HELGOL,~NDER MEERESUNTERSUCHUNGEN Helgol~nder Meeresunters. 49, 617-632 (1995)
Marine systems analysis and modeling
K. F e d r a
Advanced Computer Applications (ACA), International Institute for Appfied Systems
Analysis (IIASA); Schlossplatz 1, A-2361 Laxenburg, Austria
ABSTRACT: O c e a n o g r a p h y and marine ecology have a considerable history in the use of computers for modeling both physical and ecological processes. With increasing stress on the marine environ- ment due to h u m a n activities such as fisheries and numerous forms of pollution, the analysis of marine problems must increasingly and jointly consider physical, ecological and socio-economic aspects in a broader systems framework that transcends more traditional disciplinary boundaries. This often introduces difficult-to-quantify, "soft" elements, such as values and perceptions, into formal analysis. Thus, the problem domain combines a solid foundation in the physical sciences, with strong e l e m e n t s of ecological, socio-economic and political considerations. At the same time, the domain is also characterized by both a very large volume of some data, and an extremely data- poor situation for other variables, as well as a very high d e g r e e of uncertainty, partly due to the temporal and spatial heterogeneity of the marine environment. Consequently, marine systems analysis and m a n a g e m e n t require tools that can integrate these diverse aspects into efficient information systems that can support research as well as planning and also policy- and decision- making processes. Supporting scientific research, as well as decision-making processes and the diverse groups and actors involved, requires better access and direct u n d e r s t a n d i n g of the informa- tion basis as well as easy-to-use, but powerful tools for analysis. A d v a n c e d information technology provides the tools to design and implement s m a r t software where, in a broad sense, the emphasis is on the m a n - m a c h i n e interface. Symbolic and analogous, graphical interaction, visual representa- tion of problems, integrated data sources, and built-in domain k n o w l e d g e can effectively support users of complex and complicated software systems. Integration, interaction, visualization and intelligence are key concepts that are discussed in detail, using an operational software e x a m p l e of a coastal water quahty model. The model comprises components of a geographical information and m a p p i n g system, data bases, dynamic simulation models, and an integrated expert system. An interactive graphical user interface, dynamic visualization of model results, and a h y p e r - t e x t - b a s e d help-and-explain system illustrate some of the features of n e w and powerful software tools for marine systems analysis and modeling.
I N T R O D U C T I O N
G r o w i n g c o n c e r n a b o u t t h e e n v i r o n m e n t , i n c l u d i n g o c e a n s , c o a s t a l w a t e r s a n d t h e i m p a c t s of h u m a n a c t i v i t i e s , i m m e d i a t e a s w e l l a s l o n g - t e r m , m a k e s t h e m o n i t o r i n g of t h e s t a t e of o u r e n v i r o n m e n t , t h e p r e d i c t i o n a n d a n a l y s i s of e n v i r o n m e n t a l i m p a c t s a n d risks, a n d t h e d e s i g n of p o l i c i e s a n d s t r a t e g i e s for t h e m a n a g e m e n t a n d p r o t e c t i o n of t h e e n v i r o n m e n t a t a s k of c o n s i d e r a b l e u r g e n c y a n d g l o b a l i m p o r t a n c e . E n v i r o n m e n t a l i n f o r m a t i o n s y s t e m s t h a t i n c l u d e s i m u l a t i o n m o d e l s a r e a c l a s s of p o w e r f u l , c o m p u t e r - b a s e d t o o l s t h a t c a n s u p p o r t t h i s t a s k , b o t h for s c i e n t i f i c r e s e a r c h a n d for p l a n n i n g a n d p o l i c y m a k i n g .
618 K. F e d r a
s o m e classics in the field see, for e x a m p l e , Riley et al. (1949); N i h o u l (1975); G o l d b e r g et al. (1977); K r e m e r & Nixon (1978); F a l c o n e r et al. (1989); F r a n s z et al. (1991).
H o w e v e r , most of t h e s e a p p r o a c h e s a r e d e s i g n e d to i m p r o v e scientific u n d e r s t a n d i n g of p h y s i c a l a n d biological processes, w i t h the n o t a b l e e x c e p t i o n of s o m e of the fisheries m o d e l s that h a v e obvious m a n a g e m e n t i m p l i c a t i o n s (e.g. A n d e r s e n & Ursin, 1977). O t h e r m a n a g e m e n t - o r i e n t e d a n d m o d e l - b a s e d studies of m a r i n e s y s t e m s i n c l u d e the RAND C o r p o r a t i o n classic on the O o s t e r s c h e l d e (Bigelow et al., 1977) or the r e c e n t s t u d y of the North S e a M A N S , M a n a g e m e n t A n a l y s i s N o r t h S e a ( A n o n y m o u s 1988; 1989; Klomp, 1990). Here, as w e l l as in a n u m b e r of similar projects i n c l u d i n g models, t h e e m p h a s i s is on e n v i r o n m e n t a l a n d r e s o u r c e m a n a g e m e n t issues, on decision s u p p o r t r a t h e r t h a n p r i m a r i l y scientific progress.
