of the orbits are contaminated by sun glint so heavily that they cannot be further evaluated with today’s methods. 12 MERIS FR products from the year 2003 were available for this study. The study area had high sun glint conditions in 4 cases, 6 had medium glint and only 2 were outside the sun glint. These 2 cases spectacularly show high resolution images of the chlorophyll and suspended matter concentrations in the area, as shown in Figure 6 for the example of total suspended matter. The pattern as well as the absolute values correspond to expectations. Values around 10 mg/l are found in the coastal areas, decreasing to 1 mg/l in the channel and increasing again towards the English coast. The concentrations in the mouth of the Scheldt increase to more than 40 mg/l, which also corresponds to observations.

Figure 6: Total suspended matter concentration derived from MERIS Full Resolution image of 16.04.2003 (left). The red pins are located at the DONAR stations. The northern most transect is the Noordwijk transect which is extracted

from the image and shown on the right side. The vertical arrows show the locations where the water samples are taken.

The stations of the DONAR transects are shown as red pins in the image. The most northern transect is the Noordwijk transect, which is shown in the right part of Figure 6. This figure demonstrates the advantage which remote sensing data can provide over traditional ship measurements: the chlorophyll maximum at 40km distance off shore is missed in the ship transect because there are only stations at 20km and 70km. The satellite resolves the profile with much more detail. The TSM profile also shows that the locations for the ship sampling have been well chosen: the near coastal point is representative for the high values close to the shore, and the 10km point lies in the local suspended sediment maximum. However, for another transect or at another time, this may change.

Figure 7 shows the integration of MERIS measurement of 16.4.2003 into the long time series of the DONAR measure-ment stations at station Noordwijk 2. This must be viewed as a starting point, since these were the only data available at the time of writing. New MERIS data are becoming more readily available now, and the analysis will become more meaningful after the integration of more data points. However, this start shows that the standard MERIS Level 2 prod-uct fits very well into the DONAR time series. No tuning has been performed, and no local adaptation was necessary.

Figure 7: Comparison of MERIS measurements with the long time series of DONAR at station Noordwijk 2. The MERIS measured suspended matter (left) and chlorophyll (right) values from 16.04.2003 are plotted as red crosses

above the DONAR annual time series.

6 Conclusion

National and international agencies, responsible for monitoring European waters, have to comply with a demanding number of environmental regulations, whilst the available budget is decreasing. Therefore they need

• cost effective alternatives to expensive field measurements

• information corresponding to the requirements from international regulations

• reliable product quality with well justified error estimates

• long term commitment for data supply

Air- and space-borne remote sensing techniques can provide information which complements existing in-situ measure-ments. They offer advantages in terms of spatial and temporal coverage, which can be translated into a smart, combined system of remote sensing and in-situ measurements, thereby reducing the effort and subsequently costs. However, this needs a comparison of the different methods in order to understand how the data relate to each other. This should be made on a statistical basis rather than on a point-to-point comparison. The long term databases such as the DONAR da-tabase provide a sound basis for such a study. Statistical methods give information on reliability of the results and error estimates.

Remote sensing data are available today from a variety of platforms. SeaWiFS data need locally adapted methods in order to generate results which show the expected annual cycle. The MERIS data which have been analysed to date fit very well into the long term time series and appear very promising. These initial results have already convinced the end

user to further cooperate and to extend the study to longer time series of satellite data and to include additional instru-ments.

7 Acknowledgement

This work was performed within the OROMA project with support from the European Commission (contract number EVK3-CT-2001-00053, www.brockmann-consult.de/oroma).

Part of this work was performed within the Coastwatch project which is financed by the European Space Agency ESA (http://www.coastwatch.info).

The image visualisation and analysis was done with the BEAM toolbox, which is provided free of charge by ESA (http://envisat.esa.int/services/beam)

8 References

[1] Declaration on the Protection of the Environment of the Baltic Sea (15 February 1988) http://www.helcom.fi/helcom/declarations/1988.pdf and http://www.helcom.fi/helcom/declarations/1992.pdf

[2] 2003 Strategies of the OSPAR Commission for the Protection of the Marine Environment of the North-East At-lantic (Reference number: 2003-21) http://www.ospar.org/eng/doc/Revised_Strategies_2003.zip

[3] Directive 2000/60/EC of the European Parliament and of the Council establishing a framework for the Commu-nity action in the field of water policy http://europa.eu.int/comm/environment/water/water-framework/index_en.html

[4] Recommendation of the European Parliament and of the Council of 30. May 2002 concerning the implementation of Integrated Coastal Zone Management in Europe http://europa.eu.int/eur-lex/pri/en/oj/dat/2002/l_148/l_14820020606en00240027.pdf

[5] Bund/Länder-Messprogramm für die Meeresumwelt von Nord- und Ostsee http://www.bsh.de/de/Meeresdaten/Beobachtungen/BLMP-Messprogramm/index.jsp

[6] Communication from the Commission to the Council and the Parliament Towards a strategy to protect and con-serve the marine environment COM(2002)539 http://europa.eu.int/eur-lex/en/com/pdf/2002/com2002_0539en01.pdf

[7] OROMA homepage http://www.brockmann-consult.de/oroma

[8] Coastwatch homepage http://www.coastwatch.info/home/index.htm

[9] ESA GSE homepage http://earth.esa.int/gmes/index.html

[10] H. van der Woerd, J.H.M. Hakvoort, H.J. Hoogenboom, N. Omtzigt, R. Pasterkamp, S.W.M. Peters, K.G. Ruddick, C. de Valk C., and R.J. Vos, 2000 Towards an operational monitoring system for turbid waters, O-00/16, IVM\VU Amsterdam, 62 p.