INTRODUCTION - Integrating GIS, Remote Sensing, and Mathematical Modelling for Surface Water Quality Management - page 6

Figure (1-2): The framework for solving real world water related problems
The near-end users identify the target output objectives of the virtual world, run the analysis scenarios
and formulate objective conclusions. The last building block is the human society world , or the far-
end users, involving the decision makers and different stakeholders. The interface between this world
and the procedural world includes the development of reliable and efficient information in the form of
results from the virtual world, the development of solution scenarios based on model results, and the
receipt and application of feed-back enhancements to the virtual world. The human society world is
responsible for the safe, sustainable and efficient interventions that take place in the real world to solve
the water quality related problems. In total, hydroinformatics is the implementation tool of integrated
water resources management.
1.5. THE IMPORTANCE OF DATA AVAILABILITY
In the context of surface water quality management, data availability is a crucial issue to be
considered. Sustainable management of water quality involves dealing with different categories and
huge amounts of data. The availability of the right data sets, which are used to develop the appropriate
information needed for a water quality decision support system (DSS), is one of the problems that face
us in the management process. The over-arching problem of data programs (monitoring and data use)
was summarized by Ongley (1997) as:
“… a common observation amongst water quality professionals is that many water
quality programs, especially in developing countries, collect the wrong parameters, from
the wrong places, using the wrong substrates and at inappropriate sampling frequencies,
and produce data that are often quite unreliable; the data are not assessed or evaluated,
and are not sufficiently connected to realistic and meaningful program, legal or
management objectives. This is not the fault of developing countries; more often it
results from inappropriate technology transfer and an assumption by recipients and
donors that the data paradigm developed by western countries is appropriate in
developing countries. "