A d d r e s s i n g m a n a g e m e n t issues, a n d p l a c i n g the p h y s i c a l a n d e c o l o g i c a l p h e n o m e n a into the b r o a d e r f r a m e w o r k of t e c h n o l o g i c a l a n d s o c i o - e c o n o m i c s y s t e m s also involves different a u d i e n c e s that i n c l u d e specialists from m a n y areas, p u b l i c officials, a n d the g e n e r a l public. This i m p l i c a t e s different l a n g u a g e s a n d traditions t h a t often m a k e c o m m u n i c a t i o n difficult. A n i m p o r t a n t f e a t u r e of information systems is to p r o v i d e a c o m m o n information basis, b u t also a c o m m o n l a n g u a g e for a d i v e r s e g r o u p of users, w h i c h could include, for e x a m p l e , m a r i n e biologists, r e g i o n a l p l a n n e r s , s a n i t a r y e n g i n e e r s , fisheries m a n a g e r s , p u b l i c officials, a n d e n v i r o n m e n t a l activists.
E N V I R O N M E N T A L I N F O R M A T I O N SYSTEMS
A l a r g e a m o u n t of formal, m a t h e m a t i c a l a n d c o m p u t a t i o n a l m e t h o d s h a v e b e e n d e v e l o p e d for e n v i r o n m e n t a l a p p l i c a t i o n s , i n c l u d i n g the a r e a of p h y s i c a l a n d b i o l o g i c a l o c e a n o g r a p h y . T h e y r a n g e from r e s e a r c h - o r i e n t e d tools that a d v a n c e our u n d e r s t a n d i n g of c o m p l e x s y s t e m s a n d p h e n o m e n a , to v e r y p r a c t i c a l tools for specific m a n a g e m e n t tasks.
M a n y c o m p u t e r - b a s e d m o d e l s a n d m e t h o d s are p o t e n t i a l l y useful, a n d not only for their d e v e l o p e r s . H o w e v e r , to turn a p o t e n t i a l l y useful m e t h o d into one a c t u a l l y u s e d b y a b r o a d e r g r o u p of users, r e q u i r e s a n u m b e r of s p e c i a l f e a t u r e s as w e l l as a n a p p r o a c h t h a t t a k e s p s y c h o l o g i c a l a n d institutional a s p e c t s as w e l l as scientific a n d t e c h n i c a l o n e s into account. This, in particular, is i m p o r t a n t in the a r e a of e n v i r o n m e n t a l i m p a c t a s s e s s m e n t , p l a n n i n g a n d m a n a g e m e n t , w h e r e p h y s i c a l a n d e n g i n e e r i n g c o n s i d e r a t i o n s n e e d to b e c o m b i n e d w i t h ecological a n d u l t i m a t e l y s o c i o - e c o n o m i c a s p e c t s for a n i n t e g r a t e d a s s e s s m e n t , ultimately, the s u p p o r t of d e c i s i o n - m a k i n g p r o c e s s e s .
The a v a i l a b i l i t y of a f f o r d a b l e c o m p u t e r s , as w e l l as n e w t e c h n o l o g i e s s u c h as e x p e r t systems, g e o g r a p h i c a l i n f o r m a t i o n systems, or d y n a m i c c o m p u t e r graphics, n o w m a k e it p o s s i b l e for powerful, accessible, a n d e a s y - t o - u s e i n f o r m a t i o n a n d d e c i s i o n s u p p o r t sys- t e m s for e n v i r o n m e n t a l r e s e a r c h , p l a n n i n g , m a n a g e m e n t , a n d i m p a c t a s s e s s m e n t to b e b u i l t ( F e d r a & Loucks, 1985; Loucks & F e d r a , 1987). T h e s e s y s t e m s a r e d e s i g n e d to p r o v i d e scientists, p l a n n e r s a n d p o l i c y m a k e r s w i t h direct a n d i n t e r a c t i v e a c c e s s to a l a r g e v o l u m e of information in c o m b i n a t i o n w i t h m e t h o d s of scientific a n a l y s i s .
