The use of ocean color remote sensing in integrated coastal zone management—A case study from Himmerfjärden, Sweden

Marine Policy 43 (2014) 29–39

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Marine Policy journal homepage: www.elsevier.com/locate/marpol

The use of ocean color remote sensing in integrated coastal zone management—A case study from Himmerfjärden, Sweden Susanne Kratzer a,b,n, E. Therese Harvey a, Petra Philipson c a

Stockholm University, Svante Arrhenius väg 21a, SE-106 91 Stockholm, Sweden Brockmann Consult GmbH, Max-Planck-Str. 2, DE-21 502 Geesthacht, Germany c Brockmann Geomatics Sweden AB, Torshamnsgatan 39, SE-164 40 Kista, Sweden b

art ic l e i nf o

a b s t r a c t

Available online 22 May 2013

In this study the use of ocean color data as a diagnostic tool in integrated coastal zone management was investigated as part of the Science Policy Integration for Coastal Systems Assessment (SPICOSA) project. Parallel to this, an operational coastal monitoring system has been set up in close collaboration with endusers. The core work of the bio-optical part in the project was to develop Secchi depth and attenuation of light as indicators for coastal zone management, by linking remote sensing with the socio-economic and ecological model developed in SPICOSA. The article emphasizes the benefits of stakeholder involvement and end-user feedback for efficient and improved system development. Furthermore, conceptual models were developed on how to integrate remote sensing data into coastal zone management and into a physical-biological model of the Baltic Sea. One of the work packages in the SPICOSA project was academic training. In this work package, on-line teaching material in the field of remote sensing and biooptics was developed and disseminated on the SETnet web page. The article presented here may act as supportive material for training in bio-optics and remote sensing. & 2013 Elsevier Ltd. All rights reserved.

Keywords: Coastal remote sensing Optical indicators Integrated Coastal Zone Management (ICZM) Stakeholders Education

1. Introduction Sound ecosystem-based management of the coastal zone must be based on comprehensive and quality-assured data about the respective coastal ecosystems. Variable spatial and temporal scales and the complex dynamics of coastal processes mean that it is not practical to study these using only in situ measurements. Remote sensing can provide the improved spatial and temporal resolution required to monitor and evaluate the changes in coastal ecosystems both in space and time. In recent years, the development of coastal remote sensing has accelerated, especially due to the development of the ocean color sensor ‘Medium Resolution Imaging Spectrometer’ (MERIS). MERIS was launched in 2002, on board the Environmental Satellite ENVISAT, and delivered data to Earth for a period of 10 years. The spectral and spatial resolution of MERIS is better than for most other operational ocean color sensors and MERIS is therefore better suited for remote sensing and monitoring of coastal waters [1–3]. The advantages of using remote sensing in management are evident: remote sensing provides a synoptic view of whole water basins, including coastal areas. Furthermore, one can derive

n Corresponding author at: Stockholm University, Svante Arrhenius väg 21a, SE106 91, Stockholm, Sweden. Tel.: +46 8 161059. E-mail address: [email protected] (S. Kratzer).

0308-597X/$ - see front matter & 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.marpol.2013.03.023

information on coastal dynamics, e.g. the extent of river plumes and algal blooms. As an example, Fig. 1 shows a MERIS image of a cyanobacteria bloom in the north-western Baltic Sea. Cyanobacteria blooms are a common phenomenon in the Baltic Sea during late summer [4]. Some of these are toxic, and therefore have important management implications. The Baltic Sea is a brackish semi-enclosed intra-continental sea surrounded by nine European countries. It is connected through the Danish straits with the Skagerrak and the North Sea. Its catchment area is about four times as large as the Baltic Sea itself, with a population of approximately 85 million people. In Germany, Denmark and Poland approximately 60–70% of the catchment area consist of farmland, whereas in Finland, Russia, Sweden and Estonia between 65% and 90% of the catchment area consist of forests, wetlands and lakes [5]. Since approximately the middle of the last century, human activities at sea and throughout the catchment area of the Baltic Sea have put increasing pressure on this fragile brackish ecosystem. In 1974, the Helsinki Convention on the Protection of the Marine Environment of the Baltic Sea Area [6] was adopted by the (then) seven coastal states bordering the Baltic Sea. The Contracting Parties committed themselves to take appropriate measures to prevent and abate pollution and to protect and enhance the marine environment of the Baltic Sea Area. In 1992, a new convention [7] was signed by all the states bordering the Baltic Sea, as well as the European Community. Besides the Baltic Sea

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Fig. 1. Cyanobacteria bloom in the north-western Baltic Sea: MERIS Kd(490) image from 28 July 2008 (300 m resolution); MERIS Kd(490) algorithm [from 2]. The image was read into Google Earth. MERIS data by courtesy of the European Space Agency. Processing: Christian Vinterhav.

and its sea bed the new convention also covers inland waters, and aims to reduce land-based pollution in the whole catchment area of the Baltic Sea. The new convention entered into force in 2000, and the present Contracting Parties are all bordering countries, Denmark, Estonia, Finland, Germany, Latvia, Lithuania, Poland, Russia, Sweden and the European Community [7]. The European Council’s Urban Wastewater Treatment Directive (UWWTD) was adopted in May 1991 [8]. It regulates the collection, treatment and discharge of urban waste water and from industrial sectors in order to protect the environment from the adverse effects of waste water discharges. The UWWTD requires the European Union’s Member States to ensure that both discharges from urban wastewater treatment plants and receiving waters are monitored. In the same year the Nitrates Directive [9] was adopted that regulates the agricultural use of nitrates in organic and chemical fertilizers. It is one of the key instruments in the protection of waters against agricultural pressure and requires the monitoring of e.g. nitrates concentrations and eutrophication. In 2000, the European Union’s member states adopted the Water Framework Directive (WFD) [10]. The WFD requires the assessment of the ecological status of European transitional and coastal waters using a number of so-called ‘elements’. The elements are stated in Annex 5 of the WFD as follows: (1) biological elements (Phytoplankton, aquatic flora, benthic invertebrate fauna); (2) hydro-morphological elements supporting the biological elements (Morphological conditions, Hydrological and Tidal regime); and (3) chemical and physico-chemical elements supporting the biological elements (General elements: dissolved oxygen, nutrients, transparency, temperature, etc.; specific elements: synthetic and non-synthetic pollutants).

