Wasteload Allocation Strategeries with Uncertainty in a River Basin

• Main Authors: Liang-Chun Lin, 林亮君
• Other Authors: Ho-Wen Chen
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/4672fj

碩士 === 朝陽科技大學 === 環境工程與管理系碩士班 === 93 === Recently major policy planning for improving water quality is to control total maximum daily load. In order to estimate permissible maximum daily waste in a river under uncertainty, we use moving average, moving stand deviation and correlation analysis to evaluate flow difference between different time intervals and between locations in Kao-Ping River. Then, Monte Carlo Simulation is used to simulate stochastic properties of flows. In order to establish Multiobjectives Stochastic Programming and then to proceed three Design daily flow (Q75, Q90 and Qrd ) and four waste load allocation policies of Total Mass Control: (1) the maximum discharge policy, (2) the uniform treatment for the whole water basin, (3) the uniform treatment for each watershed and (4) the different treatment for each element to demonstrate, we then use those simulated flows to achieve minimum cost and opitimal water-quality improvement comply with regulations simultaneously. In order to solve the optimal solutions of the model, we combine against Genetic Algorithm and Mote Carlo Simulation. The results of the study show that flow at Shin-Fa Bridge, San-Lin Bridge and Liu-Kwei stations tend to diminish and variance of Li-Lin Bridge and San-Ti-Men stations tend to increase. Based on assimilative capacity of Gao-Ping River, this research finds out that our resulted TMDL is less than the current load. Results show that (4) will cost least, (3) is economically viable than (2).