Basic c o m p o n e n t s of t h e s e e n v i r o n m e n t a l software s y s t e m s i n c l u d e :
M a r i n e systems analysis a n d m o d e l i n g 619
infrastructure, resources, site-specific information (e.g. cities, w a s t e - w a t e r t r e a t m e n t plants) as well as p r o v i d i n g tools for spatial analysis;
9 Data Bases, c o n t a i n i n g n o n - s p a t i a l data such as eco-physiological data on i n d i v i d u a l species, or p a r a m e t e r s of h a z a r d o u s chemicals;
9 K n o w l e d g e Bases, r e p r e s e n t i n g qualitative (symbolic) k n o w l e d g e a b o u t the p r o b l e m domain, that allow logical d e d u c t i o n s to be m a d e ;
9
Simulation and Optimization Models,
r e p r e s e n t i n g process-oriented n u m e r i c a l a n d algorithmic a s s e s s m e n t tools;9
Graphical User Interface,
i n t e g r a t i n g the a b o v e into one c o h e r e n t system a n d provid- ing the user with interactive access a n d a high d e g r e e of d y n a m i c visualization.C o m p u t e r b a s e d tools that are easy to use, e q u i p p e d with a friendly user interface, use p r o b l e m - a d e q u a t e r e p r e s e n t a t i o n formats a n d a high d e g r e e of visualization, custo- m i z e d for a n i n s t i t u t i o n a n d its specific view of problems, a n d that are d e v e l o p e d in close collaboration with the e n d user, stand a b e t t e r c h a n c e of b e i n g u s e d t h a n tools that are b a s e d on "only" good science. Good science is a necessary, b u t certainly not a sufficient condition for a useful a n d u s a b l e e n v i r o n m e n t a l information a n d decision support system. A d v a n c e d i n f o r m a t i o n t e c h n o l o g y provides the tools to d e s i g n a n d i m p l e m e n t s m a r t software where, in a b r o a d sense, the e m p h a s i s is on the m a n - m a c h i n e interface (Fedra, 1991). Integration, i n t e r a c t i o n a n d visualization are three k e y concepts in e n v i r o n m e n t a l i n f o r m a t i o n systems (Fedra, 1990).
I n t e g r a t i o n implies that in a n y given software system for real-world applications, more t h a n o n e p r o b l e m r e p r e s e n t a t i o n form or model, several sources of i n f o r m a t i o n or data bases, a n d a multi-faceted, p r o b l e m - o r i e n t e d user interface o u g h t to be c o m b i n e d within a c o m m o n framework to provide a useful a n d realistic information base. Integra- tion also m e a n s that tools such as expert systems c o m p o n e n t s c a n be e m b e d d e d in, for example, s i m u l a t i o n models a n d user interfaces in general, p r o v i d i n g the m e a n s for smart systems behaviour. The i n c r e a s i n g complexity of such composite tools, in turn, requires a w e l l - s t r u c t u r e d a n d m o d u l a r approach supported by technological d e v e l o p m e n t s such as powerful w o r k s t a t i o n s s u p p o r t i n g b i t - m a p p e d colour graphics a n d cost-effective high- v o l u m e mass storage, d i s t r i b u t e d c o m p u t i n g a n d n e t w o r k i n g support, or o b j e c t - o r i e n t e d software.
Interaction is a c e n t r a l feature of a n y effective m a n - m a c h i n e system: a real-time dialogue allows the u s e r to define a n d explore a p r o b l e m i n c r e m e n t a l l y in r e s p o n s e to i m m e d i a t e a n s w e r s from the system; fast a n d powerful systems with m o d e r n processor technology can offer the possibility to simulate d y n a m i c processes with a n i m a t e d output, a n d they c a n provide a h i g h d e g r e e of r e s p o n s i v e n e s s that is essential for m a i n t a i n i n g a successful dialogue a n d direct control over the software. Obviously, r a w c o m p u t e r power, b u t also the availability of appropriate i n p u t a n d o u t p u t devices, such as h i g h - r e s o l u t i o n colour screens or m o u s e pointers, are key r e q u i r e m e n t s here.