In 2002, the European Parliament and the Council published a recommendation concerning the implementation of Integrated Coastal Zone Management in Europe [11]. It encompasses a strategic, ecosystem-based and sustainable approach to ICZM and requires the active involvement of coastal stakeholders in the process. It goes on to detail how both the marine and terrestrial area of the coastal zone should be addressed and how adequate systems for monitoring and dissemination of information to the public about their coastal zone should be developed. The information should be provided in appropriate and compatible formats to decision makers, and the data should be made publicly available. In 2007, the Baltic Sea Action Plan (BSAP) was adopted by HELCOM. Here, eutrophication has been identified as the most pressing environmental problem of the Baltic Sea ecosystem [12]. It is caused by excessive inputs of nitrogen and phosphorus that mainly originate from inadequately treated sewage, agricultural run-off and for nitrogen also from airborne emissions from shipping and combustion processes. The Secchi depth mean from June to September has been chosen as the primary indicator in the BSAP, since water transparency demonstrates many of the accepted effects of eutrophication [12]. Other indicators are used as supportive indicators and may give additional information on whether good environmental status has been achieved. One of these is the concentration of chlorophyll a, which may e.g. indicate the occurrence of algal blooms. The BSAP applies an ecosystem-based approach to the management of the Baltic Sea and was followed by the European Commission’s Marine Strategy Framework Directive (MSFD), adopted in 2008 [13]. The MSFD concentrates on a set of 11

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Fig. 2. Upper left: map of the Baltic Sea (from: http://maps.grida.no/baltic/) with the area of investigation indicated as a black box. The urban waste water treatment plant (UWWTP) is situated at the head of Himmerfjärden. The outlet of the UWWTP is situated close to location H5, at the head of the bay. The stations marked in the maps have been used for MERIS validation in other studies. BY31 is at Landsort Deep, the deepest part of the Baltic Sea (459 m). Gustav Dahlén is a light house housing a NASA AeronetOC station for MERIS validation. Note the difference in spatial resolution regarding the Landsat image (30 m) from 29 August 2002, the MERIS 300 m resolution and the MERIS 1.2 km resolution image from 19 August 2002.

descriptors, described in Annex 1 of the MSFD, which together summarize the functioning of the whole marine system. The WFD takes a slightly different approach, and divides the ecosystem into different elements, comparing the structure of these individually before combining them and evaluating the overall condition. The MSFD takes the ecosystem and separates that into functional objectives, and then recombines these to give a holistic approach, therefore the MSFD can be considered to adopt a ‘holistic, functional approach’ [14]. The EU directives are legally binding for member states, and therefore provide legal tools to enforce a joint monitoring and management strategy for the Baltic Sea. The task group on eutrophication of the Marine Strategy Framework Directive [15] emphasized the advantages of using remote sensing for monitoring eutrophication. Eutrophication is defined here as ‘a process driven by enrichment of water by nutrients, especially compounds of nitrogen and/or phosphorus, leading to: increased growth, primary production and biomass of

algae; changes in the balance of organisms; and water quality degradation. The consequences of eutrophication are undesirable if they appreciably degrade ecosystem health and/or the sustainable provision of goods and services’ [15]. In Sweden, the use of remote sensing in coastal management is still in its infancy. The aim of this case study is to illustrate how remote sensing and bio-optics can be incorporated in integrated coastal zone management of the Baltic Sea in general, and of Himmerfjärden (Fig. 2) in particular. Furthermore, it is described how optical parameters can be used as indicators for ecosystem health and eutrophication. In the following sections the reader will first be introduced to the area of investigation; Himmerfjärden bay, and the basics of bio-optics and remote sensing using Himmerfjärden as a case study. The work has been published in a more technical form in various remote sensing articles [2,16–17] and here relevant concepts are interpreted in relation to the WFD. After this, the development of an operational remote sensing system for the

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coastal zone is described. The system was developed in close collaboration with end-users, and the process of SPICOSA stakeholder involvement in system development is shown.

