Project Related Publications
ABSTRACTThe coastal zones of the Mediterranean are undergoing rapid development with growing and conflicting demands on the natural resources, and at the same time subject to often irreversible degradation of these resources and thus the very basis for development. Water resources and the related land use issues are a key element for the sustainable development of coastal regions. They illustrate the dependency of the usually dynamic and fast growing coastal areas on their resource catchment.
SMART (Sustainable Management of scarce resources in the coastal zone) is an INCO-MED project under the sixth framework program that brings together partners from Turkey, Lebanon, Jordan, Egypt, Tunisia, Italy, France, Portugal, and Austria, with case studies in each of the Mediterranean partner countries. The project explores methods and tools for long-term policy analysis and strategic decision support for integrated coastal development with special emphasis on water resources and land use.
The approach is based on a multi-sectoral integration of quantitative and qualitative analysis, combining advanced tools of quantitative systems engineering including GIS, remote sensing, and numerical simulation models, combined with methods of environmental, socio-economic and policy impact assessment using rule-based expert systems technology and interactive multi-criteria decision support methods. The underlying paradigm change leads from static spatial objects to complex, dynamic functional and interacting objects as the unit of analysis. Integrating GIS with dynamic, spatially distributed simulation models, expert systems, and explicit DSS tools advances the state of the art in spatial analysis beyond GIS towards new tools for sustainable development planning.
The main innovative elements of this project include the integration of advanced spatially distributed and dynamic numerical simulation and optimization tools with GIS and socio-economic elements through rule-based expert system technology for qualitative analysis; the explicit consideration of multiple criteria and conflicting objectives, uncertainty, and the necessary political trade-offs and adaptive strategies; the direct involvement of end users including the concerned public through the use, inter alia, of the Internet and the support of remote clients; the smooth integration of existing information resources and data through a distributed client-server architecture and a common framework of indicators for sustainable development; the integration of technical analysis with educational, awareness-building elements for a broad target audience, aiming at the empowerment of a broad range of actors and local stake holders. The direct integration in existing institutional structures including governmental, NGO, and academic institutions as well as the concerned citizen at large is designed to ensure the long-term sustainability of the project results. To provide the quantitative basis and feedback for any socio-economic and policy analysis, a set of readily available industry standard numerical simulation models are used to describe land use change and the water resources situation in each of the case study areas. The analytical tools are based on GIS technology and remote sensing data, cellular automata using a rule-based expert system, and classical water resources and hydrological models, based on the conservation laws (mass, momentum), using (partial) differential equations to describe dynamic water budgets in space. The integrated set of tools includes:
A hybrid expert system with embedded GIS functionality and spatial analysis and decision support extensions using a discrete multi-criteria approach; A river basin scale distributed water resources modeling system, WaterWare; A detailed 3D dynamic flow and transport modeling system, TELEMAC.
Together with the underlying GIS and remote sensing data the model system can describe any aspect of the water resources system including demand-supply patterns and water quality aspects. Driven by demographic change, changing land use patterns technological and economic change and thus the economics of water use and supply, scenarios of coastal zone development and resource management are developed, aggregated into a set of indicators, and subjected to a final discrete multi-criteria optimization step.
IntroductionIntegrated management of the coastal zone requires a balanced consideration of numerous aspects including both the socio-economic and physical, environmental domain. While this principle is well understood and published, it is rarely implemented in practice.
The scientific literature in the domain is voluminous, and often concentrating on the engineering aspects of the problem. The importance of the socio-economic components for a participatory policy and decision making process has often been overlooked. This process needs informed participants, actors or stake holders - this empowerment through information and the role of information for policy and decision making are important topics addressed in the Agenda 21, and related European policy documents and directives.
This calls for the smooth integration of quantitative tools based on applied systems analysis and information technology such as state-of-the art simulation and optimisation models and expert systems technology into the socio-political and economic framework of regional development planning and public policy with its uncertainties, qualitative criteria, and conflicting objectives.
The main innovative elements of such an integrated approach include:
SMART is based on a number of principles of Integrated Coastal Zone Management (COM(2000)547), and water resources management (2000/60/EC) in particular. These are:
Any approach to meet these principles must be inter- and multi-disciplinary, and in particular has to bring together quantitative numerical analysis as the basis for any rational resource and coastal zone management policies with the tools and methods of socio-economic research. Combining the rigor and intellectual discipline of quantitative analysis and numerical modelling with the flexibility and problem orientation of in part qualitative and semi-quantitative socio-economic analysis should result in a consistent, plausible, and practical contribution to sustainable development policies.