620 K. Fedra
A n a p p l i c a t i o n e x a m p l e
To illustrate the ideas i n t r o d u c e d above, a n application to coastal w a t e r quality m o d e l i n g is p r e s e n t e d . The system was d e v e l o p e d by IIASA's A d v a n c e d C o m p u t e r A p p l i c a t i o n s Project, i n collaboration with Delft Hydraulics, who c o n t r i b u t e d the basic n u m e r i c a l models. T h e system was i m p l e m e n t e d for a n u m b e r of locations in the Irish Sea, with a case study of S w a n s e a Bay. T h e S w a n s e a Bay area is heavily i n d u s t r i a l i z e d , l e a d i n g to w a t e r q u a h t y problems not only from domestic w a s t e w a t e r a n d s l u d g e with o r g a n i c material, BOD, a n d coliform bacteria, b u t also from several i n d u s t r i a l sources c o n t a i n i n g h e a v y metals (Collins et al., 1980). As such, it is r e p r e s e n t a t i v e of n u m e r o u s similar coastal areas suffering from various levels of pollution all over the world.
Recent applications of simulation m o d e l s in this field include, for e x a m p l e , Lewis & Riddle (1989) a n d Krohn et al. (1991). Mates & S c h e i n b e r g (1991) discuss a m o d e l with e m p h a s i s on r e c r e a t i o n a l activities, a n d Barnes (1988) looks at n o n - p o i n t sources a n d a cartographic approach. A food chain m o d e l for PCB a c c u m u l a t i o n is p r e s e n t e d by C o n n o l l y (1991), a n d Reed et al. (1989) discuss a complex model system, n a m e l y the N a t u r a l Resource D a m a g e A s s e s s m e n t M o d e l System for Coastal a n d M a r i n e E n v i r o n - m e n t s that is primarily o r i e n t e d towards accidental spills. Economic aspects in the case of effluent charges a n d chlorine residuals from the forest i n d u s t r y p o l l u t i n g the Baltic Sea are c o n s i d e r e d by H u l t k r a n t z (1991).
T h e m o d e l system for S w a n s e a Bay simulates the fate a n d d i s t r i b u t i o n of various types of pollutants, such as conservative tracers, BOD, or coliform b a c t e r i a from o n e or several outfalls or off-shore d u m p i n g locations. The system includes:
9 a data b a s e of these major sources of pollution, e.g. w a s t e w a t e r t r e a t m e n t p l a n t s a n d outfall pipelines, l i n k e d to
9 a g e o g r a p h i c a l i n f o r m a t i o n system (GIS) c o m p o n e n t that can m a n a g e spatial data, such as l a n d - u s e information or b a t h y m e t r y , as well as observational data. such as flows tidal records, or w a t e r quality m e a s u r e m e n t s ;
9 a n i n t e r a c t i v e a n d graphical interface to m o d e l scenario editors as well as for r u n n i n g the m o d e l s visualizing the d y n a m i c m o d e l output;
9 coupled to the scenario editors, a n e m b e d d e d expert system for scenario e d i t i n g a n d p a r a m e t e r estimation; a n d as a post-processor of m o d e l results, a n e x p e r t system for i m p a c t a s s e s s m e n t ;
9 coupled with the expert system's rule b a s e as well as the editor f u n c t i o n s a n d the overall help a n d e x p l a i n functions, a h y p e r t e x t system for additional t e x t u a l informa- tion.
T h e basic modules of the system are s h o w n in F i g u r e 1
T h e s i m u l a t i o n m o d e l s
M a r i n e systems analysis a n d m o d e l i n g
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For the purpose of m o d e h n g both near-field a n d far-field dispersion r e s u l t i n g from the c o n t i n u o u s release of more or less persistent s u b s t a n c e s a particle-tracking m o d e l (DELPAR) a n d a g e n e r a l finite difference w a t e r quality model (DELWAQ) were coupled. The finite difference m o d e l uses the same grid as the h y d r o d y n a m i c model, a n d uses the flowfield g e n e r a t e d by the h y d r o d y n a m i c m o d e l (Fig. 2). For the initial, s u b g r i d stage of dispersion m the vicinity of pollution sources (outfalls), a particle-tracking m o d e l was i m p l e m e n t e d . This p a r t i c l e - t r a c k i n g m o d e l e n a b l e s high sub-grid resolution a n d in- corporates i m p o r t a n t p h e n o m e n a for n e a r - f i e l d dispersion exphcitly, like vertical velocity gradients a n d w i n d effects.
The particle-tracking m o d e l a s s u m e s that c o n c e n t r a t i o n s can be s e e n as a n u m b e r of mass particles per v o l u m e . T h e mass particles are c o n s i d e r e d to be s u b j e c t to B r o w n i a n m o v e m e n t a n d small-scale t u r b u l e n c e s , b u t also to horizontal transport b y the current. T h e model computes the e x p e c t e d location of each of several t h o u s a n d s of particles a n d derives c o n c e n t r a t i o n v a l u e s (contours) from their locations.