1.1. Area of investigation Himmerfjärden is a fjord-like bay situated in the Southern Stockholm Archipelago, just south of 601 N, opening into the Baltic Sea (Fig. 2). With a mean depth of about 17 m Himmerfjärden is rather shallow and consists of a sequence of basins divided by several sills. The bay and its adjacent waters have been well studied for many years, in part because of concern about nutrient enrichment by urban waste water [18–19]. Due to the low freshwater input (flushing rate 0.025 d−1) and the presence of the sills Himmerfjärden has a weak circulation, and as observed generally in the Baltic Sea, there is virtually no tidal influence. The local catchment area consists of 57% forest, 33% land, 4% lakes and 5% urban areas [21]. Himmerfjärden is subject to frequently occurring blooms of filamentous cyanobacteria during summer, dominated by Aphanizomenon sp. and Pseudanabaena limnetica [20], as well as occasional surface blooms of Nodularia spumigena. Blooms of N. spumigena, however, are more frequent and more intense in the open Baltic Sea, where they may cover large areas that can be monitored from space. The development of large surface accumulations of cyanobacteria are usually related to persistent warm weather during summer, induced during the development of a seasonal thermocline. In particular, N. spumigena thrives in warm temperatures during the late summer months [4]. Filamentous cyanobacteria are able to fix nitrogen, which gives them a competitive advantage when compared to other phytoplankton, and they may therefore dominate the surface waters in summer, provided there is enough phosphorus available. In the head of the bay a local Urban Waste Water Treatment Plant (UWWTP) is situated that serves approximately 300,000 people and the main human impacts are caused by the UWWTP (30% of the total nitrogen input) along with agriculture and by private sewers [21]. The Himmerfjärden UWWTP started operating in 1974, and had efficient phosphorus removal from the beginning (about 96%), using Himmerfjärden bay as recipient. In 1998, the introduction of efficient nitrogen removal (up to about 85%) was introduced in the treatment plant [22]. The inner basins of Himmerfjärden were shown to be potentially phosphorus limited, and may be regarded as ‘potentially eutrophic’, despite comparatively low nutrient loading relative to their volume [23]. However, there has been strong disagreement amongst Swedish marine scientist for many years if it is phosphorus or nitrogen that is limiting for the growth of filamentous cyanobacteria in the Baltic Sea [24]. During 2007–2010, a large scale experiment was conducted by the Department of Systems Ecology, Stockholm University in collaboration with the operators of the Himmerfjärden UWWTP (SYVAB). SYVAB provided the possibility for adaptive management by adjusting the level of nitrogen treatment. In this experiment, nitrogen was not treated for a period of two years (during 2007–2008), and during 2009– 2010, nitrogen treatment was operated, again, almost to its full capacity. This experiment was conducted in order to evaluate if the increased availability of nitrogen in the recipient may reduce the occurrence of blooms of filamentous cyanobacteria in the bay, i.e. by allowing other phytoplankton to compete with the nitrogenfixing cyanobacteria. The results of the full-scale nitrogen experiment are still under investigation. The Himmerfjärden nitrogen study was performed in parallel to the SPICOSA project, and the regular stakeholder meetings provided a good opportunity for also recruiting local stakeholders to the SPICOSA project [21].

1.2. Himmerfjärden from space Fig. 2 shows three images over Himmerfjärden derived from satellite data with different spatial resolution: Landsat TM data (30 m resolution), MERIS full resolution data (300 m) and MERIS reduced resolution data (1.2 km). The comparison shows that considering the spatial resolution, Landsat TM is better suited to view this coastal area from space. However, it is not adapted for aquatic applications as it is designed as a terrestrial sensor, which means that it is not sensitive enough for detecting variations in the water-leaving radiance (the light leaving the water). Its spectral resolution is also insufficient for marine applications as it has only 3 spectral bands in the visible part of the spectrum which are too broad (60–80 nm) in order to derive optical in-water components correctly. MERIS; however, is especially adapted to the low reflectance from water, and due to its 15 narrow bands (10 nm wide) also has an improved spectral resolution. MERIS 1.2 km resolution is too low to investigate Himmerfjärden, and one can only derive a limited number of water pixels within Himmerfjärden [17]. The 300 m resolution MERIS image shows that one can derive a reasonable amount of water pixels within the bay. One can also apply an adjacency correction that corrects for the high reflectance from land [17,26]. 1.3. The main optical components in the water The optical properties of a given coastal water body are determined by the optical properties of water itself, phytoplankton, Colored Dissolved Organic Matter (CDOM, also termed humic substances), and Suspended Particulate Matter (SPM, also termed total suspended matter, TSM). Together, these substances determine the color of the sea, and also jointly contribute to the attenuation of light in the water body [25]. The light attenuation decreases exponentially with water depth and is a measure of the gradual loss in light intensity, measured as the diffuse attenuation coefficient; Kd(490). The main processes involved in the attenuation of light are absorption and scattering by all optical components in the water. CDOM, for example mostly absorbs light, especially in the blue part of the visible spectrum. Inorganic suspended matter scatters light more, which increases the water-leaving radiance, and thus is recorded on a satellite image. Phytoplankton absorbs light in the blue and in the red part of the spectrum, and also scatters light. It is these specific absorption and scattering properties that can be used to derive the concentrations of optical components in the water quantitatively. The ocean color bands in MERIS were carefully chosen in order to be able to derive the light attenuation, chlorophyll a and SPM concentration, as well as CDOM [27]. 1.4. In-water optical properties In order to interpret satellite images in the coastal zone correctly, one needs to have a good understanding of the optical properties in the coastal zone. Kratzer and Tett [16] developed an attenuation model for the coastal zone that can act as an ecosystem synthesis of a given coastal area (Fig. 3). The attenuation follows a surface water gradient from the UWWTP at the head of Himmerfjärden bay to Landsort Deep (station BY31), the deepest part of the Baltic Sea (Fig. 2). Hence, the model is 2dimensional and describes how the attenuation of the three main optical in-water components changes when moving from coastal (source) into open sea waters (sink). The model results highlight the typical optical features of a given coastal area in the Baltic Sea. The optical properties of the open Baltic Sea are clearly dominated by colored dissolved organic matter. Superimposed is an optical signal from phytoplankton, which is influenced both by nutrients

S. Kratzer et al. / Marine Policy 43 (2014) 29–39 0.9

inorganic SPM

CDOM

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Chl-a

Kd(490) - Kw(490), m-1

0.8 0.7

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Open Baltic Sea

0.5 0.4 0.3 0.2 0.1 0.0 0

5

10

15

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25

30

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Horizontal distance from sewage outlet, km Fig. 3. Stacked contributions of the main optical component (CDOM, chlorophyll a and inorganic SPM) to the diffuse attenuation coefficient, Kd(490), along a transect from the outlet of Himmerfjärden UWWTP to Landsort Deep, the deepest part of the Baltic Sea (459 m depth). Note that Kd(490) was corrected for the attenuation of water itself, Kw(490). The black line indicates the mouth of Himmerfjärden and the beginning of the open sea [after16].

