Evaluation of Uncertainty Effects in TMDL Programs- Application of Qualitative and Quantitative Uncertainty Analysis

• Main Authors: Chi-Feng Chen, 陳起鳳
• Other Authors: 馬鴻文
• Format: Others
• Language: en_US
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/17244367031369764584

博士 === 臺灣大學 === 環境工程學研究所 === 96 === This dissertation is a management-oriented study, evaluating uncertainty effects on TMDL (Total Maximum Daily Loads) decisions. The TMDL program is a water quality management with regular standard process and is verified and applied widely, especially in the U.S. However, uncertainty problems are occurred inevitably in TMDL programs and decrease the successes of implementations. The main purpose of this study is to establish a complete analysis framework to aid in address, analyze, and assess impact of uncertainties on TMDL programs. The importance of uncertainty analysis has been perceived but not completely applied. Uncertainty analysis approaches have been focus on quantifiable uncertainty effects, ignored the effects from non-quantifiable uncertainty elements. This leads to partial uncertainty analysis and might underestimate the results. Not only quantitative uncertainty but also qualitative (non-quantifiable) uncertainty should be considered in decision-making process. Due to the lack of a complete uncertainty analysis, especially for qualitative uncertainty, an integrated framework of uncertainty analysis with capable of evaluating both uncertainty effects is explored in this study. Qualitative uncertainty analysis (QLUA) with qualitative check list, belief function, and expert elicitation is developed to obtain the confidence level of target systems, which is TMDL program in this study. Quantitative uncertainty analysis (QTUA) is particularly designed for assessing the model parameter uncertainty on optimization programming of TMDL allocation. QTUA results in a distributed TMDL allocation and quantifies the uncertainty level (variability) of TMDL results. The both consequences are integrated into an uncertainty diagnose figure. The diagnose figure is able to manifest the uncertainty level of the system in terms of qualitative and quantitative uncertainty. If the uncertainty level is not complied with accepted level made by decision maker, the reliability of TMDL results might be questioned and uncertainty reduction is sought. As to uncertainty reduction, a new formulation, uncertainty value (UV), is created. The UV is used to represent the decision benefit obtained from every unit of uncertainty reduction, which is the confidence from QLUA and the variability from QTUA. Two case studies, KaoPing River and DaHan Creek, are used as applications of QLUA and QTUA, respectively. Although uncertainty exists in any decision steps and subjective assumptions (from expert elicitations) are unavoidable while seeking objective solutions, the comprehensive understandings are believed to improve quality of decision-making. The integrated framework of uncertainty analysis incorporating with individual evaluation approaches, diagnose figure, and uncertainty value function provides a systematic way to estimate uncertainty level in target systems, such as TMDL programs, and eventually; to increase the quality of decisions.