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M a r i n e systems analysis a n d m o d e l i n g 623
dispersion coefficient approach u s e d for other models. For this reason, the user is r e q u i r e d to provide the model with the p a r a m e t e r s of a diffusion formula of the type D =
at b.
From basic calculus a n d stochastic limit t h e o r e m s it can b e s h o w n that the r a n d o m step size is proportional to the s q u a r e root of D 9 A t, w h e r e D is the diffusion coefficient a n d ~ t is the time step of the simulation.
Both water quality models a n d their calibration for a case study of S w a n s e a Bay are described in Delft Hydraulics (1990).
I n t e g r a t i o n a n d u s e r i n t e r f a c e s
A complex suite of models, like the h y d r o d y n a m i c model a n d the two w a t e r quality models, are powerful a n d sophisticated tools that require s u b s t a n t i a l user expertise for the p r e p a r a t i o n of i n p u t data files, r u n n i n g of the actual code, a n d the post-processing a n d i n t e r p r e t a t i o n of the very large a m o u n t of n u m e r i c a l results g e n e r a t e d e v e n b y a single model run.
Building t h e m into a p r o b l e m - o r i e n t e d framework, with a user-friendly interface, allows a more e x p e r i m e n t a l use of the model. A user c a n c o n c e n t r a t e on the analysis, on the comparative e v a l u a t i o n of alternatives, both in terms of the d e s i g n a n d decision variables such as outfall locations a n d characteristics, or model parameters. Patterns a n d trends over time, in space, b u t also in the r e l a t i o n s h i p of d r i v i n g variables a n d systems responses can b e identified in this interactive a n d graphical approach.
The d y n a m i c a n d visual r e p r e s e n t a t i o n of m o d e l results allows the user to develop a n intuitive u n d e r s t a n d i n g of complex, spatially distributed a n d d y n a m i c systems behaviour. T h e visualization is not only helpful in c o m m u n i c a t i n g with a n o n - t e c h n i c a l a u d i e n c e : the high b a n d w i d t h of the d y n a m i c graphics e n a b l e s a user to scan a very large a m o u n t of i n f o r m a t i o n that w o u l d be clearly i n c o m p r e h e n s i b l e in a n u m e r i c a l , i.e. tabular, format. Also, m a n y b e h a v i o u r a l features of a model, a n d e v e n errors, m a y only b e c o m e obvious t h r o u g h the use of a m u l t i t u d e of r e p r e s e n t a t i o n forms a n d display styles. In the Wales model, the p r i m a r y display style is c o n s t r a i n e d b y the two d i m e n s i o n a l n a t u r e of the model: c o n c e n t r a t i o n fields are plotted over a m a p of the area (Fig. 3). As a d d e d features, b o t h the m o d e l grid a n d the flow field ( r e p r e s e n t e d by small vectors i n d i c a t i n g m a g n i t u d e a n d direction of flow) c a n b e displayed. Different colour choices, a n d the ability to interactively t u n e the graphical i n t e r p r e t a t i o n of the n u m b e r s g e n e r - ated, i.e. stretch the contrast along a u s e r - d e f i n e d r a n g e of the c o n c e n t r a t i o n f r e q u e n c y distribution, allow a b r o a d r a n g e of display options. Z o o m i n g into the m a p provides h i g h e r resolution for s u b - a r e a s (Fig. 4).
In addition to the a n i m a t e d c o n c e n t r a t i o n field, the user c a n define o b s e r v a t i o n points a n d g e n e r a t e g r a p h s of c o n c e n t r a t i o n over time for these locations.
Finally, the c o n c e n t r a t i o n field c a n also b e d i s p l a y e d in a p s e u d o 3D graph, w h e r e the functional v a l u e over each grid cell is d i s p l a y e d i n the vertical (Fig. 5).
The d y n a m i c m o d e l allows the user to simulate specific scenarios, i.e. sets of d e s i g n variables a n d a s s u m p t i o n s for m o d e l p a r a m e t e r s a n d inputs. A p r i m a r y d e s i g n v a r i a b l e is the location a n d n a t u r e of the outfalls simulated. A n o t h e r choice is that of the s u b s t a n c e simulated, e.g. a conservative tracer, BOD, or coliform bacteria.