from land as well as upwelling nutrients from the bottom of the sea. In coastal areas, inorganic suspended matter becomes increasingly important with proximity to the inner part of the bay. The three optical components in this model may act as an ecosystem synthesis of a given coastal water body: CDOM mostly relates to terrestrial inputs of freshwater, suspended particulate inorganic matter (SPIM) to land drainage and to wind-stirring in shallow waters, and phytoplankton to the production in the pelagic ecosystem, influenced by anthropogenic nutrients from the local UWWTP. One of the main conclusions from this model in relation to management is that inorganic suspended matter can be here used as an indicator for determining the extent of coastal waters. The extension of the coastal waters would in this case be in the range of 15–20 km off the coast, where inorganic suspended matter load tends towards zero (tending below 0.05 g m−3) (Fig. 3). This is about 10 times as much as the 1 nautical mile defined by the WFD [10]. The extent of the coastal zone is an issue of great relevance to Baltic Sea management as the WFD is applied to coastal waters, whereas the management of the open Baltic Sea is under the responsibility of HELCOM. Another conclusion of this model in relation to coastal management is that changes in water clarity in Baltic Sea coastal waters are not only an indication of changes in phytoplankton biomass, but may also be related to changes in CDOM or SPM concentrations [28]. A reduction of land- or humanderived nutrients, e.g. from the local UWWTP, does therefore not necessarily lead to an improved Secchi depth in the coastal zone, especially in those areas with high fluvial input. As high concentrations of CDOM and SPM also increase the attenuation of light, they may also have an effect on light limitation of phytoplankton growth. Consequently, a pilot study of the bio-optical effects on the water quality in Himmerfjärden started in 2010, to monitor CDOM and SPM along with the regular monitoring programs. This initiative was supported by the Swedish Environmental Protection Agency with the aim of developing and evaluating the monitoring elements within WFD. 1.5. Diffuse attenuation of light and Secchi depth As mentioned before, Secchi depth has been used as the main indicator for eutrophication in the BSAP [12]. Secchi depth is closely related to the diffuse attenuation coefficient, Kd(490), which can be estimated from space [29,30]. In the open Baltic Sea Kd(490) can be measured reliably from space using SeaWiFS

Fig. 4. Inverted Secchi depth derived from MERIS FR data from 22 August 2002 (FUB Plug-In) and a local algorithm derived from sea-truthing data. PINS 7a-7b-7c7d (STN H5-H2) from head to mouth of Himmerfjärden [from 2].

and MODIS data[31]. Given empirical and theoretical relationships between Kd(490) and Secchi depth, it is therefore also possible to derive Secchi depth images from remotely sensed Kd(490) data or to derive both parameters directly from spectral water-leaving radiance derived from satellite data [2,28] (Fig. 4). Until the development of MERIS it was not possible to apply these methods to areas close to the coast as most ocean color sensors have a spatial resolution of 1 km and are too coarse for coastal remote sensing. Fig. 1 shows an example of such a Kd(490) map of the Himmerfjärden area derived from MERIS data, presented via Google Earth. 1.6. Operational remote sensing system During 2008, Vattenfall Power Consultants (now BG Sweden AB) and Stockholm University started a new collaboration on developing an operational system for water quality monitoring in the Baltic Sea based on remote sensing [32]. The Swedish Environmental Protection Agency, the Swedish River Basin District Authorities, the societies for water conservation and water companies were involved in the system development and product evaluation, and financed the project together with the Swedish National Space Board. The monitoring system was based on an operational system that had initially been developed for the Swedish great lakes; Vänern, Vättern and Mälaren during 2006– 2007. In 2008, Stockholm Archipelago and the Himmerfjärden area were included as additional sites. The basic products, i.e. concentration maps of chlorophyll a, TSM and CDOM absorption, were produced for all available MERIS images and made accessible to the end-users only a few days after image registration. In addition, a number of image-based products were delivered after the monitoring season and subsequently reported to the end-users. One of the early end-user requests was user-friendly information and data access via a web-based solution. A project web page was developed (www.vattenkvalitet.se) and from this site water quality data can be accessed through an ArcGIS Server solution. The server software enables fast and reliable data delivery and administration, as well as a user friendly interface. Basic GISfunctionality is available and the end-user only needs a web browser to be able to use the services delivered. The software offers ample options for future development and capacity increase according to end-user requirements. The final development project finished in December 2009 and until the end of 2011 www. vattenkvalitet.se/ was an official monitoring service available for

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everyone in the aquatic end-user community. The near-real time service had to be discontinued until further notice due to the unexpected end of the ENVISAT mission, in spring 2012. However, the data is still available on-line. A study comparing sea-truthing and MERIS data from 2008 showed that the retrieval of chlorophyll a and TSM in the coastal zone is reliable [17]. The authors evaluated different types of MERIS processors for the area, and the best processor was then directly implemented into the operational system. A comparison of the monthly means of chlorophyll a concentrations derived from the operational monitoring system to the monthly means measured by the Swedish monitoring program has been done recently in the study area [33]. The evaluation shows that the data retrieved from satellite-based monitoring are comparable to the observations from ship-based monitoring, but satellite-based monitoring is much better in capturing the spatial dynamics [33]. By combining the methods one can increase the frequency of observations substantially. Fig. 5 shows a time series of MERIS data derived from the operational coastal monitoring system. It clearly shows the development of a cyanobacteria bloom at the end of July 2008 and exemplifies how well suited the satellite method is for monitoring the spatial extent and the dynamics of cyanobacteria blooms. The information is provided in a visual format that is easy to understand and easy to convey. 1.7. The SPICOSA approach The aim of the FP6 Integrated Project Science and Policy Integration for Coastal System Assessment (SPICOSA, www.spi cosa.eu, 2007–2011) was to develop a methodology for mobilizing the best available scientific knowledge to support decision-making processes in Integrated Coastal Zone Management (ICZM). Furthermore, SPICOSA aimed to strengthen links between science and policy using a holistic approach that takes account of the ecological, social and economic sectors of coastal zone ecosystems. The focus of the SPICOSA method is on the creation of an operational

