The management and control of a region’s water quality are known to be greatly influenced by prevailing social, political, and economic conditions. Research into how these conditions and attitudes relate over time to result in water quality control has been inadequate to date. The main objective of this research has been to illustrate how these prevailing conditions and attitudes interrelate in an information feedback and control system to produce traditional modes of system response.
Technical Report
Principal Investigator: William W. Hines (Georgia Institute of Technology)
Principal Investigator: John E. Knight (Georgia Institute of Technology)
Sponsor: GWRI
Start Date: 1968-07-01; Completion Date: 1970-06-30;
Keywords:
Description:
The management and control of a region’s water quality are known to be greatly influenced by prevailing social, political, and economic conditions. Research into how these conditions and attitudes relate over time to result in water quality control has been inadequate to date. The main objective of this research has been to illustrate how these prevailing conditions and attitudes interrelate in an information feedback and control system to produce traditional modes of system response. Included are such considerations as the level of water standards legislation, public awareness to pollution concentrations, enforcement effort by an administrative agency, and ecological deterioration due to excessive pollution concentration levels.
More specifically, the research attempted to (1) identify and quantify some controlling feedback loops in the complex system which encompasses water quality control and response in a basin, and (2) test the generalized model under a wide range of policies and parameters to illustrate system response and sensitivity to these changes. Utilizing the understanding of the system structure and its response patterns, directions for effective policy formulations can be suggested and tested. The methodology and philosophy of Industrial Dynamics was utilized to model this high order, multi-loop, non-linear feedback system. The DYNAMO simulation language was used to program this model for digital computer simulation, testing, and experimentation.
Initial emphasis in the modeling phase was placed on isolation of important system variables and identification of their relative magnitudes, periods, and phasing in historically polluted watersheds. The understanding of the relationships between these social, political, and economic factors led to the postulation and testing of interrelated feedback loops thought responsible for identified modes of behavior. Following refinement of the model, different policies and parameters were tested to determine their overall effect on total system response.
The results of the research include a systematic analysis of important feedback loops within the total complex system identified. General response patterns of water quality crises are shown to be embedded in the system structure proposed. Within the complex structure, feedback loops were found to have greater importance in system behavior than did relationships between variables in feedback loops. In addition, gaining an understanding of when and how various loops gain dominance of the system was then found to be necessary for understanding system response. For example, the non-linear public awareness to perceived water pollution concentration levels created different response according to the loop’s ability to direct the system for an extended time.
In summary, the study conclusions demonstrate that water quality management and control is deeply embedded in a complex, information feedback system involving social, political and economic pressures and forces. Furthermore, the complex system response was shown to be highly insensitive to many parameter changes and also very unintuitive in behavior. However, some critical points do exist, and through programs directed at these points, significant changes occur in system response.
The results of the study would be applicable to high level, governmental planning agencies since effective understanding of the interactions creating historical, pollution-control response patterns would lead to more effective development of future control policies and programs. Specifically, the research provides some in sight into the total system response time as conditions of public awareness, enforcement effort, and legislative commitments change over time.