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628 K. F e d r a
full tidal cycle. T h e h y d r o d y n a m i c scenarios are p r e c o m p u t e d with a two d i m e n s i o n a l , vertically a v e r a g e d h y d r o d y n a m i c simulation m o d e l TRISULA 2D (Delft Hydraulics, 1990). T h e u s e r can also set a p r e v a i l i n g w i n d direction and w i n d s p e e d that will i n f l u e n c e the p r e c o m p u t e d flow fields. Finally, the user can choose t h e n u m b e r of particles to be u s e d in the particle model, w h i c h allows an optimal c h o i c e b e t w e e n
" p r e c i s i o n " or s m o o t h n e s s of the results a n d the s p e e d of the model.
At a s e c o n d level, the " e x p e r t " l e v e l of the u s e r interface, additional m o d e l p a r a m e - ters can b e modified. At the n o r m a l u s e r interface level, default v a l u e s a r e used. To calibrate the m o d e l h o w e v e r , a m o d i f i c a t i o n of m o d e l p a r a m e t e r s such as the w i n d i n f l u e n c e p a r a m e t e r , bottom r o u g h n e s s length, or the coefficients u s e d to r e p r e s e n t diffusion as a function of time in the particle tracking a p p r o a c h (Fig. 6).
At this level, a r u l e - b a s e d e x p e r t system h e l p s to set t h e s e p a r a m e t e r s , for e x a m p l e , w h e n c a l i b r a t i n g the m o d e l a g a i n s t o b s e r v a t i o n data. T h e e x p e r t system u s e d , its syntax and functionality, as well as an a p p l i c a t i o n e x a m p l e in w a t e r r e s o u r c e s p l a n n i n g and e n v i r o n m e n t a l i m p a c t a s s e s s m e n t are d e s c r i b e d in F e d r a et al. (1991). T h e rules of the system r e p r e s e n t the e x p e r i e n c e of o n e or s e v e r a l m o d e l e r s i n t i m a t e l y f a m i l i a r with the c o d e and its b e h a v i o u r , but also the n a t u r e of the location or specific e l e m e n t s in the systems behaviour. For e x a m p l e , o b s e r v e d d e v i a t i o n s of p e a k v a l u e or the s p r e a d of the pollutant, d e v i a t i o n s r e l a t e d to t h e w i n d direction etc., can b e used to g u i d e the u s e r in a d j u s t i n g the r e s p e c t i v e p a r a m e t e r s .
F r o m s i m u l a t i o n to d e c i s i o n s u p p o r t
T h e basic m o d e of o p e r a t i o n of the system is scenario analysis. H o w e v e r , to turn the system into a useful tool for the e v a l u a t i o n of a l t e r n a t i v e outfall scenarios in t e r m s of their e n v i r o n m e n t a l c o n s e q u e n c e s , the u s e r m u s t b e p r o v i d e d with additional i n f o r m a t i o n and in particular, w i t h e c o n o m i c and p o l i c y - r e l a t e d criteria (Fedra, 1985). T h e s e m u s t include. for the outfall scenario, the cost of a g i v e n s c h e m e in terms of i n v e s t m e n t , operations, m a i n t e n a n c e , and r e p l a c e m e n t costs. At l e a s t a first a p p r o x i m a t i o n of the costs for a t r e a t m e n t plant can be e s t i m a t e d from, for e x a m p l e , the p o p u l a t i o n served, t h e a m o u n t of t r a d e waste, the l e v e l of treatment, a n d the location (distance from the plant) of the outfall.
T h e e n v i r o n m e n t a l impact, on t h e o t h e r h a n d can b e described, for e x a m p l e , in t e r m s of the a r e a a b o v e a g i v e n w a t e r quality standard, the d e g r e e a n d d u r a t i o n of the violation, or the a v e r a g e c o n c e n t r a t i o n o v e r time in a g i v e n sensitive a r e a such as the i m m e d i a t e shoreline,
T h e s e a d d i t i o n a l descriptors or criteria for a g i v e n h y d r o d y n a m i c r e f e r e n c e s c e n a n o or a r a n g e of typical h y d r o d y n a m i c scenarios p r o v i d e the basis for a multi-criteria e v a l u a t i o n of cost criteria versus e n v i r o n m e n t a l i m p a c t s a n d c o m p h a n c e w i t h s t a n d a r d s and r e g u l a t i o n s (Fig. 7).