Systems Approach Framework (SAF) for assessments of policy alternatives in coastal zone systems. The SAF is a methodology for exploring the dynamics of coastal zone systems, and examining the potential consequences of alternative policy scenarios, at different spatial and temporal scales. The SAF describes and numerically simulates cause-andeffect chains in the coastal zone that start from a human activity which creates a pressure on an ecosystem, resulting in a change in state that may impact the system’s sustainable provision of goods and services to humans. To be able to fulfill the goals of the SAF methodology there is a need for research methods that can understand and measure how the coastal zone reacts to changes or different pressures within the environment and society. The Coastal Zone System Information Feedback Loop (CZFBL) developed within SPICOSA [34,35] uses a prognostic approach to identify the different drivers, pressures, state, impacts and responses within an ecosystem. The key link in the SPICOSA science-policy feedback loop is the integrated Ecological-SocialEconomic (ESE) Assessment box. The main novelty in this precautionary approach to coastal management is that the results of the ESE assessment is used to test changes in policy and human activities, by providing a prognostic tool that can prevent any environmental, economic or social issues from causing an irreversible change in state within the system. Various policy actions and scenarios can be trialed and improved, or applied in a more time appropriate context, since the results from the ESE are fed back into the CZFBL [34]. The SPICOSA SAF was tested at 18 study sites across Europe, one of which was Himmerfjärden. At each site, ‘stakeholder groups’ were formed to select the ‘ecosystem dysfunction’ to be studied by SPICOSA and to identify policy alternatives for management. The stakeholder meetings were held on a yearly basis during 2007–2010 and were the main instrument used to provide end-user feed-back to the study, both for the management model developed in SPICOSA [21] as well as for the remote sensing work. In the SPICOSA work package ‘observational

Fig. 5. Time series of chlorophyll maps over Himmerfjärden and adjacent areas derived from MERIS data (300 m resolution) during the summer of 2008. The maps show the situation for chlorophyll a on the 23rd, 24th, 28th, 30th and 31st of July 2008. This time series illustrates the dynamics of cyanobacterial blooms, and how important it is to get a spatial coverage to capture the development and the spatial coverage of the blooms. © Lantmäteriet, Gävle 2010. Permission I 2010/0053. MERIS data with courtesy from the European Space Agency (ESA) [after 33].

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techniques’, the use of remote sensing as diagnostic tool was investigated. First, the main policy issue in Himmerfjärden was identified. Secondly, suitable indicators were identified which could be implemented into management models. Thirdly, a conceptual model was developed that explored how to use remote sensing and bio-optics in integrated coastal zone management.

2. Results 2.1. Academic training One of the work packages in the SPICOSA project was academic training. In this work package, Stockholm University was instructed to develop on-line teaching material in the field of remote sensing and bio-optics. This material was published on the SPICOSA teaching and dissemination platform SETnet at the end of the SPICOSA project in 2011. The material included the film ‘The Science of Ocean Color’, a film consisting of 5 chapters filmed and directed by Roland Doerffer. It can be downloaded directly on the SETnet web page [36]. The article presented here may be regarded as supportive material for the bio-optics and remote sensing lectures published on the SETnet web page. 2.2. Remote sensing as diagnostic tool in management The starting point for developing remote sensing as diagnostic tool was the main ‘Impact’ and ‘Policy Issue’ for the study site Himmerfjärden. Following the SPICOSA launch meeting in February 2007 the members of work task (WT) 10.3 (observational techniques) were instructed to make a list of ‘human activities’ and ‘main impacts’ for their respective sites, based on a given table of possible coastal impacts. Table 1 lists the relevant impacts and human activities for Himmerfjärden. The table was prepared by the Himmerfjärden Stockholm University SPICOSA scientific team. On 13 Nov 2007 the Swedish SPICOSA participants arranged the first Himmerfjärden stakeholder meeting in Södertälje, Sweden. During this meeting, eutrophication, caused by increased loads of

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nitrogen, was identified as the major environmental problem in Himmerfjärden, as in general for the Baltic Sea. After identifying nitrogen management as the major policy issue, the next step was to identify the key indicators of eutrophication that can be simulated within the ESE Assessment box [21], and that also could be monitored by remote sensing. Secchi depth was found to be the link between the ecological and the economic component of the ESE: In the economic model, questionnaires were used to evaluate the monetary value that the residents in the Himmerfjärden area, or visitors/tourists put on improved water clarity (e.g. a Secchi depth increase by one meter). The ecological model estimated Secchi depth according to empirical relationship between nitrogen concentration and Secchi depth. Besides nitrogen loads water exchange rates were also included in the model. Nitrogen reduction e.g. was used as a policy management tool as well as a link between the social and the ecological component by evaluating the willingness of local farmers to pay for wetland or catch crop creation [21]. The next step for the WT 10.3 group was to make a conceptual model (Fig. 6) of Himmerfjärden based on Table 1, following a template given by Tom Hopkins, the coordinator of the SPICOSA project. This template was called ‘streamlining for a systems approach’ and was distributed to all members of the WT group. Fig. 6 shows a conceptual model of this streamlining approach adapted to Himmerfjärden. The cause-and-effect diagram describes the variables and processes linked to the main management issue i.e. eutrophication in SSA Himmerfjärden and suggests how to use remote sensing as diagnostic tool for monitoring eutrophication. The diagram was prepared for the first progress report in December 2007 [37] and was iterated here after feedback from the members of the WT 10.3 group. Secchi depth was also identified as a link in SPICOSA between the ecological model and satellite data. Secchi depth is highly correlated with the diffuse attenuation coefficient at 490 nm, Kd(490), which is a common product of satellite data. Local Kd(490) and Secchi depth algorithms were derived [28] from in situ optical measurements and it was also demonstrated how these algorithms can be applied to MERIS data in order to derive Kd(490) and Secchi depth maps from space (Figs. 1 and 4). The