The approach rests on four main and iterative steps:
The Socio-economic frameworkIntegrated Coastal Zone management requires a broad, holistic perspective (COM(95)511, COM(2000)547, Post and Lundin, 1996). At the same time, water is clearly a key resource, especially in the coastal zone, and the river basin a central unit of assessment on the regional scale.
European environmental policies, as exemplified by the Water Framework Directive (WFD) (2000/60/EC), are increasingly oriented toward economic efficiency and the polluter pays principle. Extended by the principle of distributional equity, and the constraints of administrative, regulatory and enforcement efficiency, and general political feasibility, this provides a set of broad policy objectives that are equally applicable to the broader area of general resources management. This, in turn, is most dramatically at issue in the coastal zone. In the analysis, the socio-economic Part provides the driving forces, but also the valuation component translating the response of the environmental and resource system into the policy domain again. The main steps in the socio-economic analysis are:
Scenario analysis: simulation modellingTo provide the quantitative basis and feedback for any socio-economic and policy analysis, numerical simulation models are used to describe the effects of demographic, economic, technological, and land use change and the water resources situation. The models are based on GIS technology, cellular automata using a rule-based expert system, and classical water resources and hydrological models, based on the conservation laws (mass, momentum), using (partial) differential equations to describe dynamic water budgets in space. The tools include:
Policy oriented integrationThe integration of the socio-economic methods and the numerical models is accomplished in a two-stage process, using a combination of scenarios and assessment rules. The information exchange between the two levels is provided by policy oriented indicators.
The scenarios describe possible development strategies and policies (including external driving forces such as climate or demographics) in terms of, inter alia, land use change, investment in infrastructure, water allocation and pricing, water use technologies including treatment and recycling. These scenarios represent plausible futures, and explore their ranges in terms of relative changes from the baseline (status quo), using concepts such as business as usual, worst case, and a naively optimistic case. Between tem, they should cover the range of possibilities.
These development scenarios are then simulated with the numerical models. The resulting patterns and budgets of resource consumption and distribution such as water demand and supply are then analysed again in terms of their socio-economic impacts (monetary and social aggregate costs and benefits, environmental impacts). The resulting data are aggregated into policy-relevant indicators and information. Open and participatory decision making processes The final step in this approach is then to communicate these finding back to the key actors involved in the problems and possible solution strategies. Their response and reactions or preferences and trade-offs, trigger the next cycle in the policy and decision making process, by defining new scenarios for exploration.
The role of GIS and RS dataAll the above processes are spatially distributed, their elements can be georeferenced. However, socio-economic processes and data are linked to administrative units, whereas the physical system is structured by geomorphological criteria such as hydrological catchments, river networks, aquifers, ecosystems, or the coastal sub-littoral.
The role of the GIS in this context is obvious: on the one hand, it provides an organising framework for the data management, conversion from the different spatial reference units into each other, and basic spatial analysis tools, such as spatial interpolation and aggregation, overlay analysis, and many auxiliary functions such as the determination of watershed boundaries and river networks from elevation data.
Many of the basic data sets used are spatially distributed: land use and land cover, topography and coastal morphology including bathymetry, river networks and the drainage system. And main objects such as cities, industries, agricultural areas and in particular irrigation districts are well defined in space and have obvious spatial properties and constraints that define their behavioural repertoire.
On the other hand, the GIS and the topical map provides a powerful tool for visualisation, combining possibly abstract concepts with a familiar background, the map. This is a powerful tools for communication in any interactive information and decision support system. The integration of the basically static GIS, with the map and spatial objects as its main elements, and the dynamic simulation models with dynamic interaction and complex state transitions as the central elements, leads to a powerful instrument of spatial analysis that goes far beyond classical GIS both in its inherent dynamic and in the complexities of the processes represented (Fedra, 1996b).
To manage the GIS data together with the simulation models, a map server that is fully integrated in the distributed client-server architecture of the overall system, is used (Figure 2,3).
A similar example of a map server for coastal GIS is developed at The Centre for Environment and Development for the Arab Region and Europe (CEDARE) for PERSGA (The Regional Organisation for the Conservation of the Environment of the Red Sea and the Gulf of Aden, http://www.persga.org. The integration of various thematic data bases with the GIS layers build the basis for a range of applications in support of integrated coastal zone management (Figure 6,7)
The case studiesTo test the approach outlined above and its component models, SMART uses a set of case studies around the Mediterranean. The include:
Gediz River and the Izmir Coastal ZoneThe Gediz River Basin (Figure 4), neighbouring the city of Izmir and discharging into the outer bay, is characterized by water shortage and competition for water among mainly irrigation with a total command area of 110,000 ha versus the domestic and fast growing industrial demand in the coastal zone, and environmental pollution as well as recurrent droughts. Overall supply of water for various uses is currently approximately equal to the overall demand. Thus, water allocation for growing demands has to be optimized among various competing water uses under environmental as well as institutional, legal, social, and economic constraints. Izmir is the third largest city in the country and an important harbour along the Aegean. The Izmir metropolitan area, continuously growing, consumes a significant portion of the groundwater resources of the Gediz Basin.
