This study critically examines the role of visitor use information in park management planning. Few park planning documents utilise visitor use information. This is thought to result from two problems. Firstly, visitor use studies have been plagued with methodological problems such as unclear objectives, lack of rigour in the survey design and lack of synthesis of information needs. These have resulted in data which are unreliable and at times have no direct implication for management planning. The second problem arises from the lack of understanding of the role visitor use information may play in the planning process. A case study, the Centennial Park User Survey, was undertaken to demonstrate how the inadequacies of existing visitor use studies could be overcome and to provide a base for future planning of Centennial Park. The survey data have assisted Management both in day-to-day decision making and future management planning relating to control of forthcoming events, responding to public comment, traffic management, facility provision, staff changeover, park staff work programmes and rosters, allocation of financial and staff resources, promotion of the Park, provision of interpretative material and re-allocation of users. By comparing the shortcomings of previous studies with the experience of the case study, specific implications for the collection and use of visitor use information in park management planning have been identified.

Implementation of physically distributed catchment modelling systems reshapes the fundamental philosophy of traditional calibration approaches by supporting the concept of equifinality. Arising from the concept of equifinality, alternative behavioural parameter sets within a given catchment modelling system structure can generate similar levels of simulation performance. This concept is motivated by the existence of a variety of uncertainties associated with a complex catchment modelling system, such as an imperfect model structure, measurement errors in both the input data and the recorded flows, and unknown, or poorly defined, interactions among parameters. However, the difficulty of searching for behavioural parameter sets increases as the complexity of the catchment modelling systems increases. This study undertook an investigation on the feasibility and robustness of a real-value coding genetic algorithm (GA) for calibrating the physically distributed Storm Water Management Model (SWMM) using the Centennial Park catchment in Sydney as a case study. It was found that a real-value coding GA was a robust technique suitable to search for behavioural parameter sets and, in particular, it was found that this approach was capable of identifying the promising range of values for spatially variable parameters. Moreover, the widespread use of physically distributed catchment modelling systems has highlighted the importance of estimating the uncertainty in the parameter values and in the predictions obtained from a complex catchment modelling system as well as in catchment averaged, or lumped, systems that have been the focus of many previous studies. Bayesian inference has been shown to be a tool suitable for parameter uncertainty estimation in catchment modelling. However, the application of Bayesian inference faces difficulties in complex high-dimensional systems where there is little if any a priori knowledge about the proposal distribution of the parameters. In this study, a real-value coding GA was used to undertake uncertainty estimation on spatially variable control parameters with little a priori knowledge about the proposal distribution of parameters. After 50,000 evaluations, the marginal posterior distributions of spatially variable parameters which are associated with behavioural parameter sets were identified. The performance of a behavioural parameter set under a range of hydrological conditions was evaluated. Updating of the marginal distributions of these control parameters was implemented by adding additional calibration data. Interactions among the spatially variable control parameters were investigated also. Results based on the Pearson Correlation method indicate no clear relationship between any two control parameters. However, a methodology to detect relationships among groups of parameters was developed. Application of this methodology suggests that the simulation performance of SWMM was influenced by combinations of parameter values rather than values of the individual parameters. Finally, the predictive uncertainty associated with the existence of behavioural parameter sets was considered. A number of alternative strategies were used to evaluate the predictive performance. Consideration of the results suggests that use of a small number of parameter sets randomly selected from the large number of behavioural parameter sets was the best strategy in terms of efficiently obtaining predictive performance.

Implementation of physically distributed catchment modelling systems reshapes the fundamental philosophy of traditional calibration approaches by supporting the concept of equifinality. Arising from the concept of equifinality, alternative behavioural parameter sets within a given catchment modelling system structure can generate similar levels of simulation performance. This concept is motivated by the existence of a variety of uncertainties associated with a complex catchment modelling system, such as an imperfect model structure, measurement errors in both the input data and the recorded flows, and unknown, or poorly defined, interactions among parameters. However, the difficulty of searching for behavioural parameter sets increases as the complexity of the catchment modelling systems increases. This study undertook an investigation on the feasibility and robustness of a real-value coding genetic algorithm (GA) for calibrating the physically distributed Storm Water Management Model (SWMM) using the Centennial Park catchment in Sydney as a case study. It was found that a real-value coding GA was a robust technique suitable to search for behavioural parameter sets and, in particular, it was found that this approach was capable of identifying the promising range of values for spatially variable parameters. Moreover, the widespread use of physically distributed catchment modelling systems has highlighted the importance of estimating the uncertainty in the parameter values and in the predictions obtained from a complex catchment modelling system as well as in catchment averaged, or lumped, systems that have been the focus of many previous studies. Bayesian inference has been shown to be a tool suitable for parameter uncertainty estimation in catchment modelling. However, the application of Bayesian inference faces difficulties in complex high-dimensional systems where there is little if any a priori knowledge about the proposal distribution of the parameters. In this study, a real-value coding GA was used to undertake uncertainty estimation on spatially variable control parameters with little a priori knowledge about the proposal distribution of parameters. After 50,000 evaluations, the marginal posterior distributions of spatially variable parameters which are associated with behavioural parameter sets were identified. The performance of a behavioural parameter set under a range of hydrological conditions was evaluated. Updating of the marginal distributions of these control parameters was implemented by adding additional calibration data. Interactions among the spatially variable control parameters were investigated also. Results based on the Pearson Correlation method indicate no clear relationship between any two control parameters. However, a methodology to detect relationships among groups of parameters was developed. Application of this methodology suggests that the simulation performance of SWMM was influenced by combinations of parameter values rather than values of the individual parameters. Finally, the predictive uncertainty associated with the existence of behavioural parameter sets was considered. A number of alternative strategies were used to evaluate the predictive performance. Consideration of the results suggests that use of a small number of parameter sets randomly selected from the large number of behavioural parameter sets was the best strategy in terms of efficiently obtaining predictive performance.

Thesis (M.S.)--Florida State University, 2006. / Advisor: Ricardo Navarro, Florida State University, College of Visual Arts, Theatre and Dance, Dept. of Interior Design. Title and description from dissertation home page (viewed June 20, 2006). Document formatted into pages; contains xii, 96 pages. Includes bibliographical references.