Table 1 List of ‘human activities’ and ‘main impacts’ for Himmerfjärden, conducted by the members of work task 10.3 (observational techniques). (A)Impacts 1. Nutrient loading from one major and some smaller wastewater treatment plants, from agricultural land run-off, and from diffuse sources; it leads to increased primary production, which leads to eutrophication: i.e. increased biomass, leads to oxygen-depletion in sediments (when degraded by aerobic bacteria) and bio-diversity reduction 2. Shoreline development and habitat destruction: northern Hallsfjärden: harbor, dredging; harbor in Kaggfjärden 3. Erosion from boating and ship traffic 4. Invasive species, Cercopagis 5. Sediments dredging; marinas 6. Toxic pollution from industry: northern Hallsfjärden (south of Södertälje): organic pollutants, Näslandsfjärden: mercury, all of old origin; deposited in sediments, but may be released by dredging 7. Food-web changes likely 8. Biodiversity reduction 9. Water cycle disturbance 10. Fishing (professional fishing very low) 11. Erosion (small problem as yet)

(B)Human activities 1. Waste effluent discharge: Himmerfjärden sewage treatment plant (UWWTP) 30% of nitrogen input 2. Agriculture: 20% of area, use of fertilizers, 3 large farms in the area, other agriculture mostly extensive 3. Shipping: major shipping route to industrial town Södertälje and through locks to harbors in Lake Mälaren 4. Tourism: mainly swimming, recreational fishing and boating (summer residents and tourists); Swedish Allemannsrätta 5. Fisheries: mostly recreational 6. Industry: major industries in Södertälje, but discharges nowadays relatively small, but old contamination (mercury and organic pollutants); Astra Zeneca have their own sewage treatment plant; the output of medical substances is less than from Himmerfjärden UWWTP 7. Urbanization and housing: 3% of area; leads to waste discharge (UWWTP) and diffuse discharge from summer houses (see 1.) 8. Forestry: 65% of the area; probably minor impact 9. The island of Askö and its surrounding waters are a protected area (nature reserve). The marine part of the reserve was established in 2007, and is part of the Baltic Sea Protected Area (BSPA) Landsort-Hartsö-Askö. It is also a proposed Marine Protected area (MPA) 10. Aquaculture (hardly any in area)

a Swedish Allemannsrätt: each person’s right of access to the natural landscape. The Allemannsrätt allows you e.g. to collect wild berries and mushrooms or to pitch up your tent on non-cultivated ground (max. stay 48 h, no garbage left behind, if closer than 150 m to a house or cabin need to ask owner for permission). National Parks and Nature Protection Areas are usually exempted from Allemannsrätt, here any kind of overnight stay is prohibited.

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Fig. 6. The use of remote sensing as diagnostic tool for eutrophication. This diagram was prepared for Himmerfjärden combining the SPICOSA template ‘streamlining for a systems approach’ with the main impacts and human activities listed in Table 1, and the (then) recent work on bio-optics and remote sensing in Himmerfärden [after 37 revised]. Changes in impacts or human activities that are linked to eutrophication at a given functional level (starting from the bottom) also influence other levels and, therefore, may lead to changes on a different functional level.

Kd(490) algorithm was shown to be more robust than the Secchi depth algorithm when applied to other MERIS scenes. It was therefore decided that Kd(490) should be used as an optical indicator for eutrophication in the operational remote sensing system, keeping in mind that it is possible to derive Secchi depth reliably from it. During the SPICOSA stakeholder meetings, Kd(490) and chlorophyll maps from the operational remote sensing system were presented to the local stakeholder group as well as to possible end-users of the operational system. The relationship to Secchi depth was emphasized throughout meetings. The stakeholders showed a great interest in these maps, as they provided better spatial information than can be derived from single point measurements. Some of the stakeholders and researchers working in monitoring were also astonished about the spatial extent of the coastal influence (Fig. 4). Kd(490) relates to the Photosynthetic Active Radiation (PAR) diffuse attenuation, Kd(PAR) in the Baltic Sea [28,38]. This makes Kd(490) maps derived from satellite imagery applicable in a variety of ecological and oceanographic models that use light as one of the external drivers of the system. The MERIS-derived maps provide a cost-effective tool to spatially extend point measurements or existing ecological models of Himmerfjärden into areas that are less frequently monitored. The conceptual model shown in Fig. 6 was also helpful in the communication with the stakeholders as it shows on which functional level remote sensing can be applied as a diagnostic tool for eutrophication. The interpretation of the model is that changes in impacts or human activities linked to eutrophication at a given functional level (starting from the bottom) influence other levels and therefore may lead to changes on a different functional level.

(SAF) of SPICOSA proved to be a very useful tool as the progress in coastal remote sensing in Sweden could be presented to stakeholders and other end-user communities on a regular basis, who, in turn, provided feed-back to the system developers. The continuous feed-back from both scientific users as well as endusers of the operational remote sensing system was crucial to the further development of the operation system. Both users and endusers have primarily assisted in defining results and products that are useful for local stakeholders in agreement with existing fieldbased monitoring programs and the demands of the WFD. As a practical example related to monitoring, the initial CDOM product was changed to a new product, called humic absorbance, a widely used optical method for water-quality monitoring in Swedish lakes. The end-users also guided the system developers in the division of each area into different water bodies which will subsequently be used as the basis for the statistical analysis of the data in relation to the WFD status classification. Further positive outcomes of the frequent meetings with end-users were the improvement of communication with stakeholders and coastal zone managers in Himmerfjärden, as well as the possibility to develop academic and professional training in integrated coastal zone management as an inherent part of this process. As a further development of the work from the Himmerfjärden case study, a conceptual model was developed that explored how best to integrate remote sensing data in a physical-biological model of the Baltic Sea, shown in Fig. 7. In principle it is possible to use ocean color remote sensing and bio-optical measurements at two places in the CZFBL in SPICOSA: I. To sense changes in physical forcing (e.g. light regime or coastal run-off, subsequently affecting Secchi depth and Kd(490)). II. To sense changes in ecosystem response (e.g. changes in chlorophyll a-derived biomass).

