Student Independent Projects 2012: Sustainable Resource Management

Everyday Millions of disposable plates, cups and utensils are used in fast food establishments, cafeterias, restaurants and homes worldwide. These single-use disable plates, cup and utensils, when of polystyrene or plastic, do not biodegrade and decompose like fruit, vegetables or meat; they only breakdown into smaller pieces on a physical level. This lack of decomposition means that these products persist and accumulate in landfills consuming the available space and contaminate the surrounding area. With an ever growing global population, the disposable waste generated annually is increasing and landfills worldwide are rapidly filling. Therefore, more landfills are needed sooner but they are expensive to create, they consume a large amount of usable space and can harm the environment. In order to reduce the dependence on landfills, the waste can be diverted through recycling programs, reducing human consumption and purchasing reusable and/or compostable materials. These methods of waste reduction would be implemented at the municipal level but it would be possible to change provincial and state legislation so that municipalities would be required to do so rather than of their own volition. If initiated worldwide than the amount of waste produced by humans would be greatly reduced and the dependence on landfills would decrease.

Structured decision making as a tool for facilitating stakeholder engagement in non-renewable resource management: using the case study of hydraulic fracturing in the Green Point Shale formation in western Newfoundland

This thesis examines the importance of effective stakeholder engagement that complies with the doctrines of social justice in non-renewable resources management decision-making. It uses hydraulic fracturing in the Green Point Shale Formation in Western Newfoundland as a case study. The thesis uses as theoretical background John Rawls’ and David Miller’ theory of social justice, and identifies the social justice principles, which are relevant to stakeholder engagement. The thesis compares the method of stakeholder engagement employed by the Newfoundland and Labrador Hydraulic Fracturing Review Panel (NLHFRP), with the stakeholder engagement techniques recommended by the Structured Decision Making (SDM) model, as applied to a simulated case study involving hydraulic fracturing in the Green Point Shale Formation. Using the already identified social justice principles, the thesis then developed a framework to measure the level of compliance of both stakeholder engagement techniques with social justice principles. The main finding of the thesis is that the engagement techniques prescribed by the SDM model comply more closely with the doctrines of social justice than the engagement techniques applied by the NLHFRP. The thesis concludes by recommending that the SDM model be more widely used in non- renewable resource management decision making in order to ensure that all stakeholders’ concerns are effectively heard, understood and transparently incorporated in the nonrenewable resource policies to make them consistent with local priorities and goals, and with the social justice norms and institutions.

Integrated sensitivity analysis, calibration, and uncertainty propagation analysis approaches for supporting hydrological modeling

The successful performance of a hydrological model is usually challenged by the quality of the sensitivity analysis, calibration and uncertainty analysis carried out in the modeling exercise and subsequent simulation results. This is especially important under changing climatic conditions where there are more uncertainties associated with climate models and downscaling processes that increase the complexities of the hydrological modeling system. In response to these challenges and to improve the performance of the hydrological models under changing climatic conditions, this research proposed five new methods for supporting hydrological modeling. First, a design of experiment aided sensitivity analysis and parameterization (DOE-SAP) method was proposed to investigate the significant parameters and provide more reliable sensitivity analysis for improving parameterization during hydrological modeling. The better calibration results along with the advanced sensitivity analysis for significant parameters and their interactions were achieved in the case study. Second, a comprehensive uncertainty evaluation scheme was developed to evaluate three uncertainty analysis methods, the sequential uncertainty fitting version 2 (SUFI-2), generalized likelihood uncertainty estimation (GLUE) and Parameter solution (ParaSol) methods. The results showed that the SUFI-2 performed better than the other two methods based on calibration and uncertainty analysis results. The proposed evaluation scheme demonstrated that it is capable of selecting the most suitable uncertainty method for case studies. Third, a novel sequential multi-criteria based calibration and uncertainty analysis (SMC-CUA) method was proposed to improve the efficiency of calibration and uncertainty analysis and control the phenomenon of equifinality. The results showed that the SMC-CUA method was able to provide better uncertainty analysis results with high computational efficiency compared to the SUFI-2 and GLUE methods and control parameter uncertainty and the equifinality effect without sacrificing simulation performance. Fourth, an innovative response based statistical evaluation method (RESEM) was proposed for estimating the uncertainty propagated effects and providing long-term prediction for hydrological responses under changing climatic conditions. By using RESEM, the uncertainty propagated from statistical downscaling to hydrological modeling can be evaluated. Fifth, an integrated simulation-based evaluation system for uncertainty propagation analysis (ISES-UPA) was proposed for investigating the effects and contributions of different uncertainty components to the total propagated uncertainty from statistical downscaling. Using ISES-UPA, the uncertainty from statistical downscaling, uncertainty from hydrological modeling, and the total uncertainty from two uncertainty sources can be compared and quantified. The feasibility of all the methods has been tested using hypothetical and real-world case studies. The proposed methods can also be integrated as a hydrological modeling system to better support hydrological studies under changing climatic conditions. The results from the proposed integrated hydrological modeling system can be used as scientific references for decision makers to reduce the potential risk of damages caused by extreme events for long-term water resource management and planning.