T h e s a m e e m b e d d e d e x p e r t s y s t e m u s e d for p a r a m e t e r e s t i m a t i o n a n d t h e c o n s i s t e n t definition of scenarios can also b e u s e d in t h e i n t e r p r e t a t i o n of t h e m o d e l results, for e x a m p l e to assess c o m p h a n c e with w a t e r quality standards. C o m p h a n c e w i t h s t a n d a r d s c a n c o n v e n i e n t l y b e e x p r e s s e d as a rule of t h e following e q u a t i o n :
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629
T h e r u l e - b a s e d e x p e r t system can also use p e r c e p t i o n s of w a t e r quality (in t e r m s of colour, foam, a l g a e on the beach, smell, etc.) to g e n e r a t e additional, q u a l i t a t i v e criteria for the a s s e s s m e n t of a scenario. Finally, the e x p e r t system can be u s e d to perform a m o r e c o m p l e x and c o m p r e h e n s i v e i m p a c t a s s e s s m e n t at the c h o s e n s c r e e n i n g level, b a s e d on the c o m p u t e d pollutant c o n c e n t r a t i o n s (Fedra et al., 1991).
D I S C U S S I O N
Built a r o u n d one or more c o u p l e d models, n u m e r i c a l simulation m o d e l s or rule- driven i n f e r e n c e models, the a b o v e e x a m p l e features:
9 an interactive, m e n u - d r i v e n user i n t e r f a c e that g u i d e s the user with p r o m p t and e x p l a n a t o r y m e s s a g e s t h r o u g h the application. T h e c o m p u t e r assists the u s e r in its p r o p e r use; no c o m p u t e r e x p e r i e n c e is r e q u i r e d to u s e this tool;
9 d y n a m i c colour graphics for the m o d e l output a n d a symbolic r e p r e s e n t a t i o n of m a j o r p r o b l e m c o m p o n e n t s that allow e a s y a n d i m m e d i a t e u n d e r s t a n d i n g of basic p a t t e r n s a n d relationships. Rather than e m p h a s i z i n g the n u m e r i c a l results, symbolic r e p r e s e n t a - tions a n d the visualization of c o m p l e x patterns, in t i m e a n d space, support an intuitive u n d e r s t a n d i n g of the b e h a v i o u r of c o m p l e x systems:
9 the c o u p l i n g with o n e or s e v e r a l d a t a b a s e s that p r o v i d e the m o d e l s with n e c e s s a r y i n p u t information. T h e user's choice or definition of a specific scenario can be e x p r e s s e d in an a g g r e g a t e d a n d symbolic, p r o b l e m - o r i e n t e d m a n n e r , without c o n c e r n for t h e t e c h n i c a l details of the c o m p u t e r i m p l e m e n t a t i o n ;
9 e m b e d d e d AI components, such as specific k n o w l e d g e bases, allow u s e r specltlcatlons in a l l o w a b l e r a n g e s to b e c h e c k e d a n d constrained, thus e n s u r i n g the c o n s i s t e n c y of an i n t e r a c t i v e l y d e f i n e d scenario.
630 K, Fedra
error-prone tasks of data file preparation, the r o u t i n e of model runs, a n d f i n a l l y from the i n t e r p r e t a t i o n a n d t r a n s l a t i o n of n u m e r i c a l results into m e a n i n g f u l terms t h a t are ade- q u a t e to the problem. This not only allows the user to employ the models m o r e freely in a n e x p e r i m e n t a l a n d i n t e r e s t i n g way, it also allows the analyst to c o n c e n t r a t e on the more i m p o r t a n t tasks they c a n do best, i.e. the r e c o g n i t i o n of e m e r g i n g patterns, t h e compara- tive e v a l u a t i o n of complex alternatives, a n d the entire institutional a s p e c t s of a n y e n v i r o n m e n t a l i m p a c t a s s e s s m e n t rather t h a n its technicalities.
It is, however, i m p o r t a n t to recognize that there is a price to be paid for the ease of use of such systems: not only are t h e y more e x p e n s i v e to b u i l d - after all, t h e i n f o r m a t i o n that m a k e s t h e m smart has to b e compiled a n d i n c l u d e d at some stage - t h e y are also m u c h less flexible t h a n their more conventional, g e n e r a l - p u r p o s e siblings. O n l y by restricting the r a n g e of applications c a n more application*specific k n o w l e d g e b e built into the systems a n d thus m a k e t h e m a p p e a r smart. There is no such t h i n g as the g e n e r a l - p u r p o s e p r o b l e m solver, or a g e n e r i c m o d e l or decision support system that is easy to use. Mastery of a p r o b l e m area comes only at the price of n a r r o w specialization.
