A. Aboujaoude et al. : System for the Management of Agricultural PoJIution
35
Mathematical models can provide powerful support to understand the situation
and to forecast possible evolution [2]. However, there are hundreds of models
available elaborated by the scientific community, often with competing modeling
techniques, limited to specific applications, based upon specific hypotheses,
requiring specific data sets.
Consequently, it is very difficult for decision makers to have a clear view in this
jungle, and modeling has become very controversial and too poorly exploited for
management purposes.
Agricultural pollution concerns extensive geographical areas and data availability
is a major preoccupation. The natural environment is extremely heterogeneous,
and there are never enough observation results available to characterize this spatial
variability. In addition, as mentioned, pesticide detection is very expensive and,
whatever the effort, the data available often remains inadequate. Therefore, it is
necessary to process these scarce data in an optimal way in order to draw
reasonable conclusions. It is also very important to pool all existing knowledge
and skill to understand the interacting phenomena, to reliably apply existing tools
or to suggest solutions.
The solution seeking process for a contamination problem on a large scale
(catchment) is complex. It must integrate sampling strategy, analytical capabilities,
understanding of relevant natural/anthropogenic phenomena interactions,
predictive testing of remediation decisions, existing know-how or previous
experience in similar problems.
This is clearly necessary to elaborate an overall and balanced methodology,
adapted to each class of problem, so as to guide the local manager through this
intricate maze.
Recent information technology developments make it possible to integrate in
computerized user friendly systems various types of complementary tools such as
data bases, knowledge bases and predictive models, and it is a major objective of
the 90s to develop this kind of tool for environmental applications.
3
ISMAP PROJECT OBJECTIVES
To address all the above listed concerns and needs, industrial and public partners
from Italy, France and the United Kingdom, involved at various stages in
agricultural pollution, are currently collaborating in the ISMAP project within the
EUREKA framework [5].
ISMAP stands for Integrated System and services for the Management of
Agricultural Pollution. IS MAP involves a water supplier (Compagnie Generale des
Eaux), chemical manufacturers (RhOne-Poulenc, Ciba-Geigy, Grande Paroisse),
environmental administrations (Agences de l'Eau in France and ENEA in Italy),
farming industries (Gruppo Ferruzzi), research institutes and Information
Technologies companies (A.I.TEC, LHF, ITCF and CEMAGREF). A.I.TEC,
representing Gruppo Ferruzzi, is appointed as project coordinator, Compagnie
Generale des Eaux and LHF co-coordinate the French contribution.
35
Mathematical models can provide powerful support to understand the situation
and to forecast possible evolution [2]. However, there are hundreds of models
available elaborated by the scientific community, often with competing modeling
techniques, limited to specific applications, based upon specific hypotheses,
requiring specific data sets.
Consequently, it is very difficult for decision makers to have a clear view in this
jungle, and modeling has become very controversial and too poorly exploited for
management purposes.
Agricultural pollution concerns extensive geographical areas and data availability
is a major preoccupation. The natural environment is extremely heterogeneous,
and there are never enough observation results available to characterize this spatial
variability. In addition, as mentioned, pesticide detection is very expensive and,
whatever the effort, the data available often remains inadequate. Therefore, it is
necessary to process these scarce data in an optimal way in order to draw
reasonable conclusions. It is also very important to pool all existing knowledge
and skill to understand the interacting phenomena, to reliably apply existing tools
or to suggest solutions.
The solution seeking process for a contamination problem on a large scale
(catchment) is complex. It must integrate sampling strategy, analytical capabilities,
understanding of relevant natural/anthropogenic phenomena interactions,
predictive testing of remediation decisions, existing know-how or previous
experience in similar problems.
This is clearly necessary to elaborate an overall and balanced methodology,
adapted to each class of problem, so as to guide the local manager through this
intricate maze.
Recent information technology developments make it possible to integrate in
computerized user friendly systems various types of complementary tools such as
data bases, knowledge bases and predictive models, and it is a major objective of
the 90s to develop this kind of tool for environmental applications.
3
ISMAP PROJECT OBJECTIVES
To address all the above listed concerns and needs, industrial and public partners
from Italy, France and the United Kingdom, involved at various stages in
agricultural pollution, are currently collaborating in the ISMAP project within the
EUREKA framework [5].
ISMAP stands for Integrated System and services for the Management of
Agricultural Pollution. IS MAP involves a water supplier (Compagnie Generale des
Eaux), chemical manufacturers (RhOne-Poulenc, Ciba-Geigy, Grande Paroisse),
environmental administrations (Agences de l'Eau in France and ENEA in Italy),
farming industries (Gruppo Ferruzzi), research institutes and Information
Technologies companies (A.I.TEC, LHF, ITCF and CEMAGREF). A.I.TEC,
representing Gruppo Ferruzzi, is appointed as project coordinator, Compagnie
Generale des Eaux and LHF co-coordinate the French contribution.