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ICT as a tool for assisting environmental science

The section gives a detailed literature review of modern technologies broadly applied in environmental science, namely environmental modeling combining with scenario approach, use of geographic information systems and remote sensing. We should point out that application of the above mentioned technologies could provide deeper research of the Aydar- Arnasay lake system and give a more detailed analysis of the severe environmental problems specific to these lakes as well as provide some effective solution for alleviation of the existing problems.
Apart from this, this section also considers the successful worldwide environmental projects assisted by environmental modeling, scenario approach, GIS, and remote sensing.

1. Use of modeling

Modeling has become a significant tool in the contemporary study of various environmental issues i.e. climate change, water management, land use, soil degradation, transport, population dynamics, and so on (Gotelli 1995). Smyth gives a clear definition explaining that a model is an abstract and partial representation of some aspects of the world “that can be manipulated to analyze the past, define the present, and to consider possibilities of the future”. He outlines that models give an opportunity for researchers to explore issues concerning dynamics of ecological systems that cannot be checked in the field conditions because of reasons of logistics, political or financial issues (Smyth 1998).

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Considering environmental models, Clark states that they cover a full range of geographic scales, i.e. from the local to the global. Furthermore, they cover a variety of input fields: human, natural, socioeconomic, and others. Because environment is considered to be a synthesis off all of these fields, environmental models very often incorporate several aspects from the areas given above (Clarke 2000). Clarke also adds that environmental modeling is mainly applied in the fields of significant societal importance.
Considering the properties of a good environmental model, Lee concludes that among the most important properties we should specify the following: transparency, robustness, reasonable data needs, appropriate spatial-temporal resolution, and the inclusion of enough key policy variables that allow policy issues to be explored (Lee 1973). Another interesting conclusion about the creation of a good conceptual environmental model provided by Hilborn and Mangel is focused on the fact that well-developed model forces ecologists to formulate
hypotheses, establish what kinds of data are accessible, what data are necessary for research, and evaluate understanding of the key points of the system (Hilborn and Mangel 1997).
A variety of possible roles for the models in environmental research, policy making and management, was suggested by various authors over the last decades (Brown 1993); (Frans 1987); (Irvine 2005); (Larocque, Mauriello et al. 2006); (Westerlvelt and Shapiro 2000). Consequently, a various classification of the roles of models can be proposed. Generally speaking, there are two main broad categories: a) research and b) decision-making support. The models with the first role assist scientists to build up in-depth understanding of the environmental system, whereas the second type models serve as mediators between scientists and decision-makers. In particular, the models in to environmental policy and decision- making the computer models can play four different roles. Van Daaten formulated them as following:

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  Models as eye-openers;
  
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  Models as arguments in dissent;
  
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  Models as consensus building tools;
  
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  Models as management tools (Van Daaten 2002).
  

In addition, King and Kraemer also consider three main roles which environmental model plays in policy context:

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  firstly, models should be debatable and they should clarify results in a discussion;
  
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  secondly, models should induce analysis and discourse among stakeholders concerned
  
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  finally, models should draw a clear outcome for the politicians explaining the major advantages and benefits as well as risks and complications in a particular model (King and Kraemer 1993).
  

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