The seaward fringe of the Gediz Delta is an important nature reserve and has recently been designated as a Ramsar site to protect rare bird species. Due to irrigation demands, the reserve suffers from water shortages. A second component of environmental demand is the water needed for waste conveyance to the sea, requiring some minimum flow. There is a good number of creeks that discharge directly into the inner Bay, causing significant pollution problems and flooding due to recent land use changes (primarily urbanization), which exerts considerable pressure on the water resource system in general.
The primary issues in the case study are water shortage, competing use, and high levels of pollution that are typical for the coastal zone and its rapid economic development. The linkage between the physical constraints and the institutional and policy shortcoming are one of the main topics. An optimization approach is required to solve problems of water shortage and competing uses of natural resources under physical, institutional, legal, social, and economic constraints.
Abu Kir Bay RegionThe Egyptian case study in SMART covers the Abu Kir Bay Region. The region is located on the Mediterranean Sea to the west of the Nile delta of Egypt. It includes important historic cities such as Rosetta, Abu Kir and Idku. It also includes a large lagoon (Lake Idku) as one of the less polluted lakes of the five northern lakes of Egypt, nourished by the Rosetta branch of the River Nile (average flow of about 4-5 billion m3 per year).
The Governorate of Alexandria has recently decided to upgrade environmental and tourist conditions along the coast. Extensive waterfront developments have been introduced only recently. Abu Kir is located overlooking the western side of historic Abu Kir Bay. It is also close to Lake Idku and historic sites of Rosetta city and Rosetta region, which includes Lake Idku and associated wetland. Lake Idku is situated about 30 km east of Alexandria. It is a shallow (1.0-1.5 m depth) brackish water lake with one connection to the Mediterranean at El Meadia. It has an area of about 125 km2. The lake receives water from three drains along the southern and eastern sides. Seawater is primarily affecting the western side of the lake near the outlet. After construction of the Aswan High Dam, the annual drainage in the lake has increased. This has caused an increase of the level of the lake and induced flow from the lake into the sea and the lake became less influenced by salt water from the sea.
Rosetta region has been suffering from various environmental problems, prone to worsen with continuing and in fact accelerating development: coastal erosion, land based pollution to water resources, urban encroachment in agricultural land, vulnerability to sea level rise. Problems include loss of biodiversity due to pollution and deterioration of soil conditions and water quality in the region.
Tripoli and the Batroun Coastal AreaThe case study deals with the City of Tripoli and the Batroun Coastal Area. The area stretches along the northern Lebanese coast covering Tripoli City to the north, the second largest in Lebanon, southward to the town of Batroun. The coastline length is about 30km, and the coastal zone width varies between 8-12km inland. The area typifies the Lebanese coast in consisting of a narrow plain followed inland by a series of foothills, plateau, then rising through steep slopes to the coastal mountain chain. It is crossed by a river (Abou Ali) passing in Tripoli and another minor one (El-Jawz) near Batroun, with intermittent streams, dendrite drainage and dry wadis. It is hot sub-humid at the coast becoming milder inland.
The major urban complex is Tripoli, with about 300,000 people in the city, which may add another 100,000 from the surroundings. It used to be a dominantly agricultural region, but the last three decades witnessed a rapid development of urban construction, including some industries, recreational activities and infrastructure, and power plants at the expense of agriculture. The urban/rural interface around Tripoli has changed dramatically with great losses in prime land and resources. The immediate coastal foothills are highly urbanized close to cities, but outside they are cultivated. In the Chekka stretch and just north of Batroun there are heavy industries, phosphoric acid, asbestos tiles/pipes and cement. This is among the highest polluted areas in Lebanon, where quarrying, water, soil and air pollution is very noticeable. Tourist pressure is a matter of concern in the area as it is typical of the Region, and there is a fairly dense road network for easy accessibility.
There is neither a well-developed sewage network, nor wastewater control, nor proper solid waste collection and/or disposal. A major problem is the seepage of pollutants, leachates, and chemicals into the ground water affecting its quality. Thus, often spring water is polluted, and water-related diseases, especially in the suburban and rural areas, are recurrent. Problems include soil erosion and siltation, forest fires, droughts and some difficult inaccessible terrain with rock falls and landslides, as well as coastal floods.