Nevertheless, or m a y b e just b e c a u s e of these restrictions, the a b o v e e x a m p l e s illustrate that c o m p u t e r - b a s e d m e t h o d s c a n b e powerful tools to support m a r i n e systems analysis a n d m o d e l i n g . However, it is i m p o r t a n t to realize w h a t their a c t u a l role a n d limitations are.
Certainly the expert systems approach, or a n y c o m p u t e r i z e d decision s u p p o r t system for that matter, is n o t a r e p l a c e m e n t for the h u m a n expert in such a c o m p l e x p r o b l e m d o m a i n ; it still requires a k n o w l e d g e a b l e a n d responsible person to u s e it, to i n t e r p r e t a n d apply the results, w h e t h e r for research purposes or in the e n v i r o n m e n t a l p l a n n i n g a n d d e c i s i o n - m a k i n g process. However, the system will take care of the m o r e m u n d a n e tasks of data h a n d l i n g , freeing the a n a l y s t to c o n c e n t r a t e on the real p r o b l e m s that r e q u i r e h u m a n creativity, which is s o m e w h a t difficult to b u i l d into c o m p u t e r s .
Information a n d d e c i s i o n - s u p p o r t systems, w h e t h e r they are expert s y s t e m s or b a s e d on simulation or optimization models, organize the p l a n n i n g or d e c i s i o n - m a k i n g process; they provide structure, e n s u r e c o m p l e t e n e s s , a n d m a y e v e n ascertain plausibility. It is the easy-to-use "smart" interface, the fast a n d efficient operation, a n d the a p p a r e n t intel- l i g e n c e of the p r o g r a m s that m a k e s t h e m attractive. Based on the o r g a n i z e d collection of e x p e r i e n c e of n u m e r o u s experts, i n t e r n a t i o n a l literature b u t also on v a r i o u s g u i d e l i n e s . regulations, a n d e n v i r o n m e n t a l law, a systems k n o w l e d g e base, with or w i t h o u t one or more n u m e r i c a l m o d e l s i n its core, m a y i n d e e d offer i n t e l l i g e n t advice to a n y i n d i v i d u a l user.
The same holds true for the s i m u l a t i o n models: by i n t e g r a t i n g d a t a bases, GIS c o m p o n e n t s , a n d e m b e d d e d AI technology, they are easy a n d efficient to use. T h e y allow the analyst to test n u m e r o u s assumptions, r u n multiple scenarios u n d e r v a r y i n g a s s u m p - tions, a n d to explore the problem. Similar ideas of i d e n t i f y i n g a n d c o m p a r i n g several alternative m o d e l s for m a r i n e pelagic foodwebs were p r e s e n t e d more t h a n t e n years ago (Fedra, 1981); w h a t w a s t h e n a nice idea is t e c h n i c a l reality now.
M a r i n e s y s t e m s a n a l y s i s a n d m o d e l i n g 631 h a s o b v i o u s l i m i t a t i o n s . H o w e v e r , f o r e c a s t i n g r e s u l t s m u s t i n c l u d e t h e u n c e r t a i n t y of t h e e s t i m a t e a s p a r t of t h e i n f o r m a t i o n p r o v i d e d , a s a n i m p o r t a n t a s p e c t for t h e i r f u r t h e r u s e , i.e. d e c i s i o n m a k i n g .
T h e i n t e r a c t i v e a p p r o a c h , t h e i n t e g r a t i o n of t h e m o d e l s w i t h t h e n e c e s s a r y d a t a b a s e s , a n d t h e v i s u a l i z a t i o n of r e s u l t s i n f o r m a t s t h a t a r e i n t u i t i v e l y u n d e r s t a n d a b l e m a k e t h e m a t t r a c t i v e tools. By r e l y i n g o n s y m b o l i c r e p r e s e n t a t i o n a n d a m e n u - d r i v e n u s e r d i a l o g u e t h a t u s e s t h e m a c h i n e n o t o n l y to p e r f o r m t h e n e c e s s a r y i n f o r m a t i o n p r o c e s s i n g t a s k s b u t at t h e s a m e t i m e to g u i d e a n d a s s i s t t h e u s e r i n h i s a n a l y s i s a n d a s s e s s m e n t , t h e a p p r o a c h b e c o m e s s u f f i c i e n t l y g e n e r a l to b e u s e f u l in a w i d e r a n g e of i n s t i t u t i o n a l c i r c u m s t a n c e s a n d a p p l i c a t i o n a r e a s .
L I T E R A T U R E C I T E D
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