3. Discussion Here, the use of remote sensing in integrated coastal zone management is evaluated. The Systems Approach Framework

Remote sensing products can be used as model input of ecosystem variables that may act as external drivers [39,40]. SPM summarizes the effect of river run-off, tidal regime and bottom

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Fig. 7. Conceptual model: The use of Kd(490) data (or Secchi depth as an alternative) as a proxy for light forcing and as input into a physical-biological model [modified from [50]] and map of chlorophyll a as an output from the model. Note that another possible input variable derived from remote sensing in the open Baltic Sea could be CDOM as it is the prime optical parameter determining the underwater light field.

substrates, and therefore may provide a synthesis of hydromorphological drivers of a coastal system [16]. It could therefore be used as a proxy to spatially extend ‘hydro-morphological elements’ where not measured explicitly In the Baltic Sea, the diffuse attenuation coefficient could be used as a proxy for ‘light’ as an external driver for the productivity, and could therefore act as a model input for light. Humic substances (CDOM) can also be used as indicators for terrestrial run-off and are inversely related to salinity [28,41]. CDOM may also be used as a proxy for light for the open Baltic Sea, since it is optically dominant [16], except during cyanobacteria bloom events. Alternatively, remote sensing products may be used for validating the model output of the system. Taking the SPICOSA CZFBL and the advances in coastal remote sensing based on MERIS into account it is possible to monitor the distribution of chlorophyll a as well as the Secchi depth (or the diffuse attenuation coefficient), and to use these as indicators for eutrophication. Such chlorophyll maps can also be used for analyzing time series, trends and ecosystem health [42,43]. Chlorophyll a maps as provided by the operational monitoring system could also be used to test the output of a bio-geochemical model as a proxy of phytoplankton biomass. CDOM maps derived from MERIS may be used as a proxy and to spatially extend information on ‘physical-chemical elements’ since colored dissolved organic matter is generally well correlated to DOM [44]. The study presented here, shows that MERIS provides us with a new tool to assess coastal systems from space. Indicators for eutrophication, e.g. chlorophyll a and Secchi depth (respectively Kd(490)), can be successfully derived from remote sensing data. However, it does also raise some questions, such as, could the

maps shown in Figs. 1, 4, 5 and 7 be used to relate to the HELCOM objective of water transparency restoration, for which Secchi depth is a good indicator [12]? There may be an opportunity for this. In addition, increased chlorophyll a concentrations have been identified as a ‘direct effect’ or ‘primary symptom’ for eutrophication, thus it is valid to use chlorophyll a as a monitoring indicator to assess eutrophication [44]. Remote sensing is one of the methods suggested for deriving chlorophyll a in time series and climatology [15], therefore this would be consistent with existing approaches. The methods developed here are highly relevant both for monitoring the ecological status of the Baltic Sea and for international water management treaties (e.g. the WFD, MSFD and the HELCOM Convention). The methods will contribute to an improved capacity to assess and predict the changing status and trends related to eutrophication. The derived products from ocean color sensors can provide a basis for better decision making in coastal management, e.g. in choosing investigation sites with contrasting water quality, taking local gradients into account and evaluating the monitoring sites synoptically [46]. The use of remote sensing as a monitoring and management tool within ICZM and WFD has been shown to work very well in several studies [46–48]. The strength of using remote sensing in integrated coastal zone management is that it can display complex issues in a visual format that is relatively easy to understand, providing a new window to look at the Baltic Sea ecosystem (Figs. 1 and 5). Hence, the information and knowledge gained from conventional monitoring programs can be considerably strengthened and improved by including remote sensing data [15]. The good spatial and

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temporal resolution provided by MERIS, offers a firm basis for using remote sensing as a complementary monitoring method in ICZM [33,46]. Remote sensing provides synoptic data over whole water basins as well as coastal areas, and in combination with conventional monitoring, one can get a more holistic view of what processes are occurring in any given coastal ecosystem. The operational remote sensing system presented here follows the EC recommendation on ICZM on providing information and data in a format that is accessible for decision makers, that is userfriendly and readily publicly available. Furthermore, the system covers the Swedish great lakes that are also partially part of the Baltic Sea catchment area. Furthermore, remote sensing data may provide ocean boundary conditions for coastal areas, and help establish the cause of violation of quality thresholds for certain indicators. The continuous measurements provided by remote sensing can help to monitor rapid changes in algal communities, and e.g. detect peaks of algal blooms that may be missed out by ship-borne monitoring methods [33]. If remote sensing and biooptical modeling are used together, satellite-derived water quality variables can indicate the impact from nutrients from land onto coastal water bodies covered by the WFD. Applications of remote sensing techniques are therefore significant.