Gulf of AquabaJordan is a country with limited water resources where the per capita annual share of water is less than 200 m3. The total renewable water resources are about 940 million cubic meters compare to the total population of 5.0 million. These problems are of course most pronounced in the coastal region. The only coastal area in Jordan is the Gulf of Aqaba where the shoreline amounts to about 45 km. Water supply to Aqaba region are derived from the Red Sea Basin (5.0 MCM groundwater) and the adjacent Dissi aquifer system (20 MCM), supporting a population of 150,000 people.
Aqaba area has been declared a special zone as a duty free area in order to attract new investors in trade and industry. This development will increase demand for water for the growing population and future industrial activities. This development will lead to a potentially dramatic rise in water demand, but also wastewater generation. The current water consumption in the region is estimated 25 MCM where about 10 MCM goes to industrial purposes and 10 MCM for municipal purpose. Agriculture, street trees and parks receive only 3 MCM from fresh water and about 4.0 MCM treated wastewater.
Further industrial activities will have a negative impact on the coast of Aqaba. The total area is comparatively small, leading to a high concentration of economic activities along the coast and thus competition for space and addition to the competition for water. Also, the planned developments may be in conflict with each other and certainly with any development of tourism designed to exploit the unique marine life of the Gulf
HammametThe Tunisian coastline spans 1,300 km. Over the last two decades, a major shift of population growth, urbanization, industrialization and tourism towards the coastal zone could be observed. The emerging problems are typical, and usually involve a combination of rapid land use change, population growth driven to a large degree by migration from inland agricultural areas, depletion of water resources often accompanied by overexploitation of groundwater resources and consequent salt water intrusion in the immediate coastal zone, and pollution from unchecked economic development and insufficient waste and waste water management.
These development conflict with the parallel development of tourism, which depends on the same resource basis but also on a clean and attractive environment, inland and coastal areas. The Tunisian case study will analyse land use change as a major driving force as much as symptom of coastal zone management problems, and identify selected hot spots where the conflicts of land use, water resources, and pollution are most obvious. The Gulf of Hammamet (Figure 5) with its large tourist resorts like Monastir is a prototypical example of these conflicts.
The effect of institutional as well as regulatory and economic conditions of coastal zone development will be related to the patterns of land use change as the primary indicator of coastal zone development. The comparative analysis of locations along the entire Tunisian coastline, using remote sensing and GIS technology as the primary instruments, will identify selected hot spots of development problems (primary conflicts in land use, water resources allocation, and pollution) and for a detailed analysis with the dynamic water resources and spatial development models. Emphasis of the socio-economic analysis will be distributional effects of development, as well as the potential for policy instruments based on overall economic efficiency and the polluter pays principle. Implementation, administrative and regulatory efficiency, and general political acceptability are key issues to be analysed within the network of local stake holders and problem owners, including developers and tourism operators, agriculture, local municipalities, state institutions, and NGOs.
DiscussionCoastal zone development is complex, and by definition dynamic. At the same time, it is heavily influenced by the geomorphology of the land-sea interface, and the spatial distribution of activities and resources. While the latter suggest GIS as an appropriate tool, the formed calls for dynamic simulation models to capture the full behavioural repertoire of the system.
No single tool or model can capture the entire range of scales in space and time, and the fractal nature of processes that together define coastal zone development. They range from long-term socio-economic trends, that span decades, to tidal cycles, that span hours. So an obvious approach is to use several tools and methods, including GIS, together, nested, cascading, or loosely coupled within a consistent framework of concepts represented by indicators. This methodological flexibility raises questions of consistency and convergence, of errors introduced at the interfaces due to the necessary aggregation and dis-aggregation processes involved.
However, the price for increased precision is always a narrowing of the scope. From a policy and decision support point of view, the problem is not to find a best solution (which begs the questions who would define what best is supposed to mean in every case) but a better one. Evolution does not produce a single best answer, but a range of sufficiently good ones.
The integration of the different modelling tools is based on indicators. These are high-level policy oriented concepts, that are derived from the actual data and model results. The define the scenarios of socio-economic development, and link the basic chain of models: regional development, land use change, water resources, and coastal water quality. Finally, the model results are again summarised in terms of indicators and subjected to the multi-criteria assessment as the basis for the participation of stake holders and major actors.
From the methodological point of view, the integration of GIS and a range of dynamic simulation models within the indicator and DSS framework provides a powerful and flexible set of tools that go beyond what either of these methods can offer.
AcknowledgementsThe SMART project described in this paper is funded, in part, by the Commission of the European Communities under the INCO-MPC framework, Contract No. ICA-CT-2002-10006. The authors gratefull acknowledge the data and images provided by the project partners (http://www.ess.co.at/SMART/partners.html).
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