4. Conclusions In general, the focus of data acquisition on natural systems has been mostly on the spatial and temporal distributions of substances e.g. in response to natural processes or human-induced impact studies. As shown here, remote sensing is a very useful tool to illustrate such distributions. The SPICOSA approach emphasizes the capacity to make numerical predictions of a system’s natural response. This requires a well-designed, efficient model approach that extracts and validates data that can serve as a proxy for tracking system functions. Ocean color remote sensing is a relatively new technique, and when validated and combined with ship-based conventional monitoring programs, can significantly improve levels of understanding of coastal ecosystems. Once validated and integrated, such techniques can result in global near real-time and continuous monitoring of coastal ecosystems. It may be anticipated that such a shift in observational techniques will be required in order to support current and future EU directives related to sustainable development of the coastal zone. Existing approaches in coastal management in Sweden do not make full use of bio-optics and remote sensing and the associated gains in terms of spatial coverage. Chlorophyll a, Secchi depth and CDOM can be used as proxies for some of the quality elements defined in the WFD. Chlorophyll a generally acts as a proxy for biomass and is one of the biological elements in the WFD [15,45]. SPM summarizes the effect of river run-off, tidal regime and bottom substrates, and therefore may provide a synthesis of hydro-morphological drivers of a coastal system. It could therefore be used as a proxy to spatially extend ‘hydro-morphological elements’ where not measured explicitly. The MERIS mission lasted for 10 years, providing us with a decade of information on coastal areas which will support followup analysis of water status classification according to the WFD. Furthermore, new robust Secchi depth and Kd(490) algorithms have recently been developed for optically complex waters [49] that can be readily implemented in operational remote sensing systems for the coast. The MERIS mission will be continued from approximately 2014 to 2023 via the Ocean Land Color Instrument (OLCI), an ocean color sensor similar to MERIS in its optical characteristics, which will be launched in on the Sentinel-3 satellite. Its mission will provide us with a long-term perspective regarding the evaluation of the effects of climate change on e.g.

algal bloom development or the browning of the Baltic Sea due to increased humic substances.

Acknowledgments This research was funded by the Swedish National Space Board, the European Space Agency and the FP7 projects SPICOSA and Waters as well as Baltic Ecosystem Adaptive Management (BEAM), Stockholm University’s Strategic Research Marine Environment Program. The Swedish National Space Board, the Swedish Environmental Protection Agency and The Office of Regional Planning Urban Transportation (RTK), Stockholm County Council, provided the main funding for the operational system. The authors are grateful to the end-user organizations participating in the project, for investing both time and money in the developments: Societies for Water Conservation for Mälaren, Vänern and Vättern, the southern Swedish River Basin District Authorities and SYVAB (Himmerfjärdsverket), Stockholm Vatten and Norrvatten. None of the mentioned funding bodies have requested the writing of this article. Special thanks to the coastal monitoring team at the Department of Systems Ecology for providing chlorophyll a data from the Swedish coastal monitoring program. Thanks to Paul Tett, Kevin Ruddick and Adam Krężel for their help and for inspirational discussions. Thanks to the SPICOSA SU science team – Ragnar Elmgren, Jacob Walve and Ulf Larsson – and for the constructive comments from the reviewers. References [1] Doerffer R, Sorensen K, Aiken J. MERIS potential for coastal zone application. International Journal of Remote Sensing 1999;20(9):1809–18. [2] Kratzer S, Brockmann C, Moore G. Using MERIS full resolution data (300 m spatial resolution) to monitor coastal waters—a case study from Himmerfjärden, a fjord-like bay in the north-western Baltic Sea. Remote Sensing of Environment 2008;112(5):2284–300. [3] Cui T, Zhang J, Groom S, Sun L, Smyth T, Sathyendranath S. Validation of MERIS ocean-color products in the Bohai Sea: a case study for turbid coastal waters. Remote Sensing of Environment 2010;114:2326–36. [4] Kononen K, Leppänen J-M. Patchiness, scales and controlling mechanisms of cyanobacterial blooms in the Baltic Sea: application of a multiscale research strategy. Monitoring algal blooms. New techniques for detecting large-scale environmental change. Heidelberg New York: Berlin: Springer-Verlag; 63–84. [5] HELCOM. Baltic facts and figures. Available from: 〈www.helcom.fi/environ ment2/nature/en_GB/facts/〉; 2012. [6] HELCOM Convention on the protection of the marine environment of the Baltic Sea area. Helsinki Convention. Available from: 〈http:/www.helcom.fi/ stc/files/Convention/convention1974.pdf〉; 1974. [7] HELCOM Convention on the protection of the marine environment of the Baltic Sea area. Helsinki Convention. Available from: 〈http:/www.helcom.fi/ stc/files/Convention/Conv1108.pdf〉; 1992. [8] EEC European Executive Council. Council Directive 91/271/EEC of 21 May 1991 concerning urban waste-water treatment; 1991. [9] EEC European Executive Council. Council Directive 91/676/EEC of 12 December 1991 concerning the protection of waters against pollution caused by nitrates from agricultural sources; 1991. [10] EC European Commission, 2000. Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy. Official Journal of the European Communities L327, 1. 22.12.2000; 2000. [11] CEC Commission of the European Communities. Recommendation of the European Parliament and of the Council of 30 May 2002 concerning the implementation of Integrated Coastal Zone Management in Europe (2002/413/ EC). Official Journal of the European Communities L148/24 6.6.2002; 2002. [12] HELCOM. The Baltic Sea Action Plan (BSAP). HELCOM Ministerial Meeting Poland; Krakow: 15 November 2007. Available from: 〈http:/www.helcom.fi/ stc/files/BSAP/BSAP_Final.pdf〉; 2007. [13] EC European Commission. Directive 2008/56/EC of the European Parliament and of the Council of 17 June 2008 establishing a framework for Community action in the field of marine environmental policy (Marine Strategy Framework Directive). Official Journal of the European Communities L164/19 25.06.2008; 2008. [14] Borja A, Elliott M, Carstensen J, Heiskanen AS, van de Bund W. Marine management: towards an integrated implementation of the European Marine Strategy Framework and the Water Framework Directives. Marine Pollution Bulletin 2010;60(